A Single Center Retrospective Cohort Study of Auto-intoxicated Patients Admitted to the ICU

Overview

Intentional poisoning is a relevant public health issue responsible for a considerable number of cases of morbidity and mortality worldwide. There are no concrete numbers/investigations of these patients admitted to the ICU at our hospital, with limited insight on their characteristics and outcome. It is expected that this population of patients is an important burden for the ICU. It can be important to shed a light on prevalence and ratio of intoxicated patients admitted to the ICU in our center. Furthermore, during the covid-pandemic, we could expect an increase in self-poisoning prevalence due to social restrictions, more limited access to (mental) health care, etc…

Aim The aims of this study are to quantify the ratio of intensive care admissions attributable to self-poisoning in our hospital, to examine characteristics and outcome of these patients, yearly trends and impact of the covid-pandemic on these variables. Design A single center retrospective cohort study analysis of patients with self-poisoning admitted to ICU of the Jessa Hospital Hasselt Belgium over a period of 6 years (2017-2022). Sample size All patients diagnosed with self-poisoning admitted to the ICU of the Jessa hospital between 01/01/2017 and 31/12/2022 were included in the study. This were 377 patients. Study population Inclusion and exclusion criteria: All patients (\>14 years of age) diagnosed with self-poisoning and admitted to the ICU of the Jessa hospital between 01/01/2017 and 31/12/2022 were included in the study. Patient admitted for tentamen suicide but not due to intoxication were excluded as well as patients with no medical records in the Jessa hospital. Primary Outcome The prevalence of auto-intoxicated patients admitted to the ICU together with the mortality rate on the ICU. Secondary Outcome measurements Secondary outcome measurement are the ICU and hospital length of stay, ratio of auto-intoxicated patients to all patients admitted at ICU, types of drugs ingested, number of drugs involved, cause of admission, yearly trends and impact of covid-pandemic. Statistical analysis Data will be presented as mean values +/-SD, numbers(n), and percentages(%) or median (25%, 75% percentile) in case of non-parametric data. Categorical variables are presented as frequencies (%) and groups were compared using Chi-square or Fisher's exact test. Differences between patients change will be analyzed using the Student t test for continuous outcomes or, in case of non-parametric data, the Mann-Whitney U test. Univariate and multivariate logistic regression models will be used in order to predict mortality. P values \<0.05 will be considered statistically significant. Additional data collection: Additional collected parameters are listed below and are collected as a standard-of-care in our hospital: * Demographics: i.e age, gender, BMI * DNR-code * Admission route * Patient state and symptoms: i.e vital signs, GCS, … * Comorbidities: i.e smoking, obesity, hypertension, diabetes, cardiovascular disease, respiratory disease, malignancies, renal failure, liver failure, neurological conditions, mental state and disease * Technical investigation results: i.e Laboratory results, ECG, radiological findings, etc… * Complications: i.e shock, heart failure, sepsis, stroke, etc… * Ventilation: method, PEEP, FiO2, P/F ratio,… * Management: i.e antidote, supportive, mechanical ventilation, dialysis, observation,