Predictors and outcome of invasive mechanical ventilation in hospitalized patients with sepsis: data from National Inpatient Sample.
Rashmi DhitalSijan BasnetDilli Ram PoudelPublished in: Journal of community hospital internal medicine perspectives (2018)
Background: Sepsis is a significant cause of mechanical ventilation in hospitalized patients. Objective: The aim of our study was to recognize the demographic and clinical characteristics associated with an increased need for invasive mechanical ventilation in hospitalized sepsis patients. Methods: We used National Inpatient Sample database from the years 2009-2011 to identify sepsis patients requiring invasive mechanical ventilation. We compared demographic and clinical characteristics of sepsis patients requiring and not requiring ventilator support and conducted univariate and multivariate analyses to determine odds ratio (OR) of association. Results: A total of 4,827,769 sepsis patients were identified among which 21.38% required invasive ventilation. Multivariate logistic regression [OR (95% CI), p<0.001] determined the following to be associated with increased odds of ventilator use: morbid obesity [1.37 (1.31-1.42)] and age group 35-64 years [1.18 (1.14-1.22)] compared to 18-34 years, whereas females [0.90 (0.88-0.91)] and age >85 years [0.49 (0.47-0.52)] had reduced odds of invasive ventilation. Hyperkalemia [1.12 (1.09-1.16)] and hypernatremia [2.26 (2.16-2.36)] were associated with increased odds while hypokalemia [0.94 (0.91-0.97)] had reduced odds of invasive ventilation. Septic patients requiring IMV had higher length of stay by 9.72 ± 0.17 days, hospitalization cost by US $ 43010.31 ± 988.24 and in-hospital mortality (41.33% vs 8.91%). Conclusion: Sepsis is a major cause of intensive care unit admission and initiation of invasive ventilation. Baseline demographic and clinical features affect the need for invasive ventilation. A clear understanding of these risk factors is integral for an appropriate and timely management.
Keyphrases
- mechanical ventilation
- intensive care unit
- acute respiratory distress syndrome
- end stage renal disease
- ejection fraction
- respiratory failure
- acute kidney injury
- newly diagnosed
- risk factors
- type diabetes
- emergency department
- peritoneal dialysis
- adipose tissue
- patient reported outcomes
- body mass index
- machine learning
- weight loss
- obese patients
- artificial intelligence