A system for evaluating treatment efficacy and outcome prediction for senile patients with respiratory failure undergoing mechanical ventilation
- VernacularTitle:老年呼吸衰竭机械通气患者预后评估系统的建立与评价
- Author:
Dandan LIN
;
Dewei GAO
;
Senyang YU
- Publication Type:Journal Article
- Keywords:
respiratory insufficiency;
respiration, artificial;
prognostic system
- From:
Medical Journal of Chinese People's Liberation Army
1981;0(04):-
- CountryChina
- Language:Chinese
-
Abstract:
Objective On the basis of the Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ), to establish and appraise a new prognostic evaluation system for elder patients with respiratory failure undergoing mechanical ventilation in order to predict hospital mortality in the respiratory intensive care unit. Methods Two hundred and thirty-eight senile patients with respiratory failure having had mechanical ventilation during their hospitalization were retrospectively analyzed. Patients were randomly divided into 2 groups: model group (n=138) and validation group (n=100). Data of model group were analyzed by monofactorial and multifactorial regression analysis to screen the risk factors. Risk factors were given numerical values according to different grades, and complementary scoring system was then established. APACHE Ⅱ system was combined with complementary scoring system with Logistic multiple regression to form SRFMV system, a special evaluation system for the senile patients with respiratory failure undergoing mechanical ventilation. One hundred patients from validation group were evaluated by both SRFMV system and APACHE Ⅱ system, and the results were then compared to assess the validity and reliability of SRFMV system. Oxygenation index, positive end expiratory pressure (PEEP), tidal volume, phlegm quantity and character, and pulmonary auscultation were selected to serve as standard for complementary scoring system. Mortality equation was set up with logistic multiple regression analysis. Results The predication sensitivity and specificity evaluated by SRFMV system in validation group (0.878 and 0.821, respectively) outstripped that evaluated by APACHE Ⅱsystem (0.818 and 0.771, respectively); the area under ROC curve in SRFMV system and the X2 value in Lemesshow-Hosmer statistic (0.911 and 13.77, respectively) also outstripped that in APACHE Ⅱsystem (0.860 and 11.808, respectively). Conclusions SRFMV system is of better sensitivity and specificity, in which the prediction of mortality is closely consistent with the reality. SRFMV system can be applied to obtain valid predictions of relevant outcomes in senile patients with respiratory failure underwent mechanical ventilation.
