Data mining and analysis of unplanned extubation of inpatients with cancer based on association rules
XIANG Hongting
HU Meihua
PENG Siyi
HU Yonghong
SONG Caiyun
LI Xuying
Abstract：Objective:To explore the valuable association rules in unplanned extubation events of inpatients with cancer,and provide reference for the formulation of preventive measures for unplanned extubation.Methods:Data on 300 cases of unplanned extubation events reported from January 2022 to June 2024 at a tertiary Grade Ⅲ,Level A cancer specialty hospital in Changsha City were collected.The Apriori algorithm was utilized for data mining and effectiveness evaluation.Results:A total of 13 pairs of strong association rules were identified.High-risk factors for unplanned extubation events in hospitalized cancer patients include:male gender,age≥60 years,smoking history,surgical history,multiple concurrent catheters,nighttime occurrence,absence of sedation or restraints,nurses on duty with＜5 years of experience,and moderate to high risk of psychological distress,etc.Conclusions:Nursing staff should promptly identify and assess high-risk extubation patients,establish hospital-wide prevention protocols for unplanned extubation of gastric tubes and central venous catheters,implement targeted restraint protocols combined with comfort-oriented sedation,enhance nighttime pain management,strengthen risk awareness among nurses with limited clinical experience,and prioritize psychological interventions for patients at high risk of psychological distress.
Keywords：tumor patientsunplanned extubationassociation rulesdata mining
Publication Date：2025-04-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 1513-1516 )