Effect of frailty on unplanned readmission in older adults: A systematic review.

BACKGROUND: Frailty and hospital readmissions are two major problems for older people because of their impact on health, quality of life and healthcare systems. The aims of this study were to investigate the relationship between frailty and unplanned readmissions at 30, 90, 180 days and 1 year in hospitalised older people, and to identify the most relevant tools for assessing readmission risk in different clinical settings to facilitate systematic identification of this high-risk population by healthcare professionals. METHOD: This review was based on a systematic search of the MEDLINE, EMBASE and SCIENCEDIRECT databases for articles published between January 2011 and December 2021 that examined the association between frailty and unplanned readmission in hospitalised adults aged 65 years and over using identified validated tools. RESULTS: 44 eligible studies out of 1362 were included in a descriptive analysis. Sixteen countries were represented with older adults hospitalised in medical, surgical, post-acute care and rehabilitation, and emergency departments. Up to 84.5% of frail older adults had an unplanned readmission. Of the 21 tools identified, the Hospital Frailty Risk Score (HFRS), the Frailty Index (FI), its derivatives, the Clinical Frailty Scale (CFS) and the Fried model were the most widely used and relevant tools for identifying the association between frailty and unplanned readmission. CONCLUSION: Frailty is widely associated with readmission risk in older adults. The HFRS, FI, CFS and Fried model appear to be the most commonly used tools to assess frailty and prevent unplanned readmissions.

Updated systematic review and meta­analysis for risk predictors of 30­day unplanned readmission following gastric cancer surgery.

Readmission to hospital is a common occurrence due to adverse post-operative events. The primary objective of the present study was to examine the possible risk predictors for 30-day unplanned readmissions after the surgical treatment of gastric cancer. The secondary aim was to determine the clinical characteristics that are associated with readmission. Studies that reported the risk factors and clinical characteristics of patients with gastric cancer who had an unplanned 30-day post-operative readmission were identified systematically from PubMed, Cochrane Central Register of Controlled Trials, Web of Science and Embase databases, with a final search date of March 30, 2024. A systematic review and meta-analysis were then performed to estimate the risk predictors and relevant clinical characteristics for readmission. A total of 16,154 patients from 12 studies were included in the present study, with 1,736 patients who were readmitted and 14,418 patients who were not readmitted. A higher proportion of patients with an age ≥70 years, cardiovascular comorbidity, Nutritional Risk Screening (NRS) 2002 score ≥3, respiratory diseases, male sex, American Society of Anesthesiologists score ≥3, combined multi-organ resection, greater depth of invasion (T3-4/T1-2), discharge to home with provision of care services, neoadjuvant therapy, post-operative complications or a blood transfusion were found in the readmission group compared with that in the non-readmission group. A meta-analysis was also performed to calculate risk predictors using the results of multivariate regression analyses from the original literature. This identified cardiovascular comorbidity, NRS 2002 score ≥3, pancreatectomy and post-operative complications as risk predictors for 30-day unplanned readmission following surgery for gastric cancer. Therefore, it is recommended that extra attention and support should be given to patients with these high-risk predictors during the perioperative period.

Does Surgical Day of Week Affect Patient Outcomes and Hospital Costs Following Lumbar Fusion?

Background As the population ages, surgical intervention for degenerative spine conditions is increasing, and this causes a commiserate increase in healthcare expenditures associated with these procedures. Little research has been done on the effect of early-week versus later-week surgeries on patient outcomes, cost, and length of stay (LOS) in patients undergoing lumbar fusion surgery. The purpose of this study is to compare LOS, patient outcomes, and hospital costs between patients having surgery early in the week and later in the week. Methods A retrospective review of 771 patients undergoing a one-, two-, or three-level lumbar fusion from December 2020 to December 2023 at a single institution was performed. Demographics, surgical details, postoperative outcomes and cost were compared between patients who had surgery on Monday, Tuesday, and Wednesday, to those having surgery Thursday or Friday. Univariate and multivariate analyses were performed to compare the groups. Results There were no differences in age, sex, BMI, race, American Society of Anesthesiology (ASA) scores, Charlson Comorbidity Index (CCI) scores, number of operative levels or inpatient/outpatient status between early- and late-week surgeries. Postoperatively the only significant difference was cost, late-week surgeries were, on average, $3,697 more expensive than early-week surgeries ($26,506 vs. $22,809; p<0.001). On multivariate analysis late-week surgeries were 2.47 times more likely to have a non-home discharge (OR: 2.47, 95% CI: 1.24 to 4.95; p=0.010) and 2.19 times more likely to have a 30-day readmission (OR: 2.19, 95% CI:1.01 to 4.74; p=0.044) Additionally, late-week surgeries were $2,041.55 (ß:2,041.55, 95% CI: 804.72 to 3,278.38; p=0.001) more expensive than early-week surgeries. Conclusions At our institution, patients undergoing one- to three-level lumbar fusion surgery on Thursday or Friday had a higher risk of non-home discharge, 30-day readmission, and incurred higher cost than those having early-week surgery. Further research is needed to elucidate the reasons for these findings and to evaluate interventions aimed at improving outcomes for patients undergoing surgery later in the week.

