Characteristics of patients with perinatal depression in UK primary care settings
Bibliographic record
Abstract
Introduction Perinatal depression (PND) is a debilitating mood disorder that occurs during or following pregnancy. Information regarding characteristics associated with PND can aid in better understanding the disease. Objectives Examine patient characteristics and comorbidities of PND patients and matched non-PND controls in a UK electronic health record (EHR) database. Methods Women aged 12-55y with a delivery record (livebirth, stillbirth, mixed birth) during Jan 2017-Dec 2021 were selected from the Clinical Practice Research Datalink (CPRD) GOLD primary care database via a pregnancy algorithm. PND was ascertained using read codes during pregnancy or one year after the end of pregnancy date (EPD). Two ways to define PND were explored: 1) restricted definition (PND-r) where only PND codes were included; 2) broad definition (PND-b) including both PND and 34 other depression codes. For each PND case, two controls were matched on key patient variables such as age, depression history, and pregnancy outcome. Patients were required to have at least 12 months (mo) of continuous enrollment prior to and post EPD. Patient characteristics and select psychiatric and pregnancy-related comorbidities were compared, and prevalence rate ratios (PRR) and 95% Wald confidence intervals (CI) were calculated comparing cases and controls. Results The study included 2,214 cases of PND-r and 4,718 cases of PND-b, and their respective non-PND matched controls. PND-r and PND-b cases differed in timing of diagnosis. Of the PND-r cases, 6% were diagnosed during pregnancy and 47% in the first 3mo following delivery; whereas the distribution in the PND-b was, respectively, 18% and 30%. The mean age of the PND-r and PND-b cohorts was consistent (29y, SD=6). A prior recorded history of depression was present in 36% of PND-r cases and 43% of PND-b cases. Approximately 55% of PND-r cases and 65% of PND-b cases had a history of antidepressant use prior to last menstrual period. During the 12mo pre-EPD, PND-r cases had higher prevalence of hyperemesis gravidarum (PRR=1.5, 95% CI 1.3-1.8), gestational diabetes (PRR=1.4, 95% CI 1.1-1.7), and anxiety/panic disorders (PRR=1.8, 95% CI 1.3-2.3) compared to controls. During the 12mo post-EPD, PND-r cases had higher prevalence of comorbid anxiety/panic disorders (PRR=3.8, 95% CI 3.0-4.9) as well as post-traumatic stress disorder (PRR=3.1, 95% CI 1.5-6.1) compared to controls. Results were similar in the PPD-b analyses, but with higher PRR of anxiety/panic disorders (post-EPD PRR: 11.2, 95% CI 9.7-12.9). Conclusions 80% of PND-r and 71% of PND-b cases were diagnosed during pregnancy or in the first 6mo following EPD. Cases had higher prevalence of certain pregnancy and psychiatric conditions compared to controls, with comorbid anxiety/panic disorder estimates higher using the PND-b definition. Future research should consider comparing results using both broad and restricted definitions of PND in EHRs. Disclosure of Interest C. Gillis Shareolder of: Biogen, Employee of: Biogen, S. Chen Shareolder of: Biogen, Employee of: Biogen, C. Mak Shareolder of: Biogen, Employee of: Biogen, E. Tworkoski Shareolder of: Biogen, Employee of: Biogen, L. Li Shareolder of: Biogen, Employee of: Biogen, S. Eaton Shareolder of: Biogen, Employee of: Biogen, C. Green Shareolder of: Biogen, Employee of: Biogen, N. Maserejian Shareolder of: Biogen, Employee of: Biogen, M. Koch Shareolder of: Biogen, Employee of: Biogen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".