This study aimed to understand the collective impact of trace elements, vitamins, cholesterol, and prealbumin on patient outcomes in the intensive care unit (ICU) using an advanced artificial intelligence (AI) model for mortality prediction.

Data from ICU patients (December 2016 to December 2021), including serum levels of trace elements, vitamins, cholesterol, and prealbumin, were retrospectively analyzed using AI models. Models employed included category boosting (CatBoost), extreme gradient boosting (XGBoost), light gradient boosting machine (LGBM), and multilayer perceptron (MLP). Performance was evaluated using area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, and F1-score. The performance was evaluated using 10-fold crossvalidation. The SHapley Additive exPlanations (SHAP) method provided interpretability.

CatBoost emerged as the top-performing individual AI model with an AUROC of 0.756, closely followed by LGBM, MLP, and XGBoost. Furthermore, the ensemble model combining these four models achieved the highest AUROC of 0.776 and more balanced metrics, outperforming all models. SHAP analysis indicated significant influences of prealbumin, Acute Physiology and Chronic Health Evaluation II score, and age on predictions. Notably, the ratios of selenium to age and low-density lipoprotein to total cholesterol also had a notable impact on the models' output.

The study underscores the critical role of nutrition-related parameters in ICU patient outcomes. Advanced AI models, particularly in an ensemble approach, demonstrated improved predictive accuracy. SHAP analysis offered insights into specific factors influencing patient survival, highlighting the need for broader consideration of these biomarkers in critical care management.

The COVID-19 pandemic created a high demand for hospital beds and intensive care, which led to the collapse of healthcare systems. Therefore, it is critical to identify factors associated with increased mortality in patients to prioritize high-risk individuals.

Given the potential for similar pandemics in the future, this study investigated predictors of mortality in ICU patients with COVID-19 and their correlation with mortality rates.

In this retrospective study, all patients admitted to the ICUs of Ghaem and Imam Reza tertiary hospitals in Mashhad with a definitive diagnosis of COVID-19 from March 21, 2020, to December 1, 2021, were evaluated for disease severity assessment criteria, including SOFA, SAPS III, and MPM II.

One hundred seventy-two patients with COVID-19 who were admitted to the ICU were evaluated (147 patients in the non-survivor group and 25 patients in the survivor group. The median SAPS, SOFA, and MPM scores were significantly higher in non-survivors (p<0.001 in all cases). Higher SAPS, SOFA, and MPM were associated with an increased risk of mortality in COVID-19 patients in the ICU. The best cut-off points for the three scoring systems, SAPS, SOFA, and MPM, were 39, 6, and 13.7, respectively. The AUC value of the SOFA score was significantly higher than the SAPS (P = 0.0274) and MPM (P = 0.0209) scores.

COVID-19 patients admitted to the ICU with higher SOFA, MPM, and SAPS scores suffered from higher mortality rates. Because the SOFA score showed high predictive accuracy, this scoring system should be considered a priority as an essential tool in triaging and managing critically ill COVID-19 patients.

Background and Objectives: Sepsis is a critical condition with high mortality rates worldwide. The early identification of patients at an elevated risk of mortality remains a significant clinical challenge. The lactate/albumin (L/A) ratio has emerged as a potential prognostic biomarker in critically ill patients. This exploratory study aimed to evaluate the L/A ratio as a predictor of mortality in patients with sepsis or septic shock and to describe the demographic and clinical characteristics of affected patients in a tertiary referral hospital in Western Mexico. Materials and Methods: A retrospective cross-sectional study was conducted including patients diagnosed with sepsis or septic shock between January 2022 and June 2023. Clinical and biochemical data, including serum lactate and albumin levels, were collected from medical records to calculate the L/A ratio. The primary outcome was in-hospital mortality. The statistical analysis included receiver operating characteristic (ROC) curves to evaluate the L/A ratio's discriminative capacity, a bivariate analysis, and a multivariate logistic regression to identify independent risk factors for mortality. Results: A total of 141 patients were included in the study, and the median L/A ratio was significantly higher in non-survivors compared to survivors (0.95 vs. 0.60, p = 0.003). The ROC analysis showed an area under the curve (AUC) of 0.651, with a sensitivity of 36.5% and specificity of 82% at a cutoff value of 1.12. The multivariate analysis identified serum albumin levels and vasopressor use as independent predictors of mortality. Conclusions: The L/A ratio demonstrates potential as a simple and accessible prognostic biomarker for mortality in sepsis, though its utility requires further validation in larger prospective studies.

This study aimed to determine the association between postoperative organ dysfunction evaluated using eSOFA, a simplified measure of organ dysfunction, and postoperative mortality following noncardiac surgery.

This study retrospectively analyzed adult patients who underwent noncardiac surgery under general anesthesia between 2009 and 2019. The primary exposure was postoperative organ dysfunction evaluated using eSOFA within 2 postoperative days (positive eSOFA), and the primary outcome was 90-day mortality. Multivariable Cox regression analysis was employed to investigate the association between positive eSOFA and 90-day mortality. In a subanalysis of patients in the surgical intensive care unit (ICU), the predictive performance of the number of eSOFA-positive items for 90-day mortality was compared with those of the Sequential Organ Failure Assessment (SOFA) score and the Acute Physiology And Chronic Health Evaluation (APACHE) II score using Harrell's C-statistic.

This study included 24,558 patients, of whom 7.5% had positive eSOFA, and the postoperative 90-day mortality was 0.9%. Positive eSOFA was independently associated with the occurrence of 90-day mortality (adjusted hazard ratio [HR]: 3.03, 95% confidence interval: 2.16-4.25, P < 0.001). As the number of positive eSOFA items increased, the adjusted HR for 90-day mortality increased. The C-statistics for predicting 90-day mortality in surgical ICU patients using the number of eSOFA-positive items, SOFA score, and APACHE II score were 0.72 (0.65-0.79), 0.73 (0.65-0.80), and 0.74 (0.68-0.81), respectively.

Postoperative organ dysfunction evaluated using the eSOFA within 2 postoperative days was independently associated with 90-day mortality in patients who underwent noncardiac surgery.

Background Exploratory laparotomy in emergency setting is associated with significant post-operative morbidity and mortality. Several prognostic indices have been developed to predict the outcomes. The present study investigated the APACHE II (Acute Physiology and Chronic Health Evaluation II) score and C-reactive protein (CRP)/albumin ratio as predictors of morbidity and mortality in patients who underwent emergency exploratory laparotomy at a tertiary-care hospital. Methods One hundred consecutive patients undergoing emergency laparotomy were enrolled. The APACHE II score and CRP/albumin ratio were calculated. Post-operatively, all complications (Clavien-Dindo classification) and deaths within 30 days of surgery were observed. Comparison of the receiver operating characteristic curve was performed to compare the area under the curve (AUC) of APACHE II and CRP/albumin ratio in predicting complications and mortality. Results The APACHE II score ≥13 predicted major complications with a sensitivity of 93% and a specificity of 81%. The CRP/albumin ratio ≥5.1 was found to predict major complications with a sensitivity and specificity of 95% and 93%, respectively. The AUC for the APACHE II Score and CRP/albumin ratio in predicting major complications was 0.946 and 0.97, respectively (p <0.001), thus demonstrating excellent diagnostic performance. Conclusion We found that the better parameter in terms of AUC is the CRP/albumin ratio, although statistically there was no significant difference in the diagnostic performance of the two parameters.

We aimed to investigate the value of leukocyte biomarkers and disease scores for the early detection of infection in patients who have undergone elective colorectal surgery for malignancy.

