Vallot F, Paesmans M, Berghmans T, Sculier J P
Department of Medicine and Data Centre (Biostatistics Unit), Institut Jules Bordet, Centre des Tumeurs de l'Université Libre de Bruxelles, Bruxelles, Belgium.
Support Care Cancer. 2003 Apr;11(4):236-41. doi: 10.1007/s00520-002-0436-2. Epub 2003 Jan 22.
To determine prognostic factors predicting success of invasive mechanical ventilation in medical cancer patients admitted to ICU for a complication, in terms of extubation and ICU and hospital discharges.
Retrospective study
Medical ICU of an European cancer hospital.
A total of 168 consecutive cancer patients who were admitted to ICU for an acute medical complication requiring immediate mechanical ventilation or who later needed mechanical ventilation.
Variables related to the demographic, cancer, scores and complication characteristics. Extubation rates, ICU and hospital mortalities and duration of survival were measured.
Respectively, 26%, 22% and 17% of the patients were extubated, discharged from the ICU and discharged from hospital. For weaning from mechanical ventilation, a higher APACHE II score and leucopenia were poor prognostic factors in univariate analysis, but leucopenia remained the only significant one in multivariate analysis. For ICU mortality, no significant prognostic feature was identified. For hospital mortality, leucopenia was the only significant factor in univariate as well as in multivariate analyses.
Leucopenia appeared to be the only independent poor prognostic factor for both extubation and hospital discharge. None of the variables related to the cancer disease process was shown to be a predictor of success.
就拔管、重症监护病房(ICU)出院及医院出院情况而言,确定入住ICU治疗并发症的癌症患者有创机械通气成功的预后因素。
回顾性研究
一家欧洲癌症医院的内科重症监护病房
共有168例连续入住ICU的癌症患者,这些患者因急性内科并发症需要立即进行机械通气,或后来需要机械通气。
与人口统计学、癌症、评分及并发症特征相关的变量。测量拔管率、ICU及医院死亡率和生存时间。
分别有26%、22%和17%的患者成功拔管、从ICU出院及从医院出院。对于机械通气撤机,在单因素分析中,较高的急性生理与慢性健康状况评分系统(APACHE II)评分和白细胞减少是不良预后因素,但在多因素分析中,白细胞减少仍然是唯一显著的因素。对于ICU死亡率,未发现显著的预后特征。对于医院死亡率,白细胞减少在单因素及多因素分析中均是唯一显著因素。
白细胞减少似乎是拔管和医院出院唯一独立的不良预后因素。未发现与癌症疾病进程相关的变量是成功的预测因素。