Epidemiological trends among preterm infants with apnea. A twelve-year database review

Regenbogen, Elliot; Zhang, Shouling; Yang, Jie; Shroyer, A. Laurie; Zhu, Chencan; DeCristofaro, Joseph D.

doi:10.1016/j.ijporl.2018.01.036

Cited by 9 publications

(27 citation statements)

References 25 publications

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“…Unplanned rehospitalisation within 30 days in this study was relatively infrequent and is in line with much of the literature on early rehospitalisations in preterm babies. (19,33,56) Building predictive models on infrequent outcomes presents difficulties for classification and the default 0.50 classification threshold can be inappropriate. (44,57) Regression models built using infrequent event data can produce negatively biased intercepts with underestimated predicted probabilities in the direction of the majority outcome.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

“…(13)(14)(15) Rehospitalisation rates amongst preterms have been found to be significantly higher than those of full-term infants. (16)(17)(18)Factors previously found to be associated with rehospitalisation are male sex (19)(20)(21)(22), lower gestational age (23)(24)(25), low birth weightor being small for gestational age (SGA) (26), feeding problems (27)(28)(29)(30), bronchopulmonary dysplasia (BPD) (31,32)and lower socioeconomic status (21,27,33,34). To the best of our knowledge, the literature on the early rehospitalisation of preterms discussed explanatory models only and not validated predictive models.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

Reed

Morgan²,

Zeitlin

et al. 2019

Preprint

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Background Gaining a better understanding of the probability, timing and prediction of rehospitalisation amongst preterm babies could help improve outcomes. There is limited research addressing these topics amongst extremely and very preterm babies. In this context, unplanned rehospitalisations constitute an important, potentially modifiable adverse event. We aimed to establish the probability, time-distribution and predictability of unplanned rehospitalisation within 30 days of discharge in a population of French preterm babies.Methods This study used data from EPIPAGE 2, a population-based prospective study of French preterm babies. Only those babies discharged home alive and whose parents responded to the 1-year survey were eligible for inclusion in our study. For Kaplan-Meier analysis, the outcome was unplanned rehospitalisation censored at 30 days. For predictive modelling, the outcome was binary, recording unplanned rehospitalisation within 30 days of discharge. Predictors included routine clinical variables selected based on expert opinion.Results Of 3,841 eligible babies, 350 (9.1%, 95% CI 8.2-10.1) experienced an unplanned rehospitalisation within 30 days. The probability of rehospitalisation progressed at a consistent rate over the 30 days. There were significant differences in rehospitalisation probability by gestational age. The cross-validated performance of a ten predictor model demonstrated low discrimination and calibration. The area under the receiver operating characteristic curve was 0.62 (95% CI 0.59-0.65).Conclusions Unplanned rehospitalisation within 30 days of discharge was infrequent and the probability of rehospitalisation progressed at a consistent rate. Lower gestational age increased the probability of rehospitalisation. Predictive models comprised of clinically important variables had limited predictive ability.

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Section: Strengths and Limitationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

Reed

Morgan²,

Zeitlin

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…However, non-invasive respiratory support is often ineffective, with a high failure rate of up to 50% in very low birthweight (VLBW) infants [10,11], most commonly due to insufficient respiratory drive. Thus, apnoea is one of the major well-recognised challenges of prematurity, and remains one of the main indications for invasive ventilation [12][13][14]. Since the 1970s, methylxanthines have been routinely prescribed in preterm infants to prevent apnoea of prematurity (AOP) and reduce the need for invasive ventilatory support [13].…”

Section: Introductionmentioning

confidence: 99%

Caffeine in preterm infants: where are we in 2020?

et al. 2020

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The incidence of preterm birth is increasing, leading to a growing population with potential long-term pulmonary complications. Apnoea of prematurity (AOP) is one of the major challenges when treating preterm infants; it can lead to respiratory failure and the need for mechanical ventilation. Ventilating preterm infants can be associated with severe negative pulmonary and extrapulmonary outcomes, such as bronchopulmonary dysplasia (BPD), severe neurological impairment and death. Therefore, international guidelines favour non-invasive respiratory support. Strategies to improve the success rate of non-invasive ventilation in preterm infants include pharmacological treatment of AOP. Among the different pharmacological options, caffeine citrate is the current drug of choice. Caffeine is effective in reducing AOP and mechanical ventilation and enhances extubation success; it decreases the risk of BPD; and is associated with improved cognitive outcome at 2 years of age, and pulmonary function up to 11 years of age. The commonly prescribed dose (20 mg·kg−1 loading dose, 5–10 mg·kg−1 per day maintenance dose) is considered safe and effective. However, to date there is no commonly agreed standardised protocol on the optimal dosing and timing of caffeine therapy. Furthermore, despite the wide pharmacological safety profile of caffeine, the role of therapeutic drug monitoring in caffeine-treated preterm infants is still debated. This state-of-the-art review summarises the current knowledge of caffeine therapy in preterm infants and highlights some of the unresolved questions of AOP. We speculate that with increased understanding of caffeine and its metabolism, a more refined respiratory management of preterm infants is feasible, leading to an overall improvement in patient outcome.

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“…Rehospitalisation rates amongst preterms have been found to be significantly higher than those of full-term infants [16–18]. Factors previously found to be associated with rehospitalisation are male sex [19–22], lower gestational age [23–25], low birth weight or being small for gestational age (SGA) [26], feeding problems [27–30], bronchopulmonary dysplasia (BPD) [31, 32] and lower socioeconomic status [21, 27, 33, 34]. To the best of our knowledge, the literature on the early rehospitalisation of preterms discussed explanatory models only and not validated predictive models.…”

Section: Introductionmentioning

confidence: 99%

Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

et al. 2019

View full text Add to dashboard Cite

BackgroundGaining a better understanding of the probability, timing and prediction of rehospitalisation amongst preterm babies could help improve outcomes. There is limited research addressing these topics amongst extremely and very preterm babies. In this context, unplanned rehospitalisations constitute an important, potentially modifiable adverse event. We aimed to establish the probability, time-distribution and predictability of unplanned rehospitalisation within 30 days of discharge in a population of French preterm babies.MethodsThis study used data from EPIPAGE 2, a population-based prospective study of French preterm babies. Only those babies discharged home alive and whose parents responded to the one-year survey were eligible for inclusion in our study. For Kaplan-Meier analysis, the outcome was unplanned rehospitalisation censored at 30 days. For predictive modelling, the outcome was binary, recording unplanned rehospitalisation within 30 days of discharge. Predictors included routine clinical variables selected based on expert opinion.ResultsOf 3841 eligible babies, 350 (9.1, 95% CI 8.2–10.1) experienced an unplanned rehospitalisation within 30 days. The probability of rehospitalisation progressed at a consistent rate over the 30 days. There were significant differences in rehospitalisation probability by gestational age. The cross-validated performance of a ten predictor model demonstrated low discrimination and calibration. The area under the receiver operating characteristic curve was 0.62 (95% CI 0.59–0.65).ConclusionsUnplanned rehospitalisation within 30 days of discharge was infrequent and the probability of rehospitalisation progressed at a consistent rate. Lower gestational age increased the probability of rehospitalisation. Predictive models comprised of clinically important variables had limited predictive ability.

show abstract

Epidemiological trends among preterm infants with apnea. A twelve-year database review

Cited by 9 publications

References 25 publications

Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

Caffeine in preterm infants: where are we in 2020?

Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

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