发表机构
Texas State University（德克萨斯州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用System One模型Jev阅读德克萨斯州2017-2025年全部501.8万份警方碰撞叙事，识别出5467起记录妊娠的碰撞（含58起胎儿伤害），灵敏度0.999、特异度1.000，填补了碰撞数据库无妊娠记录的空白。
AI 中文摘要
机动车碰撞是美国导致创伤性胎儿死亡的主要原因，然而没有任何碰撞数据库记录妊娠状态。现有的估计来自具有宽置信区间的全国性调查样本、仅覆盖受伤者的创伤登记处，或少数几个州的记录关联研究。警方叙事文本在现场只要妊娠情况重要就会予以记录，但尚无研究在人群规模上阅读这些文本。我们阅读了德克萨斯州2017年至2025年间所有警方碰撞叙事文本，总计5,018,079份。一个正则表达式筛查标记出6,840个候选案例，Jev（一个经过校准的System One决策模型）在八问题模式下阅读这些案例，返回概率而不生成文本。Jev确认其中5,333份记录了涉及碰撞的妊娠人员，并标注了其角色、妊娠阶段和碰撞后状况。同一模型在存在性问题下阅读其余499,306份文本，以估计筛查遗漏的情况。对按概率分层样本进行的盲法人工判定得出加权灵敏度为0.999，特异度为1.000，据此使用Rogan-Gladen估计量和自助法得出有记录的妊娠碰撞数为5,467起，95%置信区间为5,306至5,577，其中包括58起记录了胎儿伤害的碰撞。个体层面记录得出每1,000名15至49岁女性驾驶员中有1.13至1.45例的比率。与生命统计中的活产预期相比，叙事文本记录了预期怀孕驾驶员的2.56%至3.09%，且记录在案状态与驾驶员自身记录的受伤情况关联最强，比值比为21.7。
英文摘要
Motor-vehicle crashes are a leading cause of traumatic fetal death in the United States, yet no crash database records pregnancy. Existing estimates come from national investigation samples with wide intervals, trauma registries seeing only the injured, or record linkage in a few states. Police narratives record pregnancy whenever it matters at the scene, and no study has read them at population scale. We read every police crash narrative in Texas from 2017 through 2025, 5,018,079 in total. A regular-expression screen flags 6,840 candidates, which Jev, a calibrated System One decision model, reads under an eight-question schema, returning probabilities and no text. It confirms 5,333 as documenting a pregnant person involved in the crash, with role, stage and post-crash condition. The same model reads 499,306 of the remainder under the presence question, to estimate what the screen missed. Blind human adjudication of a probability-stratified sample gives weighted sensitivity 0.999 and specificity 1.000, from which the Rogan-Gladen estimator and a bootstrap give 5,467 crashes with a documented pregnancy, with a 95% interval of 5,306 to 5,577, including 58 crashes documenting fetal harm. Person-level records give a rate of 1.13 to 1.45 per 1,000 female drivers aged 15 to 49. Measured against a live-birth expectation from vital statistics, narratives document 2.56% to 3.09% of expected pregnant drivers, and documented-case status is most strongly associated with the driver's own recorded injury, at an odds ratio of 21.7.
CommentsExtraction schema, pipeline and blind adjudication tool: https://github.com/pozapas/pregnancy-crash-narratives
