Association between postoperative complications and hospital length of stay: a large-scale observational study of 4,495,582 patients in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) registry.

BACKGROUND: Precise estimates of risk-adjusted increases in postoperative length of stay (LOS) associated with postoperative complications across a range of complications and operations are not available in the existing literature. METHODS: Associations between preoperative characteristics, postoperative complications and postoperative LOS were tested using medians, interquartile ranges, and nonparametric rank sum tests in a retrospective cohort study using the 2005-2018 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) dataset. A negative binomial model was used with postoperative LOS as the dependent variable and preoperative characteristics and postoperative complications as independent variables. The model was applied to estimate each patient's postoperative LOS with and without each postoperative complication to measure the association between each complication and risk-adjusted change in postoperative LOS. RESULTS: A total of 4,495,582 patients were included. After risk-adjustment, occurrence of each postoperative complication was associated with significantly increased postoperative LOS (between + 3.9 and + 20.1 days, p < 0.0001). The longest risk-adjusted postoperative LOS increases were associated with prolonged ventilator use (+ 20.1 days), wound disruption (+ 19.4 days), and acute renal failure (+ 17.1 days). CONCLUSION: Occurrence of any postoperative complication was associated with increased risk-adjusted postoperative LOS. Degree of increase varied by complication. These data could be useful for patient counseling, allocation of resources, discharge planning, and quality improvement efforts.

Risk-adjusted discrete increases in length of stay by complication following anatomic lung resection: an analysis of 32 133 cases across the USA.

OBJECTIVES: Prior studies have associated morbidity following anatomic lung resection with prolonged postoperative length of stay; however, each complication's individual impact on length of stay as a continuous variable has not been studied. The purpose of this study was to determine the risk-adjusted increase in length of stay associated with each individual postoperative complications following anatomic lung resection. METHODS: Patients who underwent anatomic lung resection cataloged in the prospectively collected American College of Surgeons National Surgical Quality Improvement Program participant use file, 2005-2018, were targeted. The association between preoperative characteristics, postoperative complications and length of stay in days was tested. A negative binomial model adjusting for the effect of preoperative characteristics and 18 concurrent postoperative complications was used to generate incidence rate ratios. This model was fit to generate risk-adjusted increases in length of stay by complication. RESULTS: Of 32 133 patients, 5065 patients (15.8%) experienced at least one post-operative complication. The most frequent complications were pneumonia (n = 1829, 5.7%), the need for transfusion (n = 1794, 5.6%) and unplanned reintubation (n = 1064, 3.3%). The occurrence of each of the 18 individual complications was associated with significantly increased length of stay. This finding persisted after risk-adjustment, with the greatest risk-adjusted increases being associated with prolonged ventilation (+17.4 days), followed by septic shock (+17.2 days), acute renal failure (+16.5 days) and deep surgical site infection (+13.2 days). CONCLUSIONS: All 18 postoperative complications studied following anatomic lung resection were associated with significant risk-adjusted increases in length of stay, ranging from an increase of 17.4 days with prolonged ventilation to 2.6 days following the need for transfusion.

Development and comparison of machine-learning models for predicting prolonged postoperative length of stay in lung cancer patients following video-assisted thoracoscopic surgery.

Objective: This study aimed to develop models for predicting prolonged postoperative length of stay (PPOLOS) in lung cancer patients undergoing video-assisted thoracoscopic surgery (VATS) by utilizing machine-learning techniques. These models aim to offer valuable insights for clinical decision-making. Methods: This retrospective cohort study analyzed a dataset of lung cancer patients who underwent VATS, identifying 25 numerical features and 45 textual features. Three classification machine-learning models were developed: XGBoost, random forest, and neural network. The performance of these models was evaluated based on accuracy (ACC) and area under the receiver operating characteristic curve, whereas the importance of variables was assessed using the feature importance parameter from the random forest model. Results: Of the 6767 lung cancer patients, 1481 patients (21.9%) experienced a postoperative length of stay of > 4 days. The majority were male (4111, 60.8%), married (6246, 92.3%), and diagnosed with adenocarcinoma (4145, 61.3%). The Random Forest classifier exhibited superior prediction performance with an area under the curve (AUC) of 0.792 and ACC of 0.804. The calibration plot revealed that all three classifiers were in close alignment with the ideal calibration line, indicating high calibration reliability. The five most critical features identified were the following: surgical duration (0.116), age (0.066), creatinine (0.062), hemoglobin (0.058), and total protein (0.054). Conclusions: This study developed and evaluated three machine-learning models for predicting PPOLOS in lung cancer patients undergoing VATS. The findings revealed that the Random Forest model is most accurately predicting the PPOLOS. Findings of this study enable the identification of crucial determinants and the formulation of targeted interventions to shorten the length of stay among lung cancer patients after VATS, which contribute to optimize the allocation of healthcare resources.

