Àrea del Medicament i Servei de Farmàcia, Gerència d'Atenció Primària Barcelona Ciutat, Institut Català de la Salut, Barcelona, Spain.
Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès), Spain.
BMJ Open. 2023 Aug 22;13(8):e071335. doi: 10.1136/bmjopen-2022-071335.
To develop an algorithm to identify pregnancy episodes in women at childbearing age using SIDIAP (Information System for the Improvement of Research in Primary Care) data (Catalunya, Spain).To describe drugs dispensed during gestation.
Construction of an algorithm to identify all pregnancy episodes occurred from January 2011 to June 2020 in women aged 12-50. The variables used to create the algorithm include first day of last menstrual period, reasons for pregnancy termination and diagnoses registered in the primary healthcare records. Population-based cohort study including the pregnancy episodes identified by the algorithm.
Catalonia, Spain.
All women aged 12-50 with at least one pregnancy episode occurred during January 2011-June 2020.
No interventions performed.
Identification of pregnancy episodes through an algorithm and description of drug exposure.
We identified 327 865 pregnancy episodes in 250 910 people with a mean age of 31.3 years. During the study period, 83.4% of the episodes were exposed to at least one drug. The most frequent groups dispensed were iron preparations (48% of pregnancy episodes), iodine therapy (40.2%), analgesics and antipyretics (28%), penicillins (19.8%), vitamin B plus folic acid (19.7%) and non-steroidal anti-inflammatory drugs (NSAIDs, 15.1%). The supplements were more frequently dispensed at least twice, and the drugs for acute conditions were mainly dispensed only once during the pregnancy episode.
We developed an algorithm to automatically identify the pregnancy periods in SIDIAP.We described prescription drugs used during pregnancy. The most used ones were supplements, analgesics, NSAID or antibiotics.SIDIAP might be an efficient database to study drug safety during pregnancy and the consequences of drug use in the offspring.
EUPAS37675.
利用 SIDIAP（初级保健研究改进信息系统）数据（西班牙加泰罗尼亚）开发一种算法来识别育龄妇女的妊娠事件。描述妊娠期间开具的药物。
构建一种算法来识别 2011 年 1 月至 2020 年 6 月期间年龄在 12-50 岁之间的所有妊娠事件。用于创建算法的变量包括末次月经第一天、妊娠终止原因和初级保健记录中记录的诊断。基于人群的队列研究，包括通过算法识别的妊娠事件。
西班牙加泰罗尼亚。
所有年龄在 12-50 岁之间且在 2011 年 1 月至 2020 年 6 月期间至少有一次妊娠事件的妇女。
未进行干预。
通过算法识别妊娠事件并描述药物暴露情况。
我们在 250910 名平均年龄为 31.3 岁的人群中识别出 327865 例妊娠事件。在研究期间，83.4%的妊娠事件暴露于至少一种药物。开出的最常见药物组是铁制剂（48%的妊娠事件）、碘治疗（40.2%）、镇痛药和退烧药（28%）、青霉素（19.8%）、维生素 B 加叶酸（19.7%）和非甾体抗炎药（NSAIDs，15.1%）。补充剂更常开至少两次，而用于急性疾病的药物在妊娠事件期间主要仅开一次。
我们开发了一种自动识别 SIDIAP 中妊娠期的算法。我们描述了妊娠期间使用的处方药物。最常用的是补充剂、镇痛药、非甾体抗炎药或抗生素。SIDIAP 可能是研究妊娠期间药物安全性和药物使用对后代影响的有效数据库。
EUPAS37675。
