Dataset Information

Effect of under triage on early mortality after major pediatric trauma: a registry-based propensity score matching analysis.

ABSTRACT:

Background

Little is known about the effect of under triage on early mortality in trauma in a pediatric population. Our objective is to describe the effect of under triage on 24-h mortality after major pediatric trauma in a regional trauma system.

Methods

This cohort study was conducted from January 2009 to December 2017. Data were obtained from the registry of the Northern French Alps Trauma System. The network guidelines triage pediatric trauma patients according to an algorithm shared with adult patients. Under triage was defined by the number of pediatric trauma patients that required specialized trauma care transported to a non-level I pediatric trauma center on the total number of injured patients with critical resource use. The effect of under triage on 24-h mortality was assessed with inverse probability treatment weighting (IPTW) and a propensity score (Ps) matching analysis.

Results

A total of 1143 pediatric patients were included (mean [SD], age 10 [5] years), mainly after a blunt trauma (1130 [99%]). Of the children, 402 (35%) had an ISS higher than 15 and 547 (48%) required specialized trauma care. Nineteen (1.7%) patients died within 24 h. Under triage rate was 33% based on the need of specialized trauma care. Under triage of children requiring specialized trauma care increased the risk of death in IPTW (risk difference 6.0 [95% CI 1.3-10.7]) and Ps matching analyses (risk difference 3.1 [95% CI 0.8-5.4]).

Conclusions

In a regional inclusive trauma system, under triage increased the risk of early death after pediatric major trauma.

SUBMITTER: Ageron FX

PROVIDER: S-EPMC7791780 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effect of under triage on early mortality after major pediatric trauma: a registry-based propensity score matching analysis.

Ageron François-Xavier FX Porteaud Jordan J Evain Jean-Noël JN Millet Anne A Greze Jules J Vallot Cécile C Levrat Albrice A Mortamet Guillaume G Bouzat Pierre P

World journal of emergency surgery : WJES 20210107 1

<h4>Background</h4>Little is known about the effect of under triage on early mortality in trauma in a pediatric population. Our objective is to describe the effect of under triage on 24-h mortality after major pediatric trauma in a regional trauma system.<h4>Methods</h4>This cohort study was conducted from January 2009 to December 2017. Data were obtained from the registry of the Northern French Alps Trauma System. The network guidelines triage pediatric trauma patients according to an algorithm ...[more]

PMID: 33413465

Similar Datasets

Project description:BackgroundThe diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding.MethodsData from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting.ResultsData of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results.ConclusionThus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.

Project description:BackgroundNatural disasters, conflict, and terrorism are major global causes of death and disability. Central to the healthcare response is triage, vital to ensure the right care is provided to the right patient at the right time. The ideal triage tool has high sensitivity for the highest priority (P1) patients with acceptably low over-triage. This study compared the performance of major incident triage tools in predicting P1 casualty status in adults in the prospective UK Trauma Audit and Research Network (TARN) registry.MethodsTARN patients aged 16+ years (January 2008-December 2017) were included. Ten existing triage tools were applied using patients' first recorded pre-hospital physiology. Patients were subsequently assigned triage categories (P1, P2, P3, Expectant or Dead) based on pre-defined, intervention-based criteria. Tool performance was assessed by comparing tool-predicted and intervention-based priority status.Findings195,709 patients were included; mortality was 7·0% (n=13,601); median Injury Severity Score (ISS) was 9 (IQR 9-17); 97·1% sustained blunt injuries. 22,144 (11·3%) patients fulfilled intervention-based criteria for P1 status, exhibiting higher mortality (12·8% vs. 5·0%, p<0.001), increased intensive care requirement (52·4% vs 5·0%, p<0.001), and more severe injuries (median ISS 21 vs 9, p<0.001) compared with P2 patients.In 16-64 year olds, the highest performing tool was the Battlefield Casualty Drills (BCD) Triage Sieve (Prediction of P1 status: 70·4% sensitivity, over-triage 70·9%, area under the receiver operating curve (AUC) 0·068 [95%CI 0·676-0·684]). The UK National Ambulance Resilience Unit (NARU) Triage Sieve had sensitivity of 44·9%; over-triage 56·4%; AUC 0·666 (95%CI 0·662-0·670). All tools performed poorly amongst the elderly (65+ years).InterpretationThe BCD Triage Sieve performed best in this nationally representative population; we recommend it supersede the NARU Triage Sieve as the UK primary major incident triage tool. Validated triage category definitions are recommended for appraising future major incidents.FundingThis study is funded by the National Institute for Health Research (NIHR) Surgical Reconstruction and Microbiology Research Centre. GVG also acknowledges support from the MRC Heath Data Research UK (HDRUK/CFC/01). The views expressed are those of the authors and not necessarily those of the NIHR, the Department of Health and Social Care, or the Ministry of Defence.