Ensemble learning-assisted prediction of prolonged hospital length of stay after spine correction surgery: a multi-center cohort study.

PURPOSE: This research aimed to develop a machine learning model to predict the potential risk of prolonged length of stay in hospital before operation, which can be used to strengthen patient management. METHODS: Patients who underwent posterior spinal deformity surgery (PSDS) from eleven medical institutions in China between 2015 and 2022 were included. Detailed preoperative patient data, including demographics, medical history, comorbidities, preoperative laboratory results, and surgery details, were collected from their electronic medical records. The cohort was randomly divided into a training dataset and a validation dataset with a ratio of 70:30. Based on Boruta algorithm, nine different machine learning algorithms and a stack ensemble model were trained after hyperparameters tuning visualization and evaluated on the area under the receiver operating characteristic curve (AUROC), precision-recall curve, calibration, and decision curve analysis. Visualization of Shapley Additive exPlanations method finally contributed to explaining model prediction. RESULTS: Of the 162 included patients, the K Nearest Neighbors algorithm performed the best in the validation group compared with other machine learning models (yielding an AUROC of 0.8191 and PRAUC of 0.6175). The top five contributing variables were the preoperative hemoglobin, height, body mass index, age, and preoperative white blood cells. A web-based calculator was further developed to improve the predictive model's clinical operability. CONCLUSIONS: Our study established and validated a clinical predictive model for prolonged postoperative hospitalization duration in patients who underwent PSDS, which offered valuable prognostic information for preoperative planning and postoperative care for clinicians. Trial registration ClinicalTrials.gov identifier NCT05867732, retrospectively registered May 22, 2023, https://classic. CLINICALTRIALS: gov/ct2/show/NCT05867732 .

Esketamine use is associated with shortened postoperative hospital stay in patients after knee arthroscopic surgery: a propensity score-matched cohort study.

BACKGROUND: Previous studies have examined anesthetics to improve postoperative prognosis after knee arthroscopic surgery. However, it is currently unknown whether perioperative anesthetics can influence postoperative hospital stay. We investigated the impact of esketamine after knee arthroscopic surgery on post-operative length of stay, fever and surgical site infection. METHODS: This study included 455 patients who underwent knee surgery between January2020 and August 2021at a tertiary hospital in China. Patient characteristics, preoperative laboratory values, intra-operative anesthetic data, and postoperative outcomes were collected. Univariate and multivariate logistic regression analyses with or without propensity score matching were performed to identify factors related to post-operative discharge within 3 days(PD3). RESULTS: A total of 297 cases met our inclusion criteria. The mean age of patients was 42 ± 14 years, mean body mass index, 24.1 ± 3.5 kg/m2, 157(53%) patients were male. Meniscus-related procedures accounted for the most part of all the procedures with a percentage of 40.4%, followed by combined procedures of 35.4%. After we adjusted for demographic and intraoperative characteristics with propensity score matching, esketamine use was significantly associated with PD3 with the highest odds ratio of 2.28 (95% confidence interval (CI): 1.18-4.41, p = 0.014). CONCLUSION: Esketamine use was associated with PD3 in patients underwent knee arthroscopic surgery. The findings of this study will be useful to anesthesiologists in making informed decisions regarding the choice of anesthetics for knee joint diseases. TRIAL REGISTRATION: This study was approved by the Ethics Committee (Approval No.:2023-041-01) of the Eighth Affiliated Hospital, Sun Yat-sen University and retrospectively registered.

Development and validation of an instrument to predict prolonged length of stay in the postanesthesia care unit following ambulatory surgery.

PURPOSE: We sought to develop and validate an Anticipated Surveillance Requirement Prediction Instrument (ASRI) for prediction of prolonged postanesthesia care unit length of stay (PACU-LOS, more than four hours) after ambulatory surgery. METHODS: We analyzed hospital registry data from patients who received anesthesia care in ambulatory surgery centres (ASCs) of university-affiliated hospital networks in New York, USA (development and internal validation cohort [n = 183,711]) and Massachusetts, USA (validation cohort [n = 148,105]). We used stepwise backwards elimination to create ASRI. RESULTS: The model showed discriminatory ability in the development, internal, and external validation cohorts with areas under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI], 0.82 to 0.83), 0.82 (95% CI, 0.81 to 0.83), and 0.80 (95% CI, 0.79 to 0.80), respectively. In cases started in the afternoon, ASRI scores ≥ 43 had a total predicted risk for PACU stay past 8 p.m. of 32% (95% CI, 31.1 to 33.3) vs 8% (95% CI, 7.9 to 8.5) compared with low score values (P-for-interaction < 0.001), which translated to a higher direct PACU cost of care of USD 207 (95% CI, 194 to 2,019; model estimate, 1.68; 95% CI, 1.64 to 1.73; P < 0.001) The effects of using the ASRI score on PACU use efficiency were greater in a free-standing ASC with no limitations on PACU bed availability. CONCLUSION: We developed and validated a preoperative prediction tool for prolonged PACU-LOS after ambulatory surgery that can be used to guide scheduling in ambulatory surgery to optimize PACU use during normal work hours, particularly in settings without limitation of PACU bed availability.

RéSUMé: OBJECTIF: Nous avons cherché à mettre au point et à valider un Instrument de prédiction anticipée des besoins de surveillance pour anticiper toute prolongation de la durée de séjour en salle de réveil (plus de quatre heures) après chirurgie ambulatoire. MéTHODE: Nous avons analysé les données enregistrées dans le registre de l'hôpital des patient·es qui ont reçu des soins d'anesthésie dans des centres de chirurgie ambulatoire (CCA) des réseaux hospitaliers affiliés à une université à New York, aux États-Unis (cohorte de développement et de validation interne [n = 183 711]) et au Massachusetts, États-Unis (cohorte de validation [n = 148 105]). Nous avons utilisé un procédé d'élimination progressive régressive pour créer notre instrument de prédiction. RéSULTATS: Le modèle a montré une capacité discriminatoire dans les cohortes de développement, de validation interne et de validation externe, avec des surfaces sous la courbe de fonction d'efficacité de l'opérateur (ROC) de 0,82 (intervalle de confiance [IC] à 95 %, 0,82 à 0,83), 0,82 (IC 95 %, 0,81 à 0,83), et 0,80 (IC 95 %, 0,79 à 0,80), respectivement. Dans les cas commencés en après-midi, les scores sur notre instrument de prédiction ≥ 43 montraient un risque total prédit de séjour en salle de réveil après 20 h de 32 % (IC 95 %, 31,1 à 33,3) vs 8 % (IC 95 %, 7,9 à 8,5) comparativement aux valeurs de score faibles (P-pour-interaction < 0,001), ce qui s'est traduit par une augmentation de 207 USD du coût direct des soins en salle de réveil (IC 95 %, 194 à 2019; estimation du modèle, 1,68; IC 95 %, 1,64 à 1,73; P < 0,001). Les effets de l'utilisation du score de notre instrument de prédiction sur l'efficacité d'utilisation de la salle de réveil étaient plus importants dans un CCA autonome sans limitation dans la disponibilité des lits en salle de réveil. CONCLUSION: Nous avons mis au point et validé un outil de prédiction préopératoire de la prolongation de la durée de séjour en salle de réveil après une chirurgie ambulatoire qui peut être utilisé pour guider la planification en chirurgie ambulatoire afin d'optimiser l'utilisation de la salle de réveil pendant les heures normales de travail, en particulier dans les milieux sans limitation de disponibilité des lits en salle de réveil.

The predictive value of the preoperative albumin-to-fibrinogen ratio for postoperative hospital length of stay in liver cancer patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is a significant global health burden, with postoperative hospital length of stay (LOS) impacting patient outcomes and healthcare costs. Existing nutritional, inflammatory, and coagulation indices can predict LOS, with particular interest in albumin, fibrinogen, and D-dimer. This study investigates the predictive value of preoperative albumin-to-fibrinogen ratio (AFR) and albumin-to-D-dimer ratio (ADR) for postoperative LOS in HCC patients. METHODS: This retrospective study involved 462 adult HCC patients who underwent partial hepatic lesion excision between February 2016 and August 2022. We analyzed demographic and clinical data, including preoperative blood samples, surgical approach, and LOS. The primary outcome measure was LOS, calculated from the date of surgery to the date of hospital discharge. Preoperative AFR and ADR were calculated. The ROC curves determined optimal cutoff points. The Cox proportional hazards model, Kaplan-Meier method, and the log-rank test were used for statistical analysis. RESULTS: The study established an optimal AFR cutoff value of 15.474, with a higher AUC value than ADR, indicating superior predictive potential for postoperative LOS. Participants with high-AFR (AFR > 15.474) had a shorter median LOS (13 vs. 15 days, p < 0.001) compared to those with low-AFR (AFR ≤15.474). Multivariate analysis revealed high-AFR (HR: 1.99; p < 0.001) as a positive influence on LOS reduction, whereas Child-Pugh rated as B (HR: 0.49; p < 0.001), laparotomy (HR: 0.37; p < 0.001) and total bilirubin >20.5 µmol/L (HR: 0.58; p < 0.001) negatively impacted LOS reduction. Subgroup analysis confirmed AFR's predictive ability for patients experiencing reduced or prolonged LOS due to Child-Pugh score, surgical methods, and total bilirubin concentrations. Even within normal albumin and fibrinogen levels, patients with high-AFR exhibited a shorter LOS (all p < 0.001). CONCLUSIONS: Our findings underscore the value of the AFR as a reliable predictor of LOS in HCC patients. An AFR greater than 15.474 consistently correlated with a shorter LOS, suggesting its potential clinical utility in guiding perioperative management and resource allocation in HCC patients.

A New Nomogram-Based Prediction Model for Postoperative Outcome after Sigmoid Resection for Diverticular Disease.

Background and Objectives: Sigmoid resection still bears a considerable risk of complications. The primary aim was to evaluate and incorporate influencing factors of adverse perioperative outcomes following sigmoid resection into a nomogram-based prediction model. Materials and Methods: Patients from a prospectively maintained database (2004-2022) who underwent either elective or emergency sigmoidectomy for diverticular disease were enrolled. A multivariate logistic regression model was constructed to identify patient-specific, disease-related, or surgical factors and preoperative laboratory results that may predict postoperative outcome. Results: Overall morbidity and mortality rates were 41.3% and 3.55%, respectively, in 282 included patients. Logistic regression analysis revealed preoperative hemoglobin levels (p = 0.042), ASA classification (p = 0.040), type of surgical access (p = 0.014), and operative time (p = 0.049) as significant predictors of an eventful postoperative course and enabled the establishment of a dynamic nomogram. Postoperative length of hospital stay was influenced by low preoperative hemoglobin (p = 0.018), ASA class 4 (p = 0.002), immunosuppression (p = 0.010), emergency intervention (p = 0.024), and operative time (p = 0.010). Conclusions: A nomogram-based scoring tool will help stratify risk and reduce preventable complications.

Postoperative length of stay following kidney transplantation in patients without delayed graft function-An analysis of center-level variation and patient outcomes.

BACKGROUND: Early discharge after surgical procedures has been proposed as a novel strategy to reduce healthcare expenditures. However, national analyses of the association between discharge timing and post-transplant outcomes following kidney transplantation are lacking. METHODS: This was a retrospective cohort study of all adult kidney transplant recipients without delayed graft function from 2014 to 2019 in the Organ Procurement and Transplantation Network and Nationwide Readmissions Databases. Recipients were divided into Early (LOS ≤ 4 days), Routine (LOS 5-7), and Delayed (LOS > 7) cohorts. RESULTS: Of 61 798 kidney transplant recipients, 26 821 (43%) were discharged Early and 23 279 (38%) Routine. Compared to Routine, patients discharged Early were younger (52 [41-61] vs. 54 [43-62] years, p < .001), less commonly Black (33% vs. 34%, p < .001), and more frequently had private insurance (41% vs. 35%, p < .001). After adjustment, Early discharge was not associated with inferior 1-year patient survival (Hazard Ratio [HR] .74, 95% Confidence Interval [CI] 0.66-0.84) or increased likelihood of nonelective readmission at 90-days (HR .93, CI .89-.97), relative to Routine discharge. Discharging all Routine patients as Early would result in an estimated cost saving of ∼$40 million per year. Multi-level modeling of post-transplantation LOS revealed that 28.8% of the variation in LOS was attributable to interhospital differences rather than patient factors. CONCLUSIONS: Early discharge after kidney transplantation appears to be cost-efficient and not associated with inferior post-transplant survival or increased readmission at 90 days. Future work should elucidate the benefits of early discharge and develop standardized enhanced recovery protocols to be implemented across transplant centers.

Clinical Validation of the Comprehensive Complication Index in a Pancreaticoduodenectomy Cohort.

INTRODUCTION: Although the Clavien-Dindo classification (CDC) is the most widely utilized method for quantifying surgical complications, it fails to properly capture all events. To address this, the comprehensive complication index (CCI) was introduced. The purpose of this study was to compare the CCI and CDC as predictors of postoperative length of stay (PLOS) and total hospitalization costs in patients undergoing pancreaticoduodenectomy (PD). METHODS: Data were collected from February 2018 to February 2021. Complications were graded on the CDC scale and the CCI was calculated for each patient. The correlations between CDC and CCI with PLOS and hospitalization costs were compared. Linear analyses were performed to identify factors associated with PLOS and costs. RESULTS: 291 patients were enrolled with an average age of 61.2 years. 286 of them developed postoperative complications at CDC grade 1 (17.8%), 2 (59.9%), 3a (13.4%), 3b (4.5%), 4 (2.1%), and 5 (0.6%). Median CCI of the study cohort was 30.8. Spearman's correlation analysis showed the CDC and CCI were significantly correlated with PLOS and hospitalization costs, but the CCI showed a stronger correlation with PLOS (+0.552 day of stay for each additional CCI point; CCI: ρ = 0.663 vs. CDC: ρ = 0.581; p = 0.036). There were no significant differences in the correlations between total hospitalization costs and the CDC or CCI (CCI: ρ = 0.566 vs. CDC: ρ = 0.565; p = 0.78). CONCLUSION: CCI is an accurate tool for quantifying morbidities after PD and shows a stronger correlation with PLOS compared with the CDC.