We conducted a prospective study at a training and research hospital. Patients who developed infection were considered to be an Infection group, and the others were regarded as a Control group. For individuals in both groups, the Sequential Organ Failure Assessment Score (SOFA), quick SOFA, and National Early Warning Score (NEWS) were calculated and blood samples were collected for flow cytometry analysis. A model was developed using logistic regression analysis to identify parameters that were predictive of mortality.

One hundred thirty-two patients were included in the study. Infections developed in 36 (27.3%) of the participants, of which 14 (38.9%) were intra-abdominal, 10 (27.8%) were pneumonia, 8 (22.2%) were superficial incisional infections, and 4 (11.1%) were urinary tract infections. The NEWS was the most effective parameter for the detection of early infection in patients undergoing surgery for colorectal malignancy.

The NEWS score can be easily used to predict infection soon after surgery for colorectal malignancy.

Continuous monitoring of acute inflammation can become a very important next step for guiding therapeutic interventions in severely ill patients. This Perspective discusses the current medical need for patients with acute inflammatory diseases and the potential of continuous biosensing technologies. First, we discuss biomarkers that could help to monitor the state of a patient with acute systemic inflammation based on theoretical studies and empirical data. Then, based on the state of the art, we describe sensing strategies that could be applied for the continuous monitoring of acute inflammatory biomarkers, followed by challenges that must be overcome. Nanoswitch-based continuous biosensors enable suitable measurement frequencies but still lack sensitivity, while regeneration risks lower sensor reliability. Developments are still needed in bioreceptors and molecular architectures, regeneration techniques, combined with suitable sampling and sample pretreatment methods, for bringing continuous biosensing of inflammation closer to reality. Furthermore, collaborations between healthcare professionals and scientists, regulatory bodies, and biosensor engineers are needed for a successful translation of sensing technologies from the laboratory to clinical practice.

To improve the outcomes in patients with abdominal cancers complicated by diffuse postoperative peritonitis (DPP) using vacuum-assisted laparostomy (VAL) with elective staged peritoneal lavage.

There were 141 patients with DPP: group I (63 patients) - VAL, group II (78 patients) - redo laparotomy on demand (RD). Negative pressure therapy was performed using commercial vacuum systems with vacuum dressing changes after 48 - 72 hours. We assessed mortality, morbidity, abdominal cavity status (Björck classification) and incidence of primary fascial closure of abdominal cavity.

There were 10 (15.9%) and 24 (30.8%) deaths, respectively (p=0.040). Complications Clavien-Dindo grade 3-5 were significantly more common in the 2nd group. According to the Björck classification, grades 2A (39.7%) and 2B (41.3%) became more common after the 2nd peritoneal lavage in the 1st group. After the 3rd and further staged peritoneal lavages, «frozen open abdomen» (grade 3A and 4) prevailed. This classification revealed significant correlations with abdominal index, intra-abdominal hypertension and C-reactive protein. Primary fascial closure of abdominal cavity was performed in 40 (63.5%) patients in the 1st group.

Vacuum-assisted laparostomy is effective for diffuse postoperative peritonitis compared to on-demand relaparotomy. This approach provides lower mortality and morbidity rates, as well as better control over local inflammatory process and intra-abdominal pressure.

Sepsis in emergency departments is a prevalent occurrence characterized by high hospitalization rate and mortality. The granulocyte colony-stimulating factor (G-CSF) is an indicator for identifying patients with sepsis.

A total of 171 patients with sepsis were included in our study who were admitted to the emergency department of Beijing Chaoyang Hospital affiliated with Capital Medical University from October 2020 to April 2021. Out of these patients, 122 did not survive on day 28. Laboratory tests, the sequential organ failure assessment (SOFA) score and the acute physiology and chronic health evaluation II (APACHE II) were calculated. Logistic regression and receiver operating characteristic curve were used to analyze the predictive value of G-CSF for 28-day mortality patients with sepsis.

There were significant differences in G-CSF, SOFA, APACHE II, systolic blood pressure (SBP), mean arterial pressure, lactate, and albumin between the survivor and non-survivor groups (P < .05). The multivariate regression analysis showed that G-CSF, SOFA, APACHE II, and SBP were independent risk factors for 28-day mortality in patients with sepsis. There was no comparative with significant differences in receiver operating characteristic curves of G-CSF, SOFA, and APACHE II for 28-day mortality in patients with sepsis (Z1 = 1.381, P = .167; Z2 = 0.095, P = .924).

The G-CSF, SOFA, APACHE II, and SBP were identified as independent risk factors for mortality among patients with sepsis. Particularly, G-CSF and SOFA exhibited a high level of predictability for 28-day mortality in this population.

To determine the diagnostic and prognostic value of soluble suppression of tumorigenicity 2 (sST2) in patients with sepsis.

A total of 113 critically ill patients were enrolled at the emergency department of Beijing Chaoyang Hospital Jing Xi Branch. Venous blood levels of sST2 were measured using the AFIAS-6 dry fluorescence immunoassay analyzer. Based on Sepsis 3.0 criteria, patients were categorized into a sepsis group (76 cases) and a non-sepsis group (37 cases). The sepsis group was further divided into non-survivors (38 cases) and survivors (38 cases) based on 28-day survival outcomes. The vital signs, blood gas analysis, routine blood tests, liver and kidney function tests, procalcitonin (PCT), C-reactive protein (CRP), sST2, left ventricular ejection fraction (LVEF), and other basic characteristics of the patients were recorded. Further, the SOFA, qSOFA and APACHE II scores of each patient were calculated. Statistical analysis was performed using SPSS 25.0, including logistic regression and ROC curve analysis to assess prognostic factors.

The serum sST2 levels in the sepsis group (125.00 ± 60.32 ng/mL) were significantly higher than in the non-sepsis group (58.55 ± 39.03 ng/mL) (p < 0.05). The SOFA score (8.08 ± 2.88), APACHE II score (18.00 ± 4.72), blood sST2 levels (168.06 ± 36.75 ng/mL) and lactic acid levels (2.89 ± 3.28) in the non-survivor group were significantly higher than the survivor group (p < 0.05). Multiple logistic regression analysis showed that sST2, SOFA score, APACHE II score and lactic acid levels were independent risk factors for poor prognosis in patients with sepsis. The ROC curve analysis of the above indexes showed no significant differences between the AUC of sST2 (0.912) and the SOFA score (0.929) (z = 0.389, p = 0.697), or the APACHE II score (0.933) (z = 0.484, p = 0.627). However, there was a significant difference between the AUC of sST2 (0.912) and lactic acid levels (0.768) (z = 2.153, p = 0.030).

Blood levels of sST2 show a clinically diagnostic and prognostic value in sepsis. Further, sST2 shows a similar predictive ability as the SOFA and APACHE II scores in determining the prognosis of sepsis patients. However, sST2 has a higher predictive ability than lactic acid levels in determining prognosis in sepsis.

The intensive care unit (ICU) is the most important department for critically ill patients. Different scoring systems are used to assess the severity of the disease and evaluate organ failure during the patient's stay in ICU. Our purpose was to evaluate the C-reactive protein/Albumin (CRP/Alb) ratio and SOFA score as indicators of 28-day mortality in ICU patients. A total of 55 patients were enrolled in this study. CRP and CRP/Alb rates, SOFA scores, and demographic data were used to evaluate 28-day mortality in a referral hospital. Survived and dead patients were significantly different in the CRP, CRP/Alb rates, and SOFA scores. However, in the adjusted model, the SOFA score was the predictor of 28-day mortality in ICU patients. SOFA score was also confirmed as a predictor of mortality in ICU patients. Besides, the role of CRP and CRP/Alb in the prediction of disease prognosis or mortality requires further studies.

Prognostic scores require fluctuating values, such as respiratory rate, which are unsuitable for retrospective auditing. Therefore, this study aimed to develop and validate a predictive model for in-hospital mortality associated with gastrointestinal surgery for retrospective auditing.

Data from patients with bacteremia related to gastrointestinal surgery performed at Shizuoka General Hospital between July 2006 and December 2021 were extracted from a prospectively maintained database. Patients suspected of having a positive blood culture with contaminating bacteria or missing laboratory data were excluded. The remaining patients were randomly assigned in a 2:1 ratio to the deviation and validation cohorts. A logistic regression model estimated the odds ratios (ORs) and created a predictive model for in-hospital mortality. The model was evaluated using receiver operating characteristic (ROC) curves and calibration plots.

Of 20,637 gastrointestinal surgeries, 398 resulted in bacteremia. The median age of patients with bacteremia was 72 years, and 66.1% were male. The most common pathogens were Staphylococcus (13.9%), followed by Bacteroides (12.4%) and Escherichia (11.4%). Multivariable logistic regression showed that creatinine abnormality (P < 0.001, OR = 3.39), decreased prognostic nutritional index (P < 0.001, OR = 0.90/unit), and age ≥ 75 years (P = 0.026, OR = 2.89) were independent prognostic factors for in-hospital mortality. The area under the ROC curve of the predictive model was 0.711 in the validation cohort. The calibration plot revealed that the model slightly overestimated mortality in the validation cohort.

Using age, creatinine level, albumin level, and lymphocyte count, the model accurately predicted in-hospital mortality after bacteremia infection related to gastrointestinal surgery, demonstrating its suitability for retrospective audits.

The occurrence of acute kidney injury (AKI) was associated with an increased mortality rate among acute pancreatitis (AP) patients, indicating the importance of accurately predicting the mortality rate of critically ill patients with acute pancreatitis-associated acute kidney injury (AP-AKI) at an early stage. This study aimed to develop and validate machine learning-based predictive models for in-hospital mortality rate in critically ill patients with AP-AKI by comparing their performance with the traditional logistic regression (LR) model.

This study used data from three clinical databases. The predictors were identified by the Recursive Feature Elimination algorithm. The LR and two machine learning models-random forest (RF) and eXtreme Gradient Boosting (XGBoost)-were developed using 10-fold cross-validation to predict in-hospital mortality rate in AP-AKI patients.

A total of 1089 patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD) were included in the training set and 176 patients from Xiangya Hospital were included in the external validation set. The in-hospital mortality rates of the training and external validation sets were 13.77% and 54.55%, respectively. Compared with the area under the curve (AUC) values of the LR model and the RF model, the AUC value of the XGBoost model {0.941 [95% confidence interval (CI) 0.931-0.952]} was significantly higher (both P < .001) and the XGBoost model had the smallest Brier score of 0.039 in the training set. In the external validation set, the performance of the XGBoost model was acceptable, with an AUC value of 0.724 (95% CI 0.648-0.800). However, it did not differ significantly from the LR and RF models.

The XGBoost model was superior to the LR and RF models in terms of both the discrimination and calibration in the training set. Whether the findings can be generalized needs to be further validated.

Gallbladder perforation (GBP) is a rare but life-threatening complication of acute cholecystitis. Despite advancements in imaging technology and biochemical analysis, perforations are still diagnosed intraoperatively in some cases. This situation has revealed the need for new markers in the diagnosis of perforation. In this study, we aimed to analyze the role of biomarkers in the diagnosis of perforated cholecystitis cases.

In this retrospective study, blood samples (white blood cells (WBC), hemoglobin, platelet count, C-reactive protein (CRP), albumin, CRP/albumin ratio (CAR), neutrophil-lymphocyte ratio (NLR), urea, creatinine, glucose, amylase, lipase, aspartate ami-notransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), total bilirubin, direct bilirubin) were analyzed in patients who were diagnosed with acute cholecystitis in the emergency department.

One hundred seventy patients were divided into two groups according to the presence or absence of gallbladder perforation. Sixty-three (37.1%) patients had perforation. Transition from laparoscopy to open operation, intensive care unit admission, length of hospital stay, and mortality were higher in the perforated group compared to the non-perforated group. When we analyzed the patients according to laboratory findings, there was a difference in WBC, NLR, CRP, albumin, and CAR parameters in the perforation group. In regression analysis, CRP and CAR performed better.

Our study showed that CRP and CAR may be diagnostic biomarkers with low specificity and sensitivity in predicting GBP in patients with acute cholecystitis. This marker is a low-cost and easily accessible parameter that may help clinicians make an early diagnosis and plan appropriate treatment for this condition with high morbidity and mortality.

We compared the prognostic value of the C-reactive protein (CRP)-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR), and modified Glasgow prognostic score (mGPS) with the Sequential Organ Failure Assessment (SOFA) score in an intensive care unit (ICUs).

This study used the data of 53,877 adult patients admitted to an ICU between June 2013 and May 2022. Using the CAR, NLR, and mGPS values, as well as the SOFA score from the ICU, we conducted multivariable logistic regression analysis and used the receiver operating characteristic (ROC) curve to compare the predictive value for 28-day and 1-year mortality.

A total of 2419 patients (4.5%) died within 28 days, and 6209 (11.5%) patients died within 1 year. After an adjustment, all predictors were found to be independent risk factors for 28-day mortality (odds ratio [OR] 1.31, 95% confidence interval [CI] 1.29-1.33, p < 0.001 for the SOFA score; OR 1.05, 95% CI 1.03-1.07, p < 0.001 for CAR; OR 1.01, 95% CI 1.00-1.02, p < 0.001 for the NLR; and OR 1.19, 95% CI 1.08-1.30, p < 0.001 for the mGPS). This trend persisted for the 1-year mortality. In ROC curve analysis, the CAR showed better predictability than the NLR and mGPS. Furthermore, the predictive power of the CAR was significantly higher than that of the SOFA score for 1-year mortality.

The CAR, NLR, and mGPS values at ICU admission were independent risk factors of mortality after ICU admission. The predictive value of CAR was higher than that of the SOFA score for 1-year mortality. CAR assessment at ICU admission may be a feasible predictor of long-term mortality.

Multiple organ dysfunction syndrome (MODS) is common after sepsis and increases mortality. Lactate (Lac) can assess the prognosis of patients. Albumin (Alb) is closely associated with inflammatory response in sepsis patients. This work evaluated the predictive value of Lac/Alb for prognosis of sepsis patients.

Data of 160 sepsis patients were retrospectively collected. Lac and Alb levels were measured upon admission, at 24 hours and 48 hours later. Using 0.45 as the cutoff value for Lac/Alb, patients were rolled into high-level (HL) and low-level (LL) groups. MODS rates and mortality rates were analyzed. Receiver operating characteristic (ROC) curves were utilized to evaluate the predictive value of 48-hour Lac/Alb for patient prognosis. Correlation between Lac/Alb and APACHE II and SOFA scores was assessed.

The 12-month follow-up revealed 52 deaths (32.5%), and MODS occurred in 49 cases (30.6%) on the 7th day. The MODS group possessed elevated Lac and Lac/Alb and decreased Alb to the N-MODS group (P<0.05), and similar results were observed by comparison the survival and death group (P<0.05). The sensitivity, specificity, and area under the ROC curve (AUC) of Lac/Alb in predicting MODS were 81.63%, 85.59%, and 0.89, respectively, while those in predicting death were 94.23%, 88.89%, and 0.91, respectively. Lac/Alb was positively correlated with APACHE II and SOFA scores (r=0.718 and 0.808, respectively).

