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. 2022 Aug 2;11(15):4508.
doi: 10.3390/jcm11154508.

Acute Poisoning Readmissions to an Emergency Department of a Tertiary Hospital: Evaluation through an Active Toxicovigilance Program

Affiliations

Acute Poisoning Readmissions to an Emergency Department of a Tertiary Hospital: Evaluation through an Active Toxicovigilance Program

Raúl Muñoz Romo et al. J Clin Med. .

Abstract

The aim of this study is to investigate hospital readmissions during 1 year after acute poisoning cases (APC), analyze the temporal behavior of early readmissions (ER) (in the month after the index episode) and predict possible ER. A descriptive analysis of the patients with APC assisted between 2011 and 2016 in the Emergency Department of Hospital La Paz is presented, and various methods of inferential statistics were applied and confirmed by Bayesian analysis in order to evaluate factors associated with total and early readmissions. Out of the 4693 cases of APC included, 968 (20.6%) presented, at least one readmission and 476 (10.1%) of them were ER. The mean age of APC with readmission was 41 years (12.7 SD), 78.9% had previous psychiatric pathology and 44.7% had a clinical history of alcohol addiction. Accidental poisoning has been a protective factor for readmission (OR 0.50; 0.26-0.96). Type of toxin ("drug of abuse" OR 8.88; 1.17-67.25), history of addiction (OR 1.93; 1.18-3.10) and psychiatric history (OR 3.30; 2.53-4.30) are risk factors for readmissions during the first year. Women showed three or more readmissions in a year. The results of the study allow for identification of the predictors for the different numbers of readmissions in the year after the index APC, as well as for ERs.

Keywords: acute intoxication; clinical toxicology; hospital readmission; quality of care; toxicological surveillance; toxicovigilance.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Time series of monthly ERs.
Figure 2
Figure 2
Time elapsed from admission to the ED for APC to readmission. Survival analysis using Kaplan–Meier curves.

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