Prolonged Length Of Stay Research Articles

#1085 Prediction models for hospitalization in patients with advanced chronic kidney disease: systematic review, external validation and development study

Abstract Background and Aims Hospitalization is a common complication in patients with advanced chronic kidney disease (CKD). Predicting hospitalization would be beneficial for clinicians and patients. Clinicians may be assisted in adequate healthcare planning by being able to anticipate hospitalizations. Additionally, patients have indicated wanting more information about their risk of hospitalization. By providing patients a personal indication of their risk of hospitalization, they better know what to expect of the future which can foster a feeling of control. Especially for incident dialysis patients this might help, as they enter a new and to them still largely unknown stage of their disease. Moreover, if a patient knows they have a high risk of hospitalization, they may better cope with the hospitalization if it occurs, as it is less unexpected. Therefore, we aimed to 1) identify and give an overview of current prediction models for hospitalization in CKD patients, 2) externally validate these models, and 3) develop a new model if no well-performing models were identified. Method We performed a systematic review in PubMed to identify prediction models for hospitalization, length of stay (LOS), and readmission. Identified models were appraised using the Prediction model Risk of Bias Assessment Tool. We targeted three external validations in hemodialysis (HD), peritoneal dialysis (PD), and pre-dialysis patients in a Dutch dialysis and European pre-dialysis cohort. Prediction models were externally validated on discrimination (C-statistic) and calibration (calibration plot, slope, and calibration-in-the-large). We developed a Fine-Gray model for hospitalization within one year in patients initiating HD, taking into account the competing risk of death. Informed by model performance, we also investigated Cox and logistic regression as modeling strategies. We performed a sensitivity analysis, redefining the outcome to be predicted as the 1-year risk of hospitalization of 3 days or longer. Results From the systematic search, we identified 17 models in 6 studies. All models were developed in the USA or in China. Two models predicted hospitalization rate in incident PD patients and 3 models predicted 30-day readmission in maintenance HD patients and in CKD stage 3-5 patients not on dialysis discharged after a heart failure hospitalization. The risk of 1 and 6 hospitalizations within one year in prevalent HD patients were predicted by one model each. Prolonged LOS in PD patients was predicted by ten models. All models were of low quality with a high risk of bias. The most common shortcomings were using future information to make predictions, inadequate handling of missing data, and model overfitting. Due to underreporting and unavailability of predictors, we could only externally validate 3 models. These models were poorly calibrated and had poor discrimination. We developed a new model in 1,020 incident HD patients predicting 1-year risk of hospitalization. We used age, cardiovascular disease, diabetes mellitus, malignancy, estimated glomerular filtration rate, and body mass index as predictors, selected based on literature and clinical expertise. The model discriminated poorly (C-statistic, 95% confidence interval [CI]; 0.55, 0.53-0.58), also in targeted external validations in 620 PD patients (0.55, 0.52-0.58) and 1,718 pre-dialysis patients (0.52, 0.52-0.54). Calibration was poor for all models. Using different modelling strategies, model performance did not improve. In the sensitivity analysis, discrimination improved but was still low (HD population: 0.58, 0.55-0.62; PD population: 0.59, 0.54-0.63; pre-dialysis: 0.55, 0.52-0.57). Conclusion Hospitalizations are important but difficult to predict for patients with advanced CKD. Current models are insufficient to predict hospitalizations. We offer two main suggestions to improve future predictions of hospitalizations. First, the outcome of hospitalization should be more specific (e.g., cardiovascular hospitalizations) to reduce outcome heterogeneity. Second, the selection of predictors should be extended with more patient-centered factors, such as patient-reported outcomes.

