Incidence, risk factors, and clinical impact of non-home discharge following surgical management of proximal humerus fractures

Preoperative factors predict prolonged length of stay, serious adverse complications, and readmission following operative intervention of proximal humerus fractures: a machine learning analysis of a national database

Background

Proximal humerus fractures are a common injury, predominantly affecting older adults. This study aimed to develop risk-prediction models for prolonged length of hospital stay (LOS), serious adverse complications, and readmission within 30 days of surgically treated proximal humerus fractures using machine learning (ML) techniques.

Methods

Adult patients (age >18) who underwent open reduction internal fixation (ORIF), hemiarthroplasty, or total shoulder arthroplasty for proximal humerus fracture between 2016 and 2021 were included. Preoperative demographic and clinical variables were collected for all patients and used to establish ML-based algorithms. The model with optimal performance was selected according to area under the curve (AUC) on the receiver operating curve (ROC) curve and overall accuracy, and the specific predictive features most important to model derivation were identified.

Results

A total of 7473 patients were included (72.1% male, mean age 66.2 ± 13.7 years). Models produced via gradient boosting performed best for predicting prolonged LOS and complications. The model predicting prolonged LOS demonstrated good discrimination and performance, as indicated by (Mean: 0.700, SE: 0.017), recall (Mean: 0.551, SE: 0.017), accuracy (Mean: 0.717, SE: 0.010), F1-score (Mean: 0.616, SE: 0.014), AUC (Mean: 0.779, SE: 0.010), and Brier score (Mean: 0.283, SE: 0.010) Preoperative hematocrit, preoperative platelet count, and patient age were considered the strongest predictive features. The model predicting serious adverse complications exhibited comparable discrimination [precision (Mean: 0.226, SE: 0.024), recall (Mean: 0.697, SE: 0.048), accuracy (Mean: 0.811, SE: 0.010), F1-score (Mean: 0.341, SE: 0.031)] and superior performance relative to the LOS model [AUC (Mean: 0.806, SE: 0.024), Brier score (Mean: 0.189, SE: 0.010), noting preoperative hematocrit, operative time, and patient age to be most influential. However, the 30-day readmission model achieved the weakest relative performance, displaying low measures of precision (Mean: 0.070, SE: 0.012) and recall (Mean: 0.389, SE: 0.053), despite good accuracy (Mean: 0.791, SE: 0.009).

Conclusion

Predictive models constructed using ML techniques demonstrated favorable discrimination and satisfactory-to-excellent performance in forecasting prolonged LOS and serious adverse complications occurring within 30 days of surgical intervention for proximal humerus fracture. Modifiable preoperative factors such as hematocrit and platelet count were identified as significant predictive features, suggesting that clinicians could address these factors during preoperative patient optimization to enhance outcomes. Overall, these findings highlight the potential for ML techniques to enhance preoperative management, facilitate shared decision-making, and enable more effective and personalized orthopedic care by exploring alternative approaches to risk stratification.

Factors affecting hospital admission, hospital length of stay and new discharge destination post proximal humeral fracture: a retrospective audit

BACKGROUND

Outcomes following proximal humeral fracture (PHF) may be impacted by a range of clinical, fracture and premorbid factors. The aim of this study was to examine factors impacting hospital admission; length of stay (LOS) and new discharge destination for patients presenting to hospital with PHF.

METHODS

Retrospective audit conducted at a tertiary health service. Data was collected from adult patients presenting to hospital with a PHF over a 54-month period. Fractures that were pathological or sustained during admission were excluded. Univariable and multivariable logistic and negative binomial regression were used to explore factors associated with hospital admission, LOS and new discharge destination.

RESULTS

Data were analyzed from 701 participants (age 70 years (IQR 60, 81); 72.8% female); 276 (39.4%) participants required a hospital admission. New discharge destination was required for 109 (15.5%) participants, of whom 49 (45%) changed from home alone to home with family/friend(s). Greater comorbidities, as indicated by the Charlson Comorbidity Index score, were associated with hospital admission, longer LOS and new discharge destination. Premorbid living situations of home with family/friend(s) or from an external care facility were associated with a decreased likelihood of hospital admission, shorter LOS and reduced risk of a new discharge destination. Surgical treatment was associated with shorter LOS. Older age and dementia diagnosis were associated with a new discharge destination.

