Background: This study evaluates the characteristics and outcome of patients admitted to the ICU following bariatric surgery.
Methods: Descriptive study. A review of a prospectively collected database of our bariatric surgery procedures from 2003 until 2006 was performed. The study was performed in a tertiary level, mixed medical and surgical, adult ICU of a large referral hospital.
Results: Of the 265 patients undergoing bariatric surgery (mainly gastroplasties and Roux-en-Y gastric bypasses), 22 (8%) were admitted to the ICU, of which 14 (64%) were on an elective basis and eight (36%) emergently. Hospital length of stay (LOS) for all patients was 4.5 days and ICU LOS was 12 days. Most elective admissions were standard procedure because of obstructive sleep apnea (OSA) or super obesity, with a median ICU stay of 1 day. Emergent admissions were mainly done after emergent surgery due to surgical complications and had a median ICU stay of 8 days. Only two patients needed intensive care for more than 3 days. There were no deaths during ICU stay.
Conclusions: The ICU admission rate in our report is 8%. This study showed that 32 ICU days are needed per 100 diverse bariatric procedures. Most patients are admitted to the ICU for only a few days and the majority of the admissions is planned.
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http://dx.doi.org/10.1007/s11695-008-9699-0 | DOI Listing |
PLoS One
January 2025
General Directorate of Infection Prevention & Control, Ministry of Health-Saudi Arabia, Riyadh, Saudi Arabia.
Background: Candida auris (C. auris) is an emerging fungus pathogen associated with nosocomial infections that is seen as a serious global health issue.
Aim: To describe the epidemiology and features of hospital-acquired Candida auris outbreaks in the Ministry of Health hospitals (MOH).
Acta Anaesthesiol Scand
February 2025
Department of Anesthesiology and Intensive Care, Kolding Hospital, Denmark.
Aim: To describe the use of invasive mechanical ventilation core strategies, adjuvant treatments and the occurrence of barotrauma and prolonged ventilation in ICU patients with COVID-19 in Denmark, retrospectively.
Methods: All ICUs admitting COVID-19 patients in Denmark from 10 March 2020 to 2 April 2021 were invited to participate. All patients with COVID-19 who received invasive mechanical ventilation were included and data was retrospectively collected from electronic patient records.
Pharmacotherapy
January 2025
Department of Clinical and Administrative Pharmacy, University of Georgia College of Pharmacy, Athens, Georgia, USA.
Background: Fluid overload (FO) in the intensive care unit (ICU) is common, serious, and may be preventable. Intravenous medications (including administered volume) are a primary cause for FO but are challenging to evaluate as a FO predictor given the high frequency and time-dependency of their use and other factors affecting FO. We sought to employ unsupervised machine learning methods to uncover medication administration patterns correlating with FO.
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December 2024
Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC.
Background: Medical mistrust may worsen communication between ICU surrogate decision-makers and intensivists. The prevalence of and risk factors for medical mistrust among surrogate decision-makers are not known.
Research Question: What are the potential sociodemographic risk factors for high medical mistrust among surrogate decision-makers of critically ill patients at high risk of death?
Study Design And Methods: In this pilot cross-sectional study conducted at a single academic medical center between August 2022 and August 2023, adult patients admitted to the medical ICU and their surrogate decision-makers were enrolled.
Health Inf Sci Syst
December 2025
Department of Cardiac, Thoracic and Vascular Surgery, National University Hospital, Singapore, Singapore.
Purpose: Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk monitoring systems, existing systems do not address uncertainties in risk assessments. We developed a novel framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring.
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