Optimal discharge planning for esophagectomy patients with enhanced recovery after surgery: Recommendations.

Background: Studies have suggested that the postoperative length of stay (PLOS) of esophagectomy patients under the enhanced recovery after surgery (ERAS) pathway should be >10 days as against the previously recommended 7 days. We investigated the distribution and influencing factors of PLOS in the ERAS pathway in order to recommend an optimal planned discharge time. Methods: This was a single-center retrospective study of 449 patients with thoracic esophageal carcinoma who underwent esophagectomy and perioperative ERAS between January 2013 and April 2021. We established a database to prospectively document the causes of delayed discharge. Results: The mean and median PLOS were 10.2 days and 8.0 days (range: 5-97), respectively. Patients were divided into four groups: group A (PLOS ≤ 7 days), 179 patients (39.9%); group B (8 ≤ PLOS ≤ 10 days), 152 (33.9%); group C (11 ≤ PLOS ≤ 14 days), 68 (15.1%); group D (PLOS > 14 days), 50 patients (11.1%). The main cause of prolonged PLOS in group B was minor complications (prolonged chest drainage, pulmonary infection, recurrent laryngeal nerve injury). Severely prolonged PLOS in groups C and D were due to major complications and comorbidities. On multivariable logistic regression analysis, open surgery, surgical duration >240 min, age >64 years, surgical complication grade >2, and critical comorbidities were identified as risk factors for delayed discharge. Conclusions: The optimal planned discharge time for patients undergoing esophagectomy with ERAS should be 7-10 days with a 4-day discharge observation window. Patients at risk of delayed discharge should be managed adopting PLOS prediction.

Causal determinants of postoperative length of stay in cardiac surgery using causal graphical learning.

OBJECTIVE: We aimed to learn the causal determinants of postoperative length of stay in cardiac surgery patients undergoing isolated coronary artery bypass grafting or aortic valve replacement surgery. METHODS: For patients undergoing isolated coronary artery bypass grafting or isolated aortic valve replacement surgeries between 2011 and 2016, we used causal graphical modeling on electronic health record data. The Fast Causal Inference (FCI) algorithm from the Tetrad software was used on data to estimate a Partial Ancestral Graph (PAG) depicting direct and indirect causes of postoperative length of stay, given background clinical knowledge. Then, we used the latent variable intervention-calculus when the directed acyclic graph is absent (LV-IDA) algorithm to estimate strengths of causal effects of interest. Finally, we ran a linear regression for postoperative length of stay to contrast statistical associations with what was learned by our causal analysis. RESULTS: In our cohort of 2610 patients, the mean postoperative length of stay was 219 hours compared with the Society of Thoracic Surgeons 2016 national mean postoperative length of stay of approximately 168 hours. Most variables that clinicians believe to be predictors of postoperative length of stay were found to be causes, but some were direct (eg, age, diabetes, hematocrit, total operating time, and postoperative complications), and others were indirect (including gender, race, and operating surgeon). The strongest average causal effects on postoperative length of stay were exhibited by preoperative dialysis (209 hours); neuro-, pulmonary-, and infection-related postoperative complications (315 hours, 89 hours, and 131 hours, respectively); reintubation (61 hours); extubation in operating room (-47 hours); and total operating room duration (48 hours). Linear regression coefficients diverged from causal effects in magnitude (eg, dialysis) and direction (eg, crossclamp time). CONCLUSIONS: By using retrospective electronic health record data and background clinical knowledge, causal graphical modeling retrieved direct and indirect causes of postoperative length of stay and their relative strengths. These insights will be useful in designing clinical protocols and targeting improvements in patient management.

Risk factors associated with postoperative complications and prolonged postoperative length of stay after laparoscopic liver resection.

