Older patients undergoing noncardiac surgery are at risk of postoperative cardiovascular events. Accurate cardiovascular risk assessment is important for informed decision-making.

This prospective cohort study enrolled older patients undergoing elective major noncardiac surgery. A frailty index based on preoperative geriatric assessment (FI-PGA) was constructed using 32 health-related parameters. The primary outcome was the occurrence of any cardiovascular events within 30 days after surgery. The associations between the FI-PGA and outcomes were assessed using logistic regression models. The added predictive value was evaluated by comparing nested models using improvement in model fit, fraction of new predictive information, net reclassification improvement, and decision curve analysis. The predictive performance of the Clinical Frailty Scale was also evaluated.

A total of 1,808 patients were included, with 316 (17.5%) patients experiencing the primary outcome. The FI-PGA was associated with increased odds of the primary outcome after adjustment for clinical predictors (odds ratio, 1.56; 95% CI, 1.33 to 1.82 per 0.1-point increment), and clinical predictors plus preoperative N-terminal pro-B-type natriuretic peptide (odds ratio, 1.37; 95% CI, 1.16 to 1.61 per 0.1-point increment). Integration of the FI-PGA in prediction models significantly improved model fit and provided new predictive information. Net reclassification improvement analysis showed that adding the FI-PGA to risk models improved risk estimation for patients who did not develop postoperative cardiovascular events, but did not improve risk estimation for those who experienced events. Decision curves showed the models containing the FI-PGA achieved higher net benefit. Improved model performance was also observed when the Clinical Frailty Scale was used for frailty assessment, although the added predictive values appeared lower.

A frailty index derived from preoperative multidimensional geriatric assessment can improve cardiovascular risk prediction before noncardiac surgery, primarily by improving risk estimation for patients who will not develop postoperative cardiovascular events.

The Japanese Society of Hepatobiliary and Pancreatic Surgery has established a certification system for experienced surgeons. Evaluating its efficacy requires accounting for patient risk variations. The National Clinical Database (NCD) facilitates this using risk-adjusted outcome measures to validate and compare surgical performance.

We analyzed the NCD from 2014 to 2020 to examine trends in adjusted odds ratios (AORs) for mortality and morbidity following pancreaticoduodenectomy using 2014 as the reference. Primary outcomes were surgical and 30-day postoperative mortality. Secondary outcomes included severe complications and grade C pancreatic fistula. Subgroup analyses considered surgeon and institutional certification.

Analysis of 78 972 pancreaticoduodenectomy reports revealed a decrease in the AOR for surgical mortality from 0.906 (95% Confidence Interval [CI]: 0.759-1.082, p = 0.276) in 2015 to 0.647 (95% CI: 0.539-0.777, p < 0.001) in 2020. A significant downward trend in the incidence of Grade C pancreatic fistula was observed. Board-certified surgeons have demonstrated superior performance compared to nonboard-certified surgeons since 2014, with board-certified training institutions having significantly lower AORs than those without certification. The AOR for surgical mortality showed an annual decrease across institutions.

The certification system for hepatobiliary-pancreatic surgery and participation in the NCD significantly decreased surgical mortality after pancreaticoduodenectomy.

Platelets are major players in the pathogenesis of cardiovascular events, and the number of circulating platelets in whole blood is routinely available in clinical testing. The relationship between the preoperative platelet count and major adverse cardiovascular events (MACE) after noncardiac surgery is uncertain.

In this paper we aim to explore the relationship between abnormal platelet counts and major adverse cardiac events (MACE) after noncardiac surgery.

We identified adults aged ≥18 years undergoing noncardiac surgery from 2009 to 2015 from the National Surgical Quality Improvement Program. Preoperative platelet counts within 90 days of surgery were recorded. Patients were prospectively followed for 30 days. The primary outcome was 30-day MACE (a composite of death, myocardial infarction, or stroke). Multivariable logistic regression models estimated the association between platelet count and the odds of postoperative outcomes.

Among 3 053 308 surgical patients, 7.5% had thrombocytopenia (6% mild [platelet count 100-150 × 109/L] and 1.5% moderate-severe [<100 × 109/L]), and 4.4% had thrombocytosis (4% moderate [400-600 × 109/L] and 0.4% severe [>600 × 109/L]). There was a U-shaped relationship between platelet count and MACE. The adjusted odds of MACE were elevated in mild (adjusted odds ratio [aOR], 1.44; 95% CI, 1.39-1.48) and moderate-severe thrombocytopenia (aOR, 2.79; 95% CI, 2.69-2.90) and in moderate (aOR, 1.57; 95% CI, 1.52-1.63) and severe (aOR, 1.91; 95% CI, 1.74-2.09) thrombocytosis. Findings were consistent for the individual endpoints of death, myocardial infarction, and stroke.

In adults undergoing noncardiac surgery, preoperative thrombocytopenia and thrombocytosis were identified in nearly 12% of cases and were associated with increased odds of cardiovascular events at 30 days.

Heart failure is a frequent comorbidity in patients undergoing non-cardiac surgery and an acknowledged risk factor for postoperative mortality. The associations between stable chronic heart failure and postoperative outcomes have not been explored extensively. The aim of this study was to determine associations between stable chronic heart failure and its peri-operative management and postoperative outcomes after major non-cardiac surgery.

This is a secondary analysis of MET-REPAIR, an international prospective cohort study including patients undergoing non-cardiac surgery aged ≥ 45 y with increased cardiovascular risk. Main exposures were stable chronic heart failure and availability of a pre-operative transthoracic echocardiogram. The primary endpoint was the incidence of postoperative major adverse cardiovascular events at 30 days. Secondary endpoints included 30-day mortality and severe in-hospital complications. Multivariable logistic regression models were calculated.

Of 15,158 included patients, 3880 (25.6%) fulfilled the diagnostic criteria for stable chronic heart failure, of whom 1397 (36%) were female. Chronic heart failure was associated with increased risk of postoperative 30-day major adverse cardiovascular events (OR 2.04, 95%CI 1.59-2.60), 30-day mortality (OR 1.50, 95%CI 1.17-1.92) and in-hospital complications (OR 1.47, 95%CI 1.30-1.66). Transthoracic echocardiography was performed in 1267 (32.7%) patients with heart failure; 146 (11.5%) patients with heart failure presented with a left ventricular ejection fraction < 40%. Reduced ejection fraction was associated with major adverse cardiovascular events (OR 2.0, 95%CI 1.01-3.81).

Stable chronic heart failure is independently associated with major adverse cardiovascular events, mortality and severe postoperative complications when measured 30 days after non-cardiac surgery.

Considering that most patients with low or no significant risk factors can safely undergo noncardiac surgery without additional cardiac evaluation, and given the excessive evaluations often performed in patients undergoing intermediate or higher risk noncardiac surgeries, practical preoperative risk assessment tools are essential to reduce unnecessary delays for urgent outpatient services and manage medical costs more efficiently.

This study aimed to use the Observational Medical Outcomes Partnership Common Data Model to develop a predictive model by applying machine learning algorithms that can effectively predict major adverse cardiac and cerebrovascular events (MACCE) in patients undergoing noncardiac surgery.

This retrospective observational network study collected data by converting electronic health records into a standardized Observational Medical Outcomes Partnership Common Data Model format. The study was conducted in 2 tertiary hospitals. Data included demographic information, diagnoses, laboratory results, medications, surgical types, and clinical outcomes. A total of 46,225 patients were recruited from Seoul National University Bundang Hospital and 396,424 from Asan Medical Center. We selected patients aged 65 years and older undergoing noncardiac surgeries, excluding cardiac or emergency surgeries, and those with less than 30 days of observation. Using these observational health care data, we developed machine learning-based prediction models using the observational health data sciences and informatics open-source patient-level prediction package in R (version 4.1.0; R Foundation for Statistical Computing). A total of 5 machine learning algorithms, including random forest, were developed and validated internally and externally, with performance assessed through the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve, and calibration plots.

All machine learning prediction models surpassed the Revised Cardiac Risk Index in MACCE prediction performance (AUROC=0.704). Random forest showed the best results, achieving AUROC values of 0.897 (95% CI 0.883-0.911) internally and 0.817 (95% CI 0.815-0.819) externally, with an area under the precision-recall curve of 0.095. Among 46,225 patients of the Seoul National University Bundang Hospital, MACCE occurred in 4.9% (2256/46,225), including myocardial infarction (907/46,225, 2%) and stroke (799/46,225, 1.7%), while in-hospital mortality was 0.9% (419/46,225). For Asan Medical Center, 6.3% (24,861/396,424) of patients experienced MACCE, with 1.5% (6017/396,424) stroke and 3% (11,875/396,424) in-hospital mortality. Furthermore, the significance of predictors linked to previous diagnoses and laboratory measurements underscored their critical role in effectively predicting perioperative risk.

Our prediction models outperformed the widely used Revised Cardiac Risk Index in predicting MACCE within 30 days after noncardiac surgery, demonstrating superior calibration and generalizability across institutions. Its use can optimize preoperative evaluations, minimize unnecessary testing, and streamline perioperative care, significantly improving patient outcomes and resource use. We anticipate that applying this model to actual electronic health records will benefit clinical practice.

Despite advancements in peri-operative care and conflicting evidence regarding the need for preoperative coronary revascularization, the optimal timing of noncardiac surgery (NCS) following cardiac operations remains unclear.

The purpose of this study was to evaluate the effect of time interval between cardiac surgery and NCS on peri-operative risk of major adverse events (MAEs).

Adults undergoing elective CABG, valve repair or replacement, or combined procedures were identified in the 2016 to 2020 Nationwide Readmissions Database, with subsequent admission for NCS analyzed. The time interval in between NCS and index cardiac operations was modeled using restricted cubic splines, and clinical outcome differences were evaluated across various NCS risk and urgency categories.

Of 1,335,175 patients undergoing cardiac surgery, 20,253 (1.5%) required a subsequent NCS. On risk-adjusted examination of MAE rates as a function of time delay after cardiac surgery, an inflection point was noted at 100 days postoperatively. Based on this threshold, 47.9% of patients who had NCS within 100 days were considered early while others were grouped as late. Late NCS was associated with significantly lower odds of MAE (adjusted OR: 0.69; 95% CI: 0.62-0.76), and in-hospital mortality (adjusted OR: 0.66; 95% CI: 0.46-0.96), as compared to early NCS. This relationship persisted across all cardiac surgical subgroups and whether subsequent NCS was elective. Additionally, nonelective procedures classically categorized as low risk in the general population, exhibited comparable rates of MAE to high-risk procedures following early NCS.

When feasible, delaying NCS, particularly beyond 100 days, appears to be associated with a reduction in adverse events, suggesting a potential opportunity for optimization of patient outcomes.

Limited data exist on noncardiac surgery patients with prior percutaneous coronary intervention (PCI) in the contemporary era. The objective was to examine rate, characteristics, and outcomes of patients who underwent noncardiac surgery within 2 years of PCI and develop a risk model of factors that predict long-term postoperative outcomes among patients with recent PCI.

Patients in the Veterans Affairs Surgical Quality Improvement Program database who underwent noncardiac surgery between October 1, 2017 and September 30, 2021 were included. Patients with versus without PCI within 2 years were propensity matched to examine major adverse cardiovascular events (MACE), defined as a 1-year composite of mortality, revascularization, and rehospitalization for myocardial infarction or stroke. Among patients with recent PCI, multivariable logistic regression was used to develop a risk model to predict 1-year postoperative MACE. Among 334 828 patients undergoing surgery, 2297 (0.68%) had PCI within 2 years. Among 9160 propensity-matched veterans, there was no difference in MACE between patients with and without preceding PCI (hazard ratio [HR], 1.04 [95% CI, 0.96-1.17]). Patients with versus without preceding PCI within 2 years had lower risk of all-cause death (HR, 0.83 [95% CI, 0.72-0.96]) but higher risk of revascularization (HR, 1.88 [95% CI, 1.50-2.36]) at 1 year. A 13-component MACE prediction model among patients with recent PCI had moderate discrimination (area under the receiver operating characteristic curve 0.73 derivation, 0.72 validation).

Among patients who underwent surgery, risk of MACE did not differ, but the risk of revascularization was higher and all-cause death was lower in patients with versus without recent PCI. A risk model can be used to stratify risk of surgery among patients with preceding PCI.

Patients anticipating surgery and anesthesia benefit from preoperative care to lower risks and facilitate services on the day of surgery. Preparing patients often requires extensive evaluation and coordination of care. Vulnerable, marginalized, and disenfranchised populations have special concerns, limitations, and needs. These patients may have unidentified or poorly managed comorbidities. Underrepresented minorities and transgender patients may either avoid or have limited access to health care. Homelessness, limited health literacy, and incarceration hinder perioperative optimization initiatives. Identifying patients who will benefit from additional resource allocation and knowledge of their special challenges is vital to reducing disparities in health and health care.

To determine whether preoperative LDL-C concentration affects the risk of perioperative major adverse cardiovascular or cerebrovascular events (MACCE) after noncardiac surgery.

Single center retrospective cohort study.

Hospital (including medical and surgical floor, intensive care unit) and patient disposition location (including the patient's home or any other receiving facility).

43,348 non-cardiac surgeries at NYU Langone Health between January 2016 and September 2020.

Patients were grouped based on preoperative LDL-C.

Complete serum lipid panel obtained within one year prior to the date of noncardiac surgery and rate of perioperative MACCE, defined as a composite of in-hospital non-fatal myocardial infarction, in-hospital acute ischemic stroke, myocardial injury after noncardiac surgery, and death from any cause within 30 days of surgery.

Perioperative MACCE occurred in 1093 patients (2.5 %) overall. After multivariable adjustment, odds of MACCE were significantly lower in patients with higher (≥100 mg/dL) versus lower (<100 mg/dL) LDL-C (adjusted odds ratio [aOR] 0.783, 95 % CI, 0.660-0.926]).

In a large cohort of patients undergoing non-cardiac surgery at a major academic health system in New York City, lower LDL-C concentrations were not associated with a lower incidence of perioperative MACCE. Further investigation into modifiable perioperative cardiovascular risk factors is needed to improve perioperative outcomes.

Perioperative stroke is a serious and potentially fatal complication following non-cardiac surgery. Thus, it is important to identify the risk factors and develop an effective prognostic model to predict the incidence of perioperative stroke following non-cardiac surgery.

We identified potential risk factors and built a model to predict the incidence of perioperative stroke using logistic regression derived from hospital registry data of adult patients that underwent non-cardiac surgery from 2008 to 2019 at The First Medical Center of Chinese PLA General Hospital. Our model was then validated using the records of two additional hospitals to demonstrate its clinical applicability. In our hospital cohorts, 223,415 patients undergoing non-cardiac surgery were included in this study with 525 (0.23%) patients experiencing a perioperative stroke. Thirty-three indicators including several intraoperative variables had been identified as potential risk factors. After multi-variate analysis and stepwise elimination (P < 0.05), 13 variables including age, American Society of Anesthesiologists (ASA) classification, hypertension, previous stroke, valvular heart disease, preoperative steroid hormones, preoperative β-blockers, preoperative mean arterial pressure, preoperative fibrinogen to albumin ratio, preoperative fasting plasma glucose, emergency surgery, surgery type and surgery length were screened as independent risk factors and incorporated to construct the final prediction model. Areas under the curve were 0.893 (95% confidence interval (CI) [0.879, 0.908]; P < 0.001) and 0.878 (95% CI [0.848, 0.909]; P < 0.001) in the development and internal validation cohorts. In the external validation cohorts derived from two other independent hospitals, the areas under the curve were 0.897 and 0.895. In addition, our model outperformed currently available prediction tools in discriminative power and positive net benefits. To increase the accessibility of our predictive model to doctors and patients evaluating perioperative stroke, we published an online prognostic software platform, 301 Perioperative Stroke Risk Calculator (301PSRC). The main limitations of this study included that we excluded surgical patients with an operation duration of less than one hour and that the construction and external validation of our model were from three independent retrospective databases without validation from prospective databases and non-Chinese databases.

In this work, we identified 13 independent risk factors for perioperative stroke and constructed an effective prediction model with well-supported external validation in Chinese patients undergoing non-cardiac surgery. The model may provide potential intervention targets and help to screen high-risk patients for perioperative stroke prevention.

The Revised Cardiac Risk Index (RCRI) has been incorporated into preoperative assessment guidelines and is used for simple preoperative screening; however, validation studies within large populations are limited. Moreover, although sex differences in perioperative risk are recognized, their effect on the performance of the RCRI remains unclear. Therefore, in this study we evaluated whether sex differences exist in the risks within the strata classified by the RCRI.

The Japan Medical Data Center database based on claim and health examination data in Japan between January 2005 and April 2021 was used. A total of 161,359 noncardiac surgeries performed during hospitalization were analyzed. The main outcome was the 30-day risk of major adverse cardiovascular events. Although there was no significant sex difference among those with an RCRI ≥1, males had a significant hazard rate (1.32 [95% confidence interval, 1.03-1.68]) of postoperative events in the low-risk group with an RCRI of 0. However, this significant difference was not detected in the population excluding those who underwent breast and gynecological surgeries.

The RCRI achieved reasonable risk stratification in validation using Japanese real-world data regardless of sex. Although further detailed analysis is necessary to determine the sex differences, the validity of using the RCRI for screening purposes is supported at this stage.

Optimised use of kidney function information might improve cardiac risk prediction in noncardiac surgery.

