IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0162797.html
   My bibliography  Save this article

A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis

Author

Listed:
  • Helder Novais Bastos
  • Nuno S Osório
  • António Gil Castro
  • Angélica Ramos
  • Teresa Carvalho
  • Leonor Meira
  • David Araújo
  • Leonor Almeida
  • Rita Boaventura
  • Patrícia Fragata
  • Catarina Chaves
  • Patrício Costa
  • Miguel Portela
  • Ivo Ferreira
  • Sara Pinto Magalhães
  • Fernando Rodrigues
  • Rui Sarmento-Castro
  • Raquel Duarte
  • João Tiago Guimarães
  • Margarida Saraiva

Abstract

Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8–7.9), age ≥50 years (OR 2.9, 95% CI 1.7–4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4–4.4), ≥1 significant comorbidity—HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease–(OR 2.3, 95% CI 1.3–3.8), and hemoglobin

Suggested Citation

  • Helder Novais Bastos & Nuno S Osório & António Gil Castro & Angélica Ramos & Teresa Carvalho & Leonor Meira & David Araújo & Leonor Almeida & Rita Boaventura & Patrícia Fragata & Catarina Chaves & Pat, 2016. "A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-14, September.
    • Handle: RePEc:plo:pone00:0162797
    DOI: 10.1371/journal.pone.0162797
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0162797
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0162797&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0162797?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Walter Bouwmeester & Nicolaas P A Zuithoff & Susan Mallett & Mirjam I Geerlings & Yvonne Vergouwe & Ewout W Steyerberg & Douglas G Altman & Karel G M Moons, 2012. "Reporting and Methods in Clinical Prediction Research: A Systematic Review," PLOS Medicine, Public Library of Science, vol. 9(5), pages 1-13, May.
    2. Karel G M Moons & Joris A H de Groot & Walter Bouwmeester & Yvonne Vergouwe & Susan Mallett & Douglas G Altman & Johannes B Reitsma & Gary S Collins, 2014. "Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist," PLOS Medicine, Public Library of Science, vol. 11(10), pages 1-12, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Santiago Ferrière-Steinert & Joaquín Valenzuela Jiménez & Sebastián Heskia Araya & Thomas Kouyoumdjian & José Ramos-Rojas & Abraham I J Gajardo, 2024. "Early high-sensitivity troponin elevation in predicting short-term mortality in sepsis: A protocol for a systematic review with meta-analysis," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-10, October.
    2. Ben Van Calster & Andrew J. Vickers, 2015. "Calibration of Risk Prediction Models," Medical Decision Making, , vol. 35(2), pages 162-169, February.
    3. Jiaxin Li & Zijun Zhou & Jianyu Dong & Ying Fu & Yuan Li & Ze Luan & Xin Peng, 2021. "Predicting breast cancer 5-year survival using machine learning: A systematic review," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-23, April.
    4. Thomas P A Debray & Karel G M Moons & Ghada Mohammed Abdallah Abo-Zaid & Hendrik Koffijberg & Richard David Riley, 2013. "Individual Participant Data Meta-Analysis for a Binary Outcome: One-Stage or Two-Stage?," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-10, April.
    5. Fangyue Chen & Piyawat Kantagowit & Tanawin Nopsopon & Arisa Chuklin & Krit Pongpirul, 2023. "Prediction and diagnosis of chronic kidney disease development and progression using machine-learning: Protocol for a systematic review and meta-analysis of reporting standards and model performance," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-10, February.
    6. Wanting Zu & Xuemiao Huang & Tianxin Xu & Lin Du & Yiming Wang & Lisheng Wang & Wenbo Nie, 2023. "Machine learning in predicting outcomes for stroke patients following rehabilitation treatment: A systematic review," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-14, June.
    7. Lukas Higi & Angela Lisibach & Patrick E Beeler & Monika Lutters & Anne-Laure Blanc & Andrea M Burden & Dominik Stämpfli, 2021. "External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-14, November.
