Derivation of a bedside score (MASH-P) to predict 6-month mortality in tuberculous meningitis

被引:6
|
作者
Rizvi, Imran [1 ]
Malhotra, Hardeep Singh [1 ]
Garg, Ravindra Kumar [1 ]
Kumar, Neeraj [1 ]
机构
[1] King Georges Med Univ, Dept Neurol, Lucknow 226003, Uttar Pradesh, India
关键词
Tuberculous meningitis; Outcome; Prognosis; Prognostic model; Bedside score; Nomogram; PROGNOSTIC-FACTORS; ADULTS;
D O I
10.1016/j.jns.2020.116877
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
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.
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页数:9
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共 46 条
  • [1] Tuberculous meningitis: is a 6-month treatment regimen sufficient?
    van Loenhout-Rooyackers, JH
    Keyser, A
    Laheij, RJF
    Verbeek, ALM
    van der Meer, JWM
    [J]. INTERNATIONAL JOURNAL OF TUBERCULOSIS AND LUNG DISEASE, 2001, 5 (11) : 1028 - 1035
  • [2] Derivation and Validation of a Prognostic Model to Predict 6-Month Mortality in an Intensive Care Unit Population
    Hadique, Sarah
    Culp, Stacey
    Sangani, Rahul G.
    Chapman, Kyle D.
    Khan, Saad
    Parker, John E.
    Moss, Alvin H.
    [J]. ANNALS OF THE AMERICAN THORACIC SOCIETY, 2017, 14 (10) : 1556 - 1561
  • [3] Validated Risk Score for Predicting 6-Month Mortality in Infective Endocarditis
    Park, Lawrence P.
    Chu, Vivian H.
    Peterson, Gail
    Skoutelis, Athanasios
    Lejko-Zupa, Tatjana
    Bouza, Emilio
    Tattevin, Pierre
    Habib, Gilbert
    Tan, Ren
    Gonzalez, Javier
    Altclas, Javier
    Edathodu, Jameela
    Fortes, Claudio Querido
    Siciliano, Rinaldo Focaccia
    Pachirat, Orathai
    Kanj, Souha
    Wang, Andrew
    Fica, Alberto
    Mella, Rodrigo Montagna
    [J]. JOURNAL OF THE AMERICAN HEART ASSOCIATION, 2016, 5 (04):
  • [4] EFFICACY OF THE "SURPRISE" QUESTION TO PREDICT 6-MONTH MORTALITY IN ICU PATIENTS
    Khan, Saad
    Hadique, Sarah
    Culp, Stacey
    Syed, Asma
    Hodder, Corbin
    Parker, John
    Moss, Alvin
    [J]. CRITICAL CARE MEDICINE, 2014, 42 (12)
  • [5] Predicting 6-Month Mortality in COPD: Assessment of Prognostic Variables to Predict COPD Mortality
    Lim, K. G.
    Du, X.
    Braun, C. M.
    Schulte, P.
    Latuche, L.
    [J]. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2020, 201
  • [6] Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer
    Parikh, Ravi B.
    Manz, Christopher
    Chivers, Corey
    Regli, Susan Harkness
    Braun, Jennifer
    Draugelis, Michael E.
    Schuchter, Lynn M.
    Shulman, Lawrence N.
    Navathe, Amol S.
    Patel, Mitesh S.
    O'Connor, Nina R.
    [J]. JAMA NETWORK OPEN, 2019, 2 (10) : E1915997
  • [7] MARSHALL CLASSIFICATION VERSUS THE ROTTERDAM SCORE IN PREDICTING 6-MONTH MORTALITY IN SEVERE TBI
    Papa, Linda
    Schmalfuss, Ilona
    Gabrielli, Andrea
    Heaton, Shelley
    Hannay, H. Julia
    Hayes, Ronald
    Wang, Kevin K. W.
    Brophy, Gretchen M.
    Robertson, Claudia
    Robicsek, Steven
    [J]. JOURNAL OF NEUROTRAUMA, 2012, 29 (10) : A191 - A192
  • [8] Predicting 6-Month Mortality in Incident Elderly Dialysis Patients: A Simple Prognostic Score
    Santos, Josefina
    Oliveira, Pedro
    Malheiro, Jorge
    Campos, Andreia
    Correia, Sofia
    Cabrita, Antonio
    Lobato, Luisa
    Fonseca, Isabel
    [J]. KIDNEY & BLOOD PRESSURE RESEARCH, 2020, 45 (01): : 38 - 50
  • [9] Stacking ensemble learning model to predict 6-month mortality in ischemic stroke patients
    Lee Hwangbo
    Yoon Jung Kang
    Hoon Kwon
    Jae Il Lee
    Han-Jin Cho
    Jun-Kyeung Ko
    Sang Min Sung
    Tae Hong Lee
    [J]. Scientific Reports, 12 (1)
  • [10] Prediction of 6-month mortality in nursing home residents with advanced dementia: Validity of a risk score
    van der Steen, Jenny T.
    Mitchell, Susan L.
    Frijters, Dinnus H. M.
    Kruse, Robin L.
    Ribbe, Miel W.
    [J]. JOURNAL OF THE AMERICAN MEDICAL DIRECTORS ASSOCIATION, 2007, 8 (07) : 464 - 468