Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment.
Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment.
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DOI：
10.1016/j.xops.2021.100070
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发表时间：
2021-12
影响因子：
--
通讯作者：
Campbell, J. Peter
中科院分区：
文献类型：
--
作者：
Chen, Jimmy S.;Anderson, Jamie E.;Coyner, Aaron S.;Ostmo, Susan;Sonmez, Kemal;Erdogmus, Deniz;Jordan, Brian K.;McEvoy, Cynthia T.;Dukhovny, Dmitry;Schelonka, Robert L.;Chan, R. V. Paul;Singh, Praveer;Kalpathy-Cramer, Jayashree;Chiang, Michael F.;Campbell, J. Peter
早产儿视网膜病变（ROP）是与早产儿氧暴露相关的儿童失明的主要原因。由于氧监测方案已经降低了需要治疗的ROP（TR-ROP）的发生率，因此尚不清楚氧暴露是否仍然是偶发性TR-ROP和侵袭性ROP（A-ROP）（一种严重的、快速进展的ROP形式）的相关风险因素。这项概念验证研究的目的是使用电子健康记录（EHR）数据来评估早期氧气暴露作为发展TR-ROP和A-ROP的预测变量。回顾性队列研究。244名婴儿在一个学术中心进行ROP筛查。对于每个婴儿，氧饱和度和吸入氧分数（FiO 2）手动提取EHR，直到31周月经后年龄（PMA）。每周计算累积最小、最大和平均血氧饱和度和FiO 2。使用胎龄（GA）和30周PMA时的累积最小FiO 2，通过5倍交叉验证训练随机森林模型，以识别发生TR-ROP的婴儿。由于样本数量较少，对有或无A-ROP的婴儿进行了二次受试者工作特征（ROC）曲线分析，未进行交叉验证。对于每个模型，使用ROC曲线下面积（AUC）和精确-召回曲线下面积（AUPRC）评分评估事件TR-ROP的交叉验证性能。对于A-ROP，我们计算了AUC，并在高灵敏度操作点评估了灵敏度和特异性。在纳入的244名婴儿中，33名发展了TR-ROP，其中5名发展了A-ROP。对于事件TR-ROP，在GA加累积最小FiO 2上训练的随机森林模型（AUC = 0.93 ± 0.06; AUPRC = 0.76 ± 0.08）并不显著优于仅在GA上训练的模型（AUC = 0.92 ± 0.06 [P = 0.59]; AUPRC = 0.74 ± 0.12 [P = 0.32]）。仅使用氧气的模型显示AUC为0.80 ± 0.09。A-ROP的ROC分析发现AUC为0.92（95%置信区间，0.87-0.96）。氧气暴露可以从EHR中提取，并量化为事件TR-ROP和A-ROP的风险因素。从EHR中提取可量化的临床特征可能有助于建立多种疾病的风险模型，并评估氧气暴露，ROP和其他早产后遗症之间的复杂关系。
Retinopathy of prematurity (ROP) is a leading cause of childhood blindness related to oxygen exposure in premature infants. Since oxygen monitoring protocols have reduced the incidence of treatment-requiring ROP (TR-ROP), it remains unclear whether oxygen exposure remains a relevant risk factor for incident TR-ROP and aggressive ROP (A-ROP), a severe, rapidly progressing form of ROP. The purpose of this proof-of-concept study was to use electronic health record (EHR) data to evaluate early oxygen exposure as a predictive variable for developing TR-ROP and A-ROP. Retrospective cohort study. Two hundred forty-four infants screened for ROP at a single academic center. For each infant, oxygen saturations and fraction of inspired oxygen (FiO2) were extracted manually from the EHR until 31 weeks postmenstrual age (PMA). Cumulative minimum, maximum, and mean oxygen saturation and FiO2 were calculated on a weekly basis. Random forest models were trained with 5-fold cross-validation using gestational age (GA) and cumulative minimum FiO2 at 30 weeks PMA to identify infants who developed TR-ROP. Secondary receiver operating characteristic (ROC) curve analysis of infants with or without A-ROP was performed without cross-validation because of small numbers. For each model, cross-validation performance for incident TR-ROP was assessed using area under the ROC curve (AUC) and area under the precision-recall curve (AUPRC) scores. For A-ROP, we calculated AUC and evaluated sensitivity and specificity at a high-sensitivity operating point. Of the 244 infants included, 33 developed TR-ROP, of which 5 developed A-ROP. For incident TR-ROP, random forest models trained on GA plus cumulative minimum FiO2 (AUC = 0.93 ± 0.06; AUPRC = 0.76 ± 0.08) were not significantly better than models trained on GA alone (AUC = 0.92 ± 0.06 [P = 0.59]; AUPRC = 0.74 ± 0.12 [P = 0.32]). Models using oxygen alone showed an AUC of 0.80 ± 0.09. ROC analysis for A-ROP found an AUC of 0.92 (95% confidence interval, 0.87–0.96). Oxygen exposure can be extracted from the EHR and quantified as a risk factor for incident TR-ROP and A-ROP. Extracting quantifiable clinical features from the EHR may be useful for building risk models for multiple diseases and evaluating the complex relationships among oxygen exposure, ROP, and other sequelae of prematurity.
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影响因子：
5.1
作者：
Kim SJ;Port AD;Swan R;Campbell JP;Chan RVP;Chiang MF
通讯作者：
Chiang MF
影响因子：
13.7
作者：
Hartnett, M. Elizabeth
通讯作者：
Hartnett, M. Elizabeth
影响因子：
2.5
作者：
Lundgren P;Lundberg L;Hellgren G;Holmström G;Hård AL;Smith LE;Wallin A;Hallberg B;Hellström A
通讯作者：
Hellström A
DOI：
10.3928/01913913-20110208-01
发表时间：
2012-01-01
影响因子：
1.2
作者：
Akcakaya, Aylin Ardagil;Yaylali, Sevil Ari;Yetik, Huseyin
通讯作者：
Yetik, Huseyin
影响因子：
3.7
作者：
Owen, Leah A.;Morrison, Margaux A.;DeAngelis, Margaret M.
通讯作者：
DeAngelis, Margaret M.