Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Institute for Digital Health & Innovation, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
J Matern Fetal Neonatal Med. 2023 Dec;36(1):2167073. doi: 10.1080/14767058.2023.2167073.
The rates of SMM have been steadily increasing in Arkansas, a southern rural state, which has the 5th highest maternal death rate among the US states. The aims of the study were to test the functionality of the Bateman index in association to SMM, in clustering the risks of pregnancies to SMM, and to study the predictability of SMM using the Bateman index.
From the ANGELS database, 72,183 pregnancies covered by Medicaid in Arkansas between 2013 and 2016 were included in this study. The expanded CDC ICD-9/ICD-10 criteria were used to identify SMM. The Bateman comorbidity index was applied in quantifying the comorbidity burden for a pregnancy. Multivariable logistic regressions, KMeans method, and five widely used predictive models were applied respectively for each of the study aims.
SMM prevalence remained persistently high among Arkansas women covered by Medicaid (195 per 10,000 deliveries) during the study period. Using the Bateman comorbidity index score, the study population was divided into four groups, with a monotonically increasing odds of SMM from a lower score group to a higher score group. The association between the index score and the occurrence of SMM is confirmed with statistical significance: relative to Bateman score falling in 0-1, adjusted Odds Ratios and 95% CIs are: 2.1 (1.78, 2.46) for score in 2-5; 5.08 (3.81, 6.79) for score in 6-9; and 8.53 (4.57, 15.92) for score ≥10. Noticeably, more than one-third of SMM cases were detected from the studied pregnancies that did not have any of the comorbid conditions identified. In the prediction analyses, we observed minimal predictability of SMM using the comorbidity index: the calculated -statistics ranged between 62% and 67%; the Precision-Recall AUC values are <7% for internal validation and <9% for external validation procedures.
The comorbidity index can be used in quantifying the risk of SMM and can help cluster the study population into risk tiers of SMM, especially in rural states where there are disproportionately higher rates of SMM; however, the predictive value of the comorbidity index for SMM is inappreciable.
在阿肯色州，一种南部农村州，母婴死亡率在美国各州中排名第五，母婴死亡率一直在稳步上升。本研究的目的是测试 Bateman 指数在母婴死亡率中的功能，用于聚类母婴死亡率的风险，并使用 Bateman 指数研究母婴死亡率的可预测性。
本研究纳入了 2013 年至 2016 年期间阿肯色州接受医疗补助的 72183 例妊娠的 ANGELS 数据库。使用扩展的 CDC ICD-9/ICD-10 标准来确定母婴死亡率。Bateman 合并症指数用于量化妊娠的合并症负担。分别应用多变量逻辑回归、KMeans 方法和五种广泛使用的预测模型来实现每个研究目的。
在研究期间，阿肯色州接受医疗补助的妇女中母婴死亡率持续居高不下（每 10000 例分娩中有 195 例）。使用 Bateman 合并症指数评分，将研究人群分为四组，从低评分组到高评分组，母婴死亡率的几率呈单调递增。指数评分与母婴死亡率之间的关联具有统计学意义：与 Bateman 评分在 0-1 相比，调整后的比值比（OR）和 95%置信区间（CI）为：评分在 2-5 时为 2.1（1.78，2.46）；评分在 6-9 时为 5.08（3.81，6.79）；评分在 10 及以上时为 8.53（4.57，15.92）。值得注意的是，研究中的三分之一以上的母婴死亡率病例是从没有任何已识别合并症的妊娠中检测到的。在预测分析中，我们观察到合并症指数对母婴死亡率的预测能力有限：计算的 -统计量在 62%到 67%之间；内部验证和外部验证过程的精度-召回 AUC 值均<7%。
合并症指数可用于量化母婴死亡率的风险，并有助于将研究人群聚类为母婴死亡率的风险分层，尤其是在母婴死亡率比例较高的农村州；然而，合并症指数对母婴死亡率的预测价值并不明显。
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