ABSTRACT
Background: Critically ill patients are frequently transported to various locations within the hospital for diagnostic and therapeutic purposes, which increases the risk of adverse events (AEs). This multicenter prospective observational study was undertaken to determine the incidence of AEs related to intrahospital transport, their severity, and their effects on patient outcomes. Patients and methods: We included consecutive unstable critically ill patients requiring intrahospital transport, across 15 Indian tertiary care centers over 5 months (October 11, 2022-February 20, 2023). Apart from the demographics and severity of illness, data related to transport itself, such as indications and destination, incidence of AEs, their category and treatment required, and patient outcomes, were recorded in a standard form. Results: Eight hundred and ninety-three patients were transported on 1065 occasions out of the intensive care unit (ICU). The mean (SD) acute physiology and chronic health evaluation II score of the patients was 15.38 (±7.35). One hundred and two AEs occurred, wherein cardiovascular instability was the most common occurrence (31, 30.4%). Two patients had cardiac arrest immediately after transport. Acute physiology and chronic health evaluation II [odds ratio (OR): 1.02, 95% confidence interval (CI) - 1.00-1.05, p = 0.04], emergent transport (OR: 5.11, 95% CI - 3.32-7.88, p = 0.00), and team composition (OR: 5.34, 95% CI - 1.63-17.5, p = 0.00) during transport were found to be independent predictors of AEs. Conclusion: We found a high incidence of AEs during intrahospital transport of critically ill patients. These events were more common during emergent transports and when the patients were transported by doctors. Transport by itself was not related to ICU mortality. We feel that stabilization of the patients before transport and adherence to a standardized protocol may help in minimizing the AEs, thereby enhancing patient safety. How to cite this article: Zirpe KG, Tiwari AM, Kulkarni AP, Govil D, Dixit SB, Munjal M, et al. Adverse Events during Intrahospital Transport of Critically Ill Patients: A Multicenter, Prospective, Observational Study (I-TOUCH Study). Indian J Crit Care Med 2023;27(9):635-641.
ABSTRACT
Background and objectives A fluid responder is a patient who can increase his stroke volume/ cardiac output by more than 10%-15% after a fluid bolus. Left ventricular outflow tract (LVOT) velocity time integral (VTI) variability is widely used as an adynamic parameter of fluid responsiveness, but a transthoracic echo view of LVOT VTI is often time-consuming and, at times, difficult to achieve. So, in the quest for another parameter that might equally be a good surrogate marker of stroke volume variation, carotid peak systolic velocity (CPSV) variation has been studied. The objective was to assess CPSV variation in patients who are already fluid responders. Methods The sample size was calculated considering a minimum correlation coefficient of 0.5. Adult patients in whom the physician wanted to give a fluid bolus and whose average LVOT VTI was more than 15% over 3 respiratory cycles were included in the study. Demographic variables, along with hemodynamic parameters such as heart rate, blood pressure, the need for vasopressors, mode of breathing (spontaneous or mechanical ventilation), and CPSV variation,were noted and averaged over three respiratory cycles. Fluid bolus (Plasmalyte) 6 ml/kg bolus over 10-15 minutes. Post-fluid hemodynamic variables, along with averaged LVOT VTI over three respiratory cycles and averaged CPSV variation over three respiratory cycles, are noted. Results Thirty adult patients were evaluated in the study. In spontaneously breathing patients (n=12), the average CPSV variation expressed as mean + standard deviation before and after fluid administration of 6ml/kg of ideal body weight was 14.1 ± 3.4 and 5.4 ± 2.6, respectively (p < 0.05). In mechanically ventilated patients (n=18), the average CPSV variation expressed as mean + standard deviation before and after fluid administration of 6ml/kg of ideal body weight fluid was 15 ± 5.3 and 6.5 ± 3.1, respectively (p <0.005). Overall, there was a statistically significant positive correlation between LVOT VTI variation and CPSV variation before fluid therapy (correlation coefficient 0.56 and p-value 0.001) and a statistically significant moderate positive correlation post-fluid therapy (correlation coefficient 0.37 and p-value 0.043). Conclusion We found a significant decrease in CPSV variation post-fluid administration in patients who are fluid responders, which mimics a decrease in stroke volume variation after fluid administration in patients who are fluid responsive.
