Volume 21 Issue 2
Feb.  2023
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Article Navigation >  Chinese Journal of General Practice  > 2023  >  21(2): 190-194
HANG Hang, ZHAO Wu, SUN Qi, GUO Qi-xiu, MA Xiao-qian, ZHENG Zi-fan. Predictive value of the first blood routine parameters within 24 hours of admission for critical illness in children[J]. Chinese Journal of General Practice, 2023, 21(2): 190-194. doi: 10.16766/j.cnki.issn.1674-4152.002842
Citation: HANG Hang, ZHAO Wu, SUN Qi, GUO Qi-xiu, MA Xiao-qian, ZHENG Zi-fan. Predictive value of the first blood routine parameters within 24 hours of admission for critical illness in children[J]. Chinese Journal of General Practice, 2023, 21(2): 190-194. doi: 10.16766/j.cnki.issn.1674-4152.002842
shu

Predictive value of the first blood routine parameters within 24 hours of admission for critical illness in children

doi: 10.16766/j.cnki.issn.1674-4152.002842

  • Department of Pediatrics, the First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui 233004, China

Funds:

 2022e07020035

  • Received Date: 2022-11-19
    Available Online: 2023-04-20
    Abstract
  •   Objective  To explore the correlation between the first blood routine parameters within 24 hours of admission and critical illness in children, and establish ROC curve and a nomogram model to evaluate their predictive value for critical illness in children.  Methods  Patients who underwent blood routine test and completed pediatric critical illness score within 24 hours of admission in the Pediatric Intensive Care Unit of the First Affiliated Hospital of Bengbu Medical College from April 2015 to December 2019 were enrolled. The patients were randomly divided into a training cohort and a validation cohort. The correlation between the variables of the training cohort and critical illness was analyzed by logistic regression analysis. The predictive performances of variables for critical illness in the two cohorts were analyzed by receiver operating characteristic curve. The nomogram prediction model of the training cohort was constructed using R language to assess the occurrence probability of critical illness.  Results  Among 496 patients, there were 283 males and 213 females, with a median age of 2.0 (0.57, 5.88) years. There were 347 patients in the training cohort, and 149 patients in the validation cohort. White cell count (WBC), red cell distribution width-coefficient of variation (RDW-CV), and reticulocyte percentage (RET%) were significantly associated with critical illness in children in the training cohort (all P < 0.05). The receiver operating characteristic curve analysis showed that the areas under the curve of WBC+RDW-CV+RET% combined index for predicting critical illness in the training cohort and the validation cohort were 0.644 and 0.711, respectively. When the optimal cut-off values of 0.357 for the training cohort and 0.290 for the validation cohort were used, sensitivities of the combined index for predicting critical illness were 46.4% and 79.6%, and specificities were 80.0% and 60.0%, respectively. The nomogram prediction model was constructed using WBC, RDW-CV, and RET% of the patients in the training cohort. The concordance index, calibration curve, decision curve, and clinical impact curve analyses indicated that this nomogram could be used to predict critical illness in children.  Conclusion  The first WBC+RDW-CV+RET% combined index within 24 hours of admission has a good predictive performance for critical illness in children. The nomogram constructed by WBC, RDW-CV, and RET% can be used to predict the occurrence probability of critical illness in children.

     

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