Antithrombin deficiency, venous thromboembolism risk, and peripartum antithrombin supplementation: A real-world analysis of delivery encounters from 2015–2024
Bibliographic record
Abstract
Abstract Background Pregnant individuals with antithrombin (AT) deficiency have an increased risk for thromboembolic complications during pregnancy, delivery, and postpartum. Overall, the risk of venous thromboembolism (VTE) is approximately five times higher in pregnant women than in non-pregnant women. VTE, including pulmonary embolism, is a leading cause of pregnancy-related mortality in the US and is associated with significant long-term morbidity. However, optimal management strategies, including the role of antithrombin concentrate (ATc) in this high-risk population, remain unclear, with current recommendations based primarily on expert consensus and case reports. We conducted a retrospective cohort analysis to describe real-world ATc use and assess thromboembolic outcomes in pregnant individuals with AT deficiency, including those with persistently low AT levels at delivery. Methods We utilized electronic health record data from the TriNetX Dataworks US network to identify a study population comprising pregnant individuals meeting the following inclusion criteria: (1) presence of an inpatient delivery encounter between Jan 1, 2015—Dec 31, 2024; (2) history of an AT level ≤80% within the 9 months leading up to the delivery encounter; and (3) history of diagnosed primary thrombophilia, as determined by International Classification of Diseases codes. We evaluated demographic and clinical characteristics, including maternal age and obstetric comorbidity burden, using the Obstetric Comorbidity Index (OBCMI), a validated scoring system that estimates the risk of maternal morbidity based on pre-existing and pregnancy-related conditions. We also examined the association between peripartum ATc administration and venous thromboembolism (VTE), with descriptive statistics used to compare clinical and outcome variables between ATc and non-ATc encounters. Results We identified a total of 154 delivery encounters from 114 patients impacted by AT deficiency, corresponding to approximately 1.5 deliveries per year, among which 13.6% (n=21) involved ATc administration. The median maternal age at delivery was 31 years [25th, 75th percentiles: 27, 35]. OBCMI scores were similar between groups, with an overall median of 26 [17, 40]. Deliveries involving ATc use had higher rates of VTE history (57.1% vs. 39.1%). To draw clinically relevant comparisons, we focused on a subgroup of delivery encounters with AT levels measured during the hospitalization. Among encounters with peripartum AT levels ≤80% (n=14), 71.4% (n=10) involved ATc use. In this subgroup, peripartum VTE occurred in 0% of ATc-treated encounters (n=0/10) compared to 25.0% (n=1/4) in those without ATc. Restricting encounters with peripartum AT levels ≤60% (n=9), an even higher proportion received ATc (77.8%, n=7). In this subgroup, peripartum VTE occurred in 0% (n=0/7) of ATc-treated encounters compared to 50.0% (n=1/2) in those without ATc. Of note, among encounters with AT levels ≤60% at delivery, LMWH was also used at some point during the hospitalization in 100% (n=7) of ATc-administered cases and 50.0% (n=1) of non-ATc cases. Conclusions In a sample of delivery encounters for obstetric patients with AT deficiency, ourfindings demonstrate that in concert with peripartum LMWH, ATc use may be associated with lower rates of VTE and related complications, particularly in those with persistently low peripartum AT levels. ATc-treated encounters more often included a history of VTE and lower baseline AT levels. While these findings are not definitive due to the small sample size and non-randomized nature of the comparison, these real-world data support the safety and efficacy of ATc in obstetric patients with AT deficiency, consistent with current expert guidelines for selected cases.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".