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion

BackgroundThe frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperatively anticipate adverse postoperative outcomes given the procedure’s expanding use. Our study aims to accomplish two goals: firstly, to develop a suite of explainable machine learning (ML) models capable of predicting adverse postoperative outcomes following ACDF surgery, and secondly, to embed these models in a user-friendly web application, demonstrating their potential utility.MethodsWe utilized data from the National Surgical Quality Improvement Program database to identify patients who underwent ACDF surgery. The outcomes of interest were four short-term postoperative adverse outcomes: prolonged length of stay (LOS), non-home discharges, 30-day readmissions, and major complications. We utilized five ML algorithms - TabPFN, TabNET, XGBoost, LightGBM, and Random Forest - coupled with the Optuna optimization library for hyperparameter tuning. To bolster the interpretability of our models, we employed SHapley Additive exPlanations (SHAP) for evaluating predictor variables’ relative importance and used partial dependence plots to illustrate the impact of individual variables on the predictions generated by our top-performing models. We visualized model performance using receiver operating characteristic (ROC) curves and precision-recall curves (PRC). Quantitative metrics calculated were the area under the ROC curve (AUROC), balanced accuracy, weighted area under the PRC (AUPRC), weighted precision, and weighted recall. Models with the highest AUROC values were selected for inclusion in a web application.ResultsThe analysis included 57,760 patients for prolonged LOS [11.1% with prolonged LOS], 57,780 for non-home discharges [3.3% non-home discharges], 57,790 for 30-day readmissions [2.9% readmitted], and 57,800 for major complications [1.4% with major complications]. The top-performing models, which were the ones built with the Random Forest algorithm, yielded mean AUROCs of 0.776, 0.846, 0.775, and 0.747 for predicting prolonged LOS, non-home discharges, readmissions, and complications, respectively.ConclusionsOur study employs advanced ML methodologies to enhance the prediction of adverse postoperative outcomes following ACDF. We designed an accessible web application to integrate these models into clinical practice. Our findings affirm that ML tools serve as vital supplements in risk stratification, facilitating the prediction of diverse outcomes and enhancing patient counseling for ACDF.

The effect of controlled vs uncontrolled hypertension on outcomes of carotid revascularization procedures

BackgroundHypertension (HTN) has been implicated as a strong predictive factor for poorer outcomes in patients undergoing various vascular procedures. However, limited research is available that examines the effect of uncontrolled HTN (uHTN) on outcomes after carotid revascularization. We aimed to determine which carotid revascularization procedure yields the best outcome in this patient population. MethodsWe studied patients undergoing carotid endarterectomy (CEA), transfemoral carotid artery stenting (TFCAS), or transcarotid artery revascularization (TCAR) from April 2020 to June 2022 using data from the Vascular Quality Initiative. Patients were stratified into two groups: those with cHTN and those with uHTN. Patients with cHTN were those with HTN treated with medication and a blood pressure of <130/80 mm Hg. Patients with uHTN had a blood pressure of ≥130/80 mm Hg. Our primary outcomes were in-hospital stroke, death, myocardial infarction (MI), and 30-day mortality. Our secondary outcomes were postoperative hypotension or HTN, reperfusion syndrome, prolonged length of stay (LOS) (>1 day), stroke/death, and stroke/death/MI. We used logistic regression models for the multivariate analysis. ResultsA total of 34,653 CEA (uHTN, 11,347 [32.7%]), 8199 TFCAS (uHTN, 2307 [28.1%]), and 17,309 TCAR (uHTN, 4990 [28.8%]) patients were included in this study. There was no significant difference in age between patients with cHTN and patients with uHTN for each carotid revascularization procedure. However, compared with patients with cHTN, patients with uHTN had significantly more comorbidities. uHTN was associated with an increased risk of combined in-hospital stroke/death/MI after CEA (adjusted odds ratio [aOR], 1.56; 95% confidence interval [CI], 1.30-1.87; P < .001), TFCAS (aOR, 1.59; 95% CI, 1.21-2.08; P < .001), and TCAR (aOR, 1.39; 95% CI, 1.12-1.73; P = .003) compared with cHTN. Additionally, uHTN was associated with a prolonged LOS after all carotid revascularization methods. For the subanalysis of patients with uHTN, TFCAS was associated with an increased risk of stroke (aOR, 1.82; 95% CI, 1.39-2.37; P < .001), in-hospital death (aOR, 3.73; 95% CI, 2.25-6.19; P < .001), reperfusion syndrome (aOR, 6.24; 95% CI, 3.57-10.93; P < .001), and extended LOS (aOR, 1.87; 95% CI, 1.51-2.32; P < .001) compared with CEA. There was no statistically significant difference between the outcomes of TCAR compared with CEA. ConclusionsThe results from this study show that patients with uHTN are at a higher risk of stroke and death postoperatively compared with patients with cHTN, highlighting the importance of treating HTN before undergoing elective carotid revascularization. Additionally, in patients with uHTN, TFCAS yields the worst outcomes, whereas CEA and TCAR proved to be safer interventions. Patients with uTHN with symptomatic carotid disease treated with CEA or TCAR have better outcomes compared with those treated with TFCAS.

