Objective <p>We aimed to determine whether clinical variables predict the success of extubation for premature infants.</p> Study design <p>Using variables preceding 320 extubations of infants ≤30 weeks or ≤1250 g at birth, we built predictive models for success at 1-, 3-, and 7-days using machine learning algorithms. We also determined whether lung ultrasound (LUS) scores (<i>n</i> = 15) were associated with success, or predicted success, of extubation.</p> Result <p>Of 84 factors considered, nine were associated with success at 1 day, seven at 3 days, and six at 7 days. The accuracies of the predictive models were 78–84%. Median LUS scores were significantly lower preceding successful extubations (at 3 days) but not correlated with the findings of the predictive models.</p> Conclusion <p>We devised robust models for predicting extubation success based on clinical antecedents. Further study is needed to determine whether LUS can further improve prediction of extubation readiness.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Predictors of extubation success for premature infants

  • Victoria M. Scarpelli,
  • Stephanie G. Galanti,
  • Iels Aan Jibu,
  • Alla Zaytseva,
  • Dalibor Kurepa,
  • Barry Weinberger

摘要

Objective

We aimed to determine whether clinical variables predict the success of extubation for premature infants.

Study design

Using variables preceding 320 extubations of infants ≤30 weeks or ≤1250 g at birth, we built predictive models for success at 1-, 3-, and 7-days using machine learning algorithms. We also determined whether lung ultrasound (LUS) scores (n = 15) were associated with success, or predicted success, of extubation.

Result

Of 84 factors considered, nine were associated with success at 1 day, seven at 3 days, and six at 7 days. The accuracies of the predictive models were 78–84%. Median LUS scores were significantly lower preceding successful extubations (at 3 days) but not correlated with the findings of the predictive models.

Conclusion

We devised robust models for predicting extubation success based on clinical antecedents. Further study is needed to determine whether LUS can further improve prediction of extubation readiness.