Investigating the impact of extreme weather events and related indicators on cardiometabolic multimorbidity.

BACKGROUND: The impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored. OBJECTIVES: Investigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations. DESIGNS: Time-stratified case-crossover design. METHODS: A distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM. RESULTS: There are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854). CONCLUSIONS: Extreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM.

Incidence of Unplanned Readmissions After One-Day Surgery Discharge Among Pediatric Patients: A Retrospective Study From a Tertiary Care Hospital in Saudi Arabia.

Introduction The prevalence of one-day surgery (also known as same-day surgery or outpatient surgery) has been increasing recently among patients and physicians in many countries due to its benefits. The main benefits of one-day surgery are that the patient is not planned to stay overnight before the surgery and can be discharged on the same day of the surgery. The lower cost to the health system can make these surgeries more favorable for both sides. However, unplanned readmission after such surgeries can happen and this has broad implications for patients, their families, and the healthcare system. Therefore, this study primarily aims to identify the incidence of unexpected hospital readmissions following one-day surgery after discharge among children. The study also aims to identify any significant variables that can be identified with the cases of readmissions to allow for further investigations in future studies Methods This study was done at King Abdullah Specialist Children's Hospital in Riyadh, Saudi Arabia. The target population included all pediatric patients who underwent one-day surgeries and were admitted within one week of their discharge from 2017 to 2023 through outpatient clinics and the emergency department. Results The study sample size was 403 patients, with male patients accounting for 241 surgeries (59.8%), and female patients accounting for 162 surgeries (40.1%). The most common American Society of Anesthesiologists (ASA) classification was II, accounting for 169 cases (41.9%). Toddlers and preschoolers (aged 1-6 years) were the age groups with the highest number of patients (n=252, 62.5% combined). Elective surgeries accounted for 382 cases (94.7%). The specialty with the highest number of surgeries was ear, nose, and throat with 284 cases (70.4%) with tonsillectomy with adenoidectomy being the most common surgery with 234 cases (58%). The most common reasons for unplanned readmission were poor oral intake (n=146, 36.2%) and bleeding (n=131, 32.5%). The most common day of readmission was the seventh day in five surgical specialties (45.4%). Conclusion Over the past seven years, 403 patients were readmitted within one week after their one-day surgery at King Abdullah Specialist Children's Hospital. Such a situation may cause dissatisfaction with the medical care that the patients were given and eventually may build an untrusted relationship between the patient and the physician. Future investigations should be established to lower such a condition and develop prevention methods to lower its prevalence.

Prevalence and risk factors associated within 48-hour unplanned paediatric intensive care unit readmissions: An integrative review.