Risk factors for malnutrition in patients with diabetic foot ulcer and its association with prolonged length of hospitalization.

The study was designed to investigate the occurrence and risk factors of malnutrition in diabetic foot ulcers (DFU) patients and examine the association between malnutrition and length of stay (LOS). This observational study included DFU hospitalized patients in two campuses of a hospital from January 2021 to June 2023. The diagnosis standard of malnutrition was established by using the Global Leadership Initiative on Malnutrition (GLIM) criteria. Patients were followed up to ascertain the length of hospitalization, and hospital stays longer than 17 days were considered as prolonged LOS. To explore the risk factors of malnutrition and the association between malnutrition and LOS, univariate and multivariate logistic regression analyses were performed. Overall 219 DFU patients were enrolled, malnutrition was identified in 38.36% of patients according to GLIM criteria, and 92 patients (42%) were recognized as prolonged LOS. Logistic regression analyses showed that BMI (P <0.001), Alb (P = 0.002), HbA1c (P <0.001), ulcer infection (P <0.001), LOS (P = 0.010), and ABI (P = 0.024) were independent risk factors for malnutrition. Besides, malnutrition by GLIM criteria was closely related to prolonged LOS and malnourished DFU patients were 2.857 times (95% CI, 1.497-5.450; P = 0.001) likely to present prolonged LOS than that of normal nutrition. Malnutrition was considered to be extremely prevalent in DFU patients and was associated with approximately three times higher likelihood of prolonged LOS. Implementing and disseminating the diagnostic criteria during routine practice is crucial, given the predictive efficacy of GLIM criteria.

The effect of diabetes mellitus on perioperative outcomes after colorectal resection: a national cohort study

BackgroundDiabetes mellitus is a significant modulator of postoperative outcomes and is an important risk factor in the patient selection process. We aimed to investigate the effect of diabetes mellitus and use of insulin on outcomes after colorectal resection using a national cohort. MethodsAdults with a recorded colorectal resection in England between 2010 and 2020 were identified from Hospital Episode Statistics data linked to the Clinical Practice Research Database. The primary outcome was 90-day mortality. Secondary outcomes included hospital length of stay (LOS) and readmission within 90 days. ResultsOf the 106 139 (52 875, 49.8% male) patients included, diabetes mellitus was prevalent in 10 931 (10.3%), 2145 (19.6%) of whom had a record of use of insulin. Unadjusted 90-day mortality risk was 5.7%, with an increased adjusted hazard ratio (aHR) for people with diabetes mellitus (aHR 1.28, 95% confidence interval [CI] 1.19–1.37, P<0.001). This risk was higher in both people with diabetes using insulin (aHR 1.51, 95% CI 1.31–1.74, P<0.001) and not using insulin (aHR 1.22, 95% CI 1.13–1.33, P<0.001), compared with those without diabetes. Ninety-day readmission occurred in 20 542 (19.4%) patients and this was more likely in those with diabetes mellitus (aHR 1.23, 95% CI 1.18–1.29, P<0.001). Median (inter-quartile range) LOS was 8 (5–15) days and was higher in people with diabetes mellitus (adjusted time ratio 1.10, 95% CI 1.08–1.11, P<0.001). ConclusionsPeople with diabetes mellitus undergoing colorectal resection are at a higher risk of 90-day mortality, prolonged LOS, and 90-day readmission, with use of insulin associated with additional risk.

Serum Albumin and Post-Stroke Outcomes: Analysis of UK Regional Registry Data, Systematic Review, and Meta-Analysis

Hypoalbuminemia associates with poor acute ischemic stroke (AIS) outcomes. We hypothesised a non-linear relationship and aimed to systematically assess this association using prospective stroke data from the Norfolk and Norwich Stroke and TIA Register. Consecutive AIS patients aged ≥40 years admitted December 2003–December 2016 were included. Outcomes: In-hospital mortality, poor discharge, functional outcome (modified Rankin score 3–6), prolonged length of stay (PLoS) &gt; 4 days, and long-term mortality. Restricted cubic spline regressions investigated the albumin–outcome relationship. We updated a systematic review (PubMed, Scopus, and Embase databases, January 2020–June 2023) and undertook a meta-analysis. A total of 9979 patients were included; mean age (standard deviation) = 78.3 (11.2) years; mean serum albumin 36.69 g/L (5.38). Compared to the cohort median, albumin &lt; 37 g/L associated with up to two-fold higher long-term mortality (HRmax; 95% CI = 2.01; 1.61–2.49) and in-hospital mortality (RRmax; 95% CI = 1.48; 1.21–1.80). Albumin &gt; 44 g/L associated with up to 12% higher long-term mortality (HRmax1.12; 1.06–1.19). Nine studies met our inclusion criteria totalling 23,597 patients. Low albumin associated with increased risk of long-term mortality (two studies; relative risk 1.57 (95% CI 1.11–2.22; I2 = 81.28)), as did low-normal albumin (RR 1.10 (95% CI 1.01–1.20; I2 = 0.00)). Strong evidence indicates increased long-term mortality in AIS patients with low or low-normal albumin on admission.

A National Analysis of Alcohol Withdrawal Syndrome in Patients with Operative Trauma

BackgroundAlcohol withdrawal syndrome (AWS) presents with a complex spectrum of clinical manifestations that complicate postoperative management. In trauma setting, subjective screening for AWS remains challenging due to the criticality of injury in these patients. We thus identified several patient characteristics and perioperative outcomes associated AWS development. MethodsThe 2016–2020 National Inpatient Sample was queried to identify all non-elective adult (≥18 years) hospitalizations for blunt or penetrating trauma undergoing operative management with a diagnosis of AWS. Patients with traumatic brain injury or with a hospital duration of stay <2 days were excluded. Outcomes of interest included in-hospital mortality, perioperative complications, hospitalization costs, length of stay (LOS) and non-home discharge. ResultsOf an estimated 2,965,079 operative trauma hospitalizations included for analysis, 36,415 (1.23 %) developed AWS following admission. The AWS cohort demonstrated increased odds of mortality (Adjusted Odds Ratio [AOR] 1.46, 95 % Confidence Interval [95 % CI] 1.23–1.73), along with infectious (AOR 1.73, 95 % CI 1.58–1.88), cardiac (AOR 1.24, 95 % CI 1.06–1.46), and respiratory (AOR 1.96, 95 % CI 1.81–2.11) complications. AWS was associated with prolonged LOS, (β: 3.3 days, 95 % CI: 3.0 to 3.5), greater cost (β: +$8900, 95 % CI $7900–9800) and incremental odds of nonhome discharge (AOR 1.43, 95 % CI 1.34–1.53). Furthermore, male sex, Medicaid insurance status, head injury and thoracic operation were linked with greater odds of development of AWS. ConclusionIn the present study, AWS development was associated with increased odds of in-hospital mortality, perioperative complications, and resource burden. The identification of patient and operative characteristics linked with AWS may improve screening protocols in trauma care.

Factors Associated With Prolonged-Stay Patients Within the Post-anesthesia Care Unit: A Cohort Retrospective Study.

The post-anesthesia care unit (PACU) plays a crucial role in providing specializedcare to postoperative patients. However, a subset of these patients experiences complications that result in a prolonged stay of 90 minutes or more in the PACU. This not only impacts the patient's quality of life but also disrupts hospital workflow, as it might cause postoperative pain, nausea, or vomiting. It is essential to identify the factors contributing to this prolonged length of stay (LOS) and explore strategies for its prevention and management. Methods: We conducted a retrospective cohort study of postoperative patients between 2020 and 2021. We included patients who had a prolonged stay, excluding cardiac patients, patients who had a planned prolonged stay, and patients waiting for an intensive care unit bed. We used a non-probability consecutive sampling technique. Data were obtained from the BestCare System, the hospital's information system, using adata collection sheet. A total of 15,170 patients underwent surgical procedures during the study period, out of which only 181 (1.19%) experienced a prolonged PACU stay. Pain and altered mental status were strongly associated with a prolonged PACU stay (P = 0.035 and P = 0.0009, respectively). However,there was no significant association between overall comorbidities and prolonged LOS in the PACU, except for patients with asthma (P = 0.003). Different types and durations of surgeriesdid not significantly contribute to a prolonged PACU stay. Our study found that among the various variables examined, asthma, pain, and altered mental status were significantly associated with a prolonged LOS in the PACU. These findings suggest that targeted interventions addressing these factors may help reduce the incidence of prolonged PACU stays and optimize patient outcomes.

