Association of Length of Stay With the Clinical Trajectory of Hospitalized Patients With Atrial Fibrillation: Staying Less Is More?

Data predicting the length of stay (LOS) in patients with concurrent atrial fibrillation (AF) are scarce. This study aimed to investigate the potential predictors for prolonged LOS and its prognostic value. In this observational post hoc analysis of the MISOAC-AF (Motivational Interviewing to Support Oral AntiCoagulation adherence in patients with non-valvular Atrial Fibrillation) randomized trial logistic regression analyses were conducted to identify the parameters associated with prolonged LOS (defined as >7 days according to diagnostic accuracy analyses). Kaplan-Meier and Cox regression analyses were performed to generate survival curves and adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) for the primary end point of all-cause mortality and for the secondary end points during a median 3.7-year follow-up. Of the 1,057 patients studied, 462 (43.7%) were hospitalized for ≥7 days. Heart failure with reduced ejection fracture (aHR 1.75, 95% CI 1.17 to 2.63), permanent AF (aHR 1.72, 95% CI 1.29 to 2.31), history of coronary artery disease (aHR 2.32, 95% CI 1.59 to 3.39), and advanced or end-stage chronic kidney disease (aHR 1.54, 95% CI 1.15 to 2.06) were independently associated with prolonged hospitalization. Prolonged LOS was independently linked with increased all-cause mortality rates (aHR 1.68, 95% CI 1.25 to 2.26), cardiovascular mortality (aHR 1.92, 95% CI 1.36 to 2.72), major bleeding (aHR 3.07, 95% CI 1.07 to 8.78), and the composite outcome of cardiovascular death or rehospitalization (aHR 1.31, 95% CI 1.04 to 1.66). Each extra day of LOS was an independent predictor of all-cause mortality (aHR 1.03, 95% CI 1.02 to 1.04). Hospitalized patients with concurrent AF carry a substantial morbidity burden being prone to extended LOS. A jointed approach seems reasonable to reduce the LOS in patients with AF.

Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis

Objective

This study aims to develop and compare different models to predict the Length of Stay (LoS) and the Prolonged Length of Stay (PLoS) of inpatients admitted through the emergency department (ED) in general patient settings. This aim is not only to promote any specific model but rather to suggest a decision-supporting tool (i.e., a prediction framework).

Methods

We analyzed a dataset of patients admitted through the ED to the "Sant"Orsola Malpighi University Hospital of Bologna, Italy, between January 1 and October 26, 2022. PLoS was defined as any hospitalization with LoS longer than 6 days. We deployed six classification algorithms for predicting PLoS: Random Forest (RF), Support Vector Machines (SVM), Gradient Boosting (GB), AdaBoost, K-Nearest Neighbors (KNN), and logistic regression (LoR). We evaluated the performance of these models with the Brier score, the area under the ROC curve (AUC), accuracy, sensitivity (recall), specificity, precision, and F1-score. We further developed eight regression models for LoS prediction: Linear Regression (LR), including the penalized linear models Least Absolute Shrinkage and Selection Operator (LASSO), Ridge and Elastic-net regression, Support vector regression, RF regression, KNN, and eXtreme Gradient Boosting (XGBoost) regression. The model performances were measured by their mean square error, mean absolute error, and mean relative error. The dataset was randomly split into a training set (70%) and a validation set (30%).

Results

A total of 12,858 eligible patients were included in our study, of whom 60.88% had a PloS. The GB classifier best predicted PloS (accuracy 75%, AUC 75.4%, Brier score 0.181), followed by LoR classifier (accuracy 75%, AUC 75.2%, Brier score 0.182). These models also showed to be adequately calibrated. Ridge and XGBoost regressions best predicted LoS, with the smallest total prediction error. The overall prediction error is between 6 and 7 days, meaning there is a 6-7 day mean difference between actual and predicted LoS.

Conclusion

Our results demonstrate the potential of machine learning-based methods to predict LoS and provide valuable insights into the risks behind prolonged hospitalizations. In addition to physicians' clinical expertise, the results of these models can be utilized as input to make informed decisions, such as predicting hospitalizations and enhancing the overall performance of a public healthcare system.

Association between the mental domain of the comprehensive geriatric assessment and prolonged length of stay in hospitalized older adults with mild to moderate frailty

Introduction

Previous researches have shown the risk factors of prolonged length of stay (PLOS) in hospitalized older adults, but it is unclear what are the risk factors of PLOS in hospitalized older adults with mild to moderate frailty.

Objective

To identify the risk factors of PLOS in hospitalized older adults with mild to moderate frailty.

Methods

We recruited adults aged ≥65 years old with mild to moderate frailty admitted to a tertiary medical center in the southern Taiwan from June 2018 to September 2018. Each individual underwent a structural questionnaire interview within 72 h after admission and 72 h after discharge. The data were collected face-to-face, including demographic characteristics, comorbidities, length of stay (LOS), and multiple domains of the comprehensive geriatric assessment. The main outcome was PLOS.

Results

Individuals who had two or more drugs, were female, did not have cognitive impairment and had a Geriatric Depression Scale score ≥ 1 had a higher risk of PLOS (probability = 0.81), and these individuals accounted for 29% of the overall study population. Among male individuals younger than 87 years old, those with cognitive impairment had a higher risk of PLOS (probability = 0.76), and among male individuals without cognitive impairment, living alone was associated with a higher risk of PLOS (probability = 0.88).

Conclusion

Early detection and management of mood and cognition in older adults, together with comprehensive discharge planning and transition care, may be an important part of reducing LOS in hospitalized older adults with mild to moderate frailty.

Incidence Rate, Pathogens and Economic Burden of Catheter-Related Bloodstream Infection: A Single-Center, Retrospective Case-Control Study

Purpose

Indwelling central venous catheters (CVCs) can cause catheter related bloodstream infection (CRBSI). CRBSI occurring in intensive care unit (ICU) patients may lead to the worse outcomes and extra medical costs. The present study aimed to assess the incidence and incidence density, pathogens and economic burden of CRBSI in ICU patients.

Patients and Methods

A case-control study was retrospectively carried out in six ICUs of one hospital between July 2013 and June 2018. The Department of Infection Control performed routinely surveillance for CRBSI on these different ICUs. Data of the clinical and microbiological characteristics of patients with CRBSI, the incidence and incidence density of CRBSI in ICUs, the attributable length of stay (LOS), and the costs among patients with CRBSI in ICU were collected and assessed.

Results

A total of 82 ICU patients with CRBSI were included into the study. The CRBSI incidence density was 1.27 per 1000 CVC-days in all ICUs, in which the highest was 3.52 per 1000 CVC-days in hematology ICU and the lowest was 0.14 per 1000 CVC-days in Special Procurement ICU. The most common pathogen causing CRBSI was Klebsiella pneumoniae (15/82, 16.67%), in which 12 (80%) were carbapenem resistant. Fifty-one patients were successfully matched with control patients. The average costs in the CRBSI group were $ 67,923, which were significantly higher (P < 0.001) than the average costs in the control group. The total average costs attributable to CRBSI were $33, 696.

Conclusion

The medical costs of ICU patients were closely related to the incidence of CRBSI. Imperative measures are needed to reduce CRBSI in ICU patients.

Determinants of Prolonged Length of Hospital Stay in Patients with Severe Acute Ischemic Stroke

OBJECTIVE

Long hospitalizations are associated with a high comorbidity and considerable hospital cost. Admissions of severe acute ischemic stroke are prone to longer hospitalizations. We aimed to explore the issue and method for improving the length of stay.

METHODS

From the prospective Stroke Registry between January 2019 and June 2020, acute ischemic strokes with an admission National Institutes of Health Stroke Scale ≥ 15 were identified. Prolonged length-of-stay was defined as in-hospital-stay ≥ 30 days. All clinical characteristics were collected, and all do-not-resuscitate documentations were categorized if the order had been written within 7 days of onset.

RESULTS

A total of 212 patients were eligible for severe stroke. Of these, 42 (19.8%) had prolonged length-of-stay and 170 had non-prolonged length-of-stay (median 43 vs. 13 days). The prolonged group was younger, mostly men, and was more likely to be in an independent state and more likely to receive reperfusion therapy, and there was a higher frequency of late do-not-resuscitate orders if signed. Although there was a lower in-hospital mortality rate in the prolonged group (12% vs. 23%), there was a higher proportion with a severe functional state (Modified Rankin Scale = 4-5) among the survivors (97% vs. 87%).

CONCLUSIONS

Severe acute ischemic stroke patients with a prolonged length-of-stay were younger, mostly male, more likely to receive reperfusion therapy, less likely to have an early do-not-resuscitate order if signed, and more likely to have poor functional status at discharge, although there was a lower rate of in-hospital mortality.

Bronchoscopic Intra-Pleural Instillation of Fibrin Glue and Autologous Blood to Manage Persistent Air Leaks after Lung Resection

Background: Persistent air leak is a common complication after lung resection causing prolonged length of stay and increased healthcare costs. Surgical intervention can be an option, but other more conservative approaches should be considered first. Here, we describe the use of flexible bronchoscopy to apply fibrin glue and autologous blood sequentially to the damaged lung. We named the technique “flexible thoracoscopy”. Methods: Medical records from patients with persistent air leaks after lung resection were collected retrospectively. Depending on the type of aerostasis that was performed, two groups were created: flexible thoracoscopy and surgery (thoracotomy). Flexible thoracoscopy was introduced at our institution in 2013. We entered the pleural space with a bronchoscope following the same surgical pathway that was used for tube thoracostomy. Perioperative characteristics and outcomes were analyzed using R software (ver. 3.4.4). Results: From 1997 to 2021, a total of 23 patients required an intervention for persistent air leaks. Aerostasis was performed via flexible thoracoscopy in seventeen patients (69%) and via thoracotomy in six patients (31%). The median age was 70 years (22–82). Twenty patients were males (87%). There was no difference in age, sex distribution, BMI, comorbidities and FEV1%. An ASA score of 3 was more represented in the flexible thoracoscopy group; however, no evidence of a difference was found when compared to the thoracotomy group (p = 0.124). Length of in-hospital stay and chest tube duration was also similar between groups (p = 1 and p = 0.68, respectively). Conclusions: Aerostasis achieved either by flexible thoracoscopy or by thoracotomy showed similar results. We believe that flexible thoracoscopy could be a valid alternative to facilitate minimally invasive treatments for persistent air leaks. Further studies are needed to confirm these results.

Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis-Treated Patients Using Stacked Generalization: Model Development and Validation Study

Background

The increasing number of patients treated with peritoneal dialysis (PD) and their consistently high rate of hospital admissions have placed a large burden on the health care system. Early clinical interventions and optimal management of patients at a high risk of prolonged length of stay (pLOS) may help improve the medical efficiency and prognosis of PD-treated patients. If timely clinical interventions are not provided, patients at a high risk of pLOS may face a poor prognosis and high medical expenses, which will also be a burden on hospitals. Therefore, physicians need an effective pLOS prediction model for PD-treated patients.

Objective

This study aimed to develop an optimal data-driven model for predicting the pLOS risk of PD-treated patients using basic admission data.

Methods

Patient data collected using the Hospital Quality Monitoring System (HQMS) in China were used to develop pLOS prediction models. A stacking model was constructed with support vector machine, random forest (RF), and K-nearest neighbor algorithms as its base models and traditional logistic regression (LR) as its meta-model. The meta-model used the outputs of all 3 base models as input and generated the output of the stacking model. Another LR-based pLOS prediction model was built as the benchmark model. The prediction performance of the stacking model was compared with that of its base models and the benchmark model. Five-fold cross-validation was employed to develop and validate the models. Performance measures included the Brier score, area under the receiver operating characteristic curve (AUROC), estimated calibration index (ECI), accuracy, sensitivity, specificity, and geometric mean (Gm). In addition, a calibration plot was employed to visually demonstrate the calibration power of each model.

Results

The final cohort extracted from the HQMS database consisted of 23,992 eligible PD-treated patients, among whom 30.3% had a pLOS (ie, longer than the average LOS, which was 16 days in our study). Among the models, the stacking model achieved the best calibration (ECI 8.691), balanced accuracy (Gm 0.690), accuracy (0.695), and specificity (0.701). Meanwhile, the stacking and RF models had the best overall performance (Brier score 0.174 for both) and discrimination (AUROC 0.757 for the stacking model and 0.756 for the RF model). Compared with the benchmark LR model, the stacking model was superior in all performance measures except sensitivity, but there was no significant difference in sensitivity between the 2 models. The 2-sided t tests revealed significant performance differences between the stacking and LR models in overall performance, discrimination, calibration, balanced accuracy, and accuracy.

Conclusions

This study is the first to develop data-driven pLOS prediction models for PD-treated patients using basic admission data from a national database. The results indicate the feasibility of utilizing a stacking-based pLOS prediction model for PD-treated patients. The pLOS prediction tools developed in this study have the potential to assist clinicians in identifying patients at a high risk of pLOS and to allocate resources optimally for PD-treated patients.

Prolonged length of stay after surgery for adult congenital heart disease: a single-centre study in a developing country

BACKGROUND

With the growing number of adults requiring operations for CHD, prolonged length of stay adds an additional burden on healthcare systems, especially in developing countries. This study aimed to identify factors associated with prolonged length of stay in adult patients undergoing operations for CHD.

METHODS

This retrospective study included all adult patients (≥18 years) who underwent cardiac surgery with cardiopulmonary bypass for their CHD from 2011 to 2016 at a tertiary-care private hospital in Pakistan. Prolonged length of stay was defined as hospital stay >75th percentile of the overall cohort (>8 days).

RESULTS

This study included 166 patients (53.6% males) with a mean age of 32.05 ± 12.11 years. Comorbid disease was present in 59.0% of patients. Most patients underwent atrial septal defect repair (42.2%). A total of 38 (22.9%) patients had a prolonged length of stay. Post-operative complications occurred in 38.6% of patients. Multivariable analysis showed that pre-operative body mass index (odds ratio: 0.779; 95% confidence interval: 0.620-0.980), intraoperative aortic cross-clamp time (odds ratio: 1.035; 95% confidence interval: 1.009-1.062), and post-operative acute kidney injury (odds ratio: 7.392; 95% confidence interval: 1.036-52.755) were associated with prolonged length of stay.

CONCLUSION

Predictors of prolonged length of stay include lower body mass index, longer aortic cross-clamp time, and development of post-operative acute kidney injury. Shorter operations, improved pre-operative nutritional optimisation, and timely management of post-operative complications could help prevent prolonged length of stay in patients undergoing operations for adult CHD.

All grades of severity of postoperative adverse events are associated with prolonged length of stay after lung cancer resection

OBJECTIVE

To determine whether all grades of severity of postoperative adverse events are associated with prolonged length of stay in patients undergoing pulmonary cancer resection.

METHODS

This was a retrospective cohort study of all patients who underwent pulmonary resection with curative intent for malignancy at The Ottawa Hospital, Division of Thoracic Surgery (January 2008 to July 2015). Postoperative adverse events were collected prospectively with the Thoracic Morbidity & Mortality System, based on the Clavien-Dindo severity classification. Patient demographics, comorbidities, preoperative investigations, cardiopulmonary assessment, pathologic staging, operative characteristics, and length of stay were retrospectively reviewed. Prolonged hospital stay was defined as >75th percentile for each procedure performed (wedge resection 6 days, segmentectomy 6 days, lobectomy 7 days, extended lobectomy 8 days, pneumonectomy 10 days). Univariable and multivariable logistic regression analyses were conducted to identify factors associated with prolonged hospital stay.

RESULTS

Of 1041 patients, 579 (55.6%) were female, 610 (58.1%) were >65 years old, 232 (22.3%) experienced prolonged hospital stay, and 416 (40.0%) patients had ≥1 postoperative adverse event. Multivariable analyses identified significant (P < .05) factors associated with prolonged hospital stay to be (odds ratio; 95% confidence interval): lower diffusion capacity of the lung for carbon monoxide (0.99; 0.98-0.99), surgical approach: open thoracotomy (1.8; 1.3-2.5), and presence of any postoperative adverse event: Grade I (5.8; 3.3-10.2), Grade II (6.0; 4.0-8.9), Grade III (11.4; 7.0-18.7), and Grade IV (19.40; 7.1-55.18).

CONCLUSIONS

Lower diffusion capacity of the lung for carbon monoxide, open thoracotomy approach, and the development of any postoperative adverse event, including minor events that required no additional therapy, were factors associated with prolonged hospital stay.

Factors associated with prolonged length of stay in older patients

INTRODUCTION

Prolonged stay in acute hospitals increases the risk of hospital-acquired infections in older patients, and disrupts patient flow and access to care due to bed shortages. We aimed to investigate the factors associated with prolonged length of stay (pLOS) among older patients (aged ≥ 78 years) in a tertiary hospital, to identify the potentially modifiable risk factors that could direct interventions to reduce length of stay (LOS).

METHODS

During a three-month period from January 2013 to March 2013, we identified 72 patients with pLOS (LOS ≥ 21 days) and compared their demographic and clinical variables with that of 281 randomly selected control patients (LOS < 21 days) using univariate and multivariate logistic regression analyses.

RESULTS

The mean age of the patients was 85.30 ± 5.34 years; 54% of them were female and 72% were of Chinese ethnicity. Logistic regression revealed the following significant factors for increased LOS: discharge to intermediate and long-term care services (odds ratio [OR] 9.22, 95% confidence interval [CI] 3.56-23.89; p < 0.001); increased severity of illness (OR 2.41, 95% CI 1.12-5.21; p = 0.025); and presence of caregiver stress (OR 3.85, 95% CI 1.67-8.91; p = 0.002).

CONCLUSION

Presence of caregiver stress and nursing home placement are potential modifiable risk factors of pLOS among older patients. Early identification and management of caregiver stress, as well as expediting discharge planning, may help to reduce the length of stay for this cohort.

Postoperative use of hypnotics is associated with increased length of stay after uncomplicated surgery for colorectal cancer

Background/Aims:

Hypnotics are used to treat perioperative sleep disorders. These drugs are associated with a higher risk of adverse effects among patients undergoing surgery. This study aims to quantify the use of hypnotics and factors influencing the administration of hypnotics in relation to colorectal cancer surgery.

Method:

A retrospective cohort study of 1979 patients undergoing colorectal cancer surgery.

Results:

In all, 381 patients (19%) received new treatment with hypnotics. Two of the six surgical centres used hypnotics less often (odds ratio (95% confidence interval), 0.24 (0.16–0.38) and 0.20 (0.12–0.35)). Active smokers (odds ratio (95% confidence interval), 1.57 (1.11–2.24)) and patients receiving perioperative blood transfusion (odds ratio (95% confidence interval), 1.58 (1.10–2.26)) had increased likelihood of receiving hypnotics. In the uncomplicated cases, a multivariable linear regression analysis showed that consumption of hypnotics postoperatively was significantly associated with increased length of stay (1.5 (0.9–2.2) days).

Conclusion:

One in five patients began treatment with hypnotics after colorectal cancer surgery. Postoperative use of hypnotics was associated with an increased length of stay for uncomplicated cases of colorectal cancer surgery.