Dataset Information

Predictive Role of QTc Prolongation in Carbon Monoxide Poisoning-Related Delayed Neuropsychiatric Sequelae.

ABSTRACT:

Objective

Delayed neuropsychiatric sequelae (DNS) are serious complications of carbon monoxide (CO) poisoning that adversely affect poisoned patients' quality of life as well as socioeconomic status. This study aimed to determine clinical predictors of DNS in patients with CO poisoning.

Methods

This retrospective study included all CO-poisoned patients admitted to the emergency department (ED) of Linkou Chang Gung Memorial Hospital in Taiwan from 1 January 2009 to 31 December 2015. The medical records of all patients with CO poisoning were carefully reviewed, and relevant data were abstracted into a standardised form. Univariate and multivariate logistic regression models were used to identify predictors of DNS after CO poisoning. Receiver operating characteristic (ROC) curve analysis was used to determine the ideal cut-off value for continuous variables that predict the development of DNS.

Results

A total of 760 patients with CO poisoning were identified during the study period. Among them, 466 were eligible for the analysis of predictors of DNS. In multivariate analysis, Glasgow Coma Scale <9 (odds ratio [OR], 2.74; 95% confidence interval [CI], 1.21-6.21), transient loss of consciousness (OR, 3.59; 95% CI, 1.31-9.79), longer duration from CO exposure to ED presentation (OR, 1.05; 95% CI, 1.03-1.08), and corrected QT (QTc) prolongation (OR, 2.61; 95% CI, 1.21-5.61) were found to be associated with a higher risk of DNS. The area under the ROC curve (AUC) for QTc interval measured within 6?h after exposure best predicted the development of DNS, with a result of 0.729 (95% CI 0.660-0.791). Moreover, the best cut-off value of the QTc interval was 471?ms, with a sensitivity of 53.3% and a specificity of 85.1%.

Conclusions

We identified several potential predictors of DNS following CO poisoning. Among them, QTc prolongation found within 6?h after exposure is a novel predictor of DNS, which may be helpful in the future care of patients with CO poisoning.

SUBMITTER: Liao SC

PROVIDER: S-EPMC6176310 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predictive Role of QTc Prolongation in Carbon Monoxide Poisoning-Related Delayed Neuropsychiatric Sequelae.

Liao Shu-Chen SC Mao Yan-Chiao YC Hung Yao-Min YM Lee Ching-Hsing CH Yang Chen-Chang CC

BioMed research international 20180925

<h4>Objective</h4>Delayed neuropsychiatric sequelae (DNS) are serious complications of carbon monoxide (CO) poisoning that adversely affect poisoned patients' quality of life as well as socioeconomic status. This study aimed to determine clinical predictors of DNS in patients with CO poisoning.<h4>Methods</h4>This retrospective study included all CO-poisoned patients admitted to the emergency department (ED) of Linkou Chang Gung Memorial Hospital in Taiwan from 1 January 2009 to 31 December 2015 ...[more]

PMID: 30356348

Similar Datasets

Project description:Importance:Preventing delayed neurological sequelae is a major goal of treating acute carbon monoxide poisoning, but to our knowledge there are no reliable tools for assessing the probability of these sequelae. Objectives:To determine whether acute brain lesions on diffusion-weighted imaging are related to subsequent development of delayed neurological sequelae after acute carbon monoxide poisoning. Design, Setting, and Participants:This registry-based observational study was conducted at a university hospital in Seoul, Korea, between April 1, 2011, and December 31, 2015. Of 700 patients (aged ?18 years) with acute carbon monoxide poisoning, 433 patients (61.9%) who underwent diffusion-weighted imaging at an emergency department were considered for the study. Patients who developed cardiac arrest before diffusion-weighted imaging (n?=?3), had persistent neurological symptoms at discharge (n?=?8), committed suicide soon after discharge (n?=?1), and were lost to follow-up (n?=?34) were excluded. Exposure:The presence of unambiguous, high-signal-intensity, acute brain lesions on diffusion-weighted imaging (b?=?1000 s/mm2). Main Outcomes and Measures:Development of delayed neurological sequelae defined as any neurological symptoms or signs that newly developed within 6 weeks of discharge. Results:Of the 387 included patients (143 women [37.0%]; median age, 42.0 years [interquartile range, 32.0-56.0 years]), acute brain lesions on diffusion-weighted imaging were observed in 104 patients (26.9%). Among these, 77 patients (19.9%) had globus pallidus lesions, 13 (3.4%) had diffuse lesions, and 57 (14.7%) had focal lesions (37 patients [9.6%] had >1 pattern concurrently). Lesions were supratentorial and infratentorial in 101 and 23 patients, respectively. Delayed neurological sequelae occurred in 101 patients (26.1%). Multivariable logistic regression analysis indicated that the presence of acute brain lesions was independently associated with development of delayed neurological sequelae (adjusted odds ratio, 13.93; 95% CI, 7.16-27.11; P?<?.001). The sensitivity and specificity of acute brain lesions to assess the probability of delayed neurological sequelae were 75.2% (95% CI, 66.8%-83.7%) and 90.2% (95% CI, 86.8%-93.7%), respectively. In addition, the positive and negative predictive values were 73.1% (95% CI, 64.6%-81.6%) and 91.2% (95% CI, 87.9%-94.5%), respectively. Conclusions and Relevance:The presence of acute brain lesions was significantly associated with the development of delayed neurological sequelae. Diffusion-weighted imaging during the acute phase of carbon monoxide poisoning may therefore help identify patients at risk of developing these debilitating sequelae.

Dataset Information

Predictive Role of QTc Prolongation in Carbon Monoxide Poisoning-Related Delayed Neuropsychiatric Sequelae.

Objective

Methods

Results

Conclusions

Publications

Predictive Role of QTc Prolongation in Carbon Monoxide Poisoning-Related Delayed Neuropsychiatric Sequelae.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets