Detecting and Dating Early Non-live Pregnancy Outcomes: Generation of a Novel Pregnancy Algorithm From Norwegian Linked Health Registries.

IF 2.4 4区医学 Q3 PHARMACOLOGY & PHARMACY Pharmacoepidemiology and Drug Safety Pub Date : 2024-09-01 DOI:10.1002/pds.70002

Hedvig Nordeng, Angela Lupattelli, Hilde M Engjom, Marleen M H J van Gelder

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Abstract

Purpose: Pregnancies ending before gestational week 12 are common but not notified to the Medical Birth Registry of Norway. Our goal was to develop an algorithm that more completely detects and dates all possible pregnancy outcomes (i.e., miscarriages, elective terminations, ectopic pregnancies, molar pregnancies, stillbirths, and live births) by using diagnostic codes from primary and secondary care registries to complement information from the birth registry.

Methods: We used nationwide linked registry data between 2008 and 2018 in a hierarchical manner: We developed the UiO pregnancy algorithm to arrive at unique pregnancy outcomes, considering codes within 56 days as the same event. To estimate the gestational age of pregnancy outcomes identified in the primary and secondary care registries, we inferred the median gestational age of pregnancy markers (45 ICD-10 codes and 9 ICPC-2 codes) from pregnancies registered in the medical birth registry. When no pregnancy markers were available, we assigned outcome-specific gestational age estimates. The performance of the algorithm was assessed by blinded clinicians.

Results: Using only the medical birth registry, we identified 649 703 pregnancies, including 1369 (0.2%) miscarriages and 3058 (0.5%) elective terminations. With the new algorithm, we detected 859 449 pregnancies, including 642 712 live-births (74.8%), 112 257 miscarriages (13.1%), 94 664 elective terminations (11.0%), 6429 ectopic pregnancies (0.7%), 2564 stillbirths (0.3%), and 823 molar pregnancies (0.1%). The median gestational age was 10⁺¹ weeks (IQR 10⁺⁰-12⁺²) for miscarriages and 8⁺⁰ weeks (IQR 8⁺⁰-9⁺⁶) for elective terminations. Gestational age could be inferred using pregnancy markers for 66.3% of miscarriages and 47.2% of elective terminations.

Conclusion: The UiO pregnancy algorithm improved the detection and dating of early non-live pregnancy outcomes that would have gone unnoticed if relying solely on the medical birth registry information.

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检测早期非活产妊娠结果并确定其日期：从挪威关联健康登记中生成新的妊娠算法。

目的：在妊娠 12 周前终止妊娠的情况很常见，但挪威出生医学登记处并没有收到相关通知。我们的目标是开发一种算法，通过使用初级和二级医疗登记的诊断代码来补充出生登记的信息，从而更全面地检测所有可能的妊娠结果（即流产、选择性终止妊娠、异位妊娠、葡萄胎、死胎和活产）并确定其日期：我们以分层方式使用了 2008 年至 2018 年期间全国范围内的关联登记数据：我们开发了 UiO 妊娠算法，将 56 天内的代码视为同一事件，从而得出唯一的妊娠结果。为了估算初级和二级医疗登记中发现的妊娠结局的孕龄，我们从出生医学登记中登记的妊娠中推断出妊娠标志物的中位孕龄（45 个 ICD-10 编码和 9 个 ICPC-2 编码）。如果没有妊娠标志物，我们就根据结果估算孕龄。算法的性能由双盲临床医生进行评估：结果：仅通过出生医学登记，我们就确定了 649 703 例妊娠，其中包括 1369 例（0.2%）流产和 3058 例（0.5%）选择性终止妊娠。使用新算法后，我们发现了 859 449 例妊娠，包括 642 712 例活产（74.8%）、112 257 例流产（13.1%）、94 664 例选择性终止妊娠（11.0%）、6429 例宫外孕（0.7%）、2564 例死胎（0.3%）和 823 例磨牙妊娠（0.1%）。流产的中位孕龄为 10+1 周（IQR 10+0-12+2），选择性终止妊娠的中位孕龄为 8+0 周（IQR 8+0-9+6）。66.3%的流产和47.2%的选择性终止妊娠可通过妊娠标志物推断出胎龄：UiO妊娠算法提高了对早期非活产妊娠结果的检测和定性，如果仅依靠出生医学登记信息，这些结果可能会被忽视。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Pharmacoepidemiology and Drug Safety 医学-药学

CiteScore

4.80

自引率

7.70%

发文量

173

审稿时长

3 months

期刊介绍： The aim of Pharmacoepidemiology and Drug Safety is to provide an international forum for the communication and evaluation of data, methods and opinion in the discipline of pharmacoepidemiology. The Journal publishes peer-reviewed reports of original research, invited reviews and a variety of guest editorials and commentaries embracing scientific, medical, statistical, legal and economic aspects of pharmacoepidemiology and post-marketing surveillance of drug safety. Appropriate material in these categories may also be considered for publication as a Brief Report. Particular areas of interest include: design, analysis, results, and interpretation of studies looking at the benefit or safety of specific pharmaceuticals, biologics, or medical devices, including studies in pharmacovigilance, postmarketing surveillance, pharmacoeconomics, patient safety, molecular pharmacoepidemiology, or any other study within the broad field of pharmacoepidemiology; comparative effectiveness research relating to pharmaceuticals, biologics, and medical devices. Comparative effectiveness research is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, as these methods are truly used in the real world; methodologic contributions of relevance to pharmacoepidemiology, whether original contributions, reviews of existing methods, or tutorials for how to apply the methods of pharmacoepidemiology; assessments of harm versus benefit in drug therapy; patterns of drug utilization; relationships between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines; evaluations of risk management plans and programmes relating to pharmaceuticals, biologics and medical devices.