Stout Molly J, Busam Rachell, Macones George A, Tuuli Methodius G
Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO.
Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO.
Am J Obstet Gynecol. 2014 Nov;211(5):530.e1-4. doi: 10.1016/j.ajog.2014.05.023. Epub 2014 May 17.
The purpose of this study was to estimate interobserver variability and correct classification of preterm birth into spontaneous and indicated subtypes.
This was a cross-sectional study in which a trained obstetric nurse, maternal fetal medicine (MFM) fellow, and MFM faculty member independently reviewed discharge summaries and full medical records to classify preterm birth into "spontaneous" and "indicated" subtypes. Consensus classification was obtained with a senior faculty member and was considered the correct classification. Proportions of correct classification by both discharge summary and full medical record review and by level of reviewer were compared with the use of the χ(2) test. Interobserver variability was estimated with the use of Fleiss' kappa.
Of 132 preterm births, 58.8% were spontaneous. Interrater agreement for classification of preterm birth subtype based on the full medical record review was substantial (0.79; 95% confidence interval, 0.76-0.80). Interrater agreement was slightly less, based on discharge summary classification alone (Kappa, 0.73; 95% confidence interval, 0.71-0.79) compared with a full medical record review, but this difference was not significant (P = .3). Correct classifications for research nurse, MFM fellow, and MFM faculty member were 85%, 95%, and 93%, respectively, for the full medical records and 85%, 93%, and 92%, respectively, for the discharge summaries alone. There was no significant improvement in correct classification based on full medical record review compared with discharge summary alone for any level of reviewer (P > .6).
There is substantial, but imperfect, agreement between reviewers for classification of preterm birth into spontaneous and indicated subtypes. Incorrect classification may occur 5-15% of the time, even with experienced research personnel. Discharge summaries that are populated with pertinent clinical data may streamline accuracy for research efficiency.
本研究旨在评估观察者间的变异性，并将早产正确分类为自发早产和医源性早产亚型。
这是一项横断面研究，一名经过培训的产科护士、母胎医学（MFM）研究员和MFM教员独立查阅出院小结和完整病历，将早产分类为“自发”和“医源性”亚型。通过一名资深教员获得共识分类，并将其视为正确分类。使用χ²检验比较出院小结和完整病历审查以及不同审查人员水平的正确分类比例。使用Fleiss'kappa估计观察者间的变异性。
在132例早产中，58.8%为自发早产。基于完整病历审查的早产亚型分类的评分者间一致性较高（0.79；95%置信区间，0.76 - 0.80）。仅基于出院小结分类的评分者间一致性略低（kappa值为0.73；95%置信区间，0.71 - 0.79），与完整病历审查相比，但差异不显著（P = 0.3）。对于完整病历，研究护士、MFM研究员和MFM教员的正确分类分别为85%、95%和93%，仅对于出院小结分别为85%、93%和92%。对于任何审查人员水平，基于完整病历审查的正确分类与仅基于出院小结相比均无显著改善（P > 0.6）。
在将早产分类为自发和医源性亚型方面，审查人员之间存在较高但并不完美的一致性。即使有经验丰富的研究人员，错误分类仍可能在5% - 15%的情况下发生。包含相关临床数据的出院小结可能会提高准确性以提升研究效率。
