Little is known about acute kidney injury (AKI) and acute kidney disease (AKD) in patients with chronic obstructive pulmonary disease (COPD) and COPD mortality based on the acute/subacute renal injury. This study develops machine learning models to predict AKI, AKD, and mortality in COPD patients, utilizing web applications for clinical decisions.

We included 2,829 inpatients from January 2016 to December 2018. Data were split into 80% for training and 20% for testing. Eight machine learning algorithms were used, and model performance was evaluated using various metrics. SHAP was used to visualize the decision process. The best models, assessed using AUROC were used to develop web applications for identifying high-risk patients.

The incidence rates were 13.71% for AKI and 15.11% for AKD. The overall mortality rate was 4.84%. LightGBM performed best with AUROC of 0.815, 0.827, and 0.934 in AKI, AKD, and mortality, respectively. Key predictors for AKI were Scr, neutrophil percentage, cystatin c, BUN, and LDH. For AKD, the key predictors were age, AKI grade, HDL-C, Scr, and BUN. The key predictors for mortality included the use of dopamine and epinephrine drugs, cystatin c, renal function trajectory, albumin, and neutrophil percentage. Force plots visualized the prediction process for individual patients.

The incidence of AKI and AKD is significant in patients with COPD. Renal function trajectory is crucial for predicting mortality in these patients. Web applications were developed to predict AKI, AKD, and mortality, improving prognosis by identifying high-risk patients and reducing adverse events and disease progression.

Hypervolemia is associated with worse outcomes in critically ill patients with acute respiratory distress syndrome (ARDS), with early positive fluid balance linked to longer intensive care unit (ICU) stays, prolonged ventilatory support, and increased mortality risk due to cardiopulmonary complications, lung edema, and extrapulmonary organ dysfunction. However, a restrictive fluid management strategy is associated with hypoperfusion and distal organ dysfunction, including acute renal failure and cognitive impairment. Indeed, fluid administration in patients with ARDS represents a challenge, as it must take into account the underlying condition, such as sepsis or acute brain injury (ABI), where optimal fluid management is a major determinant of disease outcome. In such cases, the approach to fluid administration should be individualized based on hemodynamic and clinical parameters according to the course of the disease. The strategy of "salvage, optimization, stabilization, and de-escalation" can guide fluid administration in the initial therapeutic approach, whereas negative fluid balance with the use of diuretics or renal replacement therapy (RRT) should be the goal once hemodynamic stabilization has been achieved.

Acute kidney injury (AKI) is a frequent complication in critically ill patients and triggers a systemic inflammatory response that can contribute to lung injury, ultimately worsening clinical outcomes. However, diagnostic and therapeutic strategies remain unavailable. In this issue of the JCI, Komaru et al. explored leukocyte trafficking and vascular pooling following AKI in mice as an underlying mechanism of acute lung injury. Using intravital microscopy, the authors observed rapid accumulation of neutrophils in pulmonary capillaries within minutes of AKI onset. These neutrophils followed monocytes and slowed blood flow. Notably, disruption of this process improved oxygenation. The findings provide insights into this complex inter-organ crosstalk and open avenues for future research.

To compare the incidence and drivers of major adverse kidney events (MAKEs) between COVID-19 and non-COVID-19 acute respiratory distress syndrome (ARDS) patients, with a focus on long-term kidney outcomes.

Retrospective cohort study.

Single-centre intensive care unit in the Midlands, UK.

708 ARDS patients (458 COVID-19, 250 non-COVID-19).

The primary outcome was MAKE at 365 days (MAKE-365), defined as new renal replacement therapy (RRT), estimated glomerular filtration rate (eGFR) <75% of baseline or all-cause mortality. Secondary analyses examined non-mortality MAKE components.

The incidence of MAKE-365 was significantly higher in the non-COVID-19 group compared with the COVID-19 group (66% vs 39%, p<0.001), primarily driven by increased RRT initiation, followed by mortality and eGFR decline (p=0.055). Independent predictors of MAKE-365 included lower eGFR and elevated bilirubin in both groups. Age (p<0.001) and diabetes (p=0.041) were additional predictors in the COVID-19 cohort, while lower albumin (p=0.002) was significant in the non-COVID-19 group. Excluding mortality, RRT and eGFR decline remained significant drivers of MAKE outcomes in the non-COVID-19 cohort.

Non-COVID-19 ARDS patients face a greater risk of MAKE-365 and adverse kidney outcomes due to higher RRT requirements and mortality rates. These findings underscore the importance of tailored interventions and long-term nephrology follow-up, particularly for patients with reduced eGFR, elevated bilirubin and comorbidities like diabetes and hypoalbuminaemia.

The single nucleotide polymorphism rs12979860 is associated with the production of IFNλ4, a type III interferon, which offers protection from viral infection via its proinflammatory properties. We investigated if a genetically determined increase in IFNλ4 affects disease progression in SARS-CoV-2. This prospective, single-center study involved critically ill SARS-CoV-2 patients admitted to the intensive care unit. We performed genotyping for rs12979860 and analyzed daily laboratory data. Genotype frequencies were compared with an external validation cohort. Critically ill individuals with COVID-19 (n = 184; 29.3% women) were included. Median age was 63 years. The TT genotype was present in 11%, CT in 48% and CC in 41%. At baseline, CRP, ferritin, transferrin and neopterin did not differ significantly between groups. Longitudinal analysis revealed significant genotype-dependent differences in CRP, ferritin and neopterin with the highest peak in TT patients after 10-15 days. A higher need for renal replacement therapy (31.6% vs. 11.7%, p = 0.044) and mechanical ventilation (22 days vs. 15 days, p = 0.018) was observed in the TT group. The SNP rs12979860 near IFNL4 is associated with distinct inflammatory trajectories in critically ill COVID-19 patients. Genetic determinants of the immune response influence the severity of inflammation and clinical outcomes in severe COVID-19.

The present study aimed to explore the anti-inflammatory mechanism of dexmedetomidine (Dex), an α2-adrenoceptor (α2-AR) agonist, in renal ischemia-reperfusion (RIR)-induced acute lung injury (ALI).