BACKGROUND: Unplanned paediatric intensive care unit (PICU) readmission is associated with increased morbidity/mortality, hospital length of stay, and health service cost and is recognised as a key performance indicator of quality-of-care delivery. However, research evidence on unplanned PICU readmission risk factors is limited, and results were inconsistent across studies. AIM: The aim of this experiment was to collate and synthesise unplanned within-48-h PICU readmission prevalence and associated risk factors. METHODS: An integrative review was conducted, guided by a five-stage framework. Seven electronic databases were searched (2013-30th June 2023). Studies published in English with full-text accessibility and detailed methodologies were included. The quality of included studies was critically appraised using the Joanna Briggs Institute checklists. Prevalence and risk factors were extracted, synthesised, and presented narratively. RESULTS: Ten studies met eligibility criteria and reported a varied readmission rate from 0.008% to 6.49%. Fifteen types of significant risk factors were extracted. Twelve consistently cited risk factors were age, weight, complex chronic conditions, admission source, unplanned admission, PICU length of stay, positive pressure ventilation, discharge disposition, oxygen requirements, respiratory rate, heart rate, and Glasgow Coma Score at discharge. Of the 12, five predictors were classified as modifiable factors, including discharge disposition, oxygen requirement, abnormal respiratory rate, abnormal heart rate, and decreased Glasgow Coma Score at discharge. CONCLUSION: This review acknowledges the complexity of confounding factors impacting unplanned PICU readmission and the lack of standardisation examining potential risk factors. The five modifiable factors are suggestive of clinical instability and premature PICU discharge. Patients with modifiable risk factors should have their readiness for discharge re-evaluated. Scaffolding support to manage patients at risk of readmission includes senior bedside nursing allocation, use of PICU outreach services, and 1:2 nurse-to-patient ratios in the ward setting, which are warranted to ensure patient safety.

Do Postsurgical Follow-Up Calls Reduce Unplanned 30-Day Readmissions in Neurosurgery Patients? A Quality Improvement Project in a University Hospital.

BACKGROUND: Unplanned 30-day readmissions after surgery are a source of patient dissatisfaction, monitored by the Centers for Medicare and Medicaid Services, have financial penalties for hospitals, and are publicly reported. Neurosurgical operations have a higher 30-day unplanned readmission rate after the index discharge than other specialties. After a simple initiative for a 48-72-hour postdischarge telephone call, there was an observed significant decrease in readmission rates from 17% to 8% in 7 months at Thomas Jefferson University. To better understand the role of postoperative telephone calls in this reduction, a retrospective evaluation over a longer period was performed. METHODS: A quality improvement initiative was assessed using patient records between August 2018 and May 2023. The primary observed subject is the 30-day unplanned readmission rate and secondarily a change in Physician Communication Score. Thirty-day unplanned readmission rate and Physician Communication Scores before and after the telephone call initiative were compared, checking for difference, variance, and correlation. RESULTS: 874 readmissions (average, 28/month; 95% confidence interval [CI], 25.3-29.3), 12.9% (95% CI, 11.9-13.9) were reported before the telephone call; of 673 readmissions (average, 26/month; 95% CI, 23-28.8), 12.9% (95% CI, 11.6-14.1) were reported after the telephone call. No significant difference, variance of scores or rates, or correlation of rate with communication score were noted before and after the initiative. CONCLUSIONS: Telephone calls and peridischarge efficient communication are needed after neurologic surgery. This approach decreased unplanned readmissions in certain instances without having a significant impact on neurosurgical patients.

The effects of a nurse-led discharge planning on the health outcomes of colorectal cancer patients with stomas: A randomized controlled trial.

BACKGROUND: Nursing care of colorectal cancer patients with stomas presents unique challenges, particularly during the transition from hospital to home. Early discharge programs can assist patients during this critical period. However, the effects of delivering a nurse-led discharge planning program remain under-studied. OBJECTIVE: Evaluate the effects of a nurse-led discharge planning on the quality of discharge education, stoma self-efficacy, readiness for hospital discharge, stoma quality of life, incidence of stoma complications, unplanned readmission rate, and length of stays. DESIGN: Assessor-blind parallel-arm randomized controlled trial with a repeated-measures design. SETTING(S): Participants were recruited from inpatients in the colorectal surgery unit of a university-affiliated hospital in Fujian, China. PARTICIPANTS: A total of 160 patients with colorectal cancer who received enterostomy surgery and were scheduled to be discharged to their homes. METHOD: Participants were randomly allocated to the experimental and control groups. The former received nurse-led discharge planning in addition to the usual discharge education, while the control group received only the usual discharge education. The program included an assessment, health education, stoma care, stoma support, discharge review, discharge medication and checklist integration, discharge referral, and post-hospital follow-up. Baseline data were collected prior to the intervention (T0). Data on the quality of discharge teaching, readiness for hospital discharge, stoma self-efficacy, and stoma quality of life were measured on the day of discharge from the hospital (T1). Patients' stoma self-efficacy and quality of life were repeat-measured 30 (T2) and 90 days post-discharge (T3). Data on stoma complications (T1, T2, T3), length of stays (T1), and unplanned readmission (T2, T3) were collected from medical records. RESULTS: Participants in the intervention group showed significant improvement in the quality of discharge teaching, readiness for hospital discharge, stoma self-efficacy, stoma quality of life, complications, and unplanned readmission, compared to the control group (p < 0.001). However, no statistically significant differences were observed in length of stays (p > 0.05). CONCLUSIONS: The program was effective for improving quality of discharge teaching, readiness for hospital discharge, stoma self-efficacy, and stoma quality of life, as well as for reducing complications and unplanned readmission among stoma patients. Integration of discharge planning into the usual process of care is recommended for clinical practice to facilitate a successful transition from hospital to home. REGISTRATION: This study was registered at the Chinese clinical trial registry (ChiCTR2200058756) on April 16, 2022, and participant recruitment was initiated in May 2022.

