Dataset Information

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.

ABSTRACT: Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD.We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50%) and validation samples (50%). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample.Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0% to 55% in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95% CI: 0.783, 0.888) and 0.794 (95% CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95% CI: 0.776, 0.859) and 0.770 (95% CI: 0.716, 0.823) in the validation sample.We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care.NCT02434536.

SUBMITTER: Esteban C

PROVIDER: S-EPMC4699373 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.

Esteban Cristóbal C Arostegui Inmaculada I Garcia-Gutierrez Susana S Gonzalez Nerea N Lafuente Iratxe I Bare Marisa M Fernandez de Larrea Nerea N Rivas Francisco F Quintana José M JM

Respiratory research 20151222

<h4>Background</h4>Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD.<h4>Method ...[more]

PMID: 26695935

Similar Datasets

Project description:BackgroundAsthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.ObjectiveWe propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.MethodsWe performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.ResultsThere were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91-0.94) and 0.94 (0.93-0.96), respectively, for EMR and claims data, with positive predictive value of > 94%. The algorithms are visually presented using nomograms.ConclusionWe were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.

Project description:The Surviving Sepsis Campaign Guidelines 2021 recommends that adult patients with sepsis requiring intensive care should be admitted to the ICU within 6 hours of their emergency department (ED) visits. However, there is limited evidence on whether 6 hours is the best target time for compliance with the sepsis bundle. We aimed to investigate the association between time from ED visits to ICU admission (i.e., ED length of stay [ED-LOS]) and mortality and identify the optimal ED-LOS for patients with sepsis.DesignRetrospective cohort study.SettingThe Medical Information Mart for Intensive Care Emergency Department and Medical Information Mart for Intensive Care IV databases.PatientsAdult patients (≥ 18 yr old) who were transferred from the ED to the ICU and subsequently diagnosed with sepsis based on the Sepsis-3 criteria within 24 hours of ICU admission.InterventionsNone.Measurements and main resultsAmong 1,849 patients with sepsis, we found a disproportionally higher mortality rate in patients immediately admitted to the ICU (e.g., < 2 hr). When using ED-LOS as a continuous variable, ED-LOS was not significantly associated with 28-day mortality (adjusted odds ratio [OR] per hour increase, 1.04; 95% CI, 0.96-1.13; p = 0.3) after an adjustment for potential confounders (e.g., demographics, triage vital signs, and laboratory results) in the multivariable analysis. However, when we categorized all patients into time quartiles (ED-LOS: < 3.3 hr, 3.3-4.5 hr, 4.6-6.1 hr, and > 6.1 hr), patients in the higher time quartiles (e.g., 3.3-4.5 hr) had higher 28-day mortality compared with those in the lowest time quartile (< 3.3 hr) (e.g., adjusted OR for patients in the second time quartile [3.3-4.5 hr] 1.59; 95% CI, 1.03-2.46; p = 0.04).ConclusionsEarlier admission to the ICU (e.g., within 3.3 hr of ED visits) was associated with lower 28-day mortality in patients with sepsis. Our findings suggest patients with sepsis who require intensive care may benefit from a more immediate ICU admission than 6 hours.

Project description:Many patients evaluated for acute coronary syndrome (ACS) in emergency departments (EDs) continue to experience troubling symptoms after discharge-regardless of their ultimate medical diagnosis. However, comprehensive understanding of common post-ED symptom trajectories is lacking.The aim of this study was to identify common trajectories of symptom severity in the 6 months after an ED visit for potential ACS.This was a secondary analysis of data from a larger observational, prospective study conducted in five U.S. EDs. Patients (N = 1005) who had electrocardiogram and biomarker testing ordered, and were identified by the triage nurse as potentially having ACS, were enrolled. Symptom severity was assessed in the hospital after initial stabilization and by telephone at 30 days and 6 months using the validated 13-item ACS Symptom Checklist. Growth mixture modeling was used for the secondary analysis. The eight most commonly reported symptoms (chest discomfort, chest pain, chest pressure, light-headedness, shortness of breath, shoulder pain, unusual fatigue, and upper back pain) were modeled across the three study time points. Models with increasing numbers of classes were compared, and final model selection was based on a combination of interpretability, theoretical justification, and statistical fit indices.The sample was 62.6% male with a mean age of 60.2 years (SD = 14.17 years), and 57.1% ruled out for ACS. Between two and four distinct trajectory classes were identified for each symptom. The seven different types of trajectories identified across the eight symptoms were labeled "tapering off," "mild/persistent," "moderate/persistent," "moderate/worsening," "moderate/improving," "late onset, "and "severe/improving." Trajectories differed on age, gender, and diagnosis.Research on the individual nature of symptom trajectories can contribute to patient-centered, rather than disease-centered, care. Further research is needed to verify the existence of multiple symptoms trajectories in diverse populations and to assess the antecedents and consequences of individual symptom trajectories.

Dataset Information

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.

Publications

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets