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BACKGROUND:When exposure is infrequent, propensity-score matching results in reduced precision because it discards a large proportion of unexposed patients. To our knowledge, the relative performance of propensity-score stratification in these circumstances has not been examined. METHODS:Using an empirical example of the association of first trimester statin exposure (prevalence = 0.04%) with risk of congenital malformations and 1,000 simulated cohorts (n = 20,000) with eight combinations of exposure prevalence (0.5%, 1%, 5%, 10%) and outcome risk (3.5%, 10%), we compared four propensity-score-based approaches to confounding adjustment(1) matching (1:1, 1:5, full), (2) stratification in 10, 50, and 100 strata by entire cohort propensity-score distribution, (3) stratification in 10, 50, and 100 strata by exposed group propensity-score distribution, (4) standardized mortality ratio (SMR) weighting. Weighted generalized linear models were used to derive effect estimates after weighting unexposed according to the distribution of the exposed in their stratum for the stratification approaches. RESULTS:In the empirical example, propensity-score stratification (cohort) approaches resulted in greater imbalances in covariate distributions between statin-exposed and unexposed compared with propensity-score stratification (exposed) and matching. In simulations, propensity-score stratification (exposed) resulted in smaller relative bias than the cohort approach with 10 and 50 strata, and greater precision than matching and SMR weighting at 0.5% and 1% exposure prevalence, but similar performance at 5% and 10%. CONCLUSION:For exposures with prevalence under 5%, propensity-score stratification with fine strata, based on the exposed group propensity-score distribution, produced the best results. For more common exposures, all approaches were equivalent.

Whereas some prior data had suggested a large increase in the risk of cardiac malformations among offspring of women using lithium in early pregnancy, this analysis using a large Medicaid database showed more modest increases in the risk of these complications. In the early 1970s, results from the International Register of Lithium Babies evaluating infants born to mothers who were treated with lithium early in pregnancy 1 , 2 suggested a risk of Ebstein’s anomaly, a right ventricular outflow tract obstruction defect, that was increased by a factor of 400 (on the basis of two cases associated with lithium exposure) and a risk of overall cardiac defects that was increased by a factor of 5. 3 By 1979, the final report included data on 225 infants born to lithium-exposed women; 18 infants had congenital cardiac defects (8%), including 6 with Ebstein’s anomaly (3%). 4 On . . .

Hypertensive disorders complicate up to 10% of pregnancies. Evidence suggests a potential association between maternal hypertensive disorders during pregnancy, particularly preeclampsia, and adverse neurodevelopment in the offspring, but existing studies are subject to limitations. We aimed to assess whether in-utero exposure to preeclampsia/eclampsia negatively impacts academic performance at ages 9, 12 and 15 years. Using individually linked, nationwide data from the Icelandic registries we followed all children born in 1989-2004 (N = 68,580), from birth until the end of 2014, thereof 63,014 (91.9%) took at least one standardized test. Using a stepwise, mixed-effects approach, we modelled the hypothesized relationship while adjusting for maternal, perinatal and childhood variables of interest. We compared test scores, measured on a normalized scale ranging from 0-60 with a mean of 30 and a standard deviation of 10, in the 4th, 7th, and 10th grades, between children exposed to preeclampsia or eclampsia in-utero versus children from normotensive pregnancies in the population. Children exposed to preeclampsia/eclampsia scored lower than those unexposed in mathematics across all grade levels, corresponding to a difference of 0.44 points (95% CI: 0.00, 0.89), 0.59 points (95% CI: 0.13, 1.06) and 0.59 points (95% CI: 0.08, 1.10), respectively. No differences were observed in the language arts. Our findings suggest a minimal effect of maternal preeclampsia/eclampsia on children's academic performance at ages 9, 12 and 15 years. The differences observed in mathematic scores between exposed and unexposed children were minimal, less than one tenth of a standard deviation per measurement occasion.

SARS-CoV-2-related mortality and hospitalizations differ substantially between New York City neighborhoods. Mitigation efforts require knowing the extent to which these disparities reflect differences in prevalence and understanding the associated drivers. Here, we report the prevalence of SARS-CoV-2 in New York City boroughs inferred using tests administered to 1,746 pregnant women hospitalized for delivery between March 22nd and May 3rd, 2020. We also assess the relationship between prevalence and commuting-style movements into and out of each borough. Prevalence ranged from 11.3% (95% credible interval [8.9%, 13.9%]) in Manhattan to 26.0% (15.3%, 38.9%) in South Queens, with an estimated city-wide prevalence of 15.6% (13.9%, 17.4%). Prevalence was lowest in boroughs with the greatest reductions in morning movements out of and evening movements into the borough (Pearson R = −0.88 [−0.52, −0.99]). Widespread testing is needed to further specify disparities in prevalence and assess the risk of future outbreaks. New York City is one of the areas most affected by the SARS-CoV-2 pandemic in the United States, and there has been large variation in rates of hospitalisation and death by city borough. Here, the authors show that boroughs with the largest reduction in daily commutes also had the lowest SARS-CoV-2 prevalence.

Despite the widespread use, only sparse information is available on the safety of gabapentin during pregnancy. We sought to evaluate the association between gabapentin exposure during pregnancy and risk of adverse neonatal and maternal outcomes.BACKGROUNDDespite the widespread use, only sparse information is available on the safety of gabapentin during pregnancy. We sought to evaluate the association between gabapentin exposure during pregnancy and risk of adverse neonatal and maternal outcomes.Using the United States Medicaid Analytic eXtract (MAX) dataset, we conducted a population-based study of 1,753,865 Medicaid-eligible pregnancies between January 2000 and December 2013. We examined the risk of major congenital malformations and cardiac defects associated with gabapentin exposure during the first trimester (T1), and the risk of preeclampsia (PE), preterm birth (PTB), small for gestational age (SGA), and neonatal intensive care unit admission (NICUa) associated with gabapentin exposure early, late, or both early and late in pregnancy. Gabapentin-unexposed pregnancies served as the reference. We estimated relative risks (RRs) and 95% confidence intervals (CIs) using fine stratification on the propensity score (PS) to control for over 70 confounders (e.g., maternal age, race/ethnicity, indications for gabapentin, other pain conditions, hypertension, diabetes, use of opioids, and specific morphine equivalents). We identified 4,642 pregnancies exposed in T1 (mean age = 28 years; 69% white), 3,745 exposed in early pregnancy only (28 years; 67% white), 556 exposed in late pregnancy only (27 years; 60% white), and 1,275 exposed in both early and late pregnancy (29 years; 75% white). The reference group consisted of 1,744,447 unexposed pregnancies (24 years; 40% white). The adjusted RR for major malformations was 1.07 (95% CI 0.94-1.21, p = 0.33) and for cardiac defects 1.12 (0.89-1.40, p = 0.35). Requiring ≥2 gabapentin dispensings moved the RR to 1.40 (1.03-1.90, p = 0.03) for cardiac defects. There was a higher risk of preterm birth among women exposed to gabapentin either late (RR, 1.28 [1.08-1.52], p < 0.01) or both early and late in pregnancy (RR, 1.22 [1.09-1.36], p < 0.001), SGA among women exposed to gabapentin early (1.17 [1.02-1.33], p = 0.02), late (1.39 [1.01-1.91], p = 0.05), or both early and late in pregnancy (RR, 1.32 [1.08-1.60], p < 0.01), and NICU admission among women exposed to gabapentin both early and late in pregnancy (RR, 1.35 [1.20-1.52], p < 0.001). There was no higher risk of preeclampsia among women exposed to gabapentin after adjustment. Study limitations include the potential for residual confounding and exposure misclassification.METHODS AND FINDINGSUsing the United States Medicaid Analytic eXtract (MAX) dataset, we conducted a population-based study of 1,753,865 Medicaid-eligible pregnancies between January 2000 and December 2013. We examined the risk of major congenital malformations and cardiac defects associated with gabapentin exposure during the first trimester (T1), and the risk of preeclampsia (PE), preterm birth (PTB), small for gestational age (SGA), and neonatal intensive care unit admission (NICUa) associated with gabapentin exposure early, late, or both early and late in pregnancy. Gabapentin-unexposed pregnancies served as the reference. We estimated relative risks (RRs) and 95% confidence intervals (CIs) using fine stratification on the propensity score (PS) to control for over 70 confounders (e.g., maternal age, race/ethnicity, indications for gabapentin, other pain conditions, hypertension, diabetes, use of opioids, and specific morphine equivalents). We identified 4,642 pregnancies exposed in T1 (mean age = 28 years; 69% white), 3,745 exposed in early pregnancy only (28 years; 67% white), 556 exposed in late pregnancy only (27 years; 60% white), and 1,275 exposed in both early and late pregnancy (29 years; 75% white). The reference group consisted of 1,744,447 unexposed pregnancies (24 years; 40% white). The adjusted RR for major malformations was 1.07 (95% CI 0.94-1.21, p = 0.33) and for cardiac defects 1.12 (0.89-1.40, p = 0.35). Requiring ≥2 gabapentin dispensings moved the RR to 1.40 (1.03-1.90, p = 0.03) for cardiac defects. There was a higher risk of preterm birth among women exposed to gabapentin either late (RR, 1.28 [1.08-1.52], p < 0.01) or both early and late in pregnancy (RR, 1.22 [1.09-1.36], p < 0.001), SGA among women exposed to gabapentin early (1.17 [1.02-1.33], p = 0.02), late (1.39 [1.01-1.91], p = 0.05), or both early and late in pregnancy (RR, 1.32 [1.08-1.60], p < 0.01), and NICU admission among women exposed to gabapentin both early and late in pregnancy (RR, 1.35 [1.20-1.52], p < 0.001). There was no higher risk of preeclampsia among women exposed to gabapentin after adjustment. Study limitations include the potential for residual confounding and exposure misclassification.In this large population-based study, we did not find evidence for an association between gabapentin exposure during early pregnancy and major malformations overall, although there was some evidence of a higher risk of cardiac malformations. Maternal use of gabapentin, particularly late in pregnancy, was associated with a higher risk of PTB, SGA, and NICUa.CONCLUSIONSIn this large population-based study, we did not find evidence for an association between gabapentin exposure during early pregnancy and major malformations overall, although there was some evidence of a higher risk of cardiac malformations. Maternal use of gabapentin, particularly late in pregnancy, was associated with a higher risk of PTB, SGA, and NICUa.