Patient Factors Associated With Prolonged Length of Stay After Traumatic Brain Injury.

Background For traumatic brain injury (TBI) survivors, recovery can lead to significant time spent in the inpatient/rehabilitation settings. Hospital length of stay (LOS) after TBI is a crucial metric of resource utilization and treatment costs. Risk factors for prolonged LOS (PLOS) after TBI require further characterization. Methodology We conducted a retrospective analysis of patients with diagnosed TBI at an urban trauma center. PLOS was defined as the 95th percentile of the LOS of the cohort. Patients with and without PLOS were compared using clinical/injury factors. Analyses included descriptive statistics, non-parametric analyses, and multivariable logistic regression for PLOS status. Results The threshold for PLOS was >24 days. In the cohort of 1,343 patients, 77 had PLOS. PLOS was significantly associated with longer mean intensive care unit (ICU) stays (16.4 vs. 1.5 days), higher mean injury severity scores (18.6 vs. 13.8), lower mean Glasgow coma scale scores (11.3 vs. 13.7) and greater mean complication burden (0.7 vs. 0.1). PLOS patients were more likely to have moderate/severe TBI, Medicaid insurance, and were less likely to be discharged home.In the regression model, PLOS was associated with ICU stay, inpatient disposition, ventilator use, unplanned intubation, and inpatient alcohol withdrawal. Conclusions TBI patients with PLOS were more likely to have severe injuries, in-hospital complications, and Medicaid insurance. PLOS was predicted by ICU stay, intubation, alcohol withdrawal, and disposition to inpatient/post-acute care facilities. Efforts to reduce in-hospital complications and expedite discharge may reduce LOS and accompanying costs.Further validation of these results is needed from larger multicenter studies.

Chronic Kidney Disease in Patients with Hip Fracture: Prevalence and Outcomes

Objective. Although the association between chronic kidney disease (CKD) and osteoporotic fractures is well established, data on CKD combined with hip fracture (HF) are scarce and controversial. We aimed to assess in patients with HF the prevalence of CKD, its impact on hospital mortality and length of stay (LOS) and to determine the prognostic value of CKD to predict hospital outcomes. Methods. Prospectively collected clinical data were analysed in 3623 consecutive HF patients aged ≥65 years (mean age 83.4 ± 7.50 [standard deviation] years; 74.4% females). Results. CKD among older patients with HF is highly prevalent (39.9%), has different clinical characteristics, a 2.5-fold higher mortality rate, and 40% greater risk of prolonged LOS. The strongest risk for a poor outcome was advanced age (&gt;80 years). The risk of death substantially increases in combination with chronic disorders, especially coronary artery disease, anaemia, hyperparathyroidism, and atrial fibrillation; models based only on three variables—CKD stage, age &gt;80, and presence of a specific chronic condition—predicted in-hospital death with good discrimination capability (AUC ≥ 0.700) and reasonable accuracy, the number needed to predict ranged between 5.7 and 14.5. Only 12% of HF patients received osteoporotic drugs prefracture. Conclusion. In HF patients with CKD, the risk of adverse outcomes largely increases in parallel with worsening kidney function and, especially, in combination with comorbidities; models based on three admission variables predict a fatal outcome. Assessment of renal function is essential to preventing osteoporotic fractures.

Diuretic response after neonatal cardiac surgery: a report from the NEPHRON collaborative.

Multicenter early diuretic response (DR) analysis of single furosemide dosing following neonatal cardiac surgery is lacking to inform whether early DR predicts adverse clinical outcomes. We performed a retrospective cohort study utilizing data from the NEPHRON registry. Random forest machine learning generated receiver operating characteristic-area under the curve (ROC-AUC) and odds ratios for mechanical ventilation (MV) and respiratory support (RS). Prolonged MV and RS were defined using ≥ 90th percentile of observed/expected ratios. Secondary outcomes were prolonged CICU and hospital length of stay (LOS) and kidney failure (stage III acute kidney injury (AKI), peritoneal dialysis, and/or continuous kidney replacement therapy on postoperative day three) assessed using covariate-adjusted ROC-AUC curves. A total of 782 children were included. Cumulative urine output (UOP) metrics were lower in prolonged MV and RS patients, but DR poorly predicted prolonged MV (highest AUC 0.611, OR 0.98, sensitivity 0.67, specificity 0.53, p = 0.006, 95% OR CI 0.96-0.99 for cumulative 6-h UOP) and RS (highest AUC 0.674, OR 0.94, sensitivity 0.75, specificity 0.54, p < 0.001, 95% CI 0.91-0.97 UOP between 3 and 6h). Secondary outcome results were similar. DR had fair discrimination for kidney failure (AUC 0.703, OR 0.94, sensitivity 0.63, specificity 0.71, 95% OR CI 0.91-0.98, p < 0.001, cumulative 6-h UOP). Early DR poorly discriminated patients with prolonged MV, RS, and LOS in this cohort, though it may identify severe postoperative AKI phenotype. Future work is warranted to determine if early DR or late postoperative DR later, in combination with other AKI metrics, may identify a higher-risk phenotype.

