Background: Subsyndromal delirium (SSD) is a clinical manifestation between delirium and nondelirium. There is no established guideline for diagnosing SSD, with a few different tools used for diagnosis.
Objectives: To construct and verify the risk prediction model for subdelirium syndrome in patients with advanced malignant tumors and explore its application value in risk prediction.
Methods: A total of 455 patients admitted to the Oncology Department in a tertiary grade A hospital in Hengyang City were recruited from December 2020 to May 2021. They were selected as the modeling group. The model was constructed by logistic regression. A total of 195 patients with advanced malignant tumors from June 2021 to July 2021 were selected to validate the developed model.
Results: The predictors incorporated into the model were opioids (odds ratio [OR], 1.818), sleep disorders (OR, 1.783), daily living ability score (OR, 0.969), and pain (OR, 1.810). In the modeling group, the Hosmer-Lemeshow goodness-of-fit test was P = .113, the area under the receiver operating characteristic curve was 0.884, the sensitivity was 0.820, and the specificity was 0.893. In the validation group, the Hosmer-Lemeshow goodness-of-fit test P = .108, the area under the receiver operating characteristic curve was 0.843, the Yuden index was 0.670, the sensitivity was 0.804, and the specificity was 0.866.
Conclusions: This model has excellent precision in the risk prediction of subdelirium in patients with advanced malignant tumors.
Implications for practice: The model we developed has a guiding significance for specialized tumor nurses to care for patients with advanced malignant tumors and improve their quality of life.
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