Factors Associated with Post-Intensive Care Syndrome in Patients Attending a Hospital in Northern Colombia: A Quantitative and Correlational Study

<b>Background/Objectives:</b> We identified the factors related to post-intensive care syndrome in a sample of patients from northern Colombia. <b>Methods:</b> This study employed a quantitative, observational, descriptive, and correlational approach. A sample of 277 adults was obtained through non-probabilistic convenience sampling, and a characterization form comprising sociodemographic and clinical variables was applied. The Healthy Aging Brain Care Monitor (HABC-M) instrument was also used, which is a clinical tool with a high capacity to detect post-intensive care syndrome (PICS) in surviving intensive care unit (ICU) patients. <b>Results:</b> The final sample consisted of 277 adults, 67.5% male, with university degrees, cohabiting in a marital union, working, from urban areas, and of the Catholic religion. Seventy percent of the sample presented both cardiovascular and neurological alterations and was admitted to the ICU, and 66% had a personal history of arterial hypertension (AHT) and type 2 diabetes mellitus (DM2). Patients had a mean ICU stay of 10.7 days, with a standard deviation of 4 days, and displayed a moderate risk of morbidity and mortality according to Acute Physiology and Chronic Health Evaluation II (APACHE II). A total of 38.6% of the sample received mechanical ventilation, with a mean duration of 8.3 days, and 7.5% underwent tracheostomy. As for sedation, 38.6% were administered fentanyl. In total, 83.4% of the sample presented the syndromes under study, with a predominance of the severe category. The global score of the scale was taken as the dependent variable, and statistical significance (<i>p</i> < 0.05) was found with sociodemographic variables, including origin and religion, and with clinical variables such as receiving pharmacological treatment. <b>Conclusions:</b> The sample presented PICS globally and showed how it affects the different dimensions, showing associations with the sociodemographic and clinical variables of interest.