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database.

Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. Although predictive machine learning (ML) models show promise for risk stratification in specific populations, existing studies do not address model generalizability. This study aimed to establish the generalizability of previous institutionally developed ML models to predict 30-day readmission following primary TKA using a national database. Data from 424,354 patients from the ACS-NSQIP database was used to develop and validate four ML models to predict 30-day readmission risk after primary TKA. Individual model performance was assessed and compared based on discrimination, accuracy, calibration, and clinical utility. Length of stay (> 2.5 days), body mass index (BMI) (> 33.21 kg/m2), and operation time (> 93 min) were important determinants of 30-day readmission. All ML models demonstrated equally good accuracy, calibration, and discriminatory ability (Brier score, ANN = RF = HGB = NEPLR = 0.03; ANN, slope = 0.90, intercept = - 0.11; RF, slope = 0.93, intercept = - 0.12; HGB, slope = 0.90, intercept = - 0.12; NEPLR, slope = 0.77, intercept = 0.01; AUCANN = AUCRF = AUCHGB = AUCNEPLR = 0.78). This study validates the generalizability of four previously developed ML algorithms in predicting readmission risk in patients undergoing TKA and offers surgeons an opportunity to reduce readmissions by optimizing discharge planning, BMI, and surgical efficiency.

Readiness for hospital discharge and its association with post-discharge outcomes among oesophageal cancer patients after oesophagectomy: A prospective observational study.

AIM: To examine the level and influencing factors of discharge readiness among patients with oesophageal cancer following oesophagectomy and to explore its association with post-discharge outcomes (post-discharge coping difficulty and unplanned readmission). BACKGROUND: Oesophageal cancer is common and usually treated via oesophagectomy in China. The assessment of patient's discharge readiness gradually attracts attention as patients tend to be discharged more quickly. DESIGN: Prospective observational study. The STROBE statement was followed. METHODS: In total, 154 participants with oesophageal cancer after oesophagectomy were recruited in a tertiary cancer centre in Southern China from July 2019 to January 2020. The participants completed a demographic and disease-related questionnaire, the Quality of Discharge Teaching Scale and Readiness for Hospital Discharge Scale before discharge. Post-discharge outcomes were investigated on the 21st day (post-discharge coping difficulty) and 30th day (unplanned readmission) after discharge separately. Multiple linear regressions were used for statistical analysis. RESULTS: The mean scores of discharge readiness and quality of discharge teaching were (154.02 ± 31.58) and (138.20 ± 24.20) respectively. The quality of discharge teaching, self-care ability, dysphagia and primary caregiver mainly influenced patient's discharge readiness and explained 63.0% of the variance. The low discharge readiness could predict more risk of post-discharge coping difficulty (r = -0.729, p < 0.01) and unplanned readmission (t = -2.721, p < 0.01). CONCLUSIONS: Discharge readiness among patients with oesophageal cancer following oesophagectomy is influenced by various factors, especially the quality of discharge teaching. A high discharge readiness corresponds to good post-discharge outcomes. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Healthcare professionals should improve the discharge readiness by constructing high-quality discharge teaching, cultivating patients' self-care ability, mobilizing family participation and alleviating dysphagia to decrease adverse post-discharge outcomes among patients with oesophageal cancer. PATIENTS OR PUBLIC CONTRIBUTION: Patients with oesophageal cancer after oesophagectomy who met the inclusion criteria were recruited.