Introduction: Laparoscopic liver resection (LLR) has expanded rapidly. Previously published studies are limited to small samples and selected patients. Comprehensive data that may significantly influence the incidence of perioperative complications and postoperative length of stay (PLOS) are lacking. Aim: To characterize complications after LLR and to identify risk factors associated with postoperative complications and prolonged PLOS. Material and methods: This study was carried out at a high-volume HPB centre and included all patients who underwent LLRs between 2015 and 2018. Postoperative complications were analysed in detail. Logistic regression was used to identify independent risk factors. The primary outcome was postoperative complications with a comprehensive complication index (CCI) ≥ 26.2. The second outcome was prolonged length of stay. Results: We identified 938 patients who underwent LLR. In the full cohort, 79 (8.4%) patients experienced major complications with a CCI ≥ 26.2, with postoperative mortality in 4 (0.4%) patients. On multivariate analysis, the diagnosis of primary (OR = 8.97, 95% CI: 2.54-43.74, p = 0.001) and metastatic liver tumours (OR = 5.74, 95% CI: 1.20-30.90, p = 0.028), infectious liver disease (OR = 24.04, 95% CI: 5.30-129.53, p < 0.001), difficult liver resection (OR = 2.77, 95% CI: 1.29-6.69, p = 0.014), and intraoperative bleeding > 1000 ml (OR = 9.29, 95% CI: 3.40-26.43, p < 0.001) were independent factors that increased the odds of major complications. The median PLOS after the operation was 5 days (range: 2-35 days). Factors that independently influenced prolonged PLOS on multivariate analysis were age over 70 years, metastatic liver tumour, difficult liver resection, liver cirrhosis, and right hepatectomy. Conclusions: LLR remains safe for most liver space-occupying lesions. Several preoperative and intraoperative factors associated with the risk of complications and prolonged PLOS were identified. These factors should be considered during patient selection and perioperative management.

Prolonged postoperative length of stay may be a valuable marker for susceptibility to relapse beyond established risk factors in patients with stage III colon cancer.

BACKGROUND: Delay from surgery to adjuvant chemotherapy causes impaired survival among patients undergoing radical resection for stage III colon cancer, and the underlying mechanism for this is incompletely clarified. It is established that prolonged postoperative hospital length of stay (LOS) is associated with delayed initiation of the adjuvant treatment driving the assumption that prolonged LOS is prognostically unfavorable due to this fact and case mix factors. We hypothesize that prolonged LOS after surgery is a valuable marker for susceptibility to relapse that is not detected in established prognostic factors and, alone, associated with a shorter disease-free survival (DFS). MATERIALS AND METHODS: A total of 690 consecutive patients undergoing elective radical resection for stage III colon cancer in 2000-2015 were identified in a prospective detailed facility database. Univariate and multivariate analyses were performed using Cox proportional hazards model in the evaluation of LOS as an independent prognostic factor. RESULTS: Short postoperative LOS, low comorbidity, and few complications were associated with longer DFS (p < 0.01). Fewer patients in the short and intermediate LOS groups had a relapse in their disease (28% and 33%, respectively), compared to the patients with longer LOS (40%, p < 0.05). LOS was a prognostic factor for DFS in the unadjusted univariate model (HR 1.04 per unit change) and remained statistically significant in the adjusted multivariate analysis, with a HR of 1.03 per hospital day (p < 0.01). CONCLUSIONS: Postoperative LOS independently correlates with the risk of recurrence and DFS, regardless of if adjuvant chemotherapy is given, along with the factors such as age, comorbidity, complications, and tumor features. We propose a further investigation into the causal mechanisms based on tumor and host biology linking LOS to DFS beyond established risk factors.

Is there a relationship between two different anesthetic methods and postoperative length of stay during radical resection of malignant esophageal tumors in China?: a retrospective cohort study.

BACKGROUND: Data providing a relationship between the anesthetic method and postoperative length of stay (PLOS) is limited. We aimed to investigate whether general anesthesia alone or combined with epidural anesthesia might affect perioperative risk factors and PLOS for patients undergoing radical resection of malignant esophageal tumors. METHODS: The study retrospectively analyzed the clinical data of 680 patients who underwent a radical esophageal malignant tumor resection in a Chinese hospital from January 01, 2010, to December 31, 2020. The primary outcome measure was PLOS, and the secondary outcome was perioperative risk-related parameters that affect PLOS. The independent variable was the type of anesthesia: general anesthesia (GA) or combined epidural-general anesthesia (E-GA). The dependent variable was PLOS. We conducted univariate and multivariate logistic regression and propensity score matching to compare the relationships of GA and E-GA with PLOS and identify the perioperative risk factors for PLOS. In this cohort study, the confounders included sociodemographic data, preoperative chemotherapy, coexisting diseases, laboratory parameters, intraoperative variables, and postoperative complications. RESULTS: In all patients, the average PLOS was 19.85 ± 12.60 days. There was no significant difference in PLOS between the GA group and the E-GA group either before or after propensity score matching (20.01 days ± 14.90 days vs. 19.79 days ± 11.57 days, P = 0.094, 18.09 ± 9.71 days vs. 19.39 ± 10.75 days, P = 0.145). The significant risk factors for increased PLOS were lung infection (ß = 3.35, 95% confidence interval (CI): 1.54-5.52), anastomotic leakage (ß = 25.73, 95% CI: 22.11-29.34), and surgical site infection (ß = 9.39, 95% CI: 4.10-14.68) by multivariate regression analysis. Subgroup analysis revealed a stronger association between PLOS and vasoactive drug use, blood transfusions, and open esophagectomy. The results remained essentially the same (stable and reliable) after subgroup analysis. CONCLUSIONS: Although there is no significant association between the type of anesthesia(GA or E-GA) and PLOS for patients undergoing radical esophageal malignant tumor resection, an association between PLOS and lung infection, anastomotic leakage, and surgical site infection was determined by multivariate regression analysis. A larger sample future study design may verify our results.

