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Autonomic dysfunction as a predictor of infection in neurocritical care unit: a prospective cohort study.
- Source :
- Journal of Clinical Monitoring & Computing; Apr2024, Vol. 38 Issue 2, p399-405, 7p
- Publication Year :
- 2024
-
Abstract
- Purpose: Infection in the neurocritical care unit (NCCU) can cause significant mortality and morbidity. Autonomic nervous system plays an important role in defense against infection. Autonomic dysfunction causing inflammatory dysregulation can potentiate infection. We aimed to study the relationship between autonomic dysfunction and occurrence of infection in neurologically ill patients. Methods: Fifty one patients who were on mechanical ventilation were prospectively enrolled in this study. Autonomic dysfunction was measured for three consecutive days on admission to NCCU using Ansiscope. Patients were followed up for seven days to see the occurrence of infection. Infection was defined as per centre of disease control definition. Results: A total of 386 patients were screened for eligibility. 68 patients satisfied the eligibility criteria and 51 patients were finally included in the study. The incidence of infection was 74.5%. The commonest infection was pulmonary infection (38.8%) followed by urinary tract infection (33.3%), blood stream infection(14.8%), central nervous system infection (11.1%) and wound site infection (3.7%). The degree of autonomic dysfunction (AD) percentage was more in infection group (37.7% (25.2–49.7)) compared to non infection group (23.5% (18-33.5)) and maximal on day 3 (P = 0.02). Patients with increasing trend of AD% from day 1 to day 3 had the highest infection rates. The length of NCCU stay (20(10–23) days and mortality (42.1%) was higher in infection group (p < 0.001). Conclusion: AD assessment can be used as a tool to predict development of infection in NCCU. This can help triage and institute early investigation and treatment. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13871307
- Volume :
- 38
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Clinical Monitoring & Computing
- Publication Type :
- Academic Journal
- Accession number :
- 176452573
- Full Text :
- https://doi.org/10.1007/s10877-023-01063-9