Abstract PO4-23-03: The Influence of Reconstruction Type on Outcomes in Women Undergoing Mastectomy with Immediate Reconstruction: A Nationwide Study

Abstract INTRODUCTION: Outcomes after mastectomy with immediate reconstruction may vary depending on the type of reconstruction, but the evidence is limited and inconsistent. The purpose of this study was to compare the most common reconstruction techniques in a large national cohort of women undergoing these procedures. METHODS: The Nationwide Readmissions Database for 2016-2020 was queried for all women aged 18 years or older undergoing mastectomy for breast cancer with immediate reconstruction. The primary outcome was prolonged length of stay (LOS) greater than 7 days. The secondary outcomes were readmission within 30 days and readmission to a different hospital. The types of reconstruction were compared along with all other relevant variables from the database. Univariable comparison was performed using chi-squared tests for each outcome. Multivariable logistic regression was performed using all significant confounders. RESULTS: During the study period, 35,430 patients were identified undergoing mastectomy for breast cancer with immediate reconstruction. The rate of prolonged (LOS) was 2.4% (n= 840) and the readmission rate was 5.4% (n=1,919). From the readmitted patients, the rate of readmission to a different hospital was 14.2% (n=273). Controlling for confounders with multivariable logistic regression revealed the strongest risk factors for prolonged LOS were latissimus dorsi flap (OR 5.4 [4.0-7.4] p&amp;lt; 0.001) and an investor-owned hospital (OR 4.3 [3.5-5.2] p&amp;lt; 0.001). The highest risk of readmission was a transverse rectus abdominis flap (OR 1.3 [1.1-1.6] p&amp;lt; 0.001) and the highest risk of readmission to a different hospital was a small hospital (OR 2.2 [1.6-3.1] p&amp;lt; 0.001). CONCLUSION: Reconstruction type influences outcomes in women undergoing mastectomy. These outcomes have significant implications for surgical decision-making and fragmentation of care. Further research to identify ways to reduce adverse outcomes and improve patient satisfaction is warranted. Citation Format: Lucia Castro Hernandez, Joshua Parreco. The Influence of Reconstruction Type on Outcomes in Women Undergoing Mastectomy with Immediate Reconstruction: A Nationwide Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-23-03.

Robotic transversus abdominis release (TAR) for ventral hernia repairs is associated with low surgical site occurrence rates and length of stay despite increasing modifiable comorbidities

PurposeModifiable comorbidities (MCMs) have previously been shown to complicate postoperative wound healing occasionally leading to surgeon hesitancy to repair ventral hernias prior to preoperative optimization of comorbidities. This study describes the effects of MCMs on surgical site occurrences (SSOs) and hospital length of stay (LOS) following robotic transversus abdominis release (TAR) with poly-4-hydroxybutyrate (P4HB) resorbable biosynthetic mesh retromuscular sublay for ventral hernia repair in patients who had not undergone preoperative optimization.MethodsA single-surgeon retrospective review was performed for patients who underwent the robotic TAR procedure with P4HB mesh between January 2015 and May 2022. Patients were stratified by the amount of MCMs present: 0, 1, or 2 + . MCMs included obesity, diabetes, and current tobacco use. Patient data was analyzed for the first 60 days following their operation. Primary outcomes included 60-day SSO rates and hospital LOS.ResultsThree hundred and thirty-four subjects met the inclusion criteria for SSO and prolonged LOS analysis. 16.8% had no MCM, 56.1% had 1 MCM, and 27% had 2 + MCMs. No significant difference in SSO was seen between the 3 groups; however, having 2 + MCMs was significantly associated with increased odds of SSO (odds ratio 3.25, P = .019). When the groups were broken down, only having a history of diabetes plus obesity was associated with significantly increased odds of SSO (odds ratio 3.54, P = .02). No group showed significantly increased odds of prolonged LOS.Conclusion2 + MCMs significantly increase the odds of SSO, specifically in patients who have a history of diabetes and obesity. However, the presence of any number of MCMs was not associated with increased odds of prolonged LOS.