Effect of Rothman index on unplanned readmission and complications in elderly patients undergoing total hip and knee arthroplasty / 中国组织工程研究

BACKGROUND:Total hip and knee arthroplasty is widely used in the elderly population,but there is a lack of accurate prediction methods for unplanned readmission and postoperative complications. OBJECTIVE:To investigate the effect of the Rothman index on unplanned readmission and complications in elderly patients undergoing total hip and knee arthroplasty. METHODS:A total of 153 patients who underwent elective total hip and knee arthroplasty from December 2020 to December 2022 in Ward Area One,Department of Orthopedics,The First People's Hospital of Zunyi were selected as the study subjects.According to whether they were unplanned readmission within 90 days after discharge,they were divided into a readmission group(n=21)and a non-readmission group(n=132).The general data of all patients were collected through the electronic medical record system,including gender,age,body mass index,diabetes mellitus,hypertension,and surgical joint type.The Rothman index was evaluated according to the literature.Postoperative complications were counted. RESULTS AND CONCLUSION:(1)There was no significant difference in gender,body mass index,surgical joint type,and length of hospital stay between the readmission group and the non-readmission group(P>0.05).There were significant differences in the number of comorbidities,age,and Rothman score between the two groups(P<0.05).(2)The results of multivariate Logistics regression analysis showed that the number of comorbidities,age,and Rothman score were independent influencing factors for readmission 90 days after total hip and knee arthroplasty in elderly patients with hip and knee diseases(P<0.05).(3)The results of receiver operating characteristic curve analysis exhibited that the area under the curve of the Rothman index for predicting readmission 90 days after total hip and knee arthroplasty was 0.824;the sensitivity was 80.85%;the specificity was 78.85%;the maximum Youden index was 0.597,and the optimal cutoff value was 46 points.(4)The incidence of total complications in elderly patients with Rothman<46 was higher than that in elderly patients with Rothman≥46(P<0.05).(5)It is concluded that the Rothman index can accurately predict unplanned readmission after total hip and knee arthroplasty in elderly patients with hip and knee joint diseases.Simultaneously,patients with Rothman index of less than 46 points have a higher overall risk of complications and poor joint recovery,which can be used to improve postoperative management of patients in clinical practice.

Development and validation of a risk score to predict unplanned hospital readmissions in ICU survivors: A data linkage study.

BACKGROUND: Intensive Care Unit (ICU) follow-up clinics are growing in popularity internationally; however, there is limited evidence as to which patients would benefit most from a referral to this service. OBJECTIVES: The objective of this study was to develop and validate a model to predict which ICU survivors are most likely to experience an unplanned hospital readmission or death in the year after hospital discharge and derive a risk score capable of identifying high-risk patients who may benefit from referral to follow-up services. METHODS: A multicentre, retrospective observational cohort study using linked administrative data from eight ICUs was conducted in the state of New South Wales, Australia. A logistic regression model was developed for the composite outcome of death or unplanned readmission in the 12 months after discharge from the index hospitalisation. RESULTS: 12,862 ICU survivors were included in the study, of which 5940 (46.2%) patients experienced unplanned readmission or death. Strong predictors of readmission or death included the presence of a pre-existing mental health disorder (odds ratio [OR]: 1.52, 95% confidence interval [CI]: 1.40-1.65), severity of critical illness (OR: 1.57, 95% CI: 1.39-1.76), and two or more physical comorbidities (OR: 2.39, 95% CI: 2.14-2.68). The prediction model demonstrated reasonable discrimination (area under the receiver operating characteristic curve: 0.68, 95% CI: 0.67-0.69) and overall performance (scaled Brier score: 0.10). The risk score was capable of stratifying patients into three distinct risk groups-high (64.05% readmitted or died), medium (45.77% readmitted or died), and low (29.30% readmitted or died). CONCLUSIONS: Unplanned readmission or death is common amongst survivors of critical illness. The risk score presented here allows patients to be stratified by risk level, enabling targeted referral to preventative follow-up services.