Project description:Background: Stress-induced hyperglycemia (SIH) is a form of hyperglycemia secondary to stress and commonly occurs in patients with trauma. Trauma patients with SIH have been reported to have an increased risk of mortality. However, information regarding whether these trauma patients with SIH represent a distinct group with differential outcomes when compared to those with diabetic hyperglycemia (DH) remains limited. Methods: Diabetes mellitus (DM) was determined by patient history and/or admission glycated hemoglobin (HbA1c) ≥6.5%. Non-diabetic normoglycemia (NDN) was determined by a serum glucose level <200 mg/dL in the patients without DM. Diabetic normoglycemia (DN) was determined by a serum glucose level <200 mg/dL in the patients with DM. DH and SIH was diagnosed by a serum glucose level ≥200 mg/dL in the patients with and without DM, respectively. Detailed data of these four groups of hospitalized patients, which included NDN (n = 7806), DN (n = 950), SIH (n = 493), and DH (n = 897), were retrieved from the Trauma Registry System at a level I trauma center between 1 January 2009 and 31 December 2015. Patients with incomplete registered data were excluded. Categorical data were compared with Pearson chi-square tests or two-sided Fisher exact tests. The unpaired Student's t-test and the Mann-Whitney U-test were used to analyze normally distributed continuous data and non-normally distributed data, respectively. Propensity-score-matched cohorts in a 1:1 ratio were allocated using NCSS software with logistic regression to evaluate the effect of SIH and DH on the outcomes of patients. Results: The SIH (median [interquartile range: Q1-Q3], 13 [9-24]) demonstrated a significantly higher Injury Severity Score (ISS) than NDN (9 [4-10]), DN (9 [4-9]), and DH (9 [5-13]). SIH and DH had a 12.3-fold (95% confidence interval [CI] 9.31-16.14; p < 0.001) and 2.4-fold (95% CI 1.71-3.45; p < 0.001) higher odds of mortality, respectively, when compared to NDN. However, in the selected propensity-score-matched patient population, SIH had a 3.0-fold higher odd ratio of mortality (95% CI 1.96-4.49; p < 0.001) than NDN, but DH did not have a significantly higher mortality (odds ratio 1.2, 95% CI 0.99-1.38; p = 0.065). In addition, SIH had 2.4-fold higher odds of mortality (95% CI 1.46-4.04; p = 0.001) than DH. These results suggest that the characteristics and injury severity of the trauma patients contributed to the higher mortality of these patients with hyperglycemia upon admission, and that the pathophysiological effect of SIH was different from that of DH. Conclusions: Although there were worse mortality outcomes among trauma patients presenting with hyperglycemia, this effect was only seen in patients with SIH, but not DH when controlling for age, sex, pre-existed co-morbidities, and ISS.

Dataset Information

Effect of under triage on early mortality after major pediatric trauma: a registry-based propensity score matching analysis.

Background

Methods

Results

Conclusions

Publications

Effect of under triage on early mortality after major pediatric trauma: a registry-based propensity score matching analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets