监护室重症肺炎预后影响因素分析

Analysis of Prognostic Factors for Severe Pneumonia in Multiple Intensive Care Units

摘要: 目的：探讨重症肺炎患者预后不良的独立影响因素，为临床制定干预措施提供参考依据。方法：回顾性选取2023年5月1日至2025年5月1日在本院重症监护室、呼吸监护室和急诊监护室接受治疗的139例重症肺炎患者为研究对象，根据患者的临床预后结局分为预后良好组(n = 41)和预后不良组(n = 98)。比较两组患者的临床相关资料、呼吸道病原菌、监护室化验指标极值等，通过单因素及多因素Logistic回归分析筛选监护室重症肺炎患者预后影响因素；受试者工作特征曲线(ROC曲线)分析影响因素的预测效能。结果：与预后良好组对比，预后不良组的监护室住院时间、机械通气、血管置管、镇静镇痛、病原菌分型、铜绿假单胞菌感染、白细胞max、中性粒细胞计数max、淋巴细胞计数min、血小板计数min、降钙素原max、降钙素原min、D-二聚体max，差异均有统计学(P < 0.05)。多因素Logistic回归分析显示，机械通气(OR = 3.542, 95%CI = 1.295~9.688, P = 0.014)和血管置管(OR = 3.068, 95%CI = 1.127~8.347, P = 0.028)是监护室重症肺炎患者预后不良的独立危险因素；铜绿假单胞菌(OR = 0.289, 95%CI = 0.094~0.889, P = 0.030)和血小板计数min (OR = 0.995, 95%CI = 0.990~1.000, P = 0.041)是预后的独立保护因素。ROC曲线显示，血管置管单独预测监护室重症肺炎患者预后不良的曲线下面积(AUC)最大(0.710)，机械通气的敏感度最高(87.80%)，血小板计数min的特异度最高(78.00%)；联合预测的AUC为0.802，敏感度为77.60%，特异度为73.20%。结论：在本研究队列中，需要机械通气、血管置管的监护室重症肺炎患者预后不良风险更高，铜绿假单胞菌感染及维持较高水平的血小板计数为预后保护因素，临床可通过严格把握机械通气指征、血管置管侵入操作、依据药敏结果精准抗感染、动态监测并维持血小板水平，制定个体化干预方案以改善患者预后。

Abstract: Objective: To investigate the independent influencing factors of poor prognosis in patients with severe pneumonia, and to provide references for formulating clinical intervention strategies. Methods: A total of 139 patients with severe pneumonia who received treatment in the ICU, RICU, and EICU of our hospital from May 1, 2023 to May 1, 2025 were retrospectively enrolled. According to clinical prognostic outcomes, patients were divided into the favorable prognosis group (n = 41) and the poor prognosis group (n = 98). Clinical data, respiratory pathogens, and extreme values of laboratory indicators during stay in multiple intensive care units were compared between the two groups. Univariate and multivariate Logistic regression analyses were performed to identify prognostic factors for severe pneumonia in patients from multiple intensive care units, and ROC curve was used to evaluate the predictive efficacy of these factors. Results: Compared with the favorable prognosis group, the poor prognosis group showed statistically significant differences in length of stay in multiple intensive care units, mechanical ventilation, vascular catheterization, sedation and analgesia, pathogen typing, Pseudomonas aeruginosa infection, maximum WBC, maximum NEU, minimum LYM, minimum PLT, maximum PCT, minimum PCT, and maximum D-dimer (P < 0.05). Multivariate Logistic regression analysis revealed that mechanical ventilation (OR = 3.542, 95%CI = 1.295~9.688, P = 0.014) and vascular catheterization (OR = 3.068, 95%CI = 1.127~8.347, P = 0.028) were independent risk factors for poor prognosis. In contrast, infection with susceptible strains of Pseudomonas aeruginosa (OR = 0.289, 95%CI = 0.094~0.889, P = 0.030) and minimum PLT (OR = 0.995, 95%CI = 0.990~1.000, P = 0.041) were independent protective factors. ROC curve analysis showed that vascular catheterization had the largest area under the curve (AUC = 0.710) for predicting poor prognosis alone, mechanical ventilation had the highest sensitivity (87.80%), and minimum PLT had the highest specificity (78.00%). The combined prediction model yielded an AUC of 0.802, with a sensitivity of 77.60% and a specificity of 73.20%. Conclusion: In this cohort, patients with severe pneumonia in multiple intensive care units requiring mechanical ventilation or vascular catheterization were at higher risk of poor prognosis. Infection with Pseudomonas aeruginosa and maintenance of a relatively high PLT were protective for prognosis. Clinically, individualized interventions can be developed to improve patient outcomes by strictly adhering to mechanical ventilation indications, standardizing invasive procedures such as vascular catheterization, implementing targeted anti-infection therapy based on drug sensitivity results, and dynamically monitoring and maintaining platelet levels.