Predicting Unplanned Trauma ICU Admissions for Initial Nonoperative, Non-ICU Patients.

Introduction: Unplanned intensive care unit (ICU) admissions are associated with increased morbidity and mortality. This study uses interpretable machine learning to predict unplanned ICU admissions for initial nonoperative trauma patients admitted to non-ICU locations.

Methods: TQIP (2020-2021) was queried for initial nonoperative adult patients admitted to non-ICU locations.

OnetoMap Meta-Data: Healthcare Analytics Through Research.

Introduction: Big Data has revolutionized healthcare research through the three Vs: volume, veracity, and variety. This study introduces the OnetoMap meta-data repository, a centralized inventory developed in collaboration with the University of South Florida's Department of Surgery.

Methods: The repository offers extensive details about each database, including its primary purpose, available variables, and examples of high-impact research utilizing these databases.

Hospitals with decreasing cost-to-charge ratios bill greater surgical charges for similar outcomes.

Background: The cost-to-charge ratio reflects the markup of hospital services. A lower cost-to-charge ratio indicates lower costs and/or greater charges. This study examines factors associated with cost-to-charge ratio trends to determine whether decreasing cost-to-charge ratio is associated with worse surgical outcomes.

For the Love of the Game: Calculating the Premium Associated With Academic Surgical Practice.

Objective: We sought to determine the premium associated with a career in academic surgery, as measured by compensation normalized to the work relative value unit (wRVU).

Background: An academic surgical career embodying innovation and mentorship offers intrinsic rewards but is not well monetized. We know compensation for academic surgeons is less than their nonacademic counterparts, but the value of clinical effort, as normalized to the wRVU, between academic and nonacademic surgeons has not been well characterized.

Clinical Applications of Machine Learning.

Objective: This review introduces interpretable predictive machine learning approaches, natural language processing, image recognition, and reinforcement learning methodologies to familiarize end users.

Background: As machine learning, artificial intelligence, and generative artificial intelligence become increasingly utilized in clinical medicine, it is imperative that end users understand the underlying methodologies.

Methods: This review describes publicly available datasets that can be used with interpretable predictive approaches, natural language processing, image recognition, and reinforcement learning models, outlines result interpretation, and provides references for in-depth information about each analytical framework.

Lower Socioeconomic Status Predicts Greater Obstacles to Care: Using Outpatient Cholecystectomy as a Model Cohort.

Background: Patients with low socioeconomic status (SES) are disadvantaged in terms of access to health care. A novel metric for SES is the Distressed Communities Index (DCI). This study evaluates the effect of DCI on hospital choice and distance traveled for surgery.

Meta-Analysis in Surgical Research: Methodology and Statistical Application.

In evidence-based medicine, systematic review continues to carry the highest weight in terms of quality and reliability, synthesizing robust information from previously published cohort studies to provide a comprehensive overview of a topic. Meta-analysis provides further depth by allowing for comparative analysis between the studied intervention and the control group, providing the most up-to-date evidence on their characteristics and efficacy. We discuss the principles and methodology of meta-analysis, and its applicability to the field of surgical research.

Survival Tree Provides Individualized Estimates of Survival After Lung Transplant.

Introduction: Identifying contributors to lung transplant survival is vital in mitigating mortality. To enhance individualized mortality estimation and determine variable interaction, we employed a survival tree algorithm utilizing recipient and donor data.

Methods: United Network Organ Sharing data (2000-2021) were queried for single and double lung transplants in adult patients.

Expanded analysis for patients with acute cholecystitis indicates outcomes vary based on COVID-19 status and treatment modality.

Background: The impact of different phases of COVID-19 infection on outcomes from acute calculous cholecystitis (ACC) is not well understood. Therefore, we examined outcomes of acute cholecystitis during the COVID-19 pandemic, comparing the effect of different treatment modalities and COVID-19 infection status. We hypothesized that patients with acute COVID-19 would have worse outcomes than COVID-negative patients, but there would be no difference between COVID-negative and COVID-recovered patients.

The continued financial effect of COVID: Increasing costs for non-elective major lower extremity amputations.

Background: The COVID-19 pandemic necessitated changes in processes of care, which significantly impacted surgical care. This study evaluated the impact of these changes on patient outcomes and costs for non-elective major lower extremity amputations (LEA).

Methods: The 2019-2021 Florida Agency for Health Care Administration database was queried for adult patients who underwent non-elective major LEA.

Cirrhosis Increases the Rate of Failure of Nonoperative Management in Blunt Liver Injuries.

Pre-existing cirrhosis is associated with increased mortality in blunt liver injury. Despite widespread use of nonoperative management (NOM) for blunt liver injury, there is a relative paucity of data regarding how pre-existing cirrhosis impacts the success of NOM. Herein, we perform a retrospective cohort study using ACS TQIP 2017-2020 data to assess the relationship between cirrhosis and failure of NOM for adult patients with blunt liver injury.

Examining surgeon stress in robotic and laparoscopic surgery.

Robotic surgery may decrease surgeon stress compared to laparoscopic. To evaluate intraoperative surgeon stress, we measured salivary alpha-amylase and cortisol. We hypothesized robotic elicited lower increases in surgeon salivary amylase and cortisol than laparoscopic.

The downtrending cost of robotic bariatric surgery: a cost analysis of 47,788 bariatric patients.

The surgical robot is assumed to be a fixed, indirect cost. We hypothesized rising volume of robotic bariatric procedures would decrease cost per patient over time. Patients who underwent elective, initial gastric bypass (GB) or sleeve gastrectomy (SG) for morbid obesity were selected from Florida Agency for Health Care Administration database from 2017 to 2021.

Nonelective coronary artery bypass graft outcomes are adversely impacted by Coronavirus disease 2019 infection, but not altered processes of care: A National COVID Cohort Collaborative and National Surgery Quality Improvement Program analysis.

Objective: The effects of Coronavirus disease 2019 (COVID-19) infection and altered processes of care on nonelective coronary artery bypass grafting (CABG) outcomes remain unknown. We hypothesized that patients with COVID-19 infection would have longer hospital lengths of stay and greater mortality compared with COVID-negative patients, but that these outcomes would not differ between COVID-negative and pre-COVID controls.

Methods: The National COVID Cohort Collaborative 2020-2022 was queried for adult patients undergoing CABG.

Corrigendum to "Association of state-level factors with rate of firearm-related deaths" [Surg. Open Sci. vol. 14 (2023) 114-119].

[This corrects the article DOI: 10.1016/j.sopen.

Is nonoperative management of appendicitis inferior in the COVID-19 era?

Background: Previous studies on nonoperative management (NOM) of acute appendicitis (AA) indicated comparable outcomes to surgery, but the effect of COVID-19 infection on appendicitis outcomes remains unknown. Thus, we evaluate appendicitis outcomes during the COVID-19 pandemic to determine the effect of COVID-19 infection status and treatment modality. We hypothesized that active COVID-19 patients would have worse outcomes than COVID-negative patients, but that outcomes would not differ between recovered COVID-19 and COVID-negative patients.

Patient outcomes and cost in robotic emergency general surgery.

The use of robotic technology in general surgery continues to increase, though its utility for emergency general surgery remains under-studied. This study explores the current trends in patient outcomes and cost of robotic emergency general surgery (REGS). The Florida Agency for Healthcare Administration database (2018-2020) was queried for adult patients undergoing intra-abdominal emergency general surgery within 24 h of admission and linked to CMS Cost Reports/Hospital Compare, American Hospital Association, and Rand Corporation Hospital datasets.

Association of state-level factors with rate of firearm-related deaths.

Background: Over 48,000 people died by firearm in the United States in 2021. Firearm violence has many inciting factors, but the full breadth of associations has not been characterized. We explored several state-level factors including factors not previously studied or insufficiently studied, to determine their association with state firearm-related death rates.

COVID-Induced Alterations in Surgical Care and Outcomes in Perforated Diverticulitis.

Background: COVID-19 caused healthcare systems to significantly alter processes of care. Literature on the pandemic's effect on healthcare processes and resulting surgical outcomes is lacking. This study aims to determine outcomes of open colectomy in patients with perforated diverticulitis during the pandemic.

Causal analysis of socioeconomic influence on cost of care: The emergency general surgery model.

Background: This study characterizes the relationship between SES and cost of emergency general surgery (EGS).

Methods: Utilizing Florida AHCA (2016-2020), patients undergoing the 7 most common EGS were identified. Distressed Community Index (DCI) was linked, which quantifies SES through unemployment, poverty, and other factors.