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      Five-minute Apgar score and outcomes in neonates of 24–28 weeks’ gestation

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          Abstract

          Objectives

          To assess associations between 5 min Apgar score and mortality and severe neurological injury (SNI) and to report test characteristics in preterm neonates.

          Design, setting and patients

          Retrospective cohort study of neonates 24 0 to 28 6 weeks’ gestation born between 2007 and 2016 and admitted to neonatal units in 11 high-income countries.

          Exposure

          5 min Apgar score.

          Main outcome measures

          In-hospital mortality and SNI defined as grade 3 or 4 periventricular/intraventricular haemorrhage or periventricular leukomalacia. Outcome rates were calculated for each Apgar score and compared after adjustment. The diagnostic characteristics and ORs for each value from 0 versus 1–10 to 0–9 versus 10, with 1-point increments were calculated.

          Results

          Among 92 412 included neonates, as 5 min Apgar score increased from 0 to 10, mortality decreased from 60% to 8%. However, no clear increasing or decreasing pattern was identified for SNI. There was an increase in sensitivity and decrease in specificity for both mortality and SNI associated with increasing scores. The Apgar score alone had an area under the curve of 0.64 for predicting mortality, which increased to 0.73 with the addition of gestational age.

          Conclusions

          In neonates of 24–28 weeks’ gestation admitted to neonatal units, higher 5 min Apgar score was associated with lower mortality in a graded manner, while the association with SNI remained relatively constant at all scores. Among survivors, low Apgar scores did not predict SNI.

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          Most cited references32

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          Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

          The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.
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            Incidence and evolution of subependymal and intraventricular hemorrhage: A study of infants with birth weights less than 1,500 gm

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              Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker.

              M. S. Pepe (2004)
              A marker strongly associated with outcome (or disease) is often assumed to be effective for classifying persons according to their current or future outcome. However, for this assumption to be true, the associated odds ratio must be of a magnitude rarely seen in epidemiologic studies. In this paper, an illustration of the relation between odds ratios and receiver operating characteristic curves shows, for example, that a marker with an odds ratio of as high as 3 is in fact a very poor classification tool. If a marker identifies 10% of controls as positive (false positives) and has an odds ratio of 3, then it will correctly identify only 25% of cases as positive (true positives). The authors illustrate that a single measure of association such as an odds ratio does not meaningfully describe a marker's ability to classify subjects. Appropriate statistical methods for assessing and reporting the classification power of a marker are described. In addition, the serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated.
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                Author and article information

                Contributors
                Journal
                Archives of Disease in Childhood - Fetal and Neonatal Edition
                Arch Dis Child Fetal Neonatal Ed
                BMJ
                1359-2998
                1468-2052
                June 17 2022
                July 2022
                July 2022
                November 15 2021
                : 107
                : 4
                : 437-446
                Article
                10.1136/archdischild-2021-322230
                34782368
                dd991833-d0e6-4189-84b4-e88831211d6b
                © 2021
                History

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