Explore the vast range of titles available.

Background: This study aims to clarify the perioperative risk factors and short-term prognosis of central bisectionectomy (CB) for hepatocellular carcinoma (HCC). Methods: Surgical data from 142 selected patients out of 171 HCC patients who underwent anatomical CB (H458) between 2005 and 2020 were collected from 17 expert institutions in a single-arm retrospective study. Results: Morbidities recorded by the International Study Group of Liver Surgery (ISGLS) from grade BC post-hepatectomy liver failure (PHLF) and bile leakage (PHBL), or complications requiring intervention were observed in 37% of patients. A multivariate analysis showed that increased blood loss (iBL) > 1500 mL from PHLF (risk ratio [RR]: 2.79), albumin level < 4 g/dL for PHBL (RR, 2.99), involvement of segment 1, a large size > 6 cm, or compression of the hepatic venous confluence or cava by HCC for all severe complications (RR: 5.67, 3.75, 6.51, and 8.95, respectively) (p < 0.05) were significant parameters. Four patients (3%) died from PHLF. HCC recurred in 50% of 138 surviving patients. The three-year recurrence-free and overall survival rates were 48% and 81%, respectively. Conclusions: Large tumor size and surrounding tumor involvement, or compression of major vasculatures and the related iBL > 1500 mL were independent risk factors for severe morbidities in patients with HCC undergoing CB.

As millions of surgical procedures are performed worldwide on an aging population with multiple comorbidities, accurate and simple perioperative risk stratification is critical. The cardiac biomarker, brain natriuretic peptide (BNP), has generated considerable interest as it is easy to obtain and appears to have powerful predictive and prognostic capabilities. BNP is currently being used to guide medical therapy for heart failure and has been added to several algorithms for perioperative risk stratification. This review examines the current evidence for the use of BNP in the perioperative period in patients who are at high-cardiovascular risk for noncardiac surgery. In addition, we examined the use of BNP in patients with pulmonary embolism and left ventricular assist devices. The available data strongly suggest that the addition of BNP to perioperative risk calculators is beneficial; however, whether this determination of risk will impact outcomes, remains to be seen.

Purpose Biomarkers can aid in perioperative risk stratification. While preoperative copeptin has been associated with adverse events, intraoperative information is lacking and this association may rather reflect a baseline risk. Knowledge about correlations between postoperative copeptin measurements and clinically relevant outcomes is scarce. We examined the association of perioperative copeptin concentrations with postoperative all-cause mortality and/or major adverse cardiac and cerebrovascular events (MACCE) at 12 months and 30 days as well as with perioperative myocardial injury (PMI). Methods We conducted a prospective observational cohort study of adults undergoing noncardiac surgery with intermediate to high surgical risk in Basel, Switzerland, and Düsseldorf, Germany from February 2016 to December 2020. We measured copeptin and cardiac troponin before surgery, immediately after surgery (0 hr) and once between the second and fourth postoperative day (POD 2–4). Results A primary outcome event of a composite of all-cause mortality and/or MACCE at 12 months occurred in 48/502 patients (9.6%). Elevated preoperative copeptin (> 14 pmol·L −1 ), immediate postoperative copeptin (> 90 pmol·L −1 ), and copeptin on POD 2–4 (> 14 pmol·L −1 ) were associated with lower one-year MACCE-free and/or mortality-free survival (hazard ratio [HR], 2.89; 95% confidence interval [CI], 1.62 to 5.2; HR, 2.07; 95% CI, 1.17 to 3.66; and HR, 2.47; 95% CI, 1.36 to 4.46, respectively). Multivariable analysis continued to show an association for preoperative and postoperative copeptin on POD 2–4. Furthermore, elevated copeptin on POD 2–4 showed an association with 30-day MACCE-free survival (HR, 2.15; 95% CI, 1.18 to 3.91). A total of 64 of 489 patients showed PMI (13.1%). Elevated preoperative copeptin was not associated with PMI, while immediate postoperative copeptin was modestly associated with PMI. Conclusion The results of the present prospective observational cohort study suggest that perioperative copeptin concentrations can help identify patients at risk for all-cause mortality and/or MACCE. Other identified risk factors were revised cardiac risk index, body mass index, surgical risk, and preoperative hemoglobin. Trial registration ClinicalTrials.gov (NCT02687776); first submitted 9 February 2016.

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.

  Purpose Duration and severity of exposure to excess adipose tissue are important risk factors for complications, but are generally not examined in conjunction. We developed a metric considering both factors to examine the relationship between obesity-related complications and parameters of cardiometabolic health in patients undergoing a metabolic bariatric procedure (MBS). Materials & Methods Data from patients screened for primary MBS between 2017 and 2021 were analyzed. The Obesity Exposure score (OBES), based on self-reported years of life with a BMI ≥ 25 kg/m 2 , was calculated with increased weighting applied for higher BMI categories. Multivariate logistic regression analysis was performed, adjusting for multiple potential confounders. Results In total, 2441 patients were included (76% female, age 42.1 ± 11.9 years, BMI 42.0 ± 4.9 kg/m 2 ). OBES was positively related to myocardial infarction, atrial fibrillation and renal function loss (per 10 OBES-units: OR 1.31, 95%CI [1.11–1.52], p = 0.002; OR 1.23, 95% CI [1.06–1.44], p = 0.008; and OR 1.26, 95% CI [1.04–1.51], p = 0.02). OBES was negatively associated with obstructive sleep apnea syndrome (OSAS) (OR 0.90, 95% CI [0.83–0.98], p = 0.02). In patients without obesity-related complications, OBES was related to lower HbA1c and higher HDL-cholesterol levels (ß -0.5 95% CI [-0.08-.0.02] p < 0.001 and ß 0.02 [0.00–0.04] p = 0.01). Conclusion OBES was related to myocardial infarction, atrial fibrillation and renal function loss in patients applying for MBS. OBES was negatively related to OSAS, possibly because undiagnosed years were not taken into account. In the absence of obesity-related complications, OBES was not related to metabolic blood markers. Our data may aid in improving perioperative risk assessments. Graphical Abstract

Previous studies proposed comorbidity-based prediction tools to facilitate patient-level assessment of mortality risk, which are essential for confounder adjustment in epidemiologic studies. We compared established comorbidity indices using real-world administrative data of a broad surgical population. Adult patients undergoing surgical or interventional procedures between January 2005 and June 2020 at a tertiary academic medical center in Massachusetts, USA, were included. The Elixhauser Comorbidity Index (van Walraven modification), Combined Comorbidity Score, and Charlson Comorbidity Index were compared regarding the prediction of 30-day mortality. Age and sex were included in all models. Discriminative ability was quantified by the area under the receiver operating characteristic curve (AUROC), and calibration was assessed using the Brier score and reliability plots. A total of 514,282 patients were included, of which 5849 (1.1%) died within 30 days. A model including age and sex alone had an AUROC of 0.73 (95% CI 0.72-0.74). The Elixhauser Comorbidity Index–based model showed the best discriminative ability with an AUROC of 0.86 (95% CI 0.86-0.87) compared to models, including the Combined Comorbidity Score (AUROC, 0.85 [95% CI 0.84-0.85]) and the Charlson Comorbidity Index (AUROC, 0.82 [95% CI 0.81-0.83], P < .001, respectively). The Brier score was 0.011 for all scores. Overall, score performances were similar or improved after the implementation of the 10th Revision International Classification of Diseases (Clinical Modification) coding system. The primary findings were confirmed for in-hospital, 7-day, 90-day, 180-day, and 1-year mortality and when including score comorbidities as separate indicator variables (P < .001, respectively). Patient and procedural characteristics were predictive of mortality (AUROC, 0.91 [95% CI 0.91-0.91]), with confirmatory findings and slightly improved performances when adding comorbidity scores (AUROC, 0.93 [95% CI 0.93-0.93] for the Elixhauser Comorbidity Index; AUROC, 0.93 [95% CI 0.93-0.93] for the Combined Comorbidity Score; AUROC, 0.92 [95% CI 0.92-0.93] for the Charlson Comorbidity Index, P < .001, respectively). All 3 comorbidity indices predicted mortality with excellent discrimination; however, they showed only slightly improved performance when incorporated into a model including patient and procedural characteristics. When surgical data are unavailable and in surgical setting–specific subgroups, the Elixhauser Comorbidity Index consistently performed best. [Display omitted] •Comorbidity-based prediction tools enable patient-level assessment of mortality risk.•We compared established prediction tools using electronic health records.•Among 514,282 surgical patients, the Elixhauser Comorbidity Index performed best.•The Elixhauser Comorbidity Index may be used preferably for mortality prediction in broad surgical populations.