Objectives To assess the impact of in utero co-exposure to psychotropic medications and opioids on the incidence and severity of neonatal drug withdrawal.Design Observational cohort study.Setting Nationwide sample of pregnancies in publicly insured women in the US, nested in the Medicaid Analytic eXtract (2000-10).Participants 201 275 pregnant women with public insurance who were exposed to opioids around the time of delivery and their liveborn infants.Interventions In utero exposure to psychotropic medications, in particular antidepressants, atypical antipsychotics, benzodiazepines, gabapentin, and non-benzodiazepine hypnotics (Z drugs), with prescriptions filled within the same time window as prescriptions for opioids.Main outcome measure Diagnosis of neonatal drug withdrawal in infants exposed in utero to opioids and psychotropic medications compared with opioids alone.Results The absolute risk for neonatal drug withdrawal ranged from 1.0% in infants exposed in utero to prescription opioids alone to 11.4% for those exposed to opioids co-prescribed with gabapentin. Among neonates exposed in utero to prescription opioids, the relative risk adjusted for propensity score was 1.34 (95% confidence interval 1.22 to 1.47) with concomitant exposure to antidepressants, 1.49 (1.35 to 1.63) with benzodiazepines, 1.61 (1.26 to 2.06) with gabapentin, 1.20 (0.95 to 1.51) with antipsychotics, and 1.01 (0.88 to 1.15) with Z drugs. In utero exposure to two or more psychotropic medications along with opioids was associated with a twofold increased risk of withdrawal (2.05, 1.77 to 2.37). The severity of the withdrawal seemed increased in neonates exposed to both opioids and psychotropic medications compared with opioids alone.Conclusions During pregnancy, the use of psychotropic medications in addition to prescription opioids is common, despite a lack of safety data. The current findings suggest that these drugs could further increase the risk and severity of neonatal drug withdrawal.