In 35,815 patients from the VISION cohort study and 9219 patients from the POISE-2 trial who were ≥45 yr old and underwent nonurgent inpatient noncardiac surgery, we examined (by age and sex) the association between continuous nonlinear preoperative estimated glomerular filtration rate (eGFR) and the composite of myocardial injury after noncardiac surgery, nonfatal cardiac arrest, or death owing to a cardiac cause within 30 days after surgery. We estimated contributions of predictive information, C-statistic, and net benefit from eGFR and other common patient and surgical characteristics to large multivariable models.

The primary composite occurred in 4725 (13.2%) patients in VISION and 1903 (20.6%) in POISE-2; in both studies cardiac events had a strong, graded association with lower preoperative eGFR that was attenuated by older age (Pinteraction<0.001 for VISION; Pinteraction=0.008 for POISE-2). For eGFR of 30 compared with 90 ml min-1 1.73 m-2, relative risk was 1.49 (95% confidence interval 1.26-1.78) at age 80 yr but 4.50 (2.84-7.13) at age 50 yr in female patients in VISION. This differed modestly (but not meaningfully) in men in VISION (Pinteraction=0.02) but not in POISE-2 (Pinteraction=0.79). eGFR contributed the most predictive information and mean net benefit of all predictors in both studies, most C-statistic in VISION, and third most C-statistic in POISE-2.

Continuous preoperative eGFR is among the best cardiac risk predictors in noncardiac surgery of the large set examined. Along with its interaction with age, preoperative eGFR would improve risk calculators.

ClinicalTrials.gov NCT00512109 (VISION) and NCT01082874 (POISE-2).

Abdominal and perineal repairs for rectal prolapse are offered to patients based on surgeon assessment of risk. Interpretations of risk can vary. We sought to understand how the preoperative Risk Analysis Index (RAI) score, a validated measure of frailty, aligned with our existing decision-making process for rectal prolapse repair.

Rectal prolapse repair cases were recorded in an Institutional Review Board approved registry from 2017 to 2022. Abdominal and perineal operations were determined based on an experienced surgeon's recommendation. The preoperative RAI was collected; a score≥30 indicates significant frailty. Preoperative and postoperative characteristics were compared using t-tests and Fisher's exact tests.

About 130 patients underwent abdominal repairs and 51 underwent perineal repairs. Perineal patients were more often frail (abdominal: 9 [7%] versus perineal: 21 [41%], P < 0.001) and had a higher rate of cardiac comorbidities (abdominal: 42 [32%] versus perineal: 35 [69%], P < 0.001). A similar share of patients were undergoing repair for recurrent prolapse (abdominal: n = 29 [22%] versus perineal: n = 11 [22%], P > 0.99). Perineal repair patients were more likely to need assistance with mobility (n = 24 [47%]) and live in a facility (n = 15 [29%]). Patients in both groups recovered well (complication rate abdominal: 28 [22%] versus 11 [22%], P > 0.99) and were satisfied with postoperative outcomes (Patient Global Impression of Change score abdominal: 6 [interquartile range: 6, 7] versus perineal: 6 [5, 7], P = 0.12). Recurrence rates were higher after perineal repair (abdominal: 12 [9%] versus perineal: 20 [39%], P < 0.001).

Most abdominal repair patients were not frail, but many nonfrail patients underwent perineal operations based on surgeon perception of comorbidities. Using the RAI tool may provide an opportunity to guide decision-making around operative approach for rectal prolapse and overcome potential surgeon bias.

To compare minimally invasive and open surgery for older patients with gastric cancer.

This study included 464 consecutive patients with gastric cancer aged ≥75 years who underwent open or laparoscopic gastrectomy at our institution from January 2004 to December 2018. We performed propensity score-matching and compared short- and long-term outcomes between the two groups.

After matching, 332 patients were included in the study (166 in each group). The laparoscopy group had a longer operative time, lesser blood loss, and shorter hospital stays than the open surgery group (all p < 0.020). The laparoscopy group had a lower complication rate than the open surgery group (p = 0.002). No significant differences were noted in the 3-y overall, recurrence-free, and disease-free survival between the groups (all p > 0.200).

Minimally invasive surgery for older patients with gastric cancer may be more beneficial than open gastrectomy in terms of blood loss and hospital stay.

Respiratory diseases and cardiovascular diseases (CVDs) have high prevalence and share common risk factors. In some respiratory diseases such as sleep apnoea and COPD, the evidence of their negative impact on the prognosis of CVDs seems clear. However, in other diseases it is less evident whether there is any direct relationship. With this in mind, our objective was to provide information that may be helpful to better understand the relationship between respiratory pathology and CVDs. There are different reasons for this relationship, such as shared risk factors, common pathophysiological mechanisms, side effects of treatment and the direct effect in the heart and great vessels of respiratory diseases. Indeed, aging and smoking are risk factors for CVDs and also for respiratory diseases such as obstructive sleep apnea (OSA), COPD and interstitial lung diseases (ILD). Furthermore, there are common pathophysiological mechanisms that affect both respiratory diseases and CVDs, such as accelerated atherosclerosis, microvascular dysfunction, endothelial dysfunction, inflammation, hypoxemia and oxidative stress. Besides that, it is well known that lung cancer, sarcoidosis and amyloidosis may directly affect the heart and great vessels. Finally, side effects of drugs for respiratory diseases and the discontinuation of treatments that are necessary for CVDs, such as β-blockers and aspirin, may have a deleterious impact on the cardiovascular system. In conclusion, the coexistence of respiratory diseases and CVDs is very common. It makes modifying diagnostic and therapeutic management necessary and is also a relevant prognostic factor.

While it is generally accepted that most patients undergoing joint replacement do not require a cardiac stress test, individuals with existing or potential cardiac conditions may be at an increased risk of perioperative complications following primary total knee arthroplasty (TKA). This study aims to analyze the immediate postoperative outcomes of patients who underwent primary TKA, comparing those who had a cardiac stress test with no abnormal results and subsequent cardiac interventions to those who did not undergo a stress test.

This retrospective cohort study utilized the TriNetX Research Network. The first cohort included patients who underwent a stress test within one year prior to their TKA, had no abnormal results, and did not undergo cardiac catheterization within two weeks post-stress test (Normal Stress Test). The second cohort consisted of patients who did not have a stress test in the year preceding their TKA (No Stress Test). The study analyzed data collected between January 1, 2003, and January 1, 2024. To control for confounding variables, propensity score matching was employed. P < 0.01 was considered significant.