Assess for a relationship between immediate preoperative glucose concentrations and postoperative complications. Retrospective cohort study. Single large, tertiary care academic medical center. A five-year registry of all patients at our hospital who had a glucose concentration (plasma, serum, or venous/capillary/arterial whole blood) measured up to 6 h prior to a non-emergent surgery. The glucose registry was cross-referenced with a database from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). We applied an outcomes review to the subset of patients for whom we had data from both registries (n = 1774). Preoperative glucose concentration in the full population as well as the subgroups of patients with or without diabetes were correlated with adverse postsurgical outcomes using 1) univariable analysis and 2) full multivariable analysis correcting for 27 clinical factors available from the ACS NSQIP database. Logistic regression analysis was performed using glucose level either as a continuous variable or as a categorical variable according to the following classifications: mild (≥140 mg/dL; ≥7.8 mmol/L), moderate (≥180 mg/dL; ≥10 mmol/L), or severe (≥250 mg/dL; ≥13.9 mmol/L) hyperglycemia. A third analysis was performed correcting for 7 clinically important factors (age, BMI, predicted duration of procedure, sex, CKD stage, hypoalbuminemia, and diabetic status) identified by anesthesiologists and surgeons as immediately available and important for decision making. Univariable analysis of all patients and the subgroups of patients without diabetes or with diabetes showed that immediate preoperative mild or moderate hyperglycemia correlates with postoperative complications. Statistical significance was lost in most groups using full multivariable analysis, but not when correcting for the 7 factors available immediately preoperatively. However, for all patients with diabetes, moderate hyperglycemia (≥180 mg/dL; ≥10 mmol/L) continued to significantly correlate with complications even in the full multivariable analysis [odds ratio (OR) 1.79; 95% Confidence Intervals (CI) 1.10, 2.92], and with readmission/reoperation within 30 days [OR 1.93; 95% CI 1.18, 3.13]. Preoperative hyperglycemia within 6 h of surgery is a marker of adverse postoperative outcomes. Among patients with diabetes in our study, a preoperative glucose level ≥ 180 mg/dL (≥10 mmol/L) independently correlates with risk of postoperative complications and readmission/reoperation. These results should encourage future work to determine whether addressing immediate preoperative hyperglycemia can improve complication rates, or simply serves as a marker of higher risk. •Preoperative hyperglycemia within 6 h of an elective surgery is a marker of adverse postoperative outcomes.•Among diabetic patients, a glucose > 180 mg/dl independently correlates with postoperative complications and readmission/reoperation.•Future work should determine whether addressing immediate preoperative hyperglycemia can improve outcomes, or simply serves as a marker of higher risk.