Lac/Alb was linked to MODS and mortality in sepsis patients and can be based to predict adverse outcomes.

The CRP/albumin ratio (CAR) is a mortality predictor in intensive care unit (ICU) patients. The aim of the current study was to investigate the ability of CAR to predict in-hospital mortality (IHM) in patients with isolated traumatic brain injury (iTBI). We performed a retrospective analysis including 200 patients with iTBI admitted to our neurosurgical intensive care unit (NICU) between September 2014 and December 2016. Serum biomarkers, demographic and radiological data, several ICU scores, and cardiopulmonary parameters were analyzed. The rate of IHM was 27.5% (55/200) and significantly associated with a higher AIS head score (p < 0.0001), a lower albumin level (p < 0.0001), and the necessity of a higher level of inspiratory oxygen fraction (p = 0.002). Furthermore, advanced age (odds ratio [OR] = 0.953, 95% confidence interval [CI] = 0.927-0.981, p = 0.001), a lower GCS score (OR = 1.347, 95% CI = 1.203-1.509, p < 0.0001), a higher level of lactate (OR = 0.506, 95% CI = 0.353-0.725, p < 0.0001), a higher CAR (OR = 0.547, 95% CI = 0.316-0.945, p = 0.031) and a higher norepinephrine application rate (OR = 0.000, 95% CI 0.000-0.090, p = 0.016) were identified as independent predictors of IHM. ROC analysis showed an association between IHM and a CAR cut-off value of >0.38 (Youden index 0.073, sensitivity: 27.9, specificity: 64.8, p = 0.044). We could identify a CAR > 0.38 as a new independent predictor for IHM in patients with iTBI.

We aimed to construct a validated nomogram model for predicting short-term (28-day) ischemic stroke mortality among critically ill populations.

We collected raw data from the Medical Information Mart for Intensive Care IV database, a comprehensive repository renowned for its depth and breadth in critical care information. Subsequently, a rigorous analytical framework was employed, incorporating a 10-fold cross-validation procedure to ensure robustness and reliability. Leveraging advanced statistical methodologies, specifically the least absolute shrinkage and selection operator regression, variables pertinent to 28-day mortality in ischemic stroke were meticulously screened. Next, binary logistic regression was utilized to establish nomogram, then applied concordance index to evaluate discrimination of the prediction models. Predictive performance of the nomogram was assessed by integrated discrimination improvement (IDI) and net reclassification index (NRI). Additionally, we generated calibration curves to assess calibrating ability. Finally, we evaluated the nomogram's net clinical benefit using decision curve analysis (DCA), in comparison with scoring systems clinically applied under common conditions.

A total of 2089 individuals were identified and assigned into training (n = 1443) or validation (n = 646) cohorts. Various identified risk factors, including age, ethnicity, marital status, underlying metastatic solid tumor, Charlson comorbidity index, heart rate, Glasgow coma scale, glucose concentrations, white blood cells, sodium concentrations, potassium concentrations, mechanical ventilation, use of heparin and mannitol, were associated with short-term (28-day) mortality in ischemic stroke individuals. A concordance index of 0.834 was obtained in the training dataset, indicating that our nomogram had good discriminating ability. Results of IDI and NRI in both cohorts proved that our nomogram had positive improvement of predictive performance, compared to other scoring systems. The actual and predicted incidence of mortality showed favorable concordance on calibration curves (P > 0.05). DCA curves revealed that, compared with scoring systems clinically used under common conditions, the constructed nomogram yielded a greater net clinical benefit.

Utilizing a comprehensive array of fourteen readily accessible variables, a prognostic nomogram was meticulously formulated and rigorously validated to provide precise prognostication of short-term mortality within the ischemic stroke cohort.

This study aims to develop an interpretable prediction model based on explainable artificial intelligence to predict bacterial sepsis and discover important biomarkers. A total of 1572 adult patients, 560 of whom were sepsis positive and 1012 of whom were negative, who were admitted to the emergency department with suspicion of sepsis, were examined. We investigated the performance characteristics of sepsis biomarkers alone and in combination for confirmed sepsis diagnosis using Sepsis-3 criteria. Three different tree-based algorithms-Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost)-were used for sepsis prediction, and after examining comprehensive performance metrics, descriptions of the optimal model were obtained with the SHAP method. The XGBoost model achieved accuracy of 0.898 (0.868-0.929) and area under the ROC curve (AUC) of 0.940 (0.898-0.980) with a 95% confidence interval. The five biomarkers for predicting sepsis were age, respiratory rate, oxygen saturation, procalcitonin, and positive blood culture. SHAP results revealed that older age, higher respiratory rate, procalcitonin, neutrophil-lymphocyte count ratio, C-reactive protein, plaque, leukocyte particle concentration, as well as lower oxygen saturation, systolic blood pressure, and hemoglobin levels increased the risk of sepsis. As a result, the Explainable Artificial Intelligence (XAI)-based prediction model can guide clinicians in the early diagnosis and treatment of sepsis, providing more effective sepsis management and potentially reducing mortality rates and medical costs.

Background: Blood lactate is a potentially useful biomarker to predict the mortality and severity of sepsis. The purpose of this study is to systematically review the ability of lactate to predict hierarchical sepsis clinical outcomes and distinguish sepsis, severe sepsis and septic shock. Methods: We conducted an exhaustive search of the PubMed, Embase and Cochrane Library databases for studies published before 1 October 2022. Inclusion criteria mandated the presence of case-control, cohort studies and randomized controlled trials that established the association between before-treatment blood lactate levels and the mortality of individuals with sepsis, severe sepsis or septic shock. Data was analyzed using STATA Version 16.0. Results: A total of 127 studies, encompassing 107,445 patients, were ultimately incorporated into our analysis. Meta-analysis of blood lactate levels at varying thresholds revealed a statistically significant elevation in blood lactate levels predicting mortality (OR = 1.57, 95% CI 1.48-1.65, I2 = 92.8%, p < 0.00001). Blood lactate levels were significantly higher in non-survivors compared to survivors in sepsis patients (SMD = 0.77, 95% CI 0.74-0.79, I2 = 83.7%, p = 0.000). The prognostic utility of blood lactate in sepsis mortality was validated through hierarchical summary receiver operating characteristic curve (HSROC) analysis, yielding an area under the curve (AUC) of 0.72 (95% CI 0.68-0.76), accompanied by a summary sensitivity of 0.65 (95% CI 0.59-0.7) and a summary specificity of 0.7 (95% CI 0.64-0.75). Unfortunately, the network meta-analysis could not identify any significant differences in average blood lactate values' assessments among sepsis, severe sepsis and septic shock patients. Conclusions: This meta-analysis demonstrated that high-level blood lactate was associated with a higher risk of sepsis mortality. Lactate has a relatively accurate predictive ability for the mortality risk of sepsis. However, the network analysis found that the levels of blood lactate were not effective in distinguishing between patients with sepsis, severe sepsis and septic shock.