A total of 13,881 patients successfully matched in each cohort. Within 30 days following TKA, patients in the Normal Stress Test cohort exhibited a significantly elevated risk of several complications: Transfusion (RR: 1.702), Myocardial Infarction (MI) (RR: 1.908), Acute Renal Failure (ARF) (RR: 1.504), Acute Posthemorrhagic Anemia (RR: 1.245), Wound Dehiscence (RR: 1.549), and Pneumonia (RR: 2.051). These results were consistent at the 90-day follow-up. Notably, the risk of death was only elevated before propensity score matching (RR: 2.115).

Our findings suggest that the underlying conditions prompting the use of a cardiac stress test, including congestive heart failure and renal insufficiency, may themselves be indicative of a higher overall perioperative risk, regardless of the stress test results.

Level III: Case-control study or retrospective cohort study.

Risk prediction models are an established component of the preoperative evaluation. In its guidelines the European Society for Cardiology proposes several risk scores but the benefit of these is mostly unclear for clinicians. This article describes the individual steps in the preparation of a valid prediction model with a focus on the parameters, discrimination, calibration and external validation. The clinical benefits of the risk scores proposed in the guidelines with respect to these parameters was investigated. All proposed risk scores appear to show a good discrimination in the validation cohorts. Only a few reliable data for a good calibration could be compiled. The external validity of the individual models is unclear. The general benefit of the risk scores cannot be recommended as data for calibration or discrimination in external cohorts are lacking. A precise estimation of the risk cannot be expected.

Because of the lack of specific recommendations concerning cardiac risk stratification before vascular surgery, appropriate decisions remain individual. The aim of the present study was to evaluate the perioperative cardiac management in vascular surgery in Germany.

This article is based on a survey from 2018 of heads of German vascular surgical departments or units regarding their experience with perioperative cardiac management. The questionnaire asked about the experience with preoperative cardiac evaluation and its extension, awareness of perioperative myocardial ischemia, the art of postoperative monitoring and the routine use of the best medical treatment.

In total, 62% of responders agreed that perioperative myocardial ischemia is a relevant postoperative problem in their clinic after open abdominal aortic surgery, while 47% stated the same after vascular surgery (VS) like carotid endarterectomy, peripheral arterial surgery or EVAR. Preoperative cardiological evaluations are performed routinely by 87% of responders before open abdominal aortic surgery and by 42% before VS. Preoperative cardiac evaluation included cardiac echography in 92% and stress diagnostics (stress echography, stress ECG) in 38%. Routine preoperative cardiac catheterisation is performed in 4% before OAS and only 0.5% before VS. In addition, 79% of participants initiate acetylsalicylic acid routinely and 68% use statins preoperatively. The serum troponin diagnostic test in asymptomatic patients was routinely applied by 19% of responders after OAS and by 6% after VS.

Perioperative myocardial ischemia is considered a relevant problem, primarily after aortic surgery. The preoperative cardiac stress diagnostics among vascular surgeons does not seem to be sufficiently widespread. The preoperative initiation of acetylsalicylic acid and statins is not routine in 30% of hospitals.

The "2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery" provides recommendations to guide clinicians in the perioperative cardiovascular evaluation and management of adult patients undergoing noncardiac surgery.

A comprehensive literature search was conducted from August 2022 to March 2023 to identify clinical studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline.

Recommendations from the "2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery" have been updated with new evidence consolidated to guide clinicians; clinicians should be advised this guideline supersedes the previously published 2014 guideline. In addition, evidence-based management strategies, including pharmacological therapies, perioperative monitoring, and devices, for cardiovascular disease and associated medical conditions, have been developed.

Assessing the risk of postoperative cardiovascular events before performing non-cardiac surgery is clinically important. The current risk score systems for preoperative evaluation may not adequately represent a small subset of high-risk populations. Accordingly, this study aimed at applying iterative random forest to analyze combinations of factors that could potentially be clinically valuable in identifying these high-risk populations. To this end, we used the Japan Medical Data Center database, which includes claims data from Japan between January 2005 and April 2021, and employed iterative random forests to extract factor combinations that influence outcomes. The analysis demonstrated that a combination of a prior history of stroke and extremely low LDL-C levels was associated with a high non-cardiac postoperative risk. The incidence of major adverse cardiovascular events in the population characterized by the incidence of previous stroke and extremely low LDL-C levels was 15.43 events per 100 person-30 days [95% confidence interval, 6.66-30.41] in the test data. At this stage, the results only show correlation rather than causation; however, these findings may offer valuable insights for preoperative risk assessment in non-cardiac surgery.

The "2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery" provides recommendations to guide clinicians in the perioperative cardiovascular evaluation and management of adult patients undergoing noncardiac surgery.

A comprehensive literature search was conducted from August 2022 to March 2023 to identify clinical studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline.

Recommendations from the "2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery" have been updated with new evidence consolidated to guide clinicians; clinicians should be advised this guideline supersedes the previously published 2014 guideline. In addition, evidence-based management strategies, including pharmacological therapies, perioperative monitoring, and devices, for cardiovascular disease and associated medical conditions, have been developed.

Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest (MICA) is a validated self-explanatory score applied in cardiac or noncardiac surgeries. This study aims to assess the predictive value of the MICA score for cardiovascular events after aortoiliac revascularization.

This prospective cohort underwent elective aortoiliac revascularization between 2013 and 2021. Patients' demographic, clinical characteristics, and outcomes were registered. The patients were divided into 2 groups according to the MICA score using optimal binning. Survival analysis to test for time-dependent variables and multivariate Cox regression analysis for independent predictors were performed.