    8. Anna M van Boekel & Siri L van der Meijden & Sesmu M Arbous & Rob G H H Nelissen & Karin E Veldkamp & Emma B Nieswaag & Kim F T Jochems & Jeroen Holtz & Annekee van IJlzinga Veenstra & Jeroen Reijman , 2024. "Systematic evaluation of machine learning models for postoperative surgical site infection prediction," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-17, December.
    9. Fazel, Seena & Burghart, Matthias & Fanshawe, Thomas & Gil, Sharon Danielle & Monahan, John & Yu, Rongqin, 2022. "The predictive performance of criminal risk assessment tools used at sentencing: Systematic review of validation studies," Journal of Criminal Justice, Elsevier, vol. 81(C).
    10. Fisaha Haile Tesfay & Kathryn Backholer & Christina Zorbas & Steven J. Bowe & Laura Alston & Catherine M. Bennett, 2022. "The Magnitude of NCD Risk Factors in Ethiopia: Meta-Analysis and Systematic Review of Evidence," IJERPH, MDPI, vol. 19(9), pages 1-19, April.
    11. Ben Van Calster & Ewout W. Steyerberg & Ralph B. D’Agostino Sr & Michael J. Pencina, 2014. "Sensitivity and Specificity Can Change in Opposite Directions When New Predictive Markers Are Added to Risk Models," Medical Decision Making, , vol. 34(4), pages 513-522, May.
    12. Xuecheng Zhang & Kehua Zhou & Liangzhen You & Jingjing Zhang & Ying Chen & Hengheng Dai & Siqi Wan & Zhiyue Guan & Mingzhi Hu & Jing Kang & Yan Liu & Hongcai Shang, 2023. "Risk prediction models for mortality and readmission in patients with acute heart failure: A protocol for systematic review, critical appraisal, and meta-analysis," PLOS ONE, Public Library of Science, vol. 18(7), pages 1-10, July.
    13. Shamil D. Cooray & Lihini A. Wijeyaratne & Georgia Soldatos & John Allotey & Jacqueline A. Boyle & Helena J. Teede, 2020. "The Unrealised Potential for Predicting Pregnancy Complications in Women with Gestational Diabetes: A Systematic Review and Critical Appraisal," IJERPH, MDPI, vol. 17(9), pages 1-20, April.
    14. Antonio Palazón-Bru & María José Prieto-Castelló & David Manuel Folgado-de la Rosa & Ana Macanás-Martínez & Emma Mares-García & María de los Ángeles Carbonell-Torregrosa & Vicente Francisco Gil-Guillé, 2020. "Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and ," IJERPH, MDPI, vol. 17(24), pages 1-13, December.
    15. Paul Bach & Christine Wallisch & Nadja Klein & Lorena Hafermann & Willi Sauerbrei & Ewout W Steyerberg & Georg Heinze & Geraldine Rauch & for topic group 2 of the STRATOS initiative, 2020. "Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-10, December.
    16. Paulien Van Acker & Wim Van Biesen & Evi V Nagler & Muguet Koobasi & Nic Veys & Jill Vanmassenhove, 2021. "Risk prediction models for acute kidney injury in adults: An overview of systematic reviews," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-14, April.
    17. Sara J Baart & Veerle Dam & Luuk J J Scheres & Johanna A A G Damen & René Spijker & Ewoud Schuit & Thomas P A Debray & Bart C J M Fauser & Eric Boersma & Karel G M Moons & Yvonne T van der Schouw & on, 2019. "Cardiovascular risk prediction models for women in the general population: A systematic review," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-14, January.
    18. Michael Lebenbaum & Osvaldo Espin-Garcia & Yi Li & Laura C Rosella, 2018. "Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-11, January.
    19. Hebatullah Abdulazeem & Sera Whitelaw & Gunther Schauberger & Stefanie J Klug, 2023. "A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-25, September.
    20. Hans Van Remoortel & Hans Scheers & Emmy De Buck & Winne Haenen & Philippe Vandekerckhove, 2020. "Prediction modelling studies for medical usage rates in mass gatherings: A systematic review," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-20, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0162797. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.