CONCLUSIONS

Many factors potentially impact on the likelihood or risk of hospitalization, LOS and new discharge destination post PHF. Patients with greater comorbidities are more likely to have negative outcomes, while patients who had premorbid living situations of home with family/friend(s) or from an external care facility are more likely to have positive outcomes. Early identification of factors that may impact patient outcomes may assist timely decision making in hospital settings. Further research should focus on developing tools to predict hospital outcomes in the PHF population.

Survival after multiple episodes of cardiac arrest

BACKGROUND

Cardiopulmonary resuscitation (CPR) is widely used in response to cardiac arrest. However, little is known regarding outcomes for those who undergo multiple episodes of cardiac arrest while in the hospital.

OBJECTIVES

The purpose of this study was to evaluate the association of multiple cardiac events with in-hospital mortality for patients admitted to our tertiary care hospital who underwent multiple code events.

METHODS

We performed a retrospective cohort study on all patients who underwent cardiac arrest from 2012 to 2016. Primary outcome was survival to discharge. Secondary outcomes included post-cardiac-arrest neurologic events (PCANE), non-home discharge, and one-year mortality.

RESULTS

There were 622 patients with an overall mortality rate of 78.0%. Patients undergoing CPR for cardiac arrest once during their admission had lower in-hospital mortality rates compared to those that had multiple (68.9% versus 91.3%, p<.01). Subset analysis of those who had multiple episodes of CPR revealed that more than one event within a 24-hour period led to significantly higher in-hospital mortality rates (94.7% versus 74.4%, p<.01). Other variables associated with in-hospital mortality included body mass index, female sex, malignancy, and increased down time per code. Patients that had a non-home discharge were more likely to have sustained a PCANE than those that were discharged home (31.4% versus 3.9%, p<.01). A non-home discharge was associated with higher one-year mortality rates compared to a home discharge (78.4% versus 54.3%, p=.01).

CONCLUSION

Multiple codes within a 24-hour period and the average time per code were associated with in-hospital mortality in cardiac arrest patients.

Readmission, Reoperation, and Non-home Discharge Rates in Patients Receiving Surgical Treatment for Proximal Humerus Fractures

Background

Proximal humerus fractures (PHFs) are generally surgically treated with open reduction internal fixation (ORIF), hemiarthroplasty (HA), or total shoulder arthroplasty (TSA). Diverse fracture patterns and a high prevalence in the elderly population make it difficult to establish objective guidelines for the decision to undergo surgical treatment. The purpose of this study was to investigate risk factors associated with readmission, reoperation, and nonhome discharge following ORIF, HA, and TSA for PHFs.

Methods

Data on all patients who underwent ORIF, TSA, or HA for treatment of closed PHF between 2015 and 2017 were obtained by querying the American College of Surgeons National Surgical Quality Improvement database. Rates of postoperative readmission, nonhome discharge, and reoperation within 30 days were collected. Multivariate logistic regression was employed to identify predictors of readmission, nonhome discharge, and reoperation.

Results

A total of 2825 patients were included in this study: 1829 underwent ORIF, 707 underwent TSA, and 289 underwent HA. The significant predictors for readmission were having an American Society of Anesthesiologists class ≥ 3 (odds ratio [OR] 1.95, P = .003) and being of dependent functional status (OR 3.15, P < .001). The significant predictors for reoperation were male sex (OR 2.41, P < .001) and dependent functional status (OR 2.92, P = .006). The significant predictors for nonhome discharge were age 66-80 years (OR 7.00, P < .001), age ≥ 81 years (OR 16.31, P < .001), American Society of Anesthesiologists ≥3 (OR 2.34, P < .001), dependent functional status (OR 2.48, P < .001), and inpatient status (OR 3.32, P < .001). TSA showed slightly higher rates of nonhome discharge than HA and ORIF.

Conclusion

Significant risk factors for readmission, reoperation, and nonhome discharge within 30 days following surgical treatment for PHF were identified. Additionally, TSA was significantly associated with nonhome discharge compared with HA and ORIF.

Analysis of Patient’s Willingness and Concerns for Discharge Following Shoulder Arthroplasty

Background

Patient's willingness and barriers for discharge after shoulder arthroplasty (SA) has not been studied. The aim of this study was to prospectively analyze patient's willingness for discharge and barriers to discharge beyond postoperative day #1 (POD#1) after SA.

Methods

In this prospective study, patients undergoing primary or revision SA (anatomic, reverse, or hemiarthroplasty) at our institution were enrolled to determine their willingness and concerns for discharge after SA. Patient's willingness for discharge was inquired daily until discharge. Demographic information, patient's medical history, intraoperative details (duration of surgery, estimated blood loss, intraoperative complication), discharge disposition, length of stay (LOS), and reasons for extension of LOS beyond POD#1 were analyzed.

Results

A total of 184 patients who underwent SA were included. Eight patients were discharged on POD#0, 114 patients on POD#1, 37 patients on POD#2, and 25 patients after POD#2. One hundred nineteen (119) patients were discharged to home, 40 were discharged to home with services, 15 were discharged to nursing facilities, and 10 were discharged to rehabilitation centers. Reasons for extension of LOS past POD#1 included patients failing to clear home safety evaluation (n = 4), inadequate pain control (n = 6), worsening of preexisting medical conditions (n = 8), delay in patient disposition (awaiting placement in a rehabilitation facility [n = 6] and awaiting culture results [n = 9]). Social reasons (n = 29) were the most common reasons for extension of LOS. These included patients requesting an extra day of stay (n = 20), patients requesting rehabilitation facility placement (n = 5), lack of a timely ride home (n = 2), and family-related reasons (death in the family [n = 1], lack of home help [n = 1]).

Conclusions

This prospective study demonstrates modifiable factors associated with LOS beyond POD#1 (inadequate pain control, logistic delays in disposition, and patient-related social concerns) after SA. With increasing interest in same-day discharge and rising concerns to control cost and use bundled payment initiatives with SA, improving patient's willingness to discharge by addressing their concerns can improve early discharge after SA.

Dynamics of balance indicators, activities of daily living, and quality of life of elderly suffering from Parkinson's disease and frailty after proximal humerus fracture following physiotherapeutic functional training

Balance dysfunction in elderly patients with Parkinson's disease (PD) is a high-risk fall precaution, along with sarcopenia and senile asthenia, which leads to traumas, including fractures of the proximal humerus fractures (PHF). The objective of the study was to determine the effectiveness of a functional training as part of a physical therapy program on balance, upper limb (UL) function, daily living activities, and quality of life in elderly patients with PD and frailty, following proximal humerus fractures. We examined 33 elderly patients with PD and frailty in the recovery period after PHF. The control group included individuals who underwent rehabilitation according to the general principles of kinesitherapy. The treatment group consisted of patients engaged in a program of physical therapy directed at improving balance, function of the upper UL, motor stereotype, and activities of daily living. The effectiveness of the program was evaluated using the Short Physical Performance Battery (SPPB), Berg Balance Scale (BBS), Disability of the Arm, Shoulder and Hand Outcome Measure (DASH), Wrist Dynamometry, Falls efficacy Scale International (FES-I), Barthel Activities of daily living (ADL) Index, Lawton Instrumental activities of daily living (IADL) Scale, PD Questionnaire-39 (PDQ-39). According to all studied indicators, the patients of both groups showed a statistically and significantly better result compared to the initial data (p<0.05), but the treatment group showed better outcomes compared with the control group (p<0.05).

Can We Stratify Quality and Cost for Older Patients With Proximal and Midshaft Humerus Fractures?

Introduction:

This study sought to investigate whether a validated trauma triage tool can stratify hospital quality measures and inpatient cost for middle-aged and geriatric trauma patients with isolated proximal and midshaft humerus fractures.

Materials and Methods:

Patients aged 55 and older who sustained a proximal or midshaft humerus fracture and required inpatient treatment were included. Patient demographic, comorbidity, and injury severity information was used to calculate each patient’s Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA). Based on scores, patients were stratified to create minimal, low, moderate, and high risk groups. Outcomes included length of stay, complications, operative management, ICU/SDU-level care, discharge disposition, unplanned readmission, and index admission costs.

Results:

Seventy-four patients with 74 humerus fractures met final inclusion criteria. Fifty-eight (78.4%) patients presented with proximal humerus and 16 (21.6%) with midshaft humerus fractures. Mean length of stay was 5.5 ± 3.4 days with a significant difference among risk groups (P = 0.029). Lower risk patients were more likely to undergo surgical management (P = 0.015) while higher risk patients required more ICU/SDU-level care (P < 0.001). Twenty-six (70.3%) minimal risk patients were discharged home compared to zero high risk patients (P = 0.001). Higher risk patients experienced higher total inpatient costs across operative and nonoperative treatment groups.

Conclusion:

The STTGMA tool is able to reliably predict hospital quality measures and cost outcomes that may allow hospitals and providers to improve value-based care and clinical decision-making for patients presenting with proximal and midshaft humerus fractures.

Level of Evidence:

Prognostic Level III.