This study included 130 patients with a median follow-up of 55 months. Preoperative MICA score was ≥6.5 in 41 patients. MICA ≥6.5 presented a statistically significant association, with long-term occurrence of acute heart failure (HR = 1.695, 95% CI 1.208-2.379, P = 0.002), major adverse cardiovascular events (HR = 1.222, 95% CI 1.086-1.376, P < 0.001), and all-cause mortality (HR = 1.256, 95% CI 1.107-1.425, P < 0.001). Multivariable Cox regression confirmed MICA as a significant independent predictor of long-term major adverse cardiovascular events (aHR = 1.145 95% CI 1.010-1.298, P = 0.034) and all-cause mortality (aHR = 1.172 95% CI 1.026-1.339, P = 0.020).

The MICA score is a quick, easy-to-obtain, predictive tool in identifying patients with a higher risk of postaortoiliac revascularization cardiovascular events, such as acute heart failure, major adverse cardiovascular events, and all-cause mortality. Additional research for the validation of the MICA score in the context of aortoiliac revascularization and specific interventions is necessary.

Pre-operative screening is a high volume task consuming time and resource. Streamlining patient flow by gathering information in advance reduces costs, optimises resources and diminishes patient burden whilst maintaining safety of care.

To evaluate whether 'Pre-operative triAge proCedure to streaMline elective surgicAl patieNts' (PACMAN) is able to improve pre-operative screening by selecting patients eligible for evaluation by telephone.

A single-centre, retrospective, observational cohort analysis.

A tertiary medical teaching hospital in 's-Hertogenbosch, The Netherlands.

Adults scheduled for clinical interventions under procedural sedation and all types of elective medium or low risk surgery with anaesthetic guidance were eligible. Patients answered a questionnaire to calculate the PACMAN score. This score combined with risk factors related to surgery determines suitability for phone consultation (PhC) or the need for an in-person consultation (in-PC).

Evaluation of standard care.

Primary outcome was the reduction in number of in-PCs. Secondary outcomes included reliability of PACMAN, peri-operative patient outcomes and cost-effectiveness.

Of 965 patients triaged by PACMAN, 705 (73.1%) were identified as suitable for a PhC. Of those, 688 (97.6%) were classified American Society of Anesthesiologists Physical Status (ASA-PS) I to II or III with stable comorbidities. Of the 260 in-PC patients, 47.4% were classified ASA-PS III with unstable comorbidities or ASA-PS IV. The overall incidence of unanticipated adverse peri-operative events was 1.3%. Finally, implementation of PACMAN led to a 20% increase in pre-operative department efficiency due to better deployment of personnel and resources.

Implementation of PACMAN resulted in a 73.1% reduction in pre-operative in-PCs at our hospital. Given the increasing pressure on healthcare systems globally, we suggest developing further optimisation and integration of smart triage solutions into the pre-operative process.

ClinicalTrials.gov Identifier: NCT06148701.

Preoperative medical evaluation can minimize inefficiencies and improve outcomes. Thoughtful use of preoperative testing can aid in that effort, but, conversely, indiscriminate testing can detract from it. The United Kingdom National Institute for Health Care and Excellence, European Society of Anaesthesiology, and American Society of Anesthesiologists (ASA) have all stated that routine preoperative testing is not supported by evidence. Testing is supported only when clinical indications are present. Particularly in low-risk patients, such as those with an ASA classification of 1 or 2 who are undergoing ambulatory procedures, evidence suggests that preoperative testing fails to reduce the risk of complications.

For patients considering surgery, the preoperative evaluation allows physicians to identify and treat acute cardiac conditions before less-urgent surgery, predict the benefits and harms of a proposed surgery, and make temporary management changes to reduce operative risk. Multiple risk prediction tools are reasonable for use in estimating perioperative cardiac risk, but management changes to reduce risk have proven elusive. For all but the most urgent surgical procedures, patients with active coronary syndromes or decompensated heart failure should have surgery postponed.

To evaluate the effect of malnutrition assessed by the Geriatric Nutritional Risk Index (GNRI) on major adverse cardiac and cerebrovascular events (MACCE) in the elderly patients after endovascular aortic aneurysm repair (EVAR).

This was a retrospective cohort study of elderly patients who underwent EVAR in a tertiary hospital. Malnutrition status was assessed by the GNRI. The primary outcome was MACCE. The predictive ability of the GNRI was compared with both the Revised Cardiac Risk Index (RCRI) and the modified Frailty Index (mFI) using Receiver operating characteristic (ROC) curve.

A total of 453 patients underwent EVAR November 2015 and January 2020 was retrospectively analyzed, equally divided into three (low/medium/high) groups according to GNRI values which ranked from low to high. Five (1.10%) patients were lost in follow-up after surgery, and the median length of follow-up was 28.00 (15.00-47.00) months. The high GNRI values reduced length of hospital stay following EVAR in comparison to patients in low GNRI values group (β 9.67, 95% CI 4.01-23.32, p = 0.0113; adjusted β -1.96, 95% CI -3.88, -0.05, p = 0.0454). GNRI status was associated with a significantly increased risk of long-term mortality after EVAR (Medium GNRI, unadjusted HR 0.40, 95%CI 0.23-0.70, p = 0.0014; adjusted HR 0.47, 95%CI 0.26-0.84, p = 0.0107; high GNRI, 0.27 95%CI 0.14-0.55; p = 0.0003; adjusted HR 0.32 95%CI 0.15-0.68, p = 0.0029). Both medium and high GNRI values were linked to significantly reduced risks of MACCE compared to low GNRI score patients (Medium GNRI, unadjusted HR 0.34, 95%CI 0.13-0.88, p = 0.00265; adjusted HR 0.37, 95%CI 0.14-0.96, p = 0.0408; High GNRI, 0.26 95%CI 0.09-0.78; p = 0.0168; adjusted HR 0.21 95%CI 0.06-0.73, p = 0.0029). Compared with the RCRI and mFI, the GNRI had better discrimination in predicting long-term MACCE. An area under the curve (AUC) for GNRI mFI, and RCRI is 0.707, 0.614 and 0.588, respectively. (Z statistic, GNRI vs. mFI, p = 0.0475; GNRI vs. RCRI, p = 0.0017).

