Background Delirium is a common complication in intensive care unit, which can increase the mortality and affect the prognosis. Prevention and control are more important than treatment. However, there is no assessment or early intervention to screen medium high risk and sub comprehensive delirium by joint optimization of risk stratification model at home and abroad.
Objective To explore the effect of delirium management mode based on E-PRE-DELIRIC early risk stratification model on the incidence of delirium in intensive care unit (ICU), and verify the effectiveness of the risk prediction model.
Methods Taking the patients admitted to the ICU ward of Changzhou Fourth People's Hospital from June 2019 to December 2021 as the research objects, the intervention group adopted the delirium management and control mode based on the early risk stratification model, the multi-index risk prediction model based on logistic regression was established and its prediction performance was evaluated by ROC analysis. The control group performed the conventional delirium management mode. The incidence of delirium, duration of delirium, pain score, length of stay in ICU and incidence of adverse drug reactions were compared between the two groups.
Results A total of 212 patients were included, 107 cases were in the intervention group and 105 cases in the control group. There was no significant difference between the two groups in terms of age, gender, history of cognitive impairment, history of alcoholism, past medical history, emergency admission, admission APACHE II score, BUN and MAP, glucocorticoid use rate and major combined diseases (P>0.05). Compared with the control group, the incidence of delirium in the clinical pharmacist intervention group was significantly lower (8.41% 9/98 vs 26.67% 28/77, P<0.01), the pain score was lower (0, 0 vs 0, 0.5, P<0.01), the length of stay in ICU was shorter (10.21 ± 8.21 d vs 13.32 ± 9.74 d, P<0.05), and the incidence of adverse drug reactions was significantly lower (3.74% 4/103 vs 11.43% 12/93, P<0.05). The risk prediction model based on the sample of this study was Log(P/1-P)(Joint virtual indicator / probability)=-1.317 + 0.018 × Age + 0.712 × History of cognitive impairment + 0.215 × History of alcoholism + 0.592 × Treatment experience + 0.008 × MAP value when entering ICU + 0.416 × Respiratory failure + 0.011 × BUN value when entering ICU. According to ROC analysis, the combined application of these seven indicators had high prediction efficiency for the risk of delirium in ICU patients, with ROC-AUC (95%CI), sensitivity, specificity and accuracy of 0.882 (0.834-0.931), 0.892, 0.869 and 0.873, respectively.
Conclusion Delirium management model based on early risk prediction hierarchical model can reduce the incidence of delirium in ICU patients and adverse drug reactions, and shorten the length of stay in ICU.
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