
pmid: 32423339
ObjectiveTo examine the effect of including obesity with parameters of the I‐TRACH scale in predicting the need for prolonged mechanical ventilation.Study DesignA retrospective cohort study.SettingTertiary care academic medical center.Subjects and MethodsConsecutive patients were identified retrospectively over a 45‐month period based on need for mechanical ventilation in the medical intensive care unit. Chart review was performed to collect demographic information as well as clinical data, including duration of mechanical ventilation, body mass index (BMI), and I‐TRACH parameters (heart rate >110, serum urea nitrogen >25, serum pH <7.25, serum creatinine >2, serum bicarbonate <20). Statistical analysis was performed to identify any predictors of prolonged mechanical ventilation, defined as ≥14 days and as ≥10 days.ResultsIn total, 455 patients were identified, with an average duration of mechanical ventilation of 10.4 days (range, 0‐248 days). On univariate and multivariate regression analysis, only BMI >30 reached statistical significance with respect to prolonged mechanical ventilation (P <. 05). The I‐TRACH parameters—either alone or in combination—were not significantly predictive.ConclusionThis study challenges previous findings regarding the I‐TRACH scale and the relation of its parameters to prolonged mechanical ventilation. Furthermore, BMI >30 alone was predictive of prolonged intubation. Inclusion of BMI in predictive models could assist current decision making in determining the likelihood of prolonged mechanical ventilation in medical intensive care unit patients going forward, and obesity should be considered a predictor of prolonged mechanical ventilation.
Analysis of Variance, Time Factors, Respiration, Artificial, Severity of Illness Index, Intensive Care Units, ROC Curve, Risk Factors, Humans, Regression Analysis, Obesity, Retrospective Studies
Analysis of Variance, Time Factors, Respiration, Artificial, Severity of Illness Index, Intensive Care Units, ROC Curve, Risk Factors, Humans, Regression Analysis, Obesity, Retrospective Studies
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