Malnutrition assessed by the GNRI may serve as a useful predictor of long-term MACCE in elderly patients after EVAR, with preferable discrimination abilities compared with both RCRI and mFI.

In 1994, Fischer et al. established the preoperative clinic for the perioperative services at Stanford University Medical Center. By lowering the risk of cancellation and reducing morbidity and mortality against the push to move surgeries to an outpatient, basis, they demonstrated a return on investment. In the 2000s, Aronson et al. designed the prehabilitation clinics at Duke University with the notion that the preoperative process should not only ensure that patients were appropriately risk-stratified, but also clinically optimized before surgery. With a trend towards ambulatory procedures due to current reimbursement structures, hospital administrators should be searching for potential avenues to bolster sagging profits. In this narrative review, we argue that the perioperative services needs to extend beyond the hospital into the postoperative period.

To evaluate whether major adverse cardiac events (MACE) continue to be a major causative factor for mortality after noncardiac surgery.

We performed retrospective study of 75,410 adult noncardiac surgery patients at Mayo Clinic Rochester, between January 1, 2016, and May 4, 2018. Electronic medical records were reviewed and data collected on all deaths within 30 days (n=692 patients) of surgery. The incidence of death due to MACE was calculated.

Postoperative MACE occurred in 150 patients (21.4 events per 10,000 patients; 95% CI, 18.2-25.2 events per 10,000 patients) with most occurring within 3 days of surgery (n=113). Postoperative MACE events were associated with atrial fibrillation with rapid rate response in 25 patients (16.7%), sepsis in 15 patients (10%), and bleeding in 15 patients (10%). There were 12 intraoperative deaths of which 9 were due to exsanguination (75%) and the remaining 3 (25%) due to cardiac arrest. Of the 56 deaths on the first 24 hours after surgery, 7 were due to hemorrhage, 17 due to cardiovascular causes, 20 due to sepsis, and 7 due to neurologic disease. The leading cause of total death over 30 days postoperatively was sepsis (28%), followed by malignancy (27%), cardiovascular disease (12%) neurologic disease (12%), and hemorrhage (5%).

MACE was not the leading cause of death both intraoperatively and postoperatively.

Heart failure poses significant challenges in perioperative settings, with an increasing prevalence in India. While much attention has been given to the management of symptomatic heart failure, there is a dearth of literature on asymptomatic left ventricular systolic dysfunction (ALVSD). In this case report, we present the successful perioperative management of a 35-year-old male with ALVSD and a low ejection fraction undergoing lower limb surgery under combined spinal epidural anesthesia. Our approach aimed to maintain hemodynamic stability, minimize myocardial overload, and mitigate the adverse effects of neuraxial blockade.

The American Society of Anesthesiologist's Physical Status (ASA-PS) classification system assesses comorbidities before sedation and analgesia, but inconsistencies among raters have hindered its objective use. This study aimed to develop natural language processing (NLP) models to classify ASA-PS using pre-anesthesia evaluation summaries, comparing their performance to human physicians. Data from 717,389 surgical cases in a tertiary hospital (October 2004-May 2023) was split into training, tuning, and test datasets. Board-certified anesthesiologists created reference labels for tuning and test datasets. The NLP models, including ClinicalBigBird, BioClinicalBERT, and Generative Pretrained Transformer 4, were validated against anesthesiologists. The ClinicalBigBird model achieved an area under the receiver operating characteristic curve of 0.915. It outperformed board-certified anesthesiologists with a specificity of 0.901 vs. 0.897, precision of 0.732 vs. 0.715, and F1-score of 0.716 vs. 0.713 (all p <0.01). This approach will facilitate automatic and objective ASA-PS classification, thereby streamlining the clinical workflow.

Patients undergoing noncardiac surgery have varying risk of cardiovascular complications. This study evaluated preoperative N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T to enhance cardiovascular events prediction for major noncardiac surgery.

This prospective cohort study included adult patients with cardiovascular disease or risk factors undergoing elective major noncardiac surgery at four hospitals in China. Blood samples were collected within 30 days before surgery for NT-proBNP and high-sensitivity troponin T (hs-TnT) measurements. The primary outcome was a composite of any cardiovascular events within 30 days after surgery. Logistic regression models were used to assess associations, and the predictive performance was evaluated primarily using area under the receiver operating characteristics curve (AUC) and fraction of new predictive information.

Between June 2019 and September 2021, a total of 2,833 patients were included, with 435 (15.4%) experiencing the primary outcome. In the logistic regression model that included clinical variables and both biomarkers, the odds ratio for the primary outcome was 1.68 (95% CI, 1.37 to 2.07) when comparing the 75th percentile to the 25th percentile of NT-proBNP distribution, and 1.91 (95% CI, 1.50 to 2.43) for hs-TnT. Each biomarker enhanced model discrimination beyond clinical predictors, with a change in AUC of 0.028 for NT-proBNP and 0.029 for high-sensitivity cardiac troponin T, and a fraction of new information of 0.164 and 0.149, respectively. The model combining both biomarkers demonstrated the best discrimination, with a change in AUC of 0.042 and a fraction of new information of 0.219.

Preoperative NT-proBNP and hs-TnT both improved the prediction for cardiovascular events after noncardiac surgery in addition to clinical evaluation, with their combination providing maximal predictive information.

Cardiac risk evaluation prior to noncardiac surgery is fundamental to tailor peri-operative management to patient's estimated risk. Data on the degree of adherence to guidelines in patients at cardiovascular risk in Europe and factors influencing adherence are underexplored.

The aim of this analysis was to describe the degree of adherence to [2014 European Society of Cardiology (ESC)/European Society of Anaesthesiology (ESA) guidelines] recommendations on rest echocardiography [transthoracic echocardiography (TTE)] and to stress imaging prior to noncardiac surgery in a large European sample and to assess factors potentially affecting adherence.

Secondary analysis of a multicentre, international, prospective cohort study (MET-REPAIR).

Twenty-five European centres of all levels of care that enrolled patients between 2017 and 2020.