RIR was induced in C57BL/6J mice by bilateral renal pedicles occlusion for 60 min followed by 24 h of reperfusion. Mice were pretreated with Dex alone or in combination with atipamezole (Atip), an α2-AR antagonist. Pulmonary histopathological assessment, arterial blood gas analysis, cell count and multiple cytokine examination in bronchoalveolar lavage fluid (BALF), evaluation of the global inflammation status in lung tissue, and investigation of alveolar macrophage phenotypes were carried out. In vitro, the polarization of mouse alveolar macrophages (MH-S) treated with serum from normal or RIR mice was indirectly detected by quantitative polymerase chain reaction (qPCR).

The findings demonstrated that, in comparison to RIR animals, dexmedetomidine mitigated lung injury and remarkably promoted macrophage polarization towards an anti-inflammatory M2 phenotype in the pulmonary tissue. Concurrently, a reduction in inflammatory cell infiltration and levels of pro-inflammatory cytokines was observed. In vitro studies verified that dexmedetomidine directed MH-S towards the M2 phenotype after stimulation with RIR serum. However, these effects were mostly reversed following administration of atipamezole.

Dexmedetomidine alleviates renal ischemia-reperfusion-induced ALI by activating α2-adrenoceptor, thereby inducing macrophage polarization towards an anti-inflammatory phenotype and reducing pulmonary global inflammation.

The published version of the manuscript (D´iaz, Hoffman, Hejazi Lifetime Data Anal 30, 213-236, 2024) contained an error (We would like to thank Kara Rudolph for pointing out an issue that led to uncovering the error)) in the definition of the outcome that had cascading effects and created errors in the definition of multiple objects in the paper. We correct those errors here. For completeness, we reproduce the entire manuscript, underlining places where we made a correction.Longitudinal modified treatment policies (LMTP) have been recently developed as a novel method to define and estimate causal parameters that depend on the natural value of treatment. LMTPs represent an important advancement in causal inference for longitudinal studies as they allow the non-parametric definition and estimation of the joint effect of multiple categorical, ordinal, or continuous treatments measured at several time points. We extend the LMTP methodology to problems in which the outcome is a time-to-event variable subject to a competing event that precludes observation of the event of interest. We present identification results and non-parametric locally efficient estimators that use flexible data-adaptive regression techniques to alleviate model misspecification bias, while retaining important asymptotic properties such as n -consistency. We present an application to the estimation of the effect of the time-to-intubation on acute kidney injury amongst COVID- 19 hospitalized patients, where death by other causes is taken to be the competing event.

Sex differences exist in acute kidney injury (AKI), and the role that sex and gender play along the AKI care continuum remains unclear. The 33rd Acute Disease Quality Initiative meeting evaluated available data on the role of sex and gender in AKI and identified knowledge gaps. Data from experimental models, pathophysiology, epidemiology, clinical care, gender, social determinants of health, education, and advocacy were reviewed. Recommendations include incorporating sex and gender into research along the bench-to-bedside spectrum; analyzing sex-stratified results; evaluating the effects of sex chromosomes, hormones, and gender on outcomes; considering fluctuations of hormone levels; studying the impact gender may have on access to care; and developing educational tools to inform patients, providers, and stakeholders. This meeting report summarizes what is known about sex and gender along the AKI care continuum and proposes an agenda for translational discovery to elucidate the role of sex and gender in AKI across the lifespan.

Diagnosing septic shock promptly is essential but challenging, especially due to its clinical similarity to non-septic shock. Extracellular vesicle-derived miRNAs may serve as biomarkers to distinguish septic shock from non-septic shock, providing a more accurate diagnostic tool for postsurgical patients. This study aims to identify extracellular vesicle-derived miRNA signatures that differentiate septic shock from non-septic shock in postsurgical patients, potentially improving diagnostic accuracy and clinical decision-making.

A multicentre, prospective study was conducted on miRNA profiles in shock patients. Two cohorts were recruited from the Intensive Care Units of two Spanish hospitals: a discovery cohort with 109 patients and a validation cohort with 52 patients. Plasma samples were collected within 24 h of shock diagnosis and subjected to miRNA sequencing. High-throughput sequencing data from the discovery cohort were analysed to identify differentially expressed miRNAs. These findings were validated via qPCR in the validation cohort.

Thirty miRNAs were identified as significantly differentially expressed between septic and non-septic shock patients. Among these, six miRNAs-miR-100-5p, miR-484, miR-10a-5p, miR-148a-3p, miR-342-3p, and miR-451a-demonstrated strong diagnostic capabilities for septic shock. A combination of miR-100-5p, miR-148a-3p, and miR-451a achieved an area under the curve of 0.894, with qPCR validation in the validation cohort yielding an area under the curve of 0.960.

This study highlights extracellular vesicle-derived miRNAs as promising biomarkers for differentiating septic from non-septic shock. The identified three-miRNA signature has significant potential to enhance septic shock diagnosis, thereby aiding in timely and appropriate treatment for postsurgical patients.

Compared with other solid organ transplantation, the morbidity rate of acute kidney injury is higher in lung transplantation. Our research was designed to examine the occurrence rate and risk factors for acute kidney injury after lung transplantation through a systematic review and meta-analysis.

We conducted a database search for case-control studies and cohort studies on the occurrence rate and risk factors for acute kidney injury after lung transplantation up to August 19, 2023. Stata 15.0 was used for data analysis.

Nineteen case-control or cohort studies were included, involving 1,755 cases of acute kidney injury after lung transplantation and 1,404 cases of non-acute kidney injury after lung transplantation. Based on the meta-analysis, the risk factors for acute kidney injury after lung transplantation included pulmonary fibrosis (OR, 1.34; CI [1.09-1.65]), hypertension (OR, 1.30; CI [1.07-1.58]), pre-op mechanical ventilation (OR, 3.30; CI [1.84-5.90]), pre-op extracorporeal membrane oxygenation (OR, 3.70; CI [2.51-5.45]), double lung transplantation (OR, 1.91; CI [1.45-2.53]), cardiopulmonary bypass support (OR, 1.82; CI [1.38-2.40]), cardiovascular events (OR, 1.50; CI [1.15-1.96]), intra-op hypotension (OR, 2.70; CI [1.42-5.14]), post-op extracorporeal membrane oxygenation (OR, 1.90; CI [1.20-3.01]), sepsis (OR, 3.20; CI [2.16-4.73]), dialysis (OR, 12.79; CI [6.11-26.8]).

Based on the existing evidence, clinical professionals can implement early detection, diagnosis and treatment of patients with acute kidney injury after lung transplantation, to improve the quality of life of these patients.

Approximately 30% of the patients with cancer experience kidney complications, which hinder optimal cancer management, imposing a burden on patients' quality of life and the healthcare system. The etiology of kidney complications in patients with cancer is often attributed to oncological therapies. However, the direct impact of cancer on kidney health is underestimated. Our previous study demonstrated that metastatic lung cancer adversely alters the kidney and exacerbates chemotherapy-induced nephrotoxicity, indicating lung cancer-kidney crosstalk. The current study examines whether this phenomenon is specific to the employed cancer model. Female and male mice of various strains were injected with different cell lines of remote organ cancer, and their kidney tissues were analyzed for toxicity and fibrosis. The impact of cancer on the kidney varied by cancer type. Breast cancer and specific subtypes of lung cancer, including KRAS- and epidermal growth factor receptor (EGFR)-mutant cancer, pathologically altered kidney physiology and function in a manner dependent on the metastatic potential of the cell line. This was independent of mouse strain, sex, and cancer cell line origin. Moreover, tumor DNA was not detected in the renal tissue, excluding metastases to the kidney as a causative factor for the observed pathological alterations. Lewis lung carcinoma and B16 melanoma did not cause nephrotoxicity, regardless of the tumor size. Our results confirm cancer-kidney crosstalk in specific cancer types. In the era of precision medicine, further research is essential to identify at-risk oncology populations, enabling early detection and management of renal complications.NEW & NOTEWORTHY Patients with cancer frequently experience kidney complications, often attributed to antineoplastic therapies. This emphasis on therapy-induced nephrotoxicity has led to the underestimation of the impact of cancer on the kidney. Our study demonstrates that distant organ cancer is sufficient to induce nephrotoxicity, highlighting the existence of cancer-kidney crosstalk. Our findings underscore a gap in our understanding of renal complications in patients with cancer and provide a rationale for identifying the underlying mechanisms for the development of nephroprotective agents.

Sepsis leads to dysfunctional immune responses with multi-organ damage, and acute kidney injury (AKI) is a common complication of sepsis. To gain a deeper understanding of the specific underlying mechanisms of sepsis, we investigated the effects of specific macrophages on sepsis. To gain a deeper understanding of the specific underlying mechanisms of sepsis, we investigated the effects of specific macrophages on sepsis. Single-cell sequencing of a mouse model of endotoxemia revealed that sepsis is a common complication of sepsis. Single-cell sequencing of a mouse model of endotoxemia revealed that the emerging macrophage subpopulation Ccl5+ Mac was significantly pro-inflammatory, activating a large number of pathways activating a large number of pathways associated with immune response and inflammatory response, including IL6-JAK-STAT3 signaling, TGF-β signaling, and inflammatory response. Interestingly, we found that Ccl5+ Mac recruits neutrophil through CCL5-CCR1 ligand receptor pairs by cellular communication analysis thereby further affecting sepsis. We therefore hypothesize that this macrophage subpopulation is actively involved in the underlying molecular mechanisms of AKI. We therefore hypothesize that this macrophage subpopulation is actively involved in the underlying molecular mechanisms of AKI in sepsis and provide valuable insights.

Acute kidney injury (AKI) is a severe complication in critical patients receiving invasive mechanical ventilation (MV). However, AKI which occurs in the first 48 h after MV (early AKI) and thus likely associated with the MV settings is probably different from AKI occurring following 48 h (late AKI). This study is aimed at exploring the incidence of early and late AKI in elderly patients receiving MV and identifying their different risk factors and outcomes.

This retrospective, observational, multicenter cohort study consecutively included 3271 elderly patients (≥ 75 years) receiving invasive MV at four medical centers of Chinese PLA General Hospital from 2008 to 2020. The diagnosis of AKI was made following the 2012 KDIGO criteria and categorized into early (≤ 48 h) or late (> 48 h-7 days) according to the time from MV.

There were totally 1292 cases enrolled for the final analysis. Among them, 376 patients (29.1%) developed early AKI versus 132 (10.2%) developed late AKI. The 28-day mortality rates of the non-AKI, early AKI, and late AKI patients were 14.4, 46.8, and 61.4%, respectively. After 90 days, mortality rates of three groups were 33.2, 60.6, and 72.7%, respectively. Risk factors for early AKI included PaO2/FIO2, serum creatinine, hemoglobin, and positive end-expiratory pressure at the beginning of MV, while those for late AKI were PaO2/FIO2, serum creatinine, and hemoglobin. In the multivariable adjusted analysis, both early AKI (HR = 4.035; 95% CI = 3.166-5.142; P < 0.001) and late AKI (HR = 6.272; 95% CI = 4.654-8.453; P < 0.001) were related to the increased 28-day mortality relative to non-AKI. AKI was significantly related to 90-day mortality: early AKI (HR = 2.569; 95% CI = 2.142-3.082; P < 0.001) and late AKI (HR = 3.692; 95% CI = 2.890-4.716; P < 0.001).

AKI mostly develops in the initial 48 h following MV, which is related to the health and MV settings; while AKI occurring following 48 h is not associated with MV settings. Therefore, a strategy for kidney protection in patients with MV should take these differences into consideration.

The purpose of this study was to investigate the correlation between different subtypes of acute kidney injury (AKI) and clinical outcomes following lung transplantation (LTx) and to identify a reliable indicator for predicting poor prognosis in the LTx population.

We retrospectively analyzed the clinical data of 279 LTx patients from August 2016 to March 2023. The AKI subtypes included AKI, persistent AKI on Day 7 (P7-AKI) and Day 14 (P14-AKI) after LTx, and AKI stages. The correlations of these factors with respiratory outcomes, mortality at 90 days, mortality at 1 year and data finalization were assessed, and the risk factors for the selected AKI subtypes were evaluated.

AKI occurred in 215 patients (77.1%), with 129 (46.2%) experiencing P7-AKI and 95 (34.1%) experiencing P14-AKI. P7-AKI was associated with more respiratory and mortality outcomes than were AKI and AKI stages, and P7-AKI surpassed P14-AKI in terms of a shorter diagnostic time. After adjusting for age, sex, BMI, type of transplant, transplant diagnosis and comorbidities, P7-AKI independently correlated with increased mortality risk at 90 days [HR 12.312 (95% CI: 2.839-53.402)], 1 year [HR 3.847 (95% CI: 1.840-8.044)], and data finalization [HR 2.010 (95% CI: 1.331-3.033)]. Five variables were identified as independent predictors for P7-AKI, including preoperative body mass index, prothrombin activity, hemoglobin and serum creatinine, and intraoperative colloid administration.

P7-AKI has been identified as a reliable indicator for predicting adverse outcomes in LTx patients, which may assist healthcare professionals in identifying high-risk individuals.

Patients with COVID-19 may experience a persistent increase in the blood urea nitrogen over creatinine ratio (PI-BUN/Cr). Its elevation could reflect multiple underlying pathophysiological processes beyond prerenal injury but also warrants nuanced interpretation due to its complex interplay with various factors, underscoring the importance of investigating its effects on mortality and acute kidney injury in this population.

We analized a retrospective and longitudinal cohort of patients admitted to a single center in Mexico City for patients with severe COVID-19. Between March 5, 2020 and August 25, 2021, we included patients with confirmed positive diagnosis for SARS-CoV-2, age > 18 years, disease severity was defined by clinical data of respiratory distress syndrome and a ratio of partial oxygen pressure to inspired oxygen fraction < 300 mmHg on admission. We excluded patients with End Stage Kidney Disease. Data was obtained from electronic medical records. PI-BUN/Cr was defined as an increase in the BUN/Cr ratio > 30 in more than 60% of measurements in the hospital. The outcomes included: risk factors to mortality and AKI in-hospital.

The cohort included 3,007 patients with a median age of 54.6 ± 14.5 years. 35% of patients died; 44.6% developed PI-BUN/Cr ratio and 71.4% AKI. Mortality was associated with older age > 60 years [Hazard ratio (HR)] = 1.45, 95% CI: 1.28-1.65; p < 0.001); male (HR 1.25, 95% CI 1.09-1.44; p = 0.002) and AKI (HR 3.29, 95% CI 2.42-4.46; p < 0.001); PI-BUN/CR & Non-AKI (HR = 2.82, 95% CI: 1.61-4.93; p < 0.001); Non PI-BUN/CR & AKI (HR = 5.47, 95% CI: 3.54-8.44; p < 0.001); and PI-BUN/CR & AKI (HR = 4.26, 95% CI: 2.75-6.62, p < 0.001). Only hiperuricemia was a risk factor for AKI (HR = 1.71, 95% CI: 1.30-2.25, p < 0.001).

While PI-BUN/Cr alone may not directly associate with mortality, its capacity to sub-phenotype patients according to their AKI status holds significant promise in offering valuable insights into patient prognosis and outcomes. Understanding the nuanced relationship between PI-BUN/Cr and AKI enhances our comprehension of renal function dynamics. It equips healthcare providers with a refined tool for risk stratification and personalized patient management strategies.

Acute respiratory distress syndrome (ARDS) is associated with high mortality rates, which are further exacerbated when accompanied by acute kidney injury (AKI). Presently, there is a lack of comprehensive studies thoroughly elucidating the metabolic dysregulation in ARDS patients with AKI leading to poor outcomes. We hypothesized that metabolomics can be a potent tool to highlight the differences in the metabolic profile unraveling unidentified pathophysiological mechanisms of ARDS patients with and without AKI. 1H nuclear magnetic resonance spectroscopy was used to identify key metabolites in the serum samples of 75 patients. Distinct clusters of both groups were obtained as the study's primary outcome using multivariate analysis. Notable alternations in the levels of nine metabolites were identified. Pathway analysis revealed the dysregulation of five significant cycles, which resulted in various complications, such as hyperammonemia, higher energy requirements, and mitochondrial dysfunction causing oxidative stress. Identified metabolites also showed a significant correlation with clinical scores, indicating severity. This study shows the alterations in the metabolite concentration highlighting the difference in the pathophysiology of both patient groups and its association with outcome, pointing in the direction of a personalized medicine approach and holding significant promise for application in critical care settings to improve clinical outcomes.

Internal fixation for multiple rib fractures is well established. Patients with underlying chronic obstructive pulmonary disease (COPD) have a higher rate of perioperative complications. It is unclear if these patients are suitable candidates for internal fixation and if surgical interventions are harmful to these patients.

Adult patients with ≥ 3 rib fractures and underlying COPD from the Trauma Quality Improvement Program between 2017 and 2019 were eligible for inclusion. The patients were divided into two treatment groups: operative and non-operative. Furthermore, inverse probability treatment weighting was applied to analyze mortality and adverse hospital events.

Patients with COPD in the operative group had higher ventilator use (odds ratio [OR], 3.211; 95% confidence interval [CI], 1.993-5.175; p < 0.001). Additionally, they had a longer length of stay (coefficient β, 4.139; standard error, 0.829; p < 0.001) and longer ventilator days (coefficient β, 1.937; standard error, 0.655; p = 0.003) than in the non-operative group. Furthermore, the mortality rate was lower in the operative group than in the non-operative group (OR, 0.426; 95% CI, 0.228-0.798; p = 0.008).

Internal fixation of rib fractures plays a crucial role in patients with underlying COPD disease. They presented a better mortality rate without an increased perioperative complication rate.

This narrative review delves into the intricate interplay between the lungs and the kidneys, with a focus on elucidating the pathogenesis of diseases influenced by immunological factors, acid-base regulation, and blood gas disturbances, as well as assessing the effects of various therapeutic modalities on these interactions. Key disorders, such as anti-glomerular basement membrane (anti-GBM) disease, the syndrome of inappropriate antidiuretic hormone secretion (SIADH), and Anti-neutrophil Cytoplasmic Antibodies (ANCA) associated vasculitis (AAV), are also examined to shed light on their underlying mechanisms. This review also explores the relationship between acute respiratory distress syndrome (ARDS) and acute kidney injury (AKI), emphasizing how inflammatory mediators can lead to systemic damage and impact multiple organs. In ARDS, fluid overload exacerbates pulmonary edema, while imbalances in blood volume, such as hypovolemia or hypervolemia, can precipitate renal dysfunction. The review highlights how mechanical ventilation strategies can compromise renal blood flow, trigger systemic inflammation, and induce hemodynamic and neurohormonal alterations, all contributing to lung and kidney damage. The impact of extracorporeal membrane oxygenation (ECMO) on lung-kidney interactions is evaluated, highlighting its role in severe respiratory failure and its renal implications. Emerging therapies, such as mesenchymal stem cells and extracellular vesicles, are discussed as promising avenues to mitigate organ damage and enhance outcomes in critically ill patients. Overall, this review offers a nuanced exploration of lung-kidney dynamics, bridging historical insights with contemporary perspectives. It underscores the clinical significance of these interactions in critically ill patients and advocates for integrated management approaches to optimize patient outcomes.

Approximately 30% of cancer patients experience kidney complications, which hinder optimal cancer management, imposing a burden on patients' quality of life and the healthcare system. The etiology of kidney complications in cancer patients is often attributed to nephrotoxic oncological therapies. However, the direct impact of cancer on kidney health is underestimated, as most nephrotoxic oncological therapies have been studied in animal models that do not have cancer. Our previous study demonstrated that advanced lung cancer adversely alters kidney physiology and function, and exacerbates chemotherapy-induced nephrotoxicity, indicating lung cancer-kidney crosstalk. This study examines whether this phenomenon is specific to the employed cancer model. Female and male mice of various strains were injected with different cell lines representing human and mouse lung cancer, breast cancer, and melanoma, and their kidney tissues were analyzed for toxicity and fibrosis. The impact of cancer on the kidney varied by cancer type. Breast cancer and specific subtypes of lung cancer, including KRAS- and EGFR-mutant cancer, pathologically altered kidney physiology and function in a manner dependent on the metastatic potential of the cell line. This was independent of mouse strain, sex, and cancer cell line origin. Moreover, tumor DNA was not detected in the renal tissue, excluding metastases to the kidney as a causative factor for the observed pathological alterations. Lewis lung carcinoma and B16 melanoma did not cause nephrotoxicity, regardless of the tumor size. Our results confirm cancer-kidney crosstalk in specific cancer types and highlight gaps in understanding the risk of renal complications in cancer patients. In the era of precision medicine, further research is essential to identify at-risk oncology populations, enabling early detection and management of renal complications.

Early detection is a key strategy to prevent kidney disease, its progression and related complications, but numerous studies show that awareness of kidney disease at the population level is low. Therefore, increasing knowledge and implementing sustainable solutions for early detection of kidney disease are public health priorities. Economic and epidemiological data underscore why kidney disease should be placed on the global public health agenda - kidney disease prevalence is increasing globally and it is now the seventh leading risk factor for mortality worldwide. Moreover, demographic trends, the obesity epidemic and the sequelae of climate change are all likely to increase kidney disease prevalence further, with serious implications for survival, quality of life and health care spending worldwide. Importantly, the burden of kidney disease is highest among historically disadvantaged populations that often have limited access to optimal kidney disease therapies, which greatly contributes to current socioeconomic disparities in health outcomes. This joint statement from the International Society of Nephrology, European Renal Association and American Society of Nephrology, supported by three other regional nephrology societies, advocates for the inclusion of kidney disease in the current WHO statement on major non-communicable disease drivers of premature mortality.

During COVID-19, renal impairment is associated with poor prognosis in intensive care unit (ICU). We aimed to assess the existence and incidence of early renal dysfunction and its prognostic value in patients with COVID-19-related acute respiratory distress syndrome (ARDS).

In this prospective multicenter study, patients aged over 18 years with invasive mechanical ventilation (MV) for ARDS were enrolled in 3 ICUs. Precise evaluation of renal dysfunction markers, including urinary protein electrophoresis (UPE) and quantification, was performed within 24 hours after MV onset.

From March 2020 to December 2021, 135 patients were enrolled as follows: 100 with COVID-19 ARDS and 35 with non-COVID-19 ARDS. UPE found more tubular dysfunction in patients with COVID-19 (68% vs. 21.4%, P < 0.0001) and more normal profiles in patients without COVID-19 (65.0% vs. 11.2%, P = 0.0003). Patients with COVID-19 significantly displayed early urinary leakage of tubular proteins such as beta-2-microglobulin (ß2m) and free light chains, tended to display acute kidney injury (AKI) more frequently (51.0% vs. 34.3%, P = 0.088), had longer MV (20 vs. 9 days, P < 0.0001) and longer ICU stay (26 vs. 15 days, P < 0.0001). In COVID-19 ARDS, leakage of free lambda light chain was associated with the onset of Kidney Disease: Improving Global Outcomes (KDIGO) ≥2 AKI (odds ratio [OR]: 1.014, 95% confidence interval [CI] 1.003-1.025, P = 0.011).

Patients with COVID-19-related ARDS display a proximal tubular dysfunction before the onset of AKI, which predicts AKI. Proximal tubular damage seems an important mechanism of COVID-19-induced nephropathy. Analysis of urinary proteins is a reliable noninvasive tool to assess proximal tubular dysfunction in the ICU.

Acute kidney disease (AKD) affects more than half of critically ill elderly patients with acute kidney injury (AKI), which leads to worse short-term outcomes.

We aimed to establish 2 machine learning models to predict the risk and prognosis of AKD in the elderly and to deploy the models as online apps.

Data on elderly patients with AKI (n=3542) and AKD (n=2661) from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were used to develop 2 models for predicting the AKD risk and in-hospital mortality, respectively. Data collected from Xiangya Hospital of Central South University were for external validation. A bootstrap method was used for internal validation to obtain relatively stable results. We extracted the indicators within 24 hours of the first diagnosis of AKI and the fluctuation range of some indicators, namely delta (day 3 after AKI minus day 1), as features. Six machine learning algorithms were used for modeling; the area under the receiver operating characteristic curve (AUROC), decision curve analysis, and calibration curve for evaluating; Shapley additive explanation (SHAP) analysis for visually interpreting; and the Heroku platform for deploying the best-performing models as web-based apps.

For the model of predicting the risk of AKD in elderly patients with AKI during hospitalization, the Light Gradient Boosting Machine (LightGBM) showed the best overall performance in the training (AUROC=0.844, 95% CI 0.831-0.857), internal validation (AUROC=0.853, 95% CI 0.841-0.865), and external (AUROC=0.755, 95% CI 0.699-0.811) cohorts. In addition, LightGBM performed well for the AKD prognostic prediction in the training (AUROC=0.861, 95% CI 0.843-0.878), internal validation (AUROC=0.868, 95% CI 0.851-0.885), and external (AUROC=0.746, 95% CI 0.673-0.820) cohorts. The models deployed as online prediction apps allowed users to predict and provide feedback to submit new data for model iteration. In the importance ranking and correlation visualization of the model's top 10 influencing factors conducted based on the SHAP value, partial dependence plots revealed the optimal cutoff of some interventionable indicators. The top 5 factors predicting the risk of AKD were creatinine on day 3, sepsis, delta blood urea nitrogen (BUN), diastolic blood pressure (DBP), and heart rate, while the top 5 factors determining in-hospital mortality were age, BUN on day 1, vasopressor use, BUN on day 3, and partial pressure of carbon dioxide (PaCO2).

We developed and validated 2 online apps for predicting the risk of AKD and its prognostic mortality in elderly patients, respectively. The top 10 factors that influenced the AKD risk and mortality during hospitalization were identified and explained visually, which might provide useful applications for intelligent management and suggestions for future prospective research.

A very low incidence of acute kidney injury (AKI) has been observed in COVID-19 patients purposefully treated with early pressure support ventilation (PSV) compared to those receiving mainly controlled ventilation. The prevention of subdiaphragmatic venous congestion through limited fluid intake and the lowering of intrathoracic pressure is a possible and attractive explanation for this observed phenomenon. Both venous congestion, or "venous bagging", and a positive fluid balance correlate with the occurrence of AKI. The impact of PSV on venous return, in addition to the effects of limiting intravenous fluids, may, at least in part, explain this even more clearly when there is no primary kidney disease or the presence of nephrotoxins. Optimizing the patient-ventilator interaction in PSV is challenging, in part because of the need for the ongoing titration of sedatives and opioids. The known benefits include improved ventilation/perfusion matching and reduced ventilator time. Furthermore, conservative fluid management positively influences cognitive and psychiatric morbidities in ICU patients and survivors. Here, it is hypothesized that cranial lymphatic congestion in relation to a more positive intrathoracic pressure, i.e., in patients predominantly treated with controlled mechanical ventilation (CMV), is a contributing risk factor for ICU delirium. No studies have addressed the question of how PSV can limit AKI, nor are there studies providing high-level evidence relating controlled mechanical ventilation to AKI. For this perspective article, we discuss studies in the literature demonstrating the effects of venous congestion leading to AKI. We aim to shed light on early PSV as a preventive measure, especially for the development of AKI and ICU delirium and emphasize the need for further research in this domain.

Acute kidney injury (AKI) is frequent in critically ill COVID-19 patients and is associated with a higher mortality risk. By increasing intrathoracic pressure, positive pressure ventilation (PPV) may reduce renal perfusion pressure by reducing venous return to the heart or by increasing renal venous congestion. This study's aim was to evaluate the association between AKI and haemodynamic and ventilatory parameters in COVID-19 patients with ARDS.

This is a single-centre retrospective observational study. Consecutive patients diagnosed with COVID-19 who met ARDS criteria and required invasive mechanical ventilation were enrolled. The relationship between respiratory and haemodynamic parameters influenced by PPV and AKI development was evaluated. AKI was defined according to KDIGO criteria. AKI recovery was evaluated a month after ICU admission and patients were classified as "recovered," if serum creatinine (sCr) value returned to baseline, or as having "acute kidney disease" (AKD), if criteria for AKI stage 1 or greater persisted. The 6-month all-cause mortality was collected.

A total of 144 patients were included in the analysis. AKI occurred in 69 (48%) patients and 26 (18%) required renal replacement therapy. In a multivariate logistic regression analysis, sex, hypertension, cumulative dose of furosemide, fluid balance, and plateau pressure were independently associated with AKI. Mortality at 6 months was 50% in the AKI group and 32% in the non-AKI group (p = 0.03). Among 36 patients who developed AKI and were discharged alive from the hospital, 56% had a full renal recovery after a month, while 14%, 6%, and 14% were classified as having an AKD of stage 0, 2, and 3, respectively.

In our cohort, AKI was independently associated with multiple variables, including high plateau pressure, suggesting a possible role of PPV on AKI development. Further studies are needed to clarify the role of mechanical ventilation on renal function.

Acute kidney injury is a frequent complication of acute respiratory distress syndrome (ARDS). We aim to study the evolution of kidney function in patients presenting severe ARDS and requiring veno-venous extracorporeal membrane oxygenation (VV ECMO).

We conducted a multicenter retrospective study, including adult patients requiring VV ECMO for ARDS. The primary outcome was the evolution of the serum creatinine level after VV ECMO initiation. Secondary outcomes were change in urine output, and urine biochemical parameters after VV ECMO initiation.

One hundred and two patients were included. VV ECMO was initiated after a median of 6 days of mechanical ventilation, mainly for ARDS caused by COVID-19 (73%). Serum creatinine level did not significantly differ after VV ECMO initiation (P = .20). VV ECMO was associated with a significant increase in daily urine output (+6.6 mL/kg/day, [3.8;9.3] P < .001), even after adjustment for potential confounding factors; with an increase in natriuresis. The increase in urine output under VV ECMO was associated with a reduced risk of receiving kidney replacement therapy (OR 0.4 [0.2;0.8], P = .026).

VV ECMO initiation in severe ARDS is associated with an increase in daily urine output and natriuresis, without change in glomerular filtration rate.

High-frequency ventilation (HFV) is frequently used in critically ill preterm neonates. We aimed to determine the incidence of acute kidney injury (AKI) in neonates less than 29 weeks gestation who received HFV in the first week of life and to determine if the rates of AKI differed in those who received other forms of respiratory support.

This retrospective cohort study of 24 international, level III/IV neonatal intensive care units (NICUs) included neonates less than 29 weeks gestation from the AWAKEN study database. Exclusion criteria included the following: no intravenous fluids ≥ 48 h, admission ≥ 14 days of life, congenital heart disease requiring surgical repair at < 7 days of life, lethal chromosomal anomaly, death within 48 h, severe congenital kidney abnormalities, inability to determine AKI status, insufficient data on ventilation, and when the diagnosis of early AKI was unable to be made. Subjects were grouped into three groups based on ventilation modes (CPAP/no ventilation, conventional ventilation, and HFV).

The incidence of AKI was highest in the CPAP/no ventilation group, followed by HFV, followed by conventional ventilation (CPAP/no ventilation 48.5% vs. HFV 42.6% vs. conventional ventilation 28.4% (p = 0.009). An increased risk for AKI was found for those on HFV compared to CPAP/no ventilation (HR = 2.65; 95% CI:1.22-5.73).

HFV is associated with AKI in the first week of life. Neonates on HFV should be screened for AKI. The reasons for this association are not clear. Further studies should evaluate the relationship between ventilator strategies and AKI in premature neonates. A higher resolution version of the Graphical abstract is available as Supplementary information.

COVID-19 is a global health emergency that requires worldwide collaboration to control its spread. The scientific community is working to understand the different aspects of the post-COVID-19 syndrome and potential treatment strategies. Interestingly, there have been reports of gastrointestinal tract (GIT) involvement in the post-COVID-19 syndrome, suggesting the presence of both severe and mild GIT disorders. The development of the post-COVID-19- GIT syndrome involves various factors, such as impaired GIT mucosa cells, disruptions in the feeling of satiety, reduced blood supply due to the formation of small blood clots, and increased prostaglandin secretion caused by an excessive immune response. GIT symptoms have been observed in around 16% of COVID-19 patients. Other complications include kidney damage and prolonged impairment in the filtration and excretion functions of the glomeruli and tubules. The pathogenesis of post-COVID-19 renal syndrome involves factors, like an overactive immune response, reduced lung perfusion and oxygenation, viral infection in kidney tissues, endothelial dysfunction, and decreased blood volume. Roughly 20% of hospitalized patients experience renal manifestations after recovering from COVID-19.

Longitudinal modified treatment policies (LMTP) have been recently developed as a novel method to define and estimate causal parameters that depend on the natural value of treatment. LMTPs represent an important advancement in causal inference for longitudinal studies as they allow the non-parametric definition and estimation of the joint effect of multiple categorical, ordinal, or continuous treatments measured at several time points. We extend the LMTP methodology to problems in which the outcome is a time-to-event variable subject to a competing event that precludes observation of the event of interest. We present identification results and non-parametric locally efficient estimators that use flexible data-adaptive regression techniques to alleviate model misspecification bias, while retaining important asymptotic properties such as [Formula: see text]-consistency. We present an application to the estimation of the effect of the time-to-intubation on acute kidney injury amongst COVID-19 hospitalized patients, where death by other causes is taken to be the competing event.

Extracorporeal life support (ECLS) for acute respiratory failure encompasses veno-venous extracorporeal membrane oxygenation (V-V ECMO) and extracorporeal carbon dioxide removal (ECCO2R). V-V ECMO is primarily used to treat severe acute respiratory distress syndrome (ARDS), characterized by life-threatening hypoxemia or ventilatory insufficiency with conventional protective settings. It employs an artificial lung with high blood flows, and allows improvement in gas exchange, correction of hypoxemia, and reduction of the workload on the native lung. On the other hand, ECCO2R focuses on carbon dioxide removal and ventilatory load reduction ("ultra-protective ventilation") in moderate ARDS, or in avoiding pump failure in acute exacerbated chronic obstructive pulmonary disease. Clinical indications for V-V ECLS are tailored to individual patients, as there are no absolute contraindications. However, determining the ideal timing for initiating extracorporeal respiratory support remains uncertain. Current ECLS equipment faces issues like size and durability. Innovations include intravascular lung assist devices (ILADs) and pumpless devices, though they come with their own challenges. Efficient gas exchange relies on modern oxygenators using hollow fiber designs, but research is exploring microfluidic technology to improve oxygenator size, thrombogenicity, and blood flow capacity. Coagulation management during V-V ECLS is crucial due to common bleeding and thrombosis complications; indeed, anticoagulation strategies and monitoring systems require improvement, while surface coatings and new materials show promise. Moreover, pharmacokinetics during ECLS significantly impact antibiotic therapy, necessitating therapeutic drug monitoring for precise dosing. Managing native lung ventilation during V-V ECMO remains complex, requiring a careful balance between benefits and potential risks for spontaneously breathing patients. Moreover, weaning from V-V ECMO is recognized as an area of relevant uncertainty, requiring further research. In the last decade, the concept of Extracorporeal Organ Support (ECOS) for patients with multiple organ dysfunction has emerged, combining ECLS with other organ support therapies to provide a more holistic approach for critically ill patients. In this review, we aim at providing an in-depth overview of V-V ECMO and ECCO2R, addressing various aspects of their use, challenges, and potential future directions in research and development.

Acute kidney injury has been described as a common complication in patients hospitalized with COVID-19, which may lead to the need for kidney replacement therapy (KRT) in its most severe forms. Our group developed and validated the MMCD score in Brazilian COVID-19 patients to predict KRT, which showed excellent performance using data from 2020. This study aimed to validate the MMCD score in a large cohort of patients hospitalized with COVID-19 in a different pandemic phase and assess its performance to predict in-hospital mortality.

