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Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain

OBJECTIVES: 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. DESIGN: Construction of an algorithm to identify al...

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Autores principales: Lestón Vázquez, Marta, Vilaplana-Carnerero, Carles, Gomez-Lumbreras, Ainhoa, Prat-Vallverdu, Oriol, Marsal, Josep Ramon, Vedia Urgell, Cristina, Giner-Soriano, Maria, Morros, Rosa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445402/
https://www.ncbi.nlm.nih.gov/pubmed/37607789
http://dx.doi.org/10.1136/bmjopen-2022-071335
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author Lestón Vázquez, Marta
Vilaplana-Carnerero, Carles
Gomez-Lumbreras, Ainhoa
Prat-Vallverdu, Oriol
Marsal, Josep Ramon
Vedia Urgell, Cristina
Giner-Soriano, Maria
Morros, Rosa
author_facet Lestón Vázquez, Marta
Vilaplana-Carnerero, Carles
Gomez-Lumbreras, Ainhoa
Prat-Vallverdu, Oriol
Marsal, Josep Ramon
Vedia Urgell, Cristina
Giner-Soriano, Maria
Morros, Rosa
author_sort Lestón Vázquez, Marta
collection PubMed
description OBJECTIVES: 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. DESIGN: 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. SETTING: Catalonia, Spain. PARTICIPANTS: All women aged 12–50 with at least one pregnancy episode occurred during January 2011–June 2020. INTERVENTIONS: No interventions performed. PRIMARY AND SECONDARY OUTCOME MEASURES: Identification of pregnancy episodes through an algorithm and description of drug exposure. RESULTS: 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(12) 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. CONCLUSIONS: 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. TRIAL REGISTRATION NUMBER: EUPAS37675.
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spelling pubmed-104454022023-08-24 Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain Lestón Vázquez, Marta Vilaplana-Carnerero, Carles Gomez-Lumbreras, Ainhoa Prat-Vallverdu, Oriol Marsal, Josep Ramon Vedia Urgell, Cristina Giner-Soriano, Maria Morros, Rosa BMJ Open Pharmacology and Therapeutics OBJECTIVES: 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. DESIGN: 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. SETTING: Catalonia, Spain. PARTICIPANTS: All women aged 12–50 with at least one pregnancy episode occurred during January 2011–June 2020. INTERVENTIONS: No interventions performed. PRIMARY AND SECONDARY OUTCOME MEASURES: Identification of pregnancy episodes through an algorithm and description of drug exposure. RESULTS: 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(12) 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. CONCLUSIONS: 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. TRIAL REGISTRATION NUMBER: EUPAS37675. BMJ Publishing Group 2023-08-22 /pmc/articles/PMC10445402/ /pubmed/37607789 http://dx.doi.org/10.1136/bmjopen-2022-071335 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Pharmacology and Therapeutics
Lestón Vázquez, Marta
Vilaplana-Carnerero, Carles
Gomez-Lumbreras, Ainhoa
Prat-Vallverdu, Oriol
Marsal, Josep Ramon
Vedia Urgell, Cristina
Giner-Soriano, Maria
Morros, Rosa
Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain
title Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain
title_full Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain
title_fullStr Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain
title_full_unstemmed Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain
title_short Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain
title_sort drug exposure during pregnancy in primary care: an algorithm and observational study from sidiap database, catalunya, spain
topic Pharmacology and Therapeutics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445402/
https://www.ncbi.nlm.nih.gov/pubmed/37607789
http://dx.doi.org/10.1136/bmjopen-2022-071335
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