Rishi Rattan

Risk factors and costs associated with nationwide nonelective readmission after trauma

BACKGROUND Most prior studies of readmission after trauma have been limited to single institutions, whereas multi-institutional studies have been limited to single states and an inability to distinguish between elective and nonelective readmissions. The purpose of this study was to identify the risk factors and costs associated with nonelective readmission after trauma across the United States. METHODS The Nationwide Readmission Database was queried for all patients with nonelective admissions in 2013 and 2014 with a primary diagnosis of trauma. Univariate and multivariate logistic regression identified risk factors for 30-day nonelective same- and different-hospital readmission. The diagnosis groups on readmission were evaluated, and the total cost of readmissions was calculated. RESULTS There were 1,180,144 patients admitted for trauma, the 30-day readmission rate was 9.4%, and 26.4% of readmissions occurred at a different hospital. The median readmission cost for patients readmitted to the same hospital was

Primary prevention of contact sports-related concussions in amateur athletes: a systematic review from the Eastern Association for the Surgery of Trauma

8,298 (interquartile range,

Predicting central line-associated bloodstream infections and mortality using supervised machine learning

4,899–

Hidden Costs of Hospitalization After Firearm Injury: National Analysis of Different Hospital Readmission

14,911), whereas the median readmission cost for patients readmitted to a different hospital was

Percutaneously drained intra-abdominal infections do not require longer duration of antimicrobial therapy.

8,568 (interquartile range,

Patients with Complicated Intra-Abdominal Infection Presenting with Sepsis Do Not Require Longer Duration of Antimicrobial Therapy: In reply to Spartalis and colleagues

4,935–

Closed (Blunt) Compared to Open (Penetrating) Pulmonary Contusion–A National Trauma Data Bank Review

16,078; p < 0.01). Multivariate regression revealed that patients discharged against medical advice were at increased risk of readmission (odds ratio, 2.79; p < 0.01) and readmission to a different facility (odds ratio, 1.58; p < 0.01). Home health care was associated with a decreased risk of readmission to a different hospital (odds ratio, 0.74; p < 0.01). Septicemia and disseminated infections were the most common diagnoses on readmission (8.4%) and readmission to a different hospital (8.6%). CONCLUSIONS A significant portion of US readmissions occur at different hospitals with implications for continuity of care, quality metrics, cost, and resource allocation. Home health care reduces the likelihood of nonelective readmission to a different hospital. Infection was the most common reason for readmission, with ramifications for outcomes research and quality improvement. LEVEL OF EVIDENCE Care management/epidimeological, level IV.

A survey of the practice and attitudes of surgeons regarding the treatment of appendicitis

Background Awareness of the magnitude of contact sports-related concussions has risen exponentially in recent years. Our objective is to conduct a prospectively registered systematic review of the scientific evidence regarding interventions to prevent contact sports-related concussions. Methods Using the Grading of Recommendations Assessment, Development, and Evaluation methodology, we performed a systematic review of the literature to answer seven population, intervention, comparator, and outcomes (PICO) questions regarding concussion education, head protective equipment, rules prohibiting high-risk activity and neck strengthening exercise for prevention of contact sports-related concussion in pediatric and adult amateur athletes. A query of MEDLINE, PubMed, Scopus, Cumulative Index of Nursing and Allied Health Literature, and Embase was performed. Letters to the editor, case reports, book chapters, and review articles were excluded, and all articles reviewed were written in English. Results Thirty-one studies met the inclusion criteria and were applicable to our PICO questions. Conditional recommendations are made supporting preventive interventions concussion education and rules prohibiting high-risk activity for both pediatric and adult amateur athletes and neck strengthening exercise in adult amateur athletes. Strong recommendations are supported for head protective equipment in both pediatric and adult amateur athletes. Strong recommendations regarding newer football helmet technology in adult amateur athletes and rules governing the implementation of body-checking in youth ice hockey are supported. Conclusion Despite increasing scientific attention to sports-related concussion, studies evaluating preventive interventions remain relatively sparse. This systematic review serves as a call to focus research on primary prevention strategies for sports-related concussion. Level of evidence IV. PROSPERO registration number #42016043019.

Does Isolation of Enterococcus Affect Outcomes in Intra-Abdominal Infections?

Purpose: The purpose of this study was to compare machine learning techniques for predicting central line‐associated bloodstream infection (CLABSI). Materials and methods: The Multiparameter Intelligent Monitoring in Intensive Care III database was queried for all ICU admissions. The variables included six different severities of illness scores calculated on the first day of ICU admission with their components and comorbidities. The outcomes of interest were in‐hospital mortality, central line placement, and CLABSI. Predictive models were created for these outcomes using classifiers with different algorithms: logistic regression, gradient boosted trees, and deep learning. Results: There were 57,786 total hospital admissions and the mortality rate was 10.1%. There were 38.4% patients with a central line and the rate of CLABSI was 1.5%. The classifiers using deep learning performed with the highest AUC for mortality, 0.885 ± 0.010 (p < 0.01) and central line placement, 0.816 ± 0.006 (p < 0.01). The classifier using logistic regression for predicting CLABSI performed with an AUC of 0.722 ± 0.048 (p < 0.01). Conclusions: This study demonstrates models for identifying patients who will develop CLABSI. Early identification of these patients has implications for quality, cost, and outcome improvements. HIGHLIGHTSMachine learning has proven to be useful for developing prediction models for outcomes in intensive care unit patients.This study uses illness severity scores and comorbidities provided to train artificial intelligence classifiers.These classifiers were highly accurate for predicting central line‐associated bloodstream infections and mortality.Such predictive models can be incorporated into existing medical record systems to support clinical decision making.

Management of Lower Extremity Vascular Injuries: State of the Art

Objective: To compare the risk factors and costs associated with readmission after firearm injury nationally, including different hospitals. Background: No national studies capture readmission to different hospitals after firearm injury. Methods: The 2013 to 2014 Nationwide Readmissions Database was queried for patients admitted after firearm injury. Logistic regression identified risk factors for 30-day same and different hospital readmission. Cost was calculated. Survey weights were used for national estimates. Results: There were 45,462 patients admitted for firearm injury during the study period. The readmission rate was 7.6%, and among those, 16.8% were readmitted to a different hospital. Admission cost was