Chyme reinfusion improved outcomes after definitive surgery for small-intestinal enteroatmospheric fistula in patients with enteral nutrition.

PURPOSE: In patients suffering from small-intestinal enteroatmospheric fistula who are receiving enteral nutrition (EN), although the function of the small intestine is sufficient, without chyme reinfusion (CR), disuse of the distal intestine of enteroatmospheric fistula may occur. However, CR reverses such pathological changes and have an influence on improving outcomes following definitive surgery (DS) for small-intestinal enteroatmospheric fistula. This study attempted to investigate the effect of preoperative CR in patients with EN on the outcomes after DS for small-intestinal enteroatmospheric fistula. METHODS: According to whether CR was performed between January 2012 and December 2019, patients receiving DS for small intestinal enteroatmospheric fistula were divided into the CR group and non-CR group. The effect of preoperative CR was then investigated. RESULTS: A total of 159 patients were finally enrolled, of which 72 patients were in the CR group and 87 patients were in the non-CR group. A total of 47 (29.56%) patients were found to have recurrent fistula after DS, the recurrent fistula rate in the CR group (multivariate odds ratio = 0.557; 95% CI, 0.351-0.842; P = 0.019) was lower. CR was also shown to promote postoperative recovery of bowel function (hazard ratio [HR] = 1.982; 95% CI, 1.199-3.275; P = 0.008), and shorten postoperative length of stay (LOS) (HR = 1.739; 95% CI, 1.233-2.453; P = 0.002). CONCLUSION: Preoperative CR may reduce the incidence of recurrent fistula, time to return of bowel function and postoperative LOS following DS for small-intestinal enteroatmospheric fistula.

Enhanced recovery after elective craniotomy: A randomized controlled trial.

STUDY OBJECTIVES: Enhanced recovery after surgery (ERAS) protocols have been proven to improve outcomes but have not been widely used in neurosurgery. The purpose of this study was to design a multidisciplinary enhanced recovery after elective craniotomy protocol and to evaluate its clinical efficacy and safety after implementation. DESIGN: A prospective randomized controlled trial. SETTING: The setting is at an operating room, a post-anesthesia care unit, and a hospital ward. PATIENTS: This randomized controlled trial (RCT) prospectively analyzed 151 patients who underwent elective craniotomy between January 2019 and June 2020. INTERVENTIONS: The neurosurgical ERAS group was cared for with evidence-based systematic optimization approaches, while the control group received routine care. MEASUREMENTS: The primary outcomes were the postoperative length of stay (LOS) and hospitalization costs. The secondary outcomes included 30-day readmission rates, postoperative complications, postoperative pain scores, length of intensive care unit (ICU) stay, duration of the drainage tube, time to oral intake, time to ambulation, and postoperative functional recovery status. MAIN RESULTS: After ERAS protocol implementation, the median postoperative LOS (4 days to 3 days, difference [95% confidence interval, CI], 2 [1 to 2], P < 0.0001) and hospitalization costs (6266 USD to 5880 USD, difference [95% CI], 427.0 [234.8 to 633.6], P < 0.0001) decreased. Compared to routine perioperative care, the ERAS protocol reduced the incidence of postoperative nausea and vomiting (PONV) (28.0% to 9.2%, adjusted odds ratio [OR] 0.3, 95% CI 0.1-0.7, P = 0.003), shortened urinary catheter removal time by 24 h (64.0% to 83.0%, adjusted OR 2.9, 95% CI 1.3-6.5, P = 0.031), improved ambulation on postoperative day 1 (POD 1) (30.7% to 75.0%, adjusted OR 7.5, 95% CI 3.6-15.8, P < 0.0001), shortened the time to oral intake (15 h to 13 h, difference [95% CI], 3 [1 to 4], P < 0.001), and improved perioperative pain management. CONCLUSIONS: Implementation of an enhanced recovery after elective craniotomy protocol had significant benefits over conventional perioperative management. It was associated with a significant reduction in postoperative length of stay, medical cost, and postoperative complications.

Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records: Retrospective Cross-sectional Study.

