The Effect of Sedation Protocol Using Richmond Agitation-Sedation Scale (RASS) on Some Clinical Outcomes of Mechanically Ventilated Patients in Intensive Care Units: a Randomized Clinical Trial.
Zahra TaranMasoumeh NamadianSoghrat FaghihzadehTaraneh NaghibiPublished in: Journal of caring sciences (2019)
Introduction: Providing for patients' comfort and reducing their pain is one of the important tasks of health care professionals in the Intensive Care Unit (ICU). The current study was conducted to determine the effect of a protocol using a Richmond Agitation-Sedation Scale (RASS) on some clinical outcomes of patients under mechanical ventilation (MV) in 2017. Methods: This single-blind clinical trial was conducted on 79 traumatic patients in the ICU who were randomly allocated into the intervention (N=40) and the control groups (N=39). The sedation was achieved, using a sedation protocol in the intervention group and the routine care in the control group. The clinical outcomes of the patients (duration of MV, length of staying in ICU, final outcome) were measured. As the participants had different lengths of MV and staying in ICU, the data were restructured, and were analyzed, using proper statistical methods. Results: The patients' level of sedation in the intervention group was significantly closer to the ideal score of RASS (-1 to +1). The duration of MV was significantly reduced in the intervention group, and the length of stay in the ICU was also significantly shorter. There was no difference in terms of final outcome. The ICU cost in the control group was twice as high as the cost in of the intervention group. Conclusion: The applied sedation protocol in this study would provide better sedation and could consequently lead to significantly better clinical outcomes, and the cost of caring as a result.
Keyphrases
- mechanical ventilation
- intensive care unit
- end stage renal disease
- randomized controlled trial
- newly diagnosed
- ejection fraction
- clinical trial
- healthcare
- chronic kidney disease
- acute respiratory distress syndrome
- prognostic factors
- chronic pain
- peritoneal dialysis
- machine learning
- spinal cord
- patient reported
- study protocol
- big data