Dataset Information

Evaluation and disposition of older adults presenting to the emergency department with abdominal pain.

ABSTRACT:

Background

Abdominal pain is the most common chief complaint in US emergency departments (EDs) among patients over 65, who are at high risk of mortality or incident disability after the ED encounter. We sought to characterize the evaluation, management, and disposition of older adults who present to the ED with abdominal pain.

Methods

We performed a survey-weighted analysis of the National Hospital Ambulatory Medical Care Survey (NHAMCS), comparing older adults with a chief complaint of abdominal pain to those without. Visits from 2013 to 2017 to nationally representative EDs were included. We analyzed 81,509 visits to 1211 US EDs, which projects to 531,780,629 ED visits after survey weighting. We report the diagnostic testing, evaluation, management, additional reasons for visit, and disposition of ED visits.

Results

Among older adults (≥65 years), 7% of ED visits were for abdominal pain. Older patients with abdominal pain had a lower probability of being triaged to the "Emergent" (ESI2) acuity on arrival (7.1% vs. 14.8%) yet were more likely to be admitted directly to the operating room than older adults without abdominal pain (3.6% vs. 0.8%), with no statistically significant differences in discharge home, death, or admission to critical care. Ultrasound or CT imaging was performed in 60% of older adults with abdominal pain. A minority (39%) of older patients with abdominal pain received an electrocardiogram (EKG).

Conclusions

Abdominal pain in older adults presenting to EDs is a serious condition yet is triaged to "emergent" acuity at half the rate of other conditions. Opportunities for improving diagnosis and management may exist. Further research is needed to examine whether improved recognition of abdominal pain as a syndromic presentation would improve patient outcomes.

SUBMITTER: Friedman AB

PROVIDER: S-EPMC10078825 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Evaluation and disposition of older adults presenting to the emergency department with abdominal pain.

Friedman Ari B AB Chen Angela T AT Wu Rachel R Coe Norma B NB Halpern Scott D SD Hwang Ula U Kelz Rachel R RR Cappola Anne R AR

Journal of the American Geriatrics Society 20211010 2

<h4>Background</h4>Abdominal pain is the most common chief complaint in US emergency departments (EDs) among patients over 65, who are at high risk of mortality or incident disability after the ED encounter. We sought to characterize the evaluation, management, and disposition of older adults who present to the ED with abdominal pain.<h4>Methods</h4>We performed a survey-weighted analysis of the National Hospital Ambulatory Medical Care Survey (NHAMCS), comparing older adults with a chief compla ...[more]

PMID: 34628638

Similar Datasets

Project description:BackgroundAcute abdominal pain (AAP) constitutes 5-10% of all emergency department (ED) visits, with appendicitis being a prevalent AAP etiology often necessitating surgical intervention. The variability in AAP symptoms and causes, combined with the challenge of identifying appendicitis, complicate timely intervention. To estimate the risk of appendicitis, scoring systems such as the Alvarado score have been developed. However, diagnostic errors and delays remain common. Although various machine learning (ML) models have been proposed to enhance appendicitis detection, none have been seamlessly integrated into the ED workflows for AAP or are specifically designed to diagnose appendicitis as early as possible within the clinical decision-making process. To mimic daily clinical practice, this proof-of-concept study aims to develop ML models that support decision-making using comprehensive clinical data up to key decision points in the ED workflow to detect appendicitis in patients presenting with AAP.MethodsData from the Dutch triage system at the ED, vital signs, complete medical history and physical examination findings and routine laboratory test results were retrospectively extracted from 350 AAP patients presenting to the ED of a Dutch teaching hospital from 2016 to 2023. Two eXtreme Gradient Boosting ML models were developed to differentiate cases with appendicitis from other AAP causes: one model used all data up to and including physical examination, and the other was extended with routine laboratory test results. The performance of both models was evaluated on a validation set (n = 68) and compared to the Alvarado scoring system as well as three ED physicians in a reader study.ResultsThe ML models achieved AUROCs of 0.919 without laboratory test results and 0.923 with the addition of laboratory test results. The Alvarado scoring system attained an AUROC of 0.824. ED physicians achieved AUROCs of 0.894, 0.826, and 0.791 without laboratory test results, increasing to AUROCs of 0.923, 0.892, and 0.859 with laboratory test results.ConclusionsBoth ML models demonstrated comparable high accuracy in predicting appendicitis in patients with AAP, outperforming the Alvarado scoring system. The ML models matched or surpassed ED physician performance in detecting appendicitis, with the largest potential performance gain observed in absence of laboratory test results. Integration could assist ED physicians in early and accurate diagnosis of appendicitis.

Dataset Information

Evaluation and disposition of older adults presenting to the emergency department with abdominal pain.

Background

Methods

Results

Conclusions

Publications

Evaluation and disposition of older adults presenting to the emergency department with abdominal pain.

Similar Datasets

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