BACKGROUND: Postoperative length of stay is a key indicator in the management of medical resources and an indirect predictor of the incidence of surgical complications and the degree of recovery of the patient after cancer surgery. Recently, machine learning has been used to predict complex medical outcomes, such as prolonged length of hospital stay, using extensive medical information. OBJECTIVE: The objective of this study was to develop a prediction model for prolonged length of stay after cancer surgery using a machine learning approach. METHODS: In our retrospective study, electronic health records (EHRs) from 42,751 patients who underwent primary surgery for 17 types of cancer between January 1, 2000, and December 31, 2017, were sourced from a single cancer center. The EHRs included numerous variables such as surgical factors, cancer factors, underlying diseases, functional laboratory assessments, general assessments, medications, and social factors. To predict prolonged length of stay after cancer surgery, we employed extreme gradient boosting classifier, multilayer perceptron, and logistic regression models. Prolonged postoperative length of stay for cancer was defined as bed-days of the group of patients who accounted for the top 50% of the distribution of bed-days by cancer type. RESULTS: In the prediction of prolonged length of stay after cancer surgery, extreme gradient boosting classifier models demonstrated excellent performance for kidney and bladder cancer surgeries (area under the receiver operating characteristic curve [AUC] >0.85). A moderate performance (AUC 0.70-0.85) was observed for stomach, breast, colon, thyroid, prostate, cervix uteri, corpus uteri, and oral cancers. For stomach, breast, colon, thyroid, and lung cancers, with more than 4000 cases each, the extreme gradient boosting classifier model showed slightly better performance than the logistic regression model, although the logistic regression model also performed adequately. We identified risk variables for the prediction of prolonged postoperative length of stay for each type of cancer, and the importance of the variables differed depending on the cancer type. After we added operative time to the models trained on preoperative factors, the models generally outperformed the corresponding models using only preoperative variables. CONCLUSIONS: A machine learning approach using EHRs may improve the prediction of prolonged length of hospital stay after primary cancer surgery. This algorithm may help to provide a more effective allocation of medical resources in cancer surgery.

Association of preoperative medication with postoperative length of stay in elderly patients undergoing hip fracture surgery.

BACKGROUND: For elderly patients who are about to undergo surgery, research on the effects of preoperative medication on postoperative outcomes is rare, especially preoperative discontinuation-requiring medication (PDRM) which needed to be discontinued because of its increased risk of postoperative complications. AIM: To investigate whether preoperative medication (PDRM and polypharmacy) is associated with postoperative length of hospital stay (LOS) in elderly patients undergoing hip fracture surgery. METHODS: Patients aged ≥ 65 who were scheduled for hip (limited to femoral tuberosity) fracture surgery were included. Baseline characteristics, preoperative medication and postoperative LOS were collected from the electronic medical record. The primary outcome was postoperative LOS. RESULTS: A total of 369 hip fracture patients were included. There were 188 and 122 patients exposed to PDRM and polypharmacy, respectively. Multivariate analysis models were constructed using significant factors for prolonged postoperative hospital stay from univariate analysis: Model I (body mass index (BMI), Charlson comorbidity index (CCI) ≥ 7, creatinine clearance rate (Ccr) < 60 and PDRM) and Model II (BMI, Ccr ≥ 7, Ccr < 60 and polypharmacy). CCI was the most significant factor. Its adjusted odds ratio was as large as 2.7 and attributable risk was 63%. In preoperative medication use, both polypharmacy and PDRM showed significant association with postoperative LOS. CONCLUSION: The present study supported the impact of PDRM on postoperative LOS in geriatric hip fracture patients. The results added a further aspect to preoperative medication optimization in elderly patients undergoing hip fracture surgery.

Association between perioperative fluid management and patient outcomes: a multicentre retrospective study.

BACKGROUND: Postoperative complications increase hospital length of stay and patient mortality. Optimal perioperative fluid management should decrease patient complications. This study examined associations between fluid volume and noncardiac surgery patient outcomes within a large multicentre US surgical cohort. METHODS: Adults undergoing noncardiac procedures from January 1, 2012 to December 31, 2017, with a postoperative length of stay ≥24 h, were extracted from a large US electronic health record database. Patients were segmented into quintiles based on recorded perioperative fluid volumes with Quintile 3 (Q3) serving as the reference. The primary outcome was defined as a composite of any complications during the surgical admission and a postoperative length of stay ≥7 days. Secondary outcomes included in-hospital mortality, respiratory complications, and acute kidney injury. RESULTS: A total of 35 736 patients met the study criteria. There was a U-shaped pattern with highest (Q5) and lowest (Q1) quintiles of fluid volumes having increased odds of complications and a postoperative length of stay ≥7 days (Q5: odds ratio [OR] 1.51 [95% confidence interval {CI}: 1.30-1.74], P<0.001; Q1: OR 1.20 [95% CI: 1.04-1.38], P=0.011) compared with Q3. Patients in Q5 had greater odds of more severe acute kidney injury compared with Q3 (OR 1.52 [95% CI: 1.22-1.90]; P<0.001) and respiratory complications (OR 1.44 [95% CI: 1.17-1.77]; P<0.001). CONCLUSIONS: Both very high and very low perioperative fluid volumes were associated with an increase in complications after noncardiac surgery.