Application of risk level prevention intervention based on delirium prediction models in ICU patients undergoing mechanical ventilation
Objective To investigate the application value of risk level prevention intervention based on delirium prediction models in ICU patients undergoing mechanical ventilation.Methods A randomized controlled study was conducted on 124 patients with acute respiratory distress syndrome who underwent mechanical ventilation in the ICU at the Marine Police Corps Hospital of Chinese People's Armed Police Force from January 2020 to December 2022.They were divided into an observation group and a control group,with 62 patients in each group,using a random number table method.The control group received routine intervention,while the observation group received risk level prevention intervention based on delirium prediction models.The intervention lasted for 4 weeks.The intervention effects were observed in both groups.Results In the observation group,the duration of mechanical ventilation was(149.97±29.86)hours,the duration of delirium was(2.79±1.03)days,the incidence of delirium was 3.23％(2/62),the length of ICU stay was(7.57±2.14)days,and the mortality rate was 1.61％(1/62).All of these values were significantly shorter or lower than those in the control group[(170.78±34.28)hours,(4.12±0.98)days,33.87％(21/62),(10.21±2.85)days,19.35％(12/62),t=3.60,7.37,x2=19.29,t=5.83,x2=10.40,all P＜0.001].The observation group scored significantly higher than the control group in terms of difficulty in falling asleep,sleep depth,difficulty in returning to sleep,nighttime awakenings,and overall sleep quality(t=-8.48,-4.57,-4.50,-5.26,-5.86,all P＜0.001).After the intervention,the observation group also had significantly higher scores for treatment confidence[(28.75±4.87)points],family care[(7.62±1.13)points],and intervention satisfaction[91.94％(57/62)points]compared with the control group[(28.75±4.87)points,(7.62±1.13)points,77.42％(48/62),t=-7.79,-12.74,x2=5.03,all P＜0.05].Conclusion The risk level prevention intervention based on delirium prediction models helps to reduce the duration of mechanical ventilation,the duration of delirium,and the length of ICU stay.It also controls delirium and mortality rates,improves patients'sleep quality,and enhances treatment confidence,family support,and overall satisfaction with the intervention.
DeliriumModels,organizationalForecastingRisk adjustmentIntensive care unitsRespiration,artificialSleepLength of stayPatient satisfaction
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NSTL
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