With elevated cardiovascular risk undergoing in-hospital elective, noncardiac surgery.

(Non)adherence to each pre-operative TTE and stress imaging recommendations classified as guideline-adherent, overuse and underuse. We performed descriptive analysis. To explore the impact of patients' sex, age, geographical region, and hospital teaching status, we conducted multivariate multinominal regression analysis.

Out of 15 983 patients, 15 529 were analysed (61% men, mean age 72 ± 8 years). Overuse (conduction in spite of class III) and underuse (nonconduction in spite of class I recommendation) for pre-operative TTE amounted to 16.6% (2542/15 344) and 6.6% (1015/15 344), respectively. Stress imaging overuse and underuse amounted to 1.7% (241/14 202) and 0.4% (52/14 202) respectively. Male sex, some age categories and some geographical regions were significantly associated with TTE overuse. Male sex and some regions were also associated with TTE underuse. Age and regions were associated with overuse of stress imaging. Male sex, age, and some regions were associated with stress imaging underuse.

Adherence to pre-operative stress imaging recommendation was high. In contrast, adherence to TTE recommendations was moderate. Both patients' and geographical factors affected adherence to joint ESC/ESA guidelines.

NCT03016936.

Prior publications about the association between participation in the American College of Surgeons National Surgical Quality Improvement Program and improved postoperative outcomes have reported mixed results. We aimed to perform a comprehensive analysis of preoperative characteristics and unadjusted and risk-adjusted postoperative complication rates over time in the American College of Surgeons National Surgical Quality Improvement Program dataset.

We used the American College of Surgeons National Surgical Quality Improvement Program database, 2005 to 2018, to analyze preoperative patient characteristics and unadjusted and risk-adjusted rates of adverse postoperative outcomes by year. Expected events were calculated using multiple logistic regression, with each complication as the dependent variable and the 28 non-laboratory preoperative American College of Surgeons National Surgical Quality Improvement Program variables as the independent variables. Annual observed-to-expected ratios for each outcome were used to risk-adjust outcomes over time.

The analytic cohort included 7,474,298 operations across 9 surgical specialties. Both the preoperative patient risk and the unadjusted rate of postoperative complications decreased over time. While the observed-to-expected ratio for mortality remained around 1, the observed-to-expected ratios for the other outcomes decreased over time from 2005 to 2018, except for the following cardiac complications: overall morbidity 1.11 (95% confidence interval: 1.10-1.13) to 0.97 (0.96-0.98); pulmonary 1.18 (1.15-1.21) to 0.91 (0.89-0.92); infection 1.19 (1.16-1.21) to 1.01 (1.00-1.01); urinary tract infection 1.29 (1.23-1.34) to 0.87 (0.86-0.89); venous thromboembolism 1.10 (1.03-1.16) to 0.92 (0.90-0.94) ; cardiac 0.76 (0.70-0.81) to 1.04 (1.01-1.07); renal 1.14 (1.08-1.21) to 0.96 (0.93-0.99); stroke 1.12 (1.00-1.25) to 0.98 (0.94-1.03); and bleeding 1.35 (1.33-1.36) to 0.80 (0.79-0.81).

Hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program have experienced a decrease in risk-adjusted postoperative surgical complications over time in all areas except for mortality and cardiac complications.

To determine whether concomitant use of ceftriaxone and oral or intravenous lansoprazole increases the risk of ventricular arrhythmia and cardiac arrest in the real-world setting in Japan.

The data analyzed were obtained from the JMDC hospital-based administrative claims database for the period April 2014 to August 2022. Patients who received a proton pump inhibitor (PPI) while receiving ceftriaxone or sulbactam/ampicillin were identified. The frequency of ventricular arrhythmia and cardiac arrest was analyzed according to whether oral or intravenous PPI was concomitant with ceftriaxone or sulbactam/ampicillin. Estimates of the incidence of ventricular arrhythmia and cardiac arrest were then compared among the groups, using the Fine-Gray competing risk regression model.

The results showed that the risk of ventricular arrhythmia and cardiac arrest was significantly higher with concomitant ceftriaxone and oral lansoprazole (hazard ratio 2.92, 95% confidence interval 1.99-4.29, P < 0.01) or intravenous lansoprazole (hazard ratio 4.57, 95% confidence interval 1.24-16.80, P = 0.02) than with concomitant sulbactam/ampicillin and oral or intravenous lansoprazole.

Oral and intravenous lansoprazole may increase the risk of ventricular arrhythmia and cardiac arrest in patients who are receiving ceftriaxone.

Accurate prediction of complications often informs shared decision-making. Derived over 10 years ago to enhance prediction of intra/post-operative myocardial infarction and cardiac arrest (MI/CA), the Gupta score has been criticized for unreliable calibration and inclusion of a wide spectrum of unrelated operations. In the present study, we developed a novel machine learning (ML) model to estimate perioperative risk of MI/CA and compared it to the Gupta score.

Patients undergoing major operations were identified from the 2016-2020 ACS-NSQIP. The Gupta score was calculated for each patient, and a novel ML model was developed to predict MI/CA using ACS NSQIP-provided data fields as covariates. Discrimination (C-statistic) and calibration (Brier score) of the ML model were compared to the existing Gupta score within the entire cohort and across operative subgroups.

Of 2,473,487 patients included for analysis, 25,177 (1.0%) experienced MI/CA (55.2% MI, 39.1% CA, 5.6% MI and CA). The ML model, which was fit using a randomly selected training cohort, exhibited higher discrimination within the testing dataset compared to the Gupta score (C-statistic 0.84 vs 0.80, p < 0.001). Furthermore, the ML model had significantly better calibration in the entire cohort (Brier score 0.0097 vs 0.0100). Model performance was markedly improved among patients undergoing thoracic, aortic, peripheral vascular and foregut surgery.

The present ML model outperformed the Gupta score in the prognostication of MI/CA across a heterogenous range of operations. Given the growing integration of ML into healthcare, such models may be readily incorporated into clinical practice and guide benchmarking efforts.