Malignant hyperthermia (MH) seriously threatens perioperative safety. Historically, limited awareness of MH among anesthesiologists and the unavailability of dantrolene have caused a high mortality rate of MH events in China. Although domestic dantrolene has been available in China since 2020, Chinese anesthesiologists continue to face significant challenges in managing MH crises. A WeChat applet-based National Remote Emergency System for Malignant Hyperthermia (MH-NRES) was developed to assist anesthesiologists in making rapid diagnosis, initiating dantrolene mobilization, implementing effective treatment, and subsequently constructing an MH database. However, the effectiveness of MH-NRES in real-world patients experiencing MH in China remains uncertain. This study aimed to assess the effectiveness of MH-NRES in enhancing outcomes for patients with MH. A retrospective pre-post implementation study was conducted from January 2018 to November 2024. The MH-NRES intervention was initiated in December 2022. Medical records were reviewed both before and after the implementation of our intervention, encompassing demographic characteristics, anesthesia-related data, treatment details, and clinical outcomes. Descriptive analyses and a pre-post intervention comparison were used to assess the effectiveness of the MH-NRES intervention. The primary outcome was the mortality of patients with MH. The use of dantrolene and the time interval from the MH episode to the administration of dantrolene were considered secondary outcomes. The user activity metrics of MH-NRES were also reported. After the MH-NRES was launched for public use, the cumulative number of users reached 21,835, with a maximum daily user growth of 689 (median 15, IQR 9-25). The cumulative page views amounted to 245,740 and the average daily page views were 262.8. A total of 34 patients with MH and 14 patients with MH were retrospectively collected before and after the intervention, respectively. The mortality of patients with MH in the postimplementation group was significantly lower compared with that in the preimplementation group (1/14, 7.1% vs 19/34, 55.9%; P=.002). No significant differences were observed in the early clinical manifestations of MH between the 2 groups. The rate of dantrolene use in the postimplementation group was significantly higher than that in the preimplementation group (11/14, 78.6% vs 15/34, 44.1%; P=.03). The dantrolene available time in the postimplementation group was 126.5 minutes earlier than that in the preimplementation group, but the difference did not reach statistical significance (median 113.5, IQR 54.5-244.3 vs 240, IQR 105-324 minutes, P=.08). The MH-NRES aids in improving the timely administration of dantrolene and decreasing mortality rates among patients with MH. This system represents a rare disease perioperative management model and constitutes a specialized perioperative management approach for rare diseases that suits the current medical situation in China.

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.

Purpose Daily smoking or risky drinking increases the risk of complications after surgery by ~50%. Intensive prehabilitation aimed at complete cessation reduces the complication rate but is time-consuming. The purpose of this study was to carry out preoperative pilot tests (randomized design) of the feasibility (1A) and validation (1B) of two novel prehabilitation apps, habeat® (Ha-app) or rehaviour® (Re-app). Methods Patients scheduled for hip or knee arthroplasty with daily smoking, risky drinking, or both were randomised to one of the two apps. In part 1A, eight patients and their staff measured feasibility on a visual analog scale (VAS) and were interviewed about what worked well and the challenges requiring improvement. In part 1B, seven patients and their staff tested the improved apps for up to two weeks before validating the understanding, usability, coverage, and empowerment on a VAS and being interviewed. Results In 1A, all patients and staff returned scores of ≥5 for understanding the apps and mostly suggested technical improvements. In 1B, the scores varied widely for both apps, with no consensus achieved. Two of four patients (Ha-app) and one-third of the patients (Re-app) found the apps helpful for reducing smoking, but without successful quitting. The staff experienced low app competencies among patients and high time consumption. Specifically, patients most often needed help for the Ha-app, and the staff most often for Re-app; however, the staff reported the Re-app dashboard was more user-friendly. Support and follow-up from an addiction specialist staff member were suggested to complement the apps, thereby increasing the time consumption for staff. Conclusions This pilot study to test prototype apps generated helpful feedback for the app developers. Based on the patient and staff comments, multiple improvements in functionality seem required before scaling up the evaluation for effect on prehabilitation and postoperative complications.