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* Context.--The terminology used by pathologists to describe and grade dysplasia and premalignant changes of the cervical epithelium has evolved over time. Unfortunately, coexistence of different classification systems combined with nonstandardized interpretive text has created multiple layers of interpretive ambiguity. Objective.--To use natural language processing (NLP) to automate and expedite translation of interpretive text to a single most severe, and thus actionable, cervical intraepithelial neoplasia (CIN) diagnosis. Design.--We developed and applied NLP algorithms to 35 847 unstructured cervical pathology reports and assessed NLP performance in identifying the most severe diagnosis, compared to expert manual review. NLP performance was determined by calculating precision, recall, and F score. Results.--The NLP algorithms yielded a precision of 0.957, a recall of 0.925, and an F score of 0.94. Additionally, we estimated that the time to evaluate each monthly biopsy file was significantly reduced, from 30 hours to 0.5 hours. Conclusions.--A set of validated NLP algorithms applied to pathology reports can rapidly and efficiently assign a discrete, actionable diagnosis using CIN classification to assist with clinical management of cervical pathology and disease. Moreover, discrete diagnostic data encoded as CIN terminology can enhance the efficiency of clinical research. doi: 10.5858/arpa.2021-0410-OA, Population-based cervical screening programs have led to substantial reduction of cervical cancer incidence and mortality worldwide. Cervical cancer screening aims at detecting cervical precancers that can be treated before invasion [...]

BackgroundThe absolute neutrophil count and the immature/total neutrophil ratio (I/T) provide information about the risk of early onset sepsis in newborns. However, it is not clear how to combine their potentially overlapping information into a single likelihood ratio.MethodsWe obtained electronic records of blood cultures and of complete blood counts with manual differentials drawn 4 hours of age and when the pretest probability of infection is close to the treatment threshold.

ObjectiveTo define a quantitative stratification algorithm for the risk of early-onset sepsis (EOS) in newborns ≥ 34 weeks' gestation.MethodsWe conducted a retrospective nested case-control study that used split validation. Data collected on each infant included sepsis risk at birth based on objective maternal factors, demographics, specific clinical milestones, and vital signs during the first 24 hours after birth. Using a combination of recursive partitioning and logistic regression, we developed a risk classification scheme for EOS on the derivation dataset. This scheme was then applied to the validation dataset.ResultsUsing a base population of 608,014 live births ≥ 34 weeks' gestation at 14 hospitals between 1993 and 2007, we identified all 350 EOS cases

To determine whether changing paternity affects the risk of preeclampsia or eclampsia in the subsequent pregnancy and whether the effect depends on a woman's history of preeclampsia/eclampsia with her previous partner, a cohort study was conducted based on 140, 147 women with two consecutive births during 1989–1991 identified through linking of annual California birth certificate data. Among women without preeclampsia/eclampsia in the first birth, changing partners resulted in a 30% increase in the risk of preeclampsia/eclampsia in the subsequent pregnancy compared with those who did not change partners (95% confidence interval: 1.1, 1.6). On the other hand, among women with preeclampsia/eclampsia in the first birth, changing partners resulted in a 30% reduction in the risk of preeclampsia/eclampsia in the subsequent pregnancy (95% confidence interval: 0.4, 1.2). The difference of the effect of changing paternity on the risk of preeclampsia/eclampsia between women with and those without a history of this condition was significant (p < 0.05 for the interaction term). The above estimates were adjusted for potential confounders. These findings suggest that the effect of changing paternity depends on the history of preeclampsia/eclampsia with the previous partner and support the hypothesis that parental human leukocyte antigen sharing may play a role in the etiology of preeclampsia/eclampsia. Am J Epidemiol 2000; 151:57–62. [ABSTRACT FROM PUBLISHER]

To determine whether placental abnormality (placental abruption or placental previa) during pregnancy predisposes an infant to a high risk of sudden infant death syndrome (SIDS), the authors conducted a population-based case-control study using 1989–1991 California linked birth and death certificate data. They identified 2, 107 SIDS cases, 96% of whom were diagnosed through autopsy. Ten controls were randomly selected for each case from the same linked birth-death certificate data, matched to the case on year of birth. About 1.4% of mothers of cases and 0.7% of mothers of controls had either placental abruption or placenta previa during the index pregnancy. After adjustment for potential confounders, placental abnormality during pregnancy was associated with a twofold increase in the risk of SIDS in offspring (odds ratio = 2.1, 95% confidence interval 1.3–3.1). The individual effects of placental abruption and placenta previa on the risk of SIDS did not differ significantly. An impaired fetal development due to placental abnormality may predispose an infant to a high risk of SIDS. Am J Epidemiol 1999; 149: 608–11. [ABSTRACT FROM PUBLISHER]

A response from the author of the article "Mortality Following Conjugal Bereavement And The Effects Of A Shared Environment" in the previous issue, which discusses relationship between bereavement and mortality, is presented.

Objective: To define a quantitative stratification algorithm for the risk of early-onset sepsis (EOS) in newborns ≥ 34 weeks' gestation., Methods: We conducted a retrospective nested case-control study that used split validation. Data collected on each infant included sepsis risk at birth based on objective maternal factors, demographics, specific clinical milestones, and vital signs during the first 24 hours after birth. Using a combination of recursive partitioning and logistic regression, we developed a risk classification scheme for EOS on the derivation dataset. This scheme was then applied to the validation dataset., Results: Using a base population of 608,014 live births ≥ 34 weeks' gestation at 14 hospitals between 1993 and 2007, we identified all 350 EOS cases <72 hours of age and frequency matched them by hospital and year of birth to 1063 controls. Using maternal and neonatal data, we defined a risk stratification scheme that divided the neonatal population into 3 groups: treat empirically (4.1% of all live births, 60.8% of all EOS cases, sepsis incidence of 8.4/1000 live births), observe and evaluate (11.1% of births, 23.4% of cases, 1.2/1000), and continued observation (84.8% of births, 15.7% of cases, incidence 0.11/1000)., Conclusions: It is possible to combine objective maternal data with evolving objective neonatal clinical findings to define more efficient strategies for the evaluation and treatment of EOS in term and late preterm infants. Judicious application of our scheme could result in decreased antibiotic treatment in 80,000 to 240,000 US newborns each year.