Neighborhood socioeconomic disadvantages associated with prolonged length of stay and non-home discharge following revision total hip and knee joint arthroplasty

BackgroundDischarge disposition and length of stay (LOS) are widely recognized markers of healthcare utilization patterns of total hip and knee joint arthroplasty (TJA). These markers are commonly associated with increased postoperative complications, patient dissatisfaction, and higher costs. Area deprivation index (ADI) has been validated as a composite metric of neighborhood-level disadvantage. This study aims to determine the potential association between ADI and discharge disposition or extended LOS following revision TJA. MethodsThis study conducted a retrospective analysis of a consecutive series of revision hip and knee TJA patients from a single tertiary institution. Univariate and multivariate regression analysis was used to determine the association between ADI and discharge disposition or LOS, adjusting for patient demographics and comorbidities. Results1047 consecutive revision TJA patients were identified across 463 different neighborhoods. 193 (18.4 %) had an extended LOS, and 334 (31.9 %) were discharged to non-home facilities. Compared with Q1 (least deprived cohort), Q2 (odds ratio [OR] = 1.63; p = 0.030) and Q4 (most deprived cohort: OR = 2.04; p = 0.002) cohorts demonstrated higher odds of non-home discharge. Patients in the highest ADI quartile (most deprived cohort) were associated with increased odds of prolonged LOS following revision TJA compared to those in the lowest ADI quartile (OR = 2.63; p < 0.001). ConclusionThis study suggests that higher levels of neighborhood-level disadvantage may be associated with higher odds of non-home discharge and prolonged LOS following revision TJA. Development of interventions based on the area deprivation index may improve discharge planning and reduce unnecessary non-home discharges in patients living in areas of socioeconomic deprivation.

Impact of geographical cohorting, multidisciplinary rounding and incremental case management support on hospital length of stay and readmission rates: a propensity weighted analysis

Hospital length of stay (LOS) in the USA has been increasing since the start of the COVID-19 pandemic, with numerous negative outcomes, including decreased quality of care, worsened patient satisfaction...

Predicting Prolonged Length of Hospital Stay and Identifying Risk Factors Following Total Ankle Arthroplasty: A Supervised Machine Learning Methodology

Ankle osteoarthritis (OA) is a debilitating condition that arises as a result of trauma or injury to the ankle and often progresses to chronic pain and loss of function that may require surgical intervention. Total ankle arthroplasty (TAA) has emerged as a means of operative treatment for end-stage ankle OA. Increased hospital length of stay (LOS) is a common adverse postoperative outcome that increases both the complications and cost of care associated with arthroplasty procedures. The purpose of this study was to employ four machine learning (ML) algorithms to predict LOS in patients undergoing TAA using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database. The ACS-NSQIP database was queried to identify adult patients undergoing elective TAA from 2008 to 2018. Four supervised ML classification algorithms were utilized and tasked with predicting increased hospital length of stay (LOS). Among these variables, female sex, ASA Class III, preoperative sodium, preoperative hematocrit, diabetes, preoperative creatinine, other arthritis, BMI, preoperative WBC, and Hispanic ethnicity carried the highest importance across predictions generated by 4 independent ML algorithms. Predictions generated by these algorithms were made with an average AUC of 0.7257, as well as an average accuracy of 73.98% and an average sensitivity and specificity of 48.47% and 79.38%, respectively. These findings may be useful for guiding decision-making within the perioperative period and may serve to identify patients at increased risk for a prolonged LOS.

Racial disparities in the attainment of textbook oncologic outcomes following colectomy for colon cancer: a national cancer database cohort study.

