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Derivation of a bedside score (MASH-P) to predict 6-month mortality in tuberculous meningitis
Journal of the Neurological Sciences ( IF 3.6 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.jns.2020.116877
Imran Rizvi 1 , Hardeep Singh Malhotra 1 , Ravindra Kumar Garg 1 , Neeraj Kumar 1
Affiliation  

BACKGROUND Tuberculous meningitis is commonly associated with a poor outcome. Simple bedside prognostic scores can help immensely in predicting the outcome. MATERIALS AND METHOD A total of 721 patients, from 5 of our previous studies, were included. With primary outcome measure as death, a prognostic model was derived using binary logistic regression. The model was assessed using discrimination and calibration, and internally validated using the bootstrap method. A bedside prognostic score was derived by rounding of the regression coefficients to the nearest integers. RESULTS A total of 126 (17.48%) patients died. The final model found that higher age, stage III disease, baseline MBI ≤ 12, papilledema and hydrocephalus were significant predictors of death. The final model showed good discrimination as evident by an AUC = 83.1% (95% confidence interval 79.5%-86.7%, P < .001) and good calibration (Hosmer and Lemeshow test P = .579). The model remained valid after internal validation by boot strapping. A simple bedside score with the acronym MASH-P to denote variables baseline MBI (M), age (A), stage (S), hydrocephalus (H) and papilledema (P), was thus derived. The score can range from 0 to 10. Higher the score, higher is the probability of death; a score of 0 carries a predicted probability of just 1.7% while a score of 10 corresponds to a predicted probability of 65%. An electronic ready reckoner has also been developed to aid prognostication on the go. CONCLUSION MASH-P is a simple prognostic scoring model that can be used at bedside and aid in decision making as well as counselling.

中文翻译:

预测结核性脑膜炎 6 个月死亡率的床边评分 (MASH-P) 的推导

背景结核性脑膜炎通常与不良结果相关。简单的床边预后评分可以极大地帮助预测结果。材料和方法 总共包括 721 名患者,来自我们之前的 5 项研究。将主要结果测量为死亡,使用二元逻辑回归推导出预后模型。该模型使用鉴别和校准进行评估,并使用 bootstrap 方法进行内部验证。通过将回归系数四舍五入到最接近的整数,得出床边预后评分。结果共有126例(17.48%)患者死亡。最终模型发现,较高的年龄、III 期疾病、基线 MBI ≤ 12、视乳头水肿和脑积水是死亡的重要预测因素。最终模型显示出良好的区分能力,AUC = 83。1%(95% 置信区间 79.5%-86.7%,P < .001)和良好的校准(Hosmer 和 Lemeshow 检验 P = .579)。通过引导程序进行内部验证后,该模型仍然有效。一个简单的床边评分,用首字母缩写词 MASH-P 来表示变量基线 MBI (M)、年龄 (A)、阶段 (S)、脑积水 (H) 和视乳头水肿 (P)。得分范围为 0 到 10。得分越高,死亡概率越高;0 分的预测概率仅为 1.7%,而 10 分对应的预测概率为 65%。还开发了一种电子就绪推算器,以帮助在旅途中进行预测。结论 MASH-P 是一种简单的预后评分模型,可在床边使用并帮助决策和咨询。579)。通过引导程序进行内部验证后,该模型仍然有效。一个简单的床边评分,用首字母缩写词 MASH-P 来表示变量基线 MBI (M)、年龄 (A)、阶段 (S)、脑积水 (H) 和视乳头水肿 (P)。得分范围为 0 到 10。得分越高,死亡概率越高;0 分的预测概率仅为 1.7%,而 10 分对应的预测概率为 65%。还开发了一种电子就绪推算器,以帮助在旅途中进行预测。结论 MASH-P 是一种简单的预后评分模型,可在床边使用并帮助决策和咨询。579)。通过引导程序进行内部验证后,该模型仍然有效。一个简单的床边评分,用首字母缩写词 MASH-P 来表示变量基线 MBI (M)、年龄 (A)、阶段 (S)、脑积水 (H) 和视乳头水肿 (P)。得分范围为 0 到 10。得分越高,死亡概率越高;0 分的预测概率仅为 1.7%,而 10 分对应的预测概率为 65%。还开发了一种电子就绪推算器,以帮助在旅途中进行预测。结论 MASH-P 是一种简单的预后评分模型,可在床边使用并帮助决策和咨询。脑积水 (H) 和视乳头水肿 (P),由此得出。得分范围为 0 到 10。得分越高,死亡概率越高;0 分的预测概率仅为 1.7%,而 10 分对应的预测概率为 65%。还开发了一种电子就绪推算器,以帮助在旅途中进行预测。结论 MASH-P 是一种简单的预后评分模型,可在床边使用并帮助决策和咨询。脑积水 (H) 和视乳头水肿 (P),由此得出。得分范围为 0 到 10。得分越高,死亡概率越高;0 分的预测概率仅为 1.7%,而 10 分对应的预测概率为 65%。还开发了一种电子就绪推算器,以帮助在旅途中进行预测。结论 MASH-P 是一种简单的预后评分模型,可在床边使用并帮助决策和咨询。
更新日期:2020-08-01
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