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Record W2115461251 · doi:10.1111/bcp.12020

Antidepressant use and gestational hypertension: does evidence support causality? Reply letter

2012· letter· en· W2115461251 on OpenAlexaffabout
Anick Bérard, Mary A. De Vera

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2012
Typeletter
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsObservational studyConfoundingAntidepressantCausality (physics)PregnancyMedicineDepression (economics)Causal inferencePsychiatryRelative riskPediatricsInternal medicineConfidence intervalAnxiety

Abstract

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We thank Grzeskowiak and colleagues 1 for their review of our paper published in the British Journal of Clinical Pharmacology 2. We agree that our study adds to a growing body of evidence supporting the fact that antidepressant use during pregnancy is increasing the risk of pregnancy-induced hypertension (PIH). However, we strongly feel that further clarification of their comments is needed. Studies on the risk of medication use during pregnancy are observational in nature, and one study alone cannot determine causality; hence, our study was not designed for that purpose and was not interpreted in that way, contrary to what Grzeskowiak and colleagues 1 suggest. Causality is likely to be determined by repetition of the findings between multiple studies on the same or similar research questions. While comparing studies, however, adjusted findings, which reflect the best estimate of association between an exposure (here antidepressant) and an outcome (here PIH), taking into account potential confounders, including the indication for antidepressant use (here depression), should be used. On the contrary, Grzeskowiak and colleagues 1 have used crude estimates, hence biased estimates, to compare our findings with others, resulting in an invalid interpretation. Adjusting for potential confounders, including the underlying indication, our study showed a 53% (P < 0.05) overall increase in the risk of PIH associated with antidepressant use during pregnancy, which is in line with what has been previously reported by Toh et al. 3 (90% increase in risk; P < 0.05). We acknowledge, however, that given the observational nature of our study, residual confounding can remain due to underlying maternal depression. However, Palmsten et al. 4 have shown that depressed women not treated with antidepressants during pregnancy were at the same risk of PIH as pregnant women who were not depressed, and that the increase in the risk of PIH was observed only amongst depressed women treated with antidepressants, leading to the conclusion that the increase in risk is probably due to the antidepressants and not the depression, contrary to what Grzeskowiak and colleagues 1 put forward. It is true that we have no clinical data on the severity of PIH, but we have shown that the majority of cases are pregnant women with gestational hypertension. Stratifying our analyses on a subgroup of cases with pre-eclampsia would have rendered our estimates unstable, similar to what has been reported by Toh et al. 3. Finally, we disagree with the argument of Grzeskowiak and colleagues 1 concerning the lack of validity of ICD-9 codes for the identification of PIH in the Quebec Pregnancy Registry. As mentioned by De Vera and Bérard 2, Ros et al. 5 have reported good predictive values for PIH ICD-9 diagnostic codes in the context of ‘population-based’ data similar to the Quebec Pregnancy Registry. On the contrary, however, Geller et al. 6 have reported validation estimates using data from a single hospital in the USA. One needs to be vigilant when reporting such discrepancies. Indeed, the interpretation of validation estimates of diagnostic codes needs to take into account the population setting, managed care delivery and access to care (diagnoses). The Quebec Pregnancy Registry is very similar to the Swedish Birth Register in this regard, because healthcare is universal in Quebec, and thus the Quebec Pregnancy Registry is population based (contrary to the US system), Quebec has equal access to healthcare (contrary to the USA) and Quebec has standardized prenatal follow-up regardless of underlying disease and socio-economic status (contrary to the USA). The argument that depressed pregnant women are more likely to visit their healthcare provider and therefore obtain a diagnosis of PIH is very unlikely. Indeed, it is well known that depressed women are less likely to visit their physician during and outside of pregnancy. In addition, this argument is even less of an issue when studying an outcome that is intensely investigated during pregnancy, such as PIH, which is systematically scrutinized at every prenatal visit regardless of patient comorbidities. In conclusion, our study was designed to assess the risk of PIH during pregnancy associated with gestational antidepressant use and does not provide any information on benefits of antidepressant use during pregnancy. De Vera and Bérard 2 provide one more piece of information useful in the evaluation of the risks of antidepressant use during pregnancy at the patient level. Given the consistency of results between studies published thus far on this topic, it is our belief that more attention should be given to this important maternal comorbidity when prescribing antidepressants to pregnant women. All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare that they have obtained funding from the Canadian Institutes of Health Research for this work; authors have no financial relationships with any organizations that might have an interest in the submitted work in the previous 3 years; and A.B. is a consultant in the litigation involving antidepressant use during pregnancy.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0030.008
Open science0.0040.002
Research integrity0.0300.041
Insufficient payload (model declined to judge)0.0040.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.157
GPT teacher head0.428
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes2
Has abstractyes

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