Textbook oncologic outcome (TOO) is attained when all desired short-term quality metrics are met following an oncologic operation. The objective of this study was to determine the impact of race on TOO attainment following colectomy for colon cancer. The 2004-2017 National Cancer Database was queried for patients with non-metastatic colon cancer who underwent colectomy. TOO was defined as: negative margins (R0), adequate lymphadenectomy (LAD) (n ≥ 12), no prolonged length of stay (LOS), no 30-day readmission or mortality, and initiation of systemic therapy in ≤ 12weeks. Racial groups were defined as White, Black, or Hispanic. 508,312 patients were identified of which 34% achieved TOO. Blacks attained the least TOO (31.4%) as well as the TOO criteria of adequate LAD (81.1%), no prolonged LOS (52.3%), and no 30-day readmission (89.7%). Hispanics were least likely to have met the criteria of R0 resection (94.3%), no 30-day mortality (87.3%), and initiation of systemic therapy in ≤ 12weeks (81.8%). Patients who attained TOO had a higher median overall survival (OS) than those without TOO (148.2 vs. 84.2months; P < 0.001). Hispanic TOO patients had the highest median OS (181.2months), while White non-TOO patients experienced the lowest (80.2months, P < 0.001). Multivariate logistic regression models suggest that Black and Hispanic patients are less likely to achieve TOO than their White counterparts. Racial disparities exist in the achievement of TOO, with Blacks and Hispanics being less likely to attain TOO compared to their White counterparts.

Factors Associated with Prolonged Length of Stay in the Emergency Department Prior to Hospitalization

Factors Associated with Prolonged Length of Stay in the Emergency Department Prior to Hospitalization

Early prediction of long hospital stay for Intensive Care units readmission patients using medication information

ObjectivePredicting Intensive Care Unit (ICU) Length of Stay (LOS) accurately can improve patient wellness, hospital operations, and the health system's financial status. This study focuses on predicting the prolonged ICU LOS (≥3 days) of the 2nd admission, utilizing short historical data (1st admission only) for early-stage prediction, as well as incorporating medication information. Materials and methodsWe selected 18,572 ICU patients’ records from the MIMIC-IV database for this study. We applied five machine learning classifiers: Logistic regression (LR), Random Forest (RF), Support Vector Machine (SVM), AdaBoost (AB) and XGBoost (XGB). We computed both the sum dose and the average dose for the medication and included them in our model. ResultsThe performance of the RF model demonstrates the highest level of accuracy compared to other models, as indicated by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.716 and an Expected Calibration Error (ECE) of 0.023. DiscussionThe calibration improved all five classifiers (LR, RF, SVC, AB, XGB) in terms of ECE. The most important two features for RF are the length of 1st admission and the patient's age when they visited the hospital. The most important medication features are Phytonadione and Metoprolol Succinate XL. Also, both the sum and the average dose for the medication features contributed to the prediction task. ConclusionOur model showed the capability to predict the prolonged ICU LOS of the 2nd admission by utilizing the demographic, diagnosis, and medication information from the 1st admission. This method can potentially support the prevention of patient complications and enhance resource allocation in hospitals.

Predictors of prolonged length of stay in adult patients with respiratory syncytial virus infections - a multi-center historical cohort study.

Several studies have reported risk factors for severe disease and mortality in hospitalized adults with RSV infections. There is limited information available regarding the factors that affect the duration of a patient's hospital length of stay (LOS). This was a multicenter historical cohort study of adult patients hospitalized for laboratory-confirmed RSV in Southeast Michigan between January 2017 and December 2021. Hospitalized patients were identified using the International Classification of Diseases, Tenth Revision 10 codes for RSV infection. Mean LOS was computed; prolonged LOS was defined as greater than the mean. We included 360 patients with a mean age (SD) of 69.9 ± 14.7 years, 63.6% (229) were female and 63.3% (228) of white race. The mean hospital LOS was 7.1 ± 5.4 days. Factors associated with prolonged LOS in univariable analysis were old age, body mass index (BMI), smoking status, Charlson Weighted Index of Comorbidity (CWIC), home oxygen, abnormal chest x-ray (CXR), presence of sepsis, use of oxygen, and antibiotics at the time of presentation. Predictors for prolonged LOS on admission in multivariable analysis were age on admission (p < 0.001), smoking status (p = 0.001), CWIC (p = 0.038) and abnormal CXR (p = 0.043). Our study found that age on admission, smoking history, higher CWIC and abnormal CXR on admission were significantly associated with prolonged LOS among adult patients hospitalized with RSV infection. These findings highlight the significance of promptly recognizing and implementing early interventions to mitigate the duration of hospitalization for adult patients suffering from RSV infection.