Background Selective serotonin reuptake inhibitors (SSRIs) are frequently co-prescribed with opioids, increasing the risk of pharmacokinetic and pharmacodynamic interactions. Hydrocodone, a commonly prescribed opioid metabolized by cytochrome (CYP) 2D6 and CYP3A4, may be affected by enzyme inhibition from certain SSRIs. However, it remains unclear whether all SSRIs pose equal overdose risk or if some may be safer options for patients requiring both medications. Thus, we aimed to evaluate comparative risks of opioid overdose among patients initiating SSRIs while on hydrocodone. Methods This population-based cohort study utilized US public and commercial health insurance claims data from 2004 to 2022 and included patients who initiated a SSRI (citalopram, escitalopram, fluoxetine, paroxetine, or sertraline) while receiving hydrocodone treatment. The outcome was hospitalization or emergency department visit due to opioid overdose. We balanced baseline covariates via propensity score matching weights. A weighted Cox proportional hazards model compared rates across the five SSRIs. Results Among 1,486,583 patients who initiated an SSRI while on hydrocodone, 403,488 (27.1%) initiated sertraline, 348,484 (23.4%) initiated citalopram, 311,375 (21.0%) initiated escitalopram, 258,957 (17.4%) initiated fluoxetine, and 164,279 (11.1%) initiated paroxetine. During a median on-treatment follow-up of 28 days, 1500 primary endpoints occurred. Weighted hazard ratios (HRs) for opioid overdose, using sertraline as the reference, were 1.21 (95% CI 1.02–1.42) for citalopram, 1.19 (1.00–1.41) for escitalopram, 1.29 (1.09–1.54) for fluoxetine, and 1.17 (0.95–1.43) for paroxetine. Using citalopram as the reference, HRs were 0.99 (0.83–1.17) for escitalopram, 1.07 (0.91–1.27) for fluoxetine, and 0.97 (0.79–1.18) for paroxetine. Relative to escitalopram, HRs were 1.09 (0.92–1.30) for fluoxetine and 0.98 (0.80–1.20) for paroxetine, and relative to fluoxetine, the HR was 0.90 (0.74–1.10) for paroxetine. Comparisons among SSRIs other than sertraline showed similar risks of overdose. Intention-to-treat analysis yielded similar findings, although the associations were attenuated. Conclusions In this cohort study, based on data from US healthcare claims databases, initiating citalopram, escitalopram, fluoxetine, or paroxetine while on hydrocodone was associated with an increased risk of opioid overdose compared with sertraline. No substantial risk differences were observed across SSRIs other than sertraline.

To examine the epidemiology of hypertension in women of reproductive age. Using NHANES from 1999-2008, we identified 5,521 women age 20-44 years old. Hypertension status was determined using blood pressure measurements and/or self-reported medication use. The estimated prevalence of hypertension in women of reproductive age was 7.7% (95% confidence interval (CI): 6.9%-8.5%). The prevalence of anti-hypertensive pharmacologic therapy was 4.2% (95% CI 3.5%-4.9%). The prevalence of hypertension was relatively stable across the study period; the age and race adjusted odds of hypertension in 2007-2008 did not differ significantly from 1999-2000 (odds ratio 1.2, CI 0.8 to 1.7, p = 0.45). Significant independent risk factors associated with hypertension included older age, non-Hispanic black race (compared to non-Hispanic whites), diabetes mellitus, chronic kidney disease, and higher body mass index. The most commonly used antihypertensive medications included diuretics, angiotensin-converting enzyme inhibitors (ACE), and beta blockers. Hypertension occurs in about 8% of women of reproductive age. There are remarkable differences in the prevalence of hypertension between racial/ethnic groups. Obesity is a risk factor of particular importance in this population because it affects over 30% of young women in the U.S., is associated with more than 4 fold increased risk of hypertension, and is potentially modifiable.

With increasing rates of opioid overdoses in the US, a surveillance tool to identify high-risk patients may help facilitate early intervention. To develop an algorithm to predict overdose using routinely-collected healthcare databases. Within a US commercial claims database (2011-2015), patients with ≥1 opioid prescription were identified. Patients were randomly allocated into the training (50%), validation (25%), or test set (25%). For each month of follow-up, pooled logistic regression was used to predict the odds of incident overdose in the next month based on patient history from the preceding 3-6 months (time-updated), using elastic net for variable selection. As secondary analyses, we explored whether using simpler models (few predictors, baseline only) or different analytic methods (random forest, traditional regression) influenced performance. We identified 5,293,880 individuals prescribed opioids; 2,682 patients (0.05%) had an overdose during follow-up (mean: 17.1 months). On average, patients who overdosed were younger and had more diagnoses and prescriptions. The elastic net model achieved good performance (c-statistic 0.887, 95% CI 0.872-0.902; sensitivity 80.2, specificity 80.1, PPV 0.21, NPV 99.9 at optimal cutpoint). It outperformed simpler models based on few predictors (c-statistic 0.825, 95% CI 0.808-0.843) and baseline predictors only (c-statistic 0.806, 95% CI 0.787-0.26). Different analytic techniques did not substantially influence performance. In the final algorithm based on elastic net, the strongest predictors were age 18-25 years (OR: 2.21), prior suicide attempt (OR: 3.68), opioid dependence (OR: 3.14). We demonstrate that sophisticated algorithms using healthcare databases can be predictive of overdose, creating opportunities for active monitoring and early intervention.

The authors review the many adverse effects of obesity on pregnancy, including hypertension, diabetes, insulin resistance, subfertility, miscarriage, and congenital abnormalities.