IDEAS home Printed from https://ideas.repec.org/a/plo/pntd00/0005498.html
   My bibliography  Save this article

The value of daily platelet counts for predicting dengue shock syndrome: Results from a prospective observational study of 2301 Vietnamese children with dengue

Author

Listed:
  • Phung Khanh Lam
  • Tran Van Ngoc
  • Truong Thi Thu Thuy
  • Nguyen Thi Hong Van
  • Tran Thi Nhu Thuy
  • Dong Thi Hoai Tam
  • Nguyen Minh Dung
  • Nguyen Thi Hanh Tien
  • Nguyen Tan Thanh Kieu
  • Cameron Simmons
  • Bridget Wills
  • Marcel Wolbers

Abstract

Background: Dengue is the most important mosquito-borne viral infection to affect humans. Although it usually manifests as a self-limited febrile illness, complications may occur as the fever subsides. A systemic vascular leak syndrome that sometimes progresses to life-threatening hypovolaemic shock is the most serious complication seen in children, typically accompanied by haemoconcentration and thrombocytopenia. Robust evidence on risk factors, especially features present early in the illness course, for progression to dengue shock syndrome (DSS) is lacking. Moreover, the potential value of incorporating serial haematocrit and platelet measurements in prediction models has never been assessed. Methodology/Principal findings: We analyzed data from a prospective observational study of Vietnamese children aged 5–15 years admitted with clinically suspected dengue to the Hospital for Tropical Diseases in Ho Chi Minh City between 2001 and 2009. The analysis population comprised all children with laboratory-confirmed dengue enrolled between days 1–4 of illness. Logistic regression was the main statistical model for all univariate and multivariable analyses. The prognostic value of daily haematocrit levels and platelet counts were assessed using graphs and separate regression models fitted on each day of illness. Among the 2301 children included in the analysis, 143 (6%) progressed to DSS. Significant baseline risk factors for DSS included a history of vomiting, higher temperature, a palpable liver, and a lower platelet count. Prediction models that included serial daily platelet counts demonstrated better ability to discriminate patients who developed DSS from others, than models based on enrolment information only. However inclusion of daily haematocrit values did not improve prediction of DSS. Conclusions/Significance: Daily monitoring of platelet counts is important to help identify patients at high risk of DSS. Development of dynamic prediction models that incorporate signs, symptoms, and daily laboratory measurements, could improve DSS prediction and thereby reduce the burden on health services in endemic areas. Author summary: Dengue is a very common, potentially serious, mosquito-borne viral infection. The spectrum of clinical disease is broad. Dengue shock syndrome (DSS), seen primarily in children, is the most serious life-threatening manifestation. Early identification of children presenting with dengue who are likely to develop DSS could improve triage and resource allocation in endemic areas. This study, based on data from 2301 Vietnamese children hospitalized with dengue, aimed to assess the value of readily available clinical and laboratory markers, especially platelet counts and haematocrit levels, in predicting DSS. In addition to risk factors present at the first assessment within 1–4 days from fever onset (vomiting, higher temperature, palpable liver, lower platelet count), we showed that serial daily platelet counts provide useful additional information to identify at an early stage children who are likely to develop shock. Although absolute platelet values were already known to be important, this is the first study to confirm the usefulness of sequential daily platelet counts. It also provides proof of concept for the value of incorporating serial laboratory and clinical signs into future dynamic prognostic models to allow for earlier identification and better management of children at risk of DSS.

Suggested Citation

  • Phung Khanh Lam & Tran Van Ngoc & Truong Thi Thu Thuy & Nguyen Thi Hong Van & Tran Thi Nhu Thuy & Dong Thi Hoai Tam & Nguyen Minh Dung & Nguyen Thi Hanh Tien & Nguyen Tan Thanh Kieu & Cameron Simmons , 2017. "The value of daily platelet counts for predicting dengue shock syndrome: Results from a prospective observational study of 2301 Vietnamese children with dengue," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 11(4), pages 1-20, April.
  • Handle: RePEc:plo:pntd00:0005498
    DOI: 10.1371/journal.pntd.0005498
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0005498
    Download Restriction: no