Purpose: We aimed to investigate the association between the early mean arterial pressure (MAP)/norepinephrine equivalent dose (NEQ) index and mortality risk in patients with shock on vasopressors and further identify the breakpoint value of the MAP/NEQ index for high mortality risk. Methods: Based on the Medical Information Mart for Intensive Care IV database, we conducted a retrospective cohort study involving 19,539 eligible intensive care unit records assigned to three groups (first tertile, second tertile, and third tertile) by different MAP/NEQ indexes within 24 h of intensive care unit admission. The study outcomes were 7-, 14-, 21-, and 28-day mortality. A Cox model was used to examine the risk of mortality following different MAP/NEQ indexes. The receiving operating characteristic curve was used to evaluate the predictive ability of the MAP/NEQ index. The restricted cubic spline was applied to fit the flexible correlation between the MAP/NEQ index and risk of mortality, and segmented regression was further used to identify the breakpoint value of the MAP/NEQ index for high mortality risk. Results: Multivariate Cox analysis showed that a high MAP/NEQ index was independently associated with decreased mortality risks. The areas under the receiving operating characteristic curve of the MAP/NEQ index for different mortality outcomes were nearly 0.7. The MAP/NEQ index showed an L-shaped association with mortality outcomes or mortality risks. Exploration of the breakpoint value of the MAP/NEQ index suggested that a MAP/NEQ index less than 183 might be associated with a significantly increased mortality risk. Conclusions: An early low MAP/NEQ index was indicative of poor prognosis in patients with shock on vasopressors.

Neutrophils to lymphocytes and platelets (N/LP) ratio has been confirmed as an indirect marker of inflammation. In this study, we aimed to further evaluate the prognostic significance of the N/LP ratio in sepsis patients admitted to the ICU.

Sepsis patients from the Affiliated Hospital of Jiangsu University were retrospectively enrolled from January 2015 and July 2023. The primary outcomes were 30/60 days mortality. The secondary outcomes included the incidence of AKI, vasoactive drug, CRRT, invasive ventilation, length of ICU stay, length of hospital stay and ICU mortality.

A total of 1,066 sepsis patients were enrolled with a median age of 75.0 (66.0, 85.0) years, and 62.5% of them being male. The 30 days and 60 days mortality rates were found to be 28.7 and 34.0%, respectively, while the incidence of AKI was 45.2%. Based on their N/LP ratios, we classified the sepsis patients into three groups: low, middle, and high, consisting of 266, 534, and 266 patients, respectively. According the Cox proportional hazard model, the middle and high N/LP groups were associated with a 1.990/3.106-fold increase in 30 days mortality risk and a 2.066/3.046-fold increase in 60 days mortality risk compared with the low N/LP group. Besides, multivariate logistic regression model suggested that the risk of AKI occurrence increased 2.460 fold in the high group compared to the low group. However, through subgroup analyses, we observed substantial variations in the association between N/LP ratios and 30/60 days mortality rates as well as the incidence of AKI among different populations. Notably, the N/LP ratio measured at ICU admission exhibited a higher AUC for predicting 30/60 days mortality (0.684/0.687). Additionally, we observed a good predictive power for the occurrence of AKI (AUC: 0.645) using the N/LP ratio measured at sepsis prognosis. Regarding the other secondary outcomes, the N/LP ratio was associated with disease severity in sepsis patients, including the need for vasoactive drugs, length of ICU stay, and ICU mortality.

The N/LP ratio at ICU admission was found to have a significant independent association with 30/60 days mortality and the incidence of AKI in sepsis patients.

We aimed to determine the pathogens detected by the Gastrointestinal (GI) PCR panel in patients with acute gastroenteritis (AGE), the evaluation of antibiotic use in these patients, and the investigation of the role of laboratory parameters in differentiating viral and bacterial etiologies.

The demographic characteristics, GI PCR panel results, laboratory investigations, antibiotic usage, and appropriateness of antibiotic treatment were investigated in AGE patients.

A total of 175 adult patients with AGE and GI PCR panel results were included in the study. The most common pathogens were EPEC (24.6%) and C. difficile (18.3%). Among the 102 patients receiving antibiotic treatment, 34.3% were evaluated as inappropriate antibiotic use. WBC, CRP, procalcitonin, CRP/albumin ratio, and procalcitonin/albumin ratio were found to be significantly higher in cases with bacterial origin.

The utilization of GI PCR panels in AGE patients has revolutionized the field of diagnostics by providing rapid and accurate identification of pathogens. In units without the possibility of GI PCR testing, CRP, procalcitonin, CRP/albumin ratio and procalcitonin/albumin ratio may be useful in the decision of antibiotic treatment.

Apart from being one of the main causes of death, sepsis has recently been considered a chronic critical illness. This has resulted in the implementation of standard treatment recommendations for management, with a focus on the initial phases of treatment. Early detection of sepsis and prognostic grading are now crucial for management. Despite the fact that sequential organ failure assessment score (SOFA), acute physiology, and chronic health evaluation II score (APACHE II) have been widely used in sepsis, there have been shortcomings such as feasibility and many lab parameters involved. As a result, this study was conducted to evaluate the role of serum lactate as an early marker and to compare it to current scoring systems for determining the outcome of sepsis.

This was an observational hospital-based study with 60 individuals recruited over a one-year period from July 2021 to June 2022. Serum lactate, as well as the other laboratory tests required for the computation of SOFA and APACHE II, were performed. The baseline data and the trend of lactate vs standard scores were examined in the first 48 hours, as well as their impact on outcomes in sepsis patients (as measured by mortality rates- patients were followed up for 28 days). The diagnostic accuracy of these scores was calculated using the area under the receiver operating characteristic (ROC) curve (AUROC).

The study enrolled 60 people out of a total of 162 people who were screened. The mean age was 48.4 years, with the highest mortality occurring between the ages of 41 and 60 years. Of the total 60 participants, 34 (56.6%) were male, with the respiratory tract being the most common source of infection for sepsis (36.67%). In our study, 46 patients survived while 14 patients died. The mean lactate on admission was 3.1 mmol/L in survivors and 4 mmol/L in non-survivors, whereas APACHE II was 9 and 12.36, and SOFA was 3.63 and 7.79, respectively, in survivors and non-survivors. Serum lactate and prognosis scores were compared in the survivor and non-survivor groups, and the difference in diagnostic accuracy was found to be statistically significant.

Serum lactate can be used as an early recognition marker in patients with a probability of sepsis and serial lactate monitoring has a similar diagnostic accuracy in predicting outcomes as the traditional prognostic scoring systems SOFA and APACHE II.

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. There is a need for biomarkers that can be used for the diagnosis of sepsis and the early identification of patients at high risk of death. In this study, we aimed to investigate the relationship between Mid-regional pro-adrenomedullin (MR-proADM), procalcitonin (PCT), and copeptin in sepsis. A total of 28 sepsis, 32 septic shock, and 30 control patients were included in our prospective study. Patients' MR-proADM, PCT, and copeptin levels were recorded. Sequential organ failure assessment scores, length of hospital stay, and 30-day mortality were also recorded. These values were compared between the sepsis, septic shock, and control groups. The mean age of all participants was 64.04 ± 15.83 years. In the study, 37 (61.6%) patients were female and 23 (39.3%) were male. There was no statistically significant difference in gender/age between all patient groups and the control group (for all, p > 0.05). We found a significant difference between the survivors and nonsurvivors in terms of MR-proADM, PCT, and copeptin levels. There was a significant difference between the sepsis and septic shock groups in terms of MR-proADM and PCT. A significant correlation was found between the length of hospital stay and MR-proADM and copeptin. MR-proADM, PCT, and copeptin may be useful in the prognosis of sepsis and to predict the length of stay in hospital and mortality.

Cardiopulmonary bypass (CPB) can lead to lung injury and even acute respiratory distress syndrome (ARDS) through triggering systemic inflammatory response. The objective of this study was to investigate the impact of CPB time on clinical outcomes in patients with ARDS after cardiac surgery.

Totally, patients with ARDS after cardiac surgery in Beijing Anzhen Hospital from January 2005 to December 2015 were retrospectively included and were further divided into three groups according to the median time of CPB. The primary endpoints were the ICU mortality and in-hospital mortality, and ICU and hospital stay. Restricted cubic spline (RCS), logistic regression, cox regression model, and receiver operating characteristic (ROC) curve were adopted to explore the relationship between CPB time and clinical endpoints.