One-year unplanned readmission after total hip arthroplasty in patients with osteonecrosis of the femoral head: rate, causes, and risk factors.

BACKGROUND: The primary objectives of this study were to focus on one - year unplanned readmissions after THA in ONFH patients and to investigate rates, causes, and independent risk factors. METHODS: Between October 2014 and April 2019, eligible patients undergoing THA were enrolled and divided into unplanned readmission within one year and no readmission in this study. All unplanned readmissions within 1 year of discharge were reviewed for causes and the rate of unplanned readmissions was calculated. Demographic information, ONFH characteristics, and treatment-related variables of both groups were compared and analysed. RESULTS: Finally, 41 out of 876 patients experienced unplanned readmission. The readmission rate was 1.83% in 30 days 2.63% in 90 days, and 4.68% in 1 year. Prosthesis dislocation was always the most common cause at all time points studied within a year. The final logistic regression model revealed that higher risks of unplanned readmission were associated with age > 60 years (P = 0.001), urban residence (P = 0.001), ARCO stage IV (P = 0.025), and smoking (P = 0.033). CONCLUSIONS: We recommend the introduction of a strict smoking cessation program prior to surgery and the development of comprehensive management strategies, especially for the elderly and end-stage ONFH patients, and pay more attention to preventing prosthesis dislocation in the early days after surgery.

Unplanned readmissions after hernia repair.

INTRODUCTION: Several quality indices have been set up for evaluating the impact of the reduction of the length of stay (LOS), such as the 30-day unplanned readmission (UR30) rate. The main goal of our study was to analyze the UR30 following groin hernia repair (GHR), primary- (PVHR), and incisional ventral hernia repairs (IVHR). METHODS: A French registry-based multicenter study was conducted using prospective data from all consecutive patients registered from 2015 to 2021. RESULTS: The overall incidence of UR30 was 1.32%. This included 160/18,042 (0.87%) for GHR, 41/4012 (1.02%) for PVHR, and 145/3754 (3.86%) for IVHR. The leading cause of UR30 was postoperative complications (POC). The nature of the predominant complications varied among the three categories. The correlation between UR30 and POC (and risk factors for POC) was strong in GHR but was not in IVHR due to a 'protective' longer LOS in this subgroup. As the LOS has decreased over the last years, this has 'mechanically' resulted in an increase in the occurrence of UR30, but not in a rise of POC, neither in volume nor in severity. The reduction of LOS just shifted the problem from inpatient to outpatient settings. CONCLUSION: Since the steady development of day-care surgery, the prevention of the UR not only hinges on the prevention of the POC but newly on a better organization of outpatient care which is currently a huge challenge due to a GPs' and nurses' shortage in France.

Association between obesity and risk of delayed discharge and unplanned readmission for day surgery: A systematic review and meta-analysis.

AIMS: This work aims to investigate the association between obesity and risk of delayed discharge and unplanned readmission in day surgery patients. BACKGROUND: Day surgeries are well received and developing rapidly. Associations between obesity and delayed discharge and unplanned readmission, which are clinically relevant outcomes in day surgeries, are complex. DESIGN: A systematic review and meta-analysis was conducted. DATA SOURCES: The PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, VIP, and Wan Fang databases were comprehensively searched from inception until January 2021. REVIEW METHODS: Two independent reviewers assessed the studies and extracted data. Pooled estimates were obtained using a random-effects model. RESULTS: Eleven articles published between 2007 and 2020 were finally included. Obesity appeared not to increase the risk of delayed discharge. However, morbid obesity seemed to be associated with a higher risk of delayed discharge. The meta-analysis revealed no relationship between higher body mass index (BMI) and unplanned readmission for day surgery patients. CONCLUSIONS: Obesity appeared not to increase the risk of delayed discharge except in patients with morbid obesity. Additionally, a higher BMI was not associated with increased risk of unplanned readmission after day surgery. Future studies are required to address this issue further in different types of surgery and areas.

Causes and Predictors of Unplanned Readmission in Patients Undergoing Intracranial Tumor Resection: A Multicenter Analysis of 31,776 Patients.

