IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i18p11262-d909262.html
   My bibliography  Save this article

Comparison of Three Comorbidity Measures for Predicting In-Hospital Death through a Clinical Administrative Nacional Database

Author

Listed:
  • Iván Oterino-Moreira

    (Department of Pharmacy, Hospital Universitario Fundación Alcorcón, 28922 Madrid, Spain)

  • Susana Lorenzo-Martínez

    (Department of Quality and Patient Management, Hospital Universitario Fundación Alcorcón, 28922 Madrid, Spain)

  • Ángel López-Delgado

    (Department of Clinical Analysis, Hospital Clínico San Carlos, 28040 Madrid, Spain)

  • Montserrat Pérez-Encinas

    (Department of Pharmacy, Hospital Universitario Fundación Alcorcón, 28922 Madrid, Spain)

Abstract

Background: Various authors have validated scales to measure comorbidity. However, the prognosis capacity variation according to the comorbidity measurement index used needs to be determined in order to identify which is the best predictor. Aims: To quantify the differences between the Charlson (CCI), Elixhauser (ECI) and van Walraven (WCI) comorbidity indices as prognostic factors for in-hospital mortality and to identify the best comorbidity measure predictor. Methods: A retrospective observational study that included all hospitalizations of patients over 18 years of age, discharged between 2017 and 2021 in the hospital, using the Minimum Basic Data Set (MBDS). We calculated CCI, ECI, WCI according to ICD-10 coding algorithms. The correlation and concordance between the three indices were evaluated by Spearman’s rho and Intraclass Correlation Coefficient (ICC), respectively. The logistic regression model for each index was built for predicting in-hospital mortality. Finally, we used the receiver operating characteristic (ROC) curve for comparing the performance of each index in predicting in-hospital mortality, and the Delong method was employed to test the statistical significance of differences. Results: We studied 79,425 admission episodes. The 54.29% were men. The median age was 72 years (interquartile range [IQR]: 56–80) and in-hospital mortality rate was 4.47%. The median of ECI was = 2 (IQR: 1–4), ICW was 4 (IQR: 0–12) and ICC was 1 (IQR: 0–3). The correlation was moderate: ECI vs. WCI rho = 0.645, p < 0.001; ECI vs. CCI rho = 0.721, p < 0.001; and CCI vs. WCI rho = 0.704, p < 0.001; and the concordance was fair to good: ECI vs. WCI Intraclass Correlation Coefficient type A (ICC A ) = 0.675 (CI 95% 0.665–0.684) p < 0.001; ECI vs. CCI ICC A = 0.797 (CI 95% 0.780–0.812), p < 0.001; and CCI vs. WCI ICC A = 0.731 (CI 95% 0.667–0.779), p < 0.001. The multivariate regression analysis demonstrated that comorbidity increased the risk of in-hospital mortality, with differences depending on the comorbidity measurement scale: odds ratio [OR] = 2.10 (95% confidence interval [95% CI] 2.00–2.20) p > |z| < 0 using ECI; OR = 2.31 (CI 95% 2.21–2.41) p > |z| < 0 for WCI; and OR = 2.53 (CI 95% 2.40–2.67) p > |z| < 0 employing CCI. The area under the curve [AUC] = 0.714 (CI 95% 0.706–0.721) using as a predictor of in-hospital mortality CCI, AUC = 0.729 (CI 95% 0.721–0.737) for ECI and AUC = 0.750 (CI 95% 0.743–0.758) using WCI, with statistical significance ( p < 0.001). Conclusion: Comorbidity plays an important role as a predictor of in-hospital mortality, with differences depending on the measurement scale used, the van Walraven comorbidity index being the best predictor of in-hospital mortality.

Suggested Citation

  • Iván Oterino-Moreira & Susana Lorenzo-Martínez & Ángel López-Delgado & Montserrat Pérez-Encinas, 2022. "Comparison of Three Comorbidity Measures for Predicting In-Hospital Death through a Clinical Administrative Nacional Database," IJERPH, MDPI, vol. 19(18), pages 1-13, September.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11262-:d:909262
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/18/11262/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/18/11262/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kuan-Yi Tsai & Kuan-Ying Hsieh & Shu-Yu Ou & Frank Huang-Chih Chou & Yu-Mei Chou, 2020. "Comparison of Elixhauser and Charlson Methods for Discriminative Performance in Mortality Risk in Patients with Schizophrenic Disorders," IJERPH, MDPI, vol. 17(7), pages 1-13, April.
    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.

      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:gam:jijerp:v:19:y:2022:i:18:p:11262-:d:909262. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      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.