A total of 54,217 patients underwent cardiac surgery during the above period, of whom 210 patients developed ARDS after surgery and were finally included. The ICU mortality and in-hospital mortality were 21.0% and 41.9% in all ARDS patients after cardiac surgery respectively. Patients with long CPB time (CPB time ≥ 173 min) had longer length of ICU stay (P = 0.011), higher ICU (P < 0.001) mortality and in-hospital(P = 0.002) mortality compared with non-CPB patients (CPB = 0). For each ten minutes increment in CPB time, the hazards of a worse outcome increased by 13.3% for ICU mortality and 9.3% for in-hospital mortality after adjusting for potential factors. ROC curves showed CPB time presented more satisfactory power to predict mortality compared with APCHEII score. The optimal cut-off value of CPB time were 160.5 min for ICU mortality and in-hospital mortality.

Our findings demonstrated the significant prognostic value of CPB time in patients with ARDS after cardiac surgery. Longer time of CPB was associated with poorer clinical outcomes, and could be served as an indicator to predict short-term mortality in patients with ARDS after cardiac surgery.

The objective of this study was to evaluate the effectiveness of C-reactive protein (CRP)/albumin, erythrocyte sedimentation rate (ESR)/albumin ratio, ESR, CRP and albumin to differentiate bone and soft tissue infection in persons with diabetes. We retrospectively evaluated 242 individuals admitted to hospital with diabetes-related foot infections (DFI). We categorised DFI cases as either bone (OM) or soft tissue infection based on bone culture and/or histology. We evaluated the diagnostic accuracy of CRP, ESR, albumin, CRP/albumin and ESR/albumin as biomarkers to diagnose OM in persons with diabetes. The median age was 53 years (74% male). There were 224 diabetes-related patients of which 125 had been diagnosed with osteomyelitis. The ESR/albumin and CRP/albumin ratios cut-points were >17.84 and >1.83, respectively. ESR/albumin and CRP/albumin ratios had similar diagnostic parameters: AUC (0.71, 0.71), sensitivity (70.0%, 57.0%), specificity (62.0%, 75.0%), positive predictive value (67.0%, 71.0%) and negative predictive value (66.0% and 71.0%). In contrast diagnostic efficiency of CRP and ESR were AUC 0.71 and 0.71, sensitivity (45.6%, 71.2%), specificity (85.5%, 60.7%), positive predictive value (70.0%, 65.9%) and negative predictive value (59.5%, 66.4%), respectively. When comparing area under the curves, the results showed that ESR/albumin was not significantly different to ESR alone (Delong test pvs ESR  >0.1). Similarly, CRP/albumin was not significantly different to CRP alone (Delong test pvs CRP  >0.1). In conclusion, ESR/albumin and CRP/albumin ratios provided comparable results as using ESR and CRP alone.

Hyperbilirubinemia is often the first evidence for any kind of liver disorder and over one-third of all patients in intensive care units (ICU) show elevated bilirubin concentrations. In critically ill patients, high concentrations of serum bilirubin are correlated with a poor outcome. Therapies to lower bilirubin concentrations are often just symptomatically and their effect on the patients' outcome is hardly evaluated. Therefore, this study investigates whether the extracorporeal elimination of bilirubin with the cytokine adsorber CytoSorb® (CS) reduces mortality in patients with hyperbilirubinemia.

Patients with bilirubin concentrations >10 mg/dL at the ICU were screened for evaluation from 2018 to 2020. Patients with kidney replacement therapy and older than 18 years were included. Patients with continuously decreasing bilirubin concentrations after liver transplantation or other liver support systems (i.e., Molecular Adsorbents Recirculating System [MARS®], Advanced Organ Support [ADVOS]) were excluded. CS therapy was used in clinical routine and was indicated by the treating physicians. Statistical analysis was performed with IBM SPSS statistics utilizing a multivariate model. Primary outcome measure was the effect of CS on the 30-day mortality.

Data from 82 patients (mean Simplified Acute Physiology Score [SAPS] II: 74 points, mean bilirubin: 18 mg/dL, mean lactate: 3.7 mmol/L) were analyzed. There were no significant differences in patients with and without CS treatment. The multivariate model showed no significant effect of CS therapy (p = 0.402) on the 30-day mortality. In addition, a significant effect of bilirubin concentration (p = 0.274) or Model for End-Stage Liver Disease score (p = 0.928) on the 30-day mortality could not be shown. In contrast, lactate concentration (p = 0.001, b = 0.044) and SAPS II (p = 0.025, b = 0.008) had significant impact on 30-day mortality.

The use of CS in patients with hyperbilirubinemia did not result in a significant reduction in 30-day mortality. Randomized and controlled studies with mortality as primary outcome measure are needed in the future to justify their use.

To investigate the potential role and prognostic value of interleukin-15 (IL-15) in predicting 28-day mortality in elderly patients with sepsis.

According to the Sepsis-3.0 diagnostic criteria for sepsis, elderly patients with sepsis who were admitted to the emergency department of the Shi jingshan branch of Beijing Chaoyang Hospital between October 2021 and June 2022 were enrolled in this retrospective cohort study. After observation for 28 days, patients were divided into a survival group and a nonsurvival group. Samples for laboratory tests, baseline characteristic data, and SOFA and Acute Physiology and Chronic Health Evaluation (APACHE II) scores were collected or recorded within 24 h after admission to the emergency department. Quantitative detection of IL-15 was performed with a Luminex assay. Logistic regression analysis and receiver operating characteristic curve (ROC) analysis were conducted for comparison.

In total, 220 elderly patients with sepsis were enrolled, 69 of whom were in the survival group and 151 of whom were in the nonsurvival group at the 28-day interval. Systolic pressure, high-density lipoprotein (HDL), platelets (PLT) and albumin (ALB) were significantly higher in the survival group (P<0.05), while IL-15, SOFA, and APACHE II were significantly higher in the nonsurvival group (P<0.05). IL-15 was an independent risk factor associated with 28-day mortality (OR=1.842, 95% CI [1.323, 2.565]). The area under the receiver operating characteristic curve (AUROC) of IL-15 alone was 0.691 (95% CI [0.618, 0.764]), with a sensitivity of 46.67% and a specificity of 85.81%. The AUROC of the combined IL-15 and SOFA reached 0.880 (95% CI [0.672, 0.812]), for which the sensitivity and specificity were 80.95% and 85.08%, respectively.

IL-15 possesses the prognostic value for predicting 28-day mortality in elderly patients with sepsis.

Early evaluation of severe mycoplasma pneumoniae pneumonia (SMPP) and the prompt utilization of fiberoptic bronchoscopic manipulation can effectively alleviate complications and restrict the progression of sequelae. This study aim to establish a nomogram forecasting model for SMPP in children and explore an optimal early therapeutic bronchoalveolar lavage (TBAL) treatment strategy.

This retrospective study included children with mycoplasma pneumoniae pneumonia (MPP) from January 2019 to December 2021. Multivariate logistic regression analysis was used to screen independent risk factors for SMPP and establish a nomogram model. The bootstrap method was employed and a receiver operator characteristic (ROC) curve was drawn to evaluate the accuracy and robustness of the model. Kaplan-Meier analysis was used to assess the effect of lavage and hospitalization times.

A total of 244 cases were enrolled in the study, among whom 68 with SMPP and 176 with non-SMPP (NSMPP). A prediction model with five independent risk factors: left upper lobe computed tomography (CT) score, sequential organ failure assessment (SOFA) score, acute physiology and chronic health assessment (APACHE) II score, bronchitis score (BS), and c-reactive protein (CRP) was established based on the multivariate logistic regression analysis. The ROC curve of the prediction model showed the area under ROC curve (AUC) was 0.985 (95% confidence interval (CI) 0.972-0.997). The Hosmer-Lemeshow goodness-of-fit test results showed that the nomogram model predicted the risk of SMPP well (χ2 = 2.127, P = 0.977). The log-rank result suggested that an early BAL treatment could shorten MPP hospitalization time (P = 0.0057).

This nomogram model, based on the left upper lobe CT score, SOFA score, APACHE II score, BS, and CRP level, represents a valuable tool to predict the risk of SMPP in children and optimize the timing of TBAL.

Sepsis is one of the most common causes of death after surgery. Several conventional scoring systems have been developed to predict the outcome of sepsis; however, their predictive power is insufficient. The present study applies explainable machine-learning algorithms to improve the accuracy of predicting postoperative mortality in patients with sepsis caused by peritonitis.

We performed a retrospective analysis of data from demographic, clinical, and laboratory analyses, including the delta neutrophil index (DNI), WBC and neutrophil counts, and CRP level. Laboratory data were measured before surgery, 12-36 hours after surgery, and 60-84 hours after surgery. The primary study output was the probability of mortality. The areas under the receiver operating characteristic curves (AUCs) of several machine-learning algorithms using the Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score (SAPS) 3 models were compared. 'SHapley Additive exPlanations' values were used to indicate the direction of the relationship between a variable and mortality.

The CatBoost model yielded the highest AUC (0.933) for mortality compared to SAPS3 and SOFA (0.860 and 0.867, respectively). Increased DNI on day 3, septic shock, use of norepinephrine therapy, and increased international normalized ratio on day 3 had the greatest impact on the model's prediction of mortality.

Machine-learning algorithms increase the accuracy of predicting postoperative mortality in patients with sepsis caused by peritonitis.

Stroke is a major healthcare problem worldwide, particularly in the elderly population. Despite limited research on the development of prediction models for mortality in elderly individuals with ischemic stroke, our study aimed to address this knowledge gap. By leveraging data from the Medical Information Mart for Intensive Care IV database, we collected comprehensive raw data pertaining to elderly patients diagnosed with ischemic stroke. Through meticulous screening of clinical variables associated with 28-day mortality, we successfully established a robust nomogram. To assess the performance and clinical utility of our nomogram, various statistical analyses were conducted, including the concordance index, integrated discrimination improvement (IDI), net reclassification index (NRI), calibration curves and decision curve analysis (DCA). Our study comprised a total of 1259 individuals, who were further divided into training (n = 894) and validation (n = 365) cohorts. By identifying several common clinical features, we developed a nomogram that exhibited a concordance index of 0.809 in the training dataset. Notably, our findings demonstrated positive improvements in predictive performance through the IDI and NRI analyses in both cohorts. Furthermore, calibration curves indicated favorable agreement between the predicted and actual incidence of mortality (P > 0.05). DCA curves highlighted the substantial net clinical benefit of our nomogram compared to existing scoring systems used in routine clinical practice. In conclusion, our study successfully constructed and validated a prognostic nomogram, which enables accurate short-term mortality prediction in elderly individuals with ischemic stroke.

Flexible bronchoscopy (FB) plays an important role in critical care patients. But, critical care patients with respiratory failure are at an increased risk of developing complications. Considering the developments in intensive care unit care in recent years, we aimed to evaluate the use of FB in these patients. We retrospectively reviewed patients who underwent FB in critical care between 2014 and 2020. A total of 143 patients underwent FB during the study period. Arterial blood gas measurement on the FB day revealed a mean PaO2/FiO2 of 186.94±28.47. Eighty-one (56.6%) patients underwent an fiberoptic bronchoscopy procedure under conventional oxygen supplementation, 10 (7%) on noninvasive ventilation, 13 (9.1%) on high flow nasal cannula, and 39 (27.3%) on invasive mechanical ventilation. During and immediately after bronchoscopy, none of the patients experienced life-threatening complications. Fifty-five (38.5%) patients developed complications that could be controlled. Multivariate analysis indicated that increased Apache-II score and presence of cardiovascular disease were significantly associated with an increased complication risk. Although critical care patients with respiratory failure are more prone to complications, diagnostic and therapeutic bronchoscopy may be performed following appropriate patient selection, without leading to major complications.

C-reactive protein (CRP) to Albumin ratio (CAR) has been used in multiple clinical settings to predict early mortality. However, there is a lack of evidence on the predictive role of CAR in 30-day mortality after a hip fracture. The purpose of this study was to establish a potential association between CAR and 30-day mortality and to assess if the CAR Receiving Operating Characteristics curve (ROC) can be a reliable predictor of early mortality.

We retrospectively reviewed the charts of 676 patients (>65 years) treated for hip fracture between 2006 and 2018. All hip fractures were included. Treatment strategies included closed reduction and internal fixation, open reduction and internal fixation, hemiarthroplasty, or total joint arthroplasty. Statistical analysis included T-test, Pearson correlation for CAR and other markers, ROC curves and area under the curve, Youden Model, and Odds Ratio.

The 30-day mortality rate analysis showed that higher preoperative levels of CAR were associated with higher early mortality. When analyzing the area under the ROC curve (AUROC) for 30-day mortality, the reported value was 0.816. The point of the ROC curve corresponding to 14.72 was considered a cut-off with a specificity of 87% and a sensibility of 40.8%. When analyzing values higher than 14.72, the 30-day mortality rate was 17.9%, whilst, for values lower than 14.72, the 30-day mortality rate was 1.8%.

Patients older than 65 years affected by a hip fracture with increased preoperative levels of CAR are associated with higher 30-day mortality. Despite a moderate sensibility, considering the low cost and the predictivity of CAR, it should be considered a standard predictive marker.

In traumatic brain injury (TBI) patients, a complex cascade of inflammatory responses are frequently observed following trauma. Numerous dietary agents have long been found to have potential in modulating inflammatory responses. This pilot study, designed an enteral formula with low inflammatory properties based on the dietary inflammatory index (DII®) and evaluated its effect on inflammatory and metabolic factors in critically ill TBI patients. This single-blind randomized controlled pilot study was conducted at the Neurosurgical ICU of Shahid Kamyab Hospital (Mashhad, Iran). A total of 20 TBI patients were randomly assigned to receive either low-DII score or standard formula at the intensive care unit (ICU). The primary outcomes of the study included clinical status, inflammatory biomarkers, APACHE II, SAPS II, SOFA, and NUTRIC scores. The trial groups did not differ significantly in baseline values. Following 14 days of intervention, there was a statistically significant decrease in the APACHE II, SAPS II, and NUTRIC scores and a significant increase in the GCS score in the low-DII score formula group compared to the standard formula group. Over 2 weeks, high sensitivity C-reactive protein (hs-CRP) values of -2.73 (95% CI: -3.67, -1.79) mg/dL in the low-DII score formula group versus 0.65 (95% CI: -0.29, 1.58) mg/dL in controls were obtained. Moreover, the length of hospital stay was longer for the standard formula group than for the low-DII score formula group. The low-DII score formula improves inflammatory factors (serum hs-CRP) and metabolic biomarkers (LDL-c and FBS). Furthermore, clinical outcomes, including the length of hospital stay and disease severity, appear to be enhanced.

Malnutrition in critically ill patients is closely linked with clinical outcomes. During acute inflammatory states, nutrition cannot reverse the loss of body cell mass completely. Studies on nutritional screening and strategy considering metabolic changes have not yet been conducted. We aimed to identify nutrition strategies using the modified Nutrition Risk in the Critically ill (mNUTIRC) score. Nutrition support data, laboratory nutrition indicators, and prognosis indices were prospectively collected on the 2nd and 7th day after admission. It was to identify the effect of the changes on the metabolic status and critical target of nutrition intervention. To discriminate the high-risk group of malnutrition, receiver operating characteristic curves were plotted. Risk factors associated with 28 day-mortality were evaluated using multivariable Cox proportional hazards regression. A total of 490 and 266 patients were analyzed on the 2nd and 7th day, respectively. Only the mNUTRIC score showed significant differences in nutritional risk stratification. The use of vasopressors, hypoprotein supply (<1.0 g/kg/day), high mNUTRIC score, and hypoalbuminemia (<2.5 mg/dL) in the recovery phase were strongly associated with a 28-day mortality. The implementation of the mNUTRIC score and protein supply in the post-acute phase is critical to improve 28-day mortality in critically ill patients.

Critically ill patients with sepsis account for significant disease morbidity and healthcare costs. Sarcopenia has been proposed as an independent risk factor for poor short-term outcomes, although its effect on long-term outcomes remains unclear.

Retrospective cohort analysis of patients treated at a tertiary care medical center over 6 years (09/2014 - 12/2020). Critically ill patients meeting Sepsis-3 criteria were included, with sarcopenia defined by skeletal muscle index at the L3 lumbar area on abdominal Computed-Tomography scan. The prevalence of sarcopenia and its association with clinical outcomes was analyzed.

Sarcopenia was present in 34 (23%) of 150 patients, with median skeletal muscle indices of 28.1 cm 2 /m 2 and 37.3 cm 2 /m 2 in sarcopenic females and males, respectively. In-hospital mortality was not associated with sarcopenia when adjusted for age and illness severity. One year mortality was increased in sarcopenic patients, after adjustment for illness severity (HR 1.9, p = 0.02) and age (HR 2.4, p = 0.001). However, it was not associated with increased likelihood for discharge to long-term rehabilitation or hospice care in adjusted analyses.

Sarcopenia independently predicts one year mortality but is not associated with unfavorable hospital discharge disposition in critically ill patients with sepsis.

Status epilepticus (SE) is a common neurological emergency with unsatisfying prognoses, and accurate prediction of functional outcome is beneficial in clinical decision-making. The relationship between serum albumin concentration and outcome of SE patients has yet to be unveiled.

Clinical profiles of SE patients admitted to Xiangya Hospital, Central South University, from April 2017 to November 2020, were analyzed retrospectively. Outcomes of SE patients at discharge were divided into two groups based on the modified Rankin Scale (mRS): favorable outcome (mRS: 0-3) and unfavorable outcome (mRS: 4-6).

Fifty-one patients were enrolled. Unfavorable functional outcome at discharge was reported in 60.8% (31/51). Serum albumin concentration at admission and the Encephalitis-NCSE-Diazepam resistance-Image abnormalities-Tracheal intubation (END-IT) score remained independent predictors for functional outcome of SE patients. A lower albumin concentration at admission and higher END-IT score indicated a higher chance of unfavorable outcome for SE patients. The cut-off value of serum albumin to predict unfavorable outcome was 35.2 g/L, with a sensitivity of 67.7% and specificity of 85.0%, and an area under the receiver operating characteristic curve (ROC) of .738 (95% CI: .600-.876, p = .004). The preferable END-IT score with optimal sensitivity (74.2%) and specificity (60%) was 2 and the area under the ROC was .742, with 95% CI of .608-.876 (p = .004).

Serum albumin concentration at admission and the END-IT score are two independent predictive factors for short-term outcome of SE patients, moreover, the serum albumin concentration is not inferior to the END-IT score in indicating functional outcome at discharge.

To date, the Clavien-Dindo classification system represents the most popular assessment tool of postoperative events that ranks surgical complications by the extent of respective required therapeutic interventions. This uniform grading system allows for an objective evaluation of outcomes from a surgical procedure by accurately and standardly defining surgical complications. However, many scientists have meanwhile heavily criticized the Clavien-Dindo classification system as an overly generalized and conservative grading system that requires modification. Herein, we aim to explain the need for reconsideration of the Clavien-Dindo classification system, and discuss the features of an ideal system for the classification of complications that should evaluate not only surgical complications, but also the risk and patient's general performance status.

Systemic inflammatory response syndrome (SIRS) and sepsis are inflammatory responses to infection or trauma, causing symptoms and adverse outcomes such as organ shutdown and death. Different scoring systems can help in the diagnosis of SIRS and sepsis. Several biomarkers such as C-reactive protein (CRP), procalcitonin (PCT), and white blood cells (WBCs) can serve as predictors of sepsis. Surgery, trauma, and burns are the non-inflammatory causes of SIRS and sepsis. In postoperative patients, both inflammatory and non-inflammatory causes of immune response may co-exist. The role of inflammatory biomarkers in identifying sepsis development, deciding to use antibiotics, and discharging patients needs further exploration and clarity. We searched medical databases such as PubMed/Medline, PMC, ScienceDirect, Cochrane Library, and Google Scholar for relevant medical literature. The identified papers were screened, eligibility criteria were applied, and 15 research papers were identified. The finalized papers explored the roles of CRP and PCT in postoperative patients. Both CRP and PCT are raised in a postoperative patient, and then, gradually, the levels decrease. However, in case of an infection, these levels continue to rise and signify an infection, which may progress to sepsis. The cut-off values can guide decision-making about when to start antibiotics and discharge the patient. PCT was found to be more reliable in identifying the infection and preventing the development of sepsis. Further research is needed to identify the exact cut-off values that can help in decision-making.

Patients with severe acute respiratory distress syndrome (ARDS) have high mortality rates; therefore, new biomarkers are necessary to predict the prognosis in the early stages. Serum lactate dehydrogenase (LDH) level is a specific marker of lung damage, but it is not sensitive because it is affected by several factors. This study aimed to determine whether the LDH/albumin ratio could be used as a prognostic biomarker in patients with severe ARDS due to COVID 19.

Tertiary intensive care unit (ICU) patients with severe ARDS and confirmed COVID-19 diagnosis between August 1, 2020, and October 31, 2021, were included. The demographic and clinical characteristics of the patients were recorded from the hospital databases, together with laboratory results on the day of admission to the ICU and the length of stay in the ICU and hospital. LDH/albumin, lactate/albumin, C-reactive protein (CRP)/albumin, and BUN/albumin ratios were calculated. Logistic regression analysis was performed to determine independent risk factors affecting mortality.

Nine hundred and five patients hospitalized in a tertiary ICU were evaluated. Three hundred fifty-one patients with severe ARDS were included in this study. The mortality rate of the included patients was 61.8% (of 217/351). LDH/albumin, lactate/albumin, and BUN/albumin ratios were higher in the nonsurvivor group (P < .001). The area under the curve (AUC) from the receiver operating characteristic analysis that predicted in-hospital mortality was 0.627 (95% confidence intervals (CI): 0.574-0.678, P < .001) for the LDH/albumin ratio, 0.605 (95% CI: 0.551-0.656, P < .001) for lactate/albumin, and 0.638 (95% CI: 0.585-0.688, P < .001) for BUN/albumin. However, LDH/albumin ratio was independently associated with mortality in multivariate logistic regression analysis.

LDH/albumin ratio can be used as an independent prognostic factor for mortality in patients with severe ARDS caused by COVID-19.