BACKGROUND: Although unplanned readmission is a postoperative outcome metric associated with significant morbidity and financial burden, precise assessment tools for its prediction have not yet been developed. The Risk Analysis Index (RAI) could potentially be used to help improve the prediction of unplanned readmissions for patients undergoing intracranial tumor resection (ITR). In the present study, we evaluate the predictive accuracy of frailty on 30-day unplanned readmission after ITR using the RAI. METHODS: Data were obtained from the American College of Surgeons National Surgical Quality Improvement Program database. The baseline characteristics, preoperative clinical status, and outcomes were compared between patients with and without unplanned readmission. Frailty was calculated using the RAI. Univariate and multivariate logistic regression analyses were performed to identify independent associations between unplanned readmissions and patient characteristics. RESULTS: The unplanned readmission rate for this cohort (n = 31,776) was 10.8% (n = 3420). Of the 3420 readmitted patients, 958 required unplanned reoperation. Multiple characteristics were significantly different between the 2 groups, including age, body mass index, comorbidities, and RAI groups (P < 0.05). The common causes of unplanned readmission included infection (9.4%), seizures (6%), and pulmonary embolism (4%). The patient characteristics identified as reliable predictors of unplanned readmission included age, body mass index, functional status, diabetes, hypertension, hyponatremia, and the patient's RAI score (P < 0.05). Frail status, hyponatremia, leukocytosis, hypertension, and thrombocytosis were significant predictors of unplanned readmissions. CONCLUSIONS: The RAI is a reliable preoperative frailty index for predicting unplanned readmissions after ITR. Using the RAI could decrease unplanned readmissions by identifying high-risk patients and enabling future implementation of appropriate management guidelines.

Risk Factors for Unexpected Admission Following Outpatient Rotator Cuff Repair: A National Database Study.

Introduction  Rotator cuff repair (RCR) procedures are some of the most common orthopaedic surgeries performed in the United States. Compared to other orthopaedic procedures, RCRs are of relatively low morbidity. However, complications may arise that result in readmission to an inpatient healthcare facility. The purpose of this study is to identify the demographics and risk factors associated with unplanned 30-day readmission after RCR. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was used to identify patients that underwent elective RCR from 2015-2019. Univariate and multivariate analyses were utilized to assess patient demographics, comorbidities, and peri-operative variables predicting unplanned 30-day readmission. Results Of the identified 45,548 patients that underwent RCR, 597 (1.3%) required readmission within 30 days of the procedure. Multivariate analysis identified male sex (OR 1.36, 95% CI: 1.10, 1.67), hypertension (OR 1.29, 95% CI:1.03, 1.62), chronic obstructive pulmonary disease (COPD) (OR 2.07, 95% CI: 1.46, 2.93), American Society of Anesthesiologists (ASA) Class III (OR 1.85, 95% CI: 1.07, 3.18), ASA Class IV (OR 5.38, 95% CI: 2.70, 10.72), and total operative time (OR 1.002, 95% CI: 1.000, 1.004) as independent risk factors for unplanned readmission. Conclusion Unplanned 30-day readmission after RCR is infrequent. However, certain patients may be at increased risk for unplanned 30-day admission to an inpatient facility. This study confirmed male sex, COPD, hypertension, ASA Class III, ASA Class IV, and total operative time to be independent risk factors for readmission following outpatient RCR.

Development of a prediction model for the risk of 30-day unplanned readmission in older patients with heart failure: A multicenter retrospective study.

BACKGROUND AND AIM: Heart failure (HF) imposes significant global health costs due to its high incidence, readmission, and mortality rate. Accurate assessment of readmission risk and precise interventions have become important measures to improve health for patients with HF. Therefore, this study aimed to develop a machine learning (ML) model to predict 30-day unplanned readmissions in older patients with HF. METHODS AND RESULTS: This study collected data on hospitalized older patients with HF from the medical data platform of Chongqing Medical University from January 1, 2012, to December 31, 2021. A total of 5 candidate algorithms were selected from 15 ML algorithms with excellent performance, which was evaluated by area under the operating characteristic curve (AUC) and accuracy. Then, the 5 candidate algorithms were hyperparameter tuned by 5-fold cross-validation grid search, and performance was evaluated by AUC, accuracy, sensitivity, specificity, and recall. Finally, an optimal ML model was constructed, and the predictive results were explained using the SHapley Additive exPlanations (SHAP) framework. A total of 14,843 older patients with HF were consecutively enrolled. CatBoost model was selected as the best prediction model, and AUC was 0.732, with 0.712 accuracy, 0.619 sensitivity, and 0.722 specificity. NT.proBNP, length of stay (LOS), triglycerides, blood phosphorus, blood potassium, and lactate dehydrogenase had the greatest effect on 30-day unplanned readmission in older patients with HF, according to SHAP results. CONCLUSIONS: The study developed a CatBoost model to predict the risk of unplanned 30-day special-cause readmission in older patients with HF, which showed more significant performance compared with the traditional logistic regression model.

Incidence, causes, and risk factors for unplanned readmission in patients admitted with pulmonary tuberculosis in China.

INTRODUCTION: To investigate the incidence, causes, and risk factors for unplanned readmission within 30 days of discharge in patients with pulmonary tuberculosis (TB). METHODOLOGY: The clinical data of 1,062 patients with confirmed pulmonary TB who were admitted to our hospital from October 2018 to October 2021 were analysed retrospectively. The subjects were divided into a readmission group (354 cases) and a non-readmission group (708 cases) according to whether there was an unplanned admission within 30 days of discharge. We analysed the risk factors for unplanned readmission within 30 days after discharge with pulmonary TB. RESULTS: The incidence of unplanned readmission in patients with pulmonary TB was 5.2%. Being female (OR = 0.63, 95% CI: 0.434-0.942) and living in cities (OR = 0.218, 95% CI: 0.151-0.315) were protective factors for the readmission of patients with TB (p < 0.05). However, being ≥ 65 years old (OR = 2.574, 95% CI: 1.709-3.870), being a smoker (OR = 2.773, 95% CI: 1.751-4.390), having chronic obstructive pulmonary disease (COPD) (OR = 3.373, 95% CI: 1.708-6.660), having viral hepatitis (OR= 2.079, 95% CI: 1.067-4.052), receiving non-standard treatment (OR = 15.620, 95% CI: 10.413-23.431), having medical side effects (OR = 6.138, 95% CI: 3.798-9.922) and l unauthorised discharge (OR = 2.570, 95% CI: 1.509-4.376) were risk factors for the readmission to hospital of patients with TB (p < 0.05). CONCLUSIONS: Gender, age, place of residence, smoking, COPD, hepatitis, non-standard treatment, adverse drug reactions and unauthorised discharge were risk factors of TB for unplanned readmission.

Pediatric patients with malignant brain tumor treated at children's hospitals: association with fewer unplanned readmissions.

OBJECTIVE: Pediatric primary brain tumors are the leading cause of death among childhood cancers. Guidelines recommend specialized care with a multidisciplinary team and focused treatment protocols to optimize outcomes in this patient population. Furthermore, readmission is a key metric of patient outcomes and has been used to inform reimbursement. However, no prior study has analyzed national database-level records to evaluate the role of care in a designated children's hospital following pediatric tumor resection and its impact on readmission rates. The goal of this study was to investigate whether treatment at a children's hospital rather than a nonchildren's hospital has a significant effect on outcome. METHODS: The Nationwide Readmissions Database records from 2010 to 2018 were analyzed retrospectively to evaluate the effect of hospital designation on patient outcomes after craniotomy for brain tumor resection, and results are reported as national estimates. Univariate and multivariate regression analyses of patient and hospital characteristics were conducted to evaluate if craniotomy for tumor resection at a designated children's hospital was independently associated with 30-day readmissions, mortality rate, and length of stay. RESULTS: A total of 4003 patients who underwent craniotomy for tumor resection were identified using the Nationwide Readmissions Database, with 1258 of these cases (31.4%) treated at children's hospitals. Patients treated at children's hospitals were associated with decreased likelihood of 30-day hospital readmission (OR 0.68, 95% CI 0.48-0.97, p = 0.036) compared to patients treated at nonchildren's hospitals. There was no significant difference in index mortality between patients treated at children's hospitals and those treated at nonchildren's hospitals. CONCLUSIONS: The authors found that patients undergoing craniotomy for tumor resection at children's hospitals were associated with decreased rates of 30-day readmission, with no significant difference in index mortality. Future prospective studies may be warranted to confirm this association and identify components contributing to improved outcomes in care at children's hospitals.