The Impact of Different Case Ascertainment Definitions on the Prevalence of Major Congenital Malformations and their Association with Asthma During Pregnancy

Validation of case definition algorithms for the ascertainment of congenital anomalies

BACKGROUND

Congenital anomalies (CA) are one of the leading causes of infant mortality and long-term disability. Many jurisdictions rely on health administrative data to monitor these conditions. Case definition algorithms can be used to monitor CA; however, validation of these algorithms is needed to understand the strengths and limitations of the data. This study aimed to validate case definition algorithms used in a CA surveillance system in British Columbia (BC), Canada.

METHODS

A cohort of births between March 2000 and April 2002 in BC was linked to the Health Status Registry (HSR) and the BC Congenital Anomalies Surveillance System (BCCASS) to identify cases and non-cases of specific anomalies within each surveillance system. Measures of algorithm performance were calculated for each CA using the HSR as the reference standard. Agreement between both databases was calculated using kappa coefficient. The modified Standards for Reporting Diagnostic Accuracy guidelines were used to enhance the quality of the study.

RESULTS

Measures of algorithm performance varied by condition. Positive predictive value (PPV) ranged between approximately 73%-100%. Sensitivity was lower than PPV for most conditions. Internal congenital anomalies or conditions not easily identifiable at birth had the lowest sensitivity. Specificity and negative predictive value exceeded 99% for all algorithms.

CONCLUSION

Case definition algorithms may be used to monitor CA at the population level. Accuracy of algorithms is higher for conditions that are easily identified at birth. Jurisdictions with similar administrative data may benefit from using validated case definitions for CA surveillance as this facilitates cross-jurisdictional comparison.

Major congenital malformations in offspring of women with chronic diseases-impact of the disease or the treatment?

In a narrative review, we summarized previous findings on the risk of major congenital malformations in offspring of women with chronic hypertension, hypothyroidism, or depression compared with the background population, and evaluated whether exposure to medical treatment in the first trimester affected this risk. In a literature search in the PubMed database, cohort studies were included if they were published from 2010 to 2022 and contained data on major congenital malformations from ≥500 offspring of women with chronic hypertension, hypothyroidism, or depression during the first trimester of pregnancy, and data on both untreated and treated women. Data were compared with the background population of women without these diseases. In total, 7 cohort studies were identified. In comparison with the background population, 2 studies including 54,996 offspring of women with chronic hypertension showed an adjusted odds ratio of 1.20 to 1.30 for major congenital malformations in the offspring, regardless of antihypertensive treatment. One study including 16,364 offspring of women with hypothyroidism showed an adjusted odds ratio of 1.14 (1.06-1.22) for major congenital malformations in the offspring, regardless of thyroid substitution. Four studies including 48,913 offspring of women with depression showed adjusted odds ratios of 1.07 to 1.27 (0.91-1.78) for major congenital malformations in the offspring of untreated women. Three of these 4 studies showed similar prevalence of malformations in women treated for depression. The findings of this narrative review suggest that chronic hypertension and hypothyroidism, rather than exposure to their medical treatments in the first trimester, were associated with increased risk of major congenital malformations, whereas depression was generally not associated with major congenital malformations.

Timing of Maternal Asthma Diagnosis in Relation to Adverse Perinatal Outcomes

BACKGROUND

It is unclear if asthma diagnosed during pregnancy puts the fetus at a higher risk of poor perinatal outcomes than pre-existing asthma.

OBJECTIVE

To assess if the risks of prematurity, major malformations, and small-for-gestational age (SGA) are higher in women with asthma diagnosed during versus pre-pregnancy.

METHODS

We retrospectively analyzed a cohort of pregnant women aged ≥15 years with and without incident asthma, constructed from health administrative databases. Follow-up began 24 months before pregnancy onset (cohort entry) and ended at delivery. Incident asthma was defined as a first diagnosis among those without asthma in the 8 years before cohort entry. Time was classified into pre-pregnancy and each trimester until delivery. We fit inverse probability weighted Poisson models to estimate marginal relative risks (RRs) for prematurity (delivery <37th week), major malformations, and SGA (birth weight <10th percentile) comparing women with and without asthma, assessing the asthma timing of diagnosis interaction term via a Wald test.

RESULTS

In a cohort of 122,880 deliveries, the increased risk of prematurity, but not SGA, due to incident asthma was higher in those diagnosed during the second (RR, 1.34; 95% confidence interval [CI], 1.08-1.65; Wald P = .05) and third (RR, 1.93; 95% CI, 1.62-2.29; Wald P < .01) trimesters relative to pre-pregnancy (RR, 1.06; 95% CI, 0.98-1.15). A trend toward an increased risk of major malformations was observed in those diagnosed during the first trimester (RR, 1.18; 95% CI, 0.94-1.49; Wald P = .15) than pre-pregnancy (RR, 0.99; 95% CI, 0.92-1.07).

CONCLUSIONS

Asthma diagnosed during, versus before, pregnancy was associated with a greater prematurity risk, suggesting an important role of preconception and prenatal screening.