Building prognostic models for adverse outcomes in a prospective cohort of hospitalised patients with acute leptospirosis infection in the Philippines
Building prognostic models for adverse outcomes in a prospective cohort of hospitalised patients with acute leptospirosis infection in the Philippines
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DOI：
10.1093/trstmh/try015
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发表时间：
2017-12-01
影响因子：
2.2
通讯作者：
Parry, Christopher M.
中科院分区：
文献类型：
--
作者：
Lee, Nathaniel;Kitashoji, Emi;Parry, Christopher M.
钩端螺旋体病是菲律宾的地方病。10%的病例将发展成严重或致命的疾病。很难预测进展的严重程度。风险因素已经提出，但很少有人尝试建立预测模型来指导临床决策。我们提出了两个模型来预测死亡率和进展为严重疾病的风险。数据来自2011年至2013年在马尼拉San Lazaro医院进行的前瞻性队列研究。从文献综述中确定了预测因素。利用向后逐步消除和多元分数多项式的策略确定了关键的预测因素。共有203例患者符合入选标准。总死亡率为6.84%。多变量logistic回归分析显示，中性粒细胞计数[OR 1.38，95%CI 1.15-1.67]和血小板计数[OR 0.99，95%CI 0.97-0.99]可预测死亡风险。多变量logistic回归显示，男性（OR 3.29，95% CI 1.22-12.57）和症状发作与抗生素使用之间的天数（OR 1.28，95% CI 1.08-1.53）可预测进展为重度疾病的风险。死亡率和进展为严重疾病的风险的多变量预后模型可能是有用的，通过早期识别患者的不良结局的风险，指导临床管理。
Leptospirosis is endemic to the Philippines. Ten per cent of cases will develop severe or fatal disease. Predicting progression to severity is difficult. Risk factors have been suggested, but few attempts have been made to create predictive models to guide clinical decisions. We present two models to predict the risk of mortality and progression to severe disease. Data was used from a prospective cohort study conducted between 2011 and 2013 in San Lazaro Hospital, Manila. Predictive factors were identified from a literature review. A strategy utilizing backwards stepwise-elimination and multivariate fractional polynomials identified key predictive factors. A total of 203 patients met the inclusion criteria. The overall mortality rate was 6.84%. Multivariable logistic regression revealed that neutrophil counts [OR 1.38, 95% CI 1.15-1.67] and platelet counts [OR 0.99, 95% CI 0.97-0.99] were predictive for risk of mortality. Multivariable logistic regression revealed that male sex (OR 3.29, 95% CI 1.22-12.57) and number of days between symptom onset and antibiotic use (OR 1.28, 95% CI 1.08-1.53) were predictive for risk of progression to severe disease. The multivariable prognostic models for the risks of mortality and progression to severe disease developed could be useful in guiding clinical management by the early identification of patients at risk of adverse outcomes.