This study is part of the "Brazilian COVID-19 Registry", a retrospective observational cohort of consecutive patients hospitalized for laboratory-confirmed COVID-19 in 25 Brazilian hospitals between March 2021 and August 2022. The primary outcome was KRT during hospitalization and the secondary was in-hospital mortality. We also searched literature for other prediction models for KRT, to assess the results in our database. Performance was assessed using area under the receiving operator characteristic curve (AUROC) and the Brier score.

A total of 9422 patients were included, 53.8% were men, with a median age of 59 (IQR 48-70) years old. The incidence of KRT was 8.8% and in-hospital mortality was 18.1%. The MMCD score had excellent discrimination and overall performance to predict KRT (AUROC: 0.916 [95% CI 0.909-0.924]; Brier score = 0.057). Despite the excellent discrimination and overall performance (AUROC: 0.922 [95% CI 0.914-0.929]; Brier score = 0.100), the calibration was not satisfactory concerning in-hospital mortality. A random forest model was applied in the database, with inferior performance to predict KRT requirement (AUROC: 0.71 [95% CI 0.69-0.73]).

The MMCD score is not appropriate for in-hospital mortality but demonstrates an excellent predictive ability to predict KRT in COVID-19 patients. The instrument is low cost, objective, fast and accurate, and can contribute to supporting clinical decisions in the efficient allocation of assistance resources in patients with COVID-19.

How to cite this article: Banerjee T, Bose P. Kidney-lung Crosstalk in Determining the Prognosis of Acute Kidney Injury Phenotypes in Acute Respiratory Distress Syndrome Patients. Indian J Crit Care Med 2023;27(10):701-703.

Limited data are available on renal complications in patients with acute fulminant myocarditis (AFM) receiving venoarterial extracorporeal membrane oxygenation (VA-ECMO) support in China. To evaluate the impact of renal complications on outcomes in adult patients with AFM supported with VA-ECMO.

Data were extracted from Chinese Society of ExtraCorporeal Life Support (CSECLS) Registry database. Adult patients who were diagnosed with AFM receiving VA-ECMO support in the database were included. The primary outcome was 30-day mortality in patients with AFM supported with VA-ECMO. Logistic regression model was used to examine the impact of renal complications on 30-day mortality by adjusting confounders.

A total of 202 patients were included. The median age was 38 years (IQR 29-48) and males (n = 103) represented 51.0% of the total accounted patients. The median ECMO duration was 142.9 h (IQR 112.1-188.8 h). 178 (88.1%) patients weaned from ECMO and 156 (71.9%) patients survived. 94(46.5%) patients developed renal complications while on ECMO course. Patients with renal complications had higher 30-day mortality (40.7% (37 of 94) vs 8.3% (9 of 108), P < 0.001) compared with those without. The development of renal complications was related to a 3.12-fold increase risk of 30-day mortality (adjusted OR 3.120, 95%CI 1.002-6.577, P = 0.049). Increasing age (adjusted OR1.025, 95% CI 1.008-1.298, P = 0.040) and higher SOFA score (adjusted OR 1.162, 95%CI 1.012-1.334, P = 0.034) were independent risk factors of renal complications.

Our findings demonstrated that patients with AFM receiving VA-ECMO at high risk of developing renal complications. Advancing age and higher SOFA score was associated with increased risk of developing renal complications. The onset of renal complications was significantly associated with 30-day mortality.

Kidneys are sensitive to disturbances in oxygen homeostasis. Hypoxia and activation of the hypoxia-inducible factor (HIF) pathway alter the expression of genes involved in the metabolism of renal and immune cells, interfering with their functioning. Whether the transcriptional activity of HIF protects the kidneys or participates in the pathogenesis of renal diseases is unclear. Several studies have indicated that HIF signaling promotes fibrosis in experimental models of kidney disease. Other reports showed a protective effect of HIF activation on kidney inflammation and injury. In addition to the direct effect of HIF on the kidneys, experimental evidence indicates that HIF-mediated metabolic shift activates inflammatory cells, supporting the HIF cascade as a link between lung or gut damage and worsening of renal disease. Although hypoxia and HIF activation are present in several scenarios of renal diseases, further investigations are needed to clarify whether interfering with the HIF pathway is beneficial in different pathological contexts.

Acute kidney injury is a common postoperative complication affecting between 10% and 30% of surgical patients. Acute kidney injury is associated with increased resource usage and chronic kidney disease development, with more severe acute kidney injury suggesting more aggressive deterioration in clinical outcomes and mortality.

We considered 42,906 surgical patients admitted to University of Florida Health (n = 51,806) between 2014 and 2021. Acute kidney injury stages were determined using the Kidney Disease Improving Global Outcomes serum creatinine criteria. We developed a recurrent neural network-based model to continuously predict acute kidney injury risk and state in the following 24 hours and compared it with logistic regression, random forest, and multi-layer perceptron models. We used medications, laboratory and vital measurements, and derived features from past one-year records as inputs. We analyzed the proposed model with integrated gradients for enhanced explainability.

Postoperative acute kidney injury at any stage developed in 20% (10,664) of the cohort. The recurrent neural network model was more accurate in predicting nearly all categories of next-day acute kidney injury stages (including the no acute kidney injury group). The area under the receiver operating curve and 95% confidence intervals for recurrent neural network and logistic regression models were for no acute kidney injury (0.98 [0.98-0.98] vs 0.93 [0.93-0.93]), stage 1 (0.95 [0.95-0.95] vs. 0.81 [0.80-0.82]), stage 2/3 (0.99 [0.99-0.99] vs 0.96 [0.96-0.97]), and stage 3 with renal replacement therapy (1.0 [1.0-1.0] vs 1.0 [1.0-1.0].

The proposed model demonstrates that temporal processing of patient information can lead to more granular and dynamic modeling of acute kidney injury status and result in more continuous and accurate acute kidney injury prediction. We showcase the integrated gradients framework's utility as a mechanism for enhancing model explainability, potentially facilitating clinical trust for future implementation.