    File URL: https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0005498&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pntd.0005498?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. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Simon N. Wood, 2011. "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 3-36, January.
    3. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    4. Samir Bhatt & Peter W. Gething & Oliver J. Brady & Jane P. Messina & Andrew W. Farlow & Catherine L. Moyes & John M. Drake & John S. Brownstein & Anne G. Hoen & Osman Sankoh & Monica F. Myers & Dylan , 2013. "The global distribution and burden of dengue," Nature, Nature, vol. 496(7446), pages 504-507, April.
    5. Nguyen Tien Huy & Tran Van Giang & Dinh Ha Duy Thuy & Mihoko Kikuchi & Tran Tinh Hien & Javier Zamora & Kenji Hirayama, 2013. "Factors Associated with Dengue Shock Syndrome: A Systematic Review and Meta-Analysis," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 7(9), pages 1-15, September.
    6. Lukas Tanner & Mark Schreiber & Jenny G H Low & Adrian Ong & Thomas Tolfvenstam & Yee Ling Lai & Lee Ching Ng & Yee Sin Leo & Le Thi Puong & Subhash G Vasudevan & Cameron P Simmons & Martin L Hibberd , 2008. "Decision Tree Algorithms Predict the Diagnosis and Outcome of Dengue Fever in the Early Phase of Illness," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 2(3), pages 1-9, March.
    7. Phung Khanh Lam & Dong Thi Hoai Tam & Nguyen Minh Dung & Nguyen Thi Hanh Tien & Nguyen Tan Thanh Kieu & Cameron Simmons & Jeremy Farrar & Bridget Wills & Marcel Wolbers, 2015. "A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-13, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tran Quang Thach & Heba Gamal Eisa & AlMotsim Ben Hmeda & Hazem Faraj & Tieu Minh Thuan & Manal Mahmoud Abdelrahman & Mario Gerges Awadallah & Ha Xuan Nam & Michael Noeske & Jeza Muhamad Abdul Aziz & , 2021. "Predictive markers for the early prognosis of dengue severity: A systematic review and meta-analysis," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 15(10), pages 1-25, October.
    2. Sangshin Park & Anon Srikiatkhachorn & Siripen Kalayanarooj & Louis Macareo & Sharone Green & Jennifer F Friedman & Alan L Rothman, 2018. "Use of structural equation models to predict dengue illness phenotype," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 12(10), pages 1-14, October.

    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. Sangshin Park & Anon Srikiatkhachorn & Siripen Kalayanarooj & Louis Macareo & Sharone Green & Jennifer F Friedman & Alan L Rothman, 2018. "Use of structural equation models to predict dengue illness phenotype," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 12(10), pages 1-14, October.
    2. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    3. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    4. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    5. Kath, Christopher & Ziel, Florian, 2021. "Conformal prediction interval estimation and applications to day-ahead and intraday power markets," International Journal of Forecasting, Elsevier, vol. 37(2), pages 777-799.
    6. Dindaroglu, Burak & Ertac, Seda, 2024. "An empirical study of sequential offer bargaining during the Festival of Sacrifice," Journal of Economic Psychology, Elsevier, vol. 101(C).
    7. Kath, Christopher & Ziel, Florian, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Energy Economics, Elsevier, vol. 76(C), pages 411-423.
    8. Andreas Groll & Gerhard Tutz, 2017. "Variable selection in discrete survival models including heterogeneity," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 305-338, April.
    9. Brunori, Paolo & Salas-Rojo, Pedro & Verme, Paolo, 2022. "Estimating Inequality with Missing Incomes," GLO Discussion Paper Series 1138, Global Labor Organization (GLO).
    10. Claude Renaux & Laura Buzdugan & Markus Kalisch & Peter Bühlmann, 2020. "Hierarchical inference for genome-wide association studies: a view on methodology with software," Computational Statistics, Springer, vol. 35(1), pages 1-40, March.
    11. Phung Khanh Lam & Dong Thi Hoai Tam & Nguyen Minh Dung & Nguyen Thi Hanh Tien & Nguyen Tan Thanh Kieu & Cameron Simmons & Jeremy Farrar & Bridget Wills & Marcel Wolbers, 2015. "A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-13, May.
    12. Danhyang Lee & Jae Kwang Kim, 2022. "Semiparametric imputation using conditional Gaussian mixture models under item nonresponse," Biometrics, The International Biometric Society, vol. 78(1), pages 227-237, March.
    13. Jacqueline K Kueper & Daniel J Lizotte & Manuel Montero-Odasso & Mark Speechley & for the Alzheimer’s Disease Neuroimaging Initiative, 2020. "Cognition and motor function: The gait and cognition pooled index," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    14. Andree,Bo Pieter Johannes, 2021. "Estimating Food Price Inflation from Partial Surveys," Policy Research Working Paper Series 9886, The World Bank.
    15. Joshua G X Wong & Tun Linn Thein & Yee-Sin Leo & Junxiong Pang & David C Lye, 2016. "Identifying Adult Dengue Patients at Low Risk for Clinically Significant Bleeding," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-12, February.
    16. Paul Ghelasi & Florian Ziel, 2024. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Papers 2406.00326, arXiv.org, revised Aug 2024.
    17. Goldsmith, Jeff & Scheipl, Fabian, 2014. "Estimator selection and combination in scalar-on-function regression," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 362-372.
    18. Ting‐Huei Chen & Hanaa Boughal, 2021. "A penalized structural equation modeling method accounting for secondary phenotypes for variable selection on genetically regulated expression from PrediXcan for Alzheimer's disease," Biometrics, The International Biometric Society, vol. 77(1), pages 362-371, March.
    19. Rachel Sippy & Daniel F Farrell & Daniel A Lichtenstein & Ryan Nightingale & Megan A Harris & Joseph Toth & Paris Hantztidiamantis & Nicholas Usher & Cinthya Cueva Aponte & Julio Barzallo Aguilar & An, 2020. "Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(2), pages 1-20, February.
    20. Halewijn M. Drent & Barbara van den Hoofdakker & Jan K. Buitelaar & Pieter J. Hoekstra & Andrea Dietrich, 2022. "Factors Related to Perceived Stigma in Parents of Children and Adolescents in Outpatient Mental Healthcare," IJERPH, MDPI, vol. 19(19), pages 1-14, October.

    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:pntd00:0005498. 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: plosntds (email available below). General contact details of provider: https://journals.plos.org/plosntds/ .

    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.