Antihypertensive utilization patterns among pregnant persons with pre-existing hypertension in the US: A population-based study.

BACKGROUND: Hypertension among persons with childbearing potential is on the rise. Maintaining proper blood pressure during pregnancy is vital to prevent maternal and neonatal complications. Yet, limited evidence on the risk-benefit of various antihypertensives presents challenges for informed decision-making during this critical period. This study aimed to examine the utilization patterns of different classes of antihypertensives among persons with pre-existing hypertension before, during, and after pregnancy. METHODS: We used MarketScan® Commercial Database 2011-2020 to analyze antihypertensive utilization among pregnant persons aged 12 to 55 identified via a validated algorithm. Pre-existing hypertension was defined as ≥1 inpatient or ≥2 outpatient encounters for hypertension within the 180 days preceding the LMP. Antihypertensive utilization was described during target periods: 0-3 months (0-3M) before pregnancy, 1st/2nd/3rd trimester (T1/2/3), 0-3M, and 4-6M after pregnancy. RESULTS: We identified 1,950,292 pregnancies, of which 20,576 (12,978 live and 7,598 non-live) had pre-existing hypertension. Both groups had similar antihypertensive use (80.1% and 81.0%, respectively) during the 6 months before pregnancy (baseline). For live-birth pregnancies, 13.9% of baseline users discontinued treatment during pregnancy, while 28.9% of non-users initiated antihypertensives during pregnancy, and 17.2% started postpartum. Before pregnancy, the predominant antihypertensives included thiazide diuretics (21.9%), combined α- and ß-blockers (18.4%), and dihydropyridines (16.2%). During pregnancy, thiazide diuretics, cardioselective ß-blockers, and ACE inhibitors declined (T3: 3.0%, 4.2%, and 0.8%). Dihydropyridine use was steady during pregnancy, but preference shifted from amlodipine to nifedipine in T3 (2.2.% vs.10.8%). Central α2-agonists increased during pregnancy (up to 15.2% in T3) compared to both pre- (9.8%) and post-pregnancy (5.7%). ARBs mirrored ACE inhibitors, with less than 1% utilization in later trimesters. Combination agents dropped from 10.8% pre-pregnancy to 0.8% in T3, then rebounded to 7.3% post-pregnancy. CONCLUSION: Research is warranted to evaluate the choice of antihypertensives and optimal timing to switch to safer alternatives, considering maternal and fetal outcomes.

Common teratogenic medication exposures-a population-based study of pregnancies in the United States.

BACKGROUND: Risk mitigation for most teratogenic medications relies on risk communication via drug label, and prenatal exposures remain common. Information on the types of and risk factors for prenatal exposures to medications with teratogenic risk can guide strategies to reduce exposure. OBJECTIVE: This study aimed to identify medications with known or potential teratogenic risk commonly used during pregnancy among privately insured persons. STUDY DESIGN: We used the Merative™ MarketScan® Commercial Database to identify pregnancies with live or nonlive (ectopic pregnancies, spontaneous and elective abortions, stillbirths) outcomes among persons aged 12 to 55 years from 2011 to 2018. Start/end dates of medication exposure and pregnancy outcomes were identified via an adapted algorithm based on validation studies. We required continuous health plan enrollment from 90 days before conception until 30 days after the pregnancy end date. Medications with known or potential teratogenic risk were selected from TERIS (Teratogen Information System) and drug monographs based on the level of risk and quality of evidence (138 with known and 60 with potential risk). We defined prenatal exposure on the basis of ≥1 outpatient pharmacy claim or medical encounter for medication administration during target pregnancy periods considering medication risk profiles (eg, risk only in the first trimester or at a certain dose threshold). Sex hormones and hormone analogs, and abortion and postpartum/abortion hemorrhage treatments were not considered as teratogenic medications because of challenges in separating pregnancy-related indications, nor were opioids (because of complex risk-benefit considerations) or antiobesity medications if their only teratogenic mechanism was weight loss. RESULTS: Among all pregnancies, the 10 medications with known teratogenic risk and the highest prenatal exposures were sulfamethoxazole/trimethoprim (1988 per 100,000 pregnancy-years), high-dose fluconazole (1248), topiramate (351), lisinopril (144), warfarin (57), losartan (56), carbamazepine (50), valproate (49), vedolizumab (28 since 2015), and valsartan (25). Prevalence of exposure to sulfamethoxazole/trimethoprim decreased from 2346 to 1453 per 100,000 pregnancy-years from 2011 to 2018, but prevalence of exposure to vedolizumab increased 6-fold since its approval in 2015. Prenatal exposures in the first trimester were higher among nonlive pregnancies than among live-birth pregnancies, with the largest difference observed for warfarin (nonlive 370 vs live birth 78), followed by valproate (258 vs 86) and topiramate (1728 vs 674). Prenatal exposures to medications with potential teratogenic risk were most prevalent for low-dose fluconazole (6495), metoprolol (1325), and atenolol (448). The largest first-trimester exposure differences between nonlive and live-birth pregnancies were observed for lithium (242 vs 89), gabapentin (1639 vs 653), and duloxetine (1914 vs 860). Steady increases in hydralazine and gabapentin exposures were observed during the study years, whereas atenolol exposure decreased (561 to 280). CONCLUSION: Several medications with teratogenic risk for which there are potentially safer alternatives continue to be used during pregnancy. The fluctuating rates of prenatal exposure observed for select teratogenic medications suggest that regular reevaluation of risk mitigation strategies is needed. Future research focusing on understanding the clinical context of medication use is necessary to develop effective strategies for reducing exposures to medications with teratogenic risk during pregnancy.

Prenatal exposure to teratogenic medications in the era of Risk Evaluation and Mitigation Strategies.

BACKGROUND: Prevention of prenatal exposures to teratogenic drugs is a significant clinical and public health concern. With the enactment of the US Food and Drug Administration Amendments Act in 2007, the US Food and Drug Administration has begun to require manufacturers to implement Risk Evaluation and Mitigation Strategies to prevent prenatal exposures. Among 12 risk evaluation and mitigation strategy drugs, several had predecessor risk mitigation plans (eg, isotretinoin) and some were newly required (eg, mycophenolate). Only a small proportion of teratogenic drugs are currently subject to Risk Evaluation and Mitigation Strategies, and the extent of prenatal exposure to the universe of teratogenic drugs compared with drugs subject to Risk Evaluation and Mitigation Strategies is unknown. Moreover, the effectiveness of such advanced risk mitigation programs in preventing prenatal exposure is not clear. OBJECTIVE: This study aimed to characterize the epidemiology of prenatal exposures to definite and potential teratogens during the risk evaluation and mitigation strategy era. STUDY DESIGN: We constructed a time-series of pregnancies identified from a national private insurance claims database (IBM MarketScan) to estimate prenatal exposures to teratogenic drugs (2006-2017). Pregnancy outcomes, gestational age, and the onset of pregnancy were determined with previously validated algorithms. The Teratology Information Service and Clinical Pharmacology databases were used to identify drugs with definite (n=141) or potential (n=65) teratogenic effects, and drugs with debatable risks such as benzodiazepines, statins, tetracyclines, sex hormones, infertility treatments, and gonadotropin-releasing hormone analogs were excluded. We defined prenatal exposure as ≥1 prescription fill or medical encounter involving administration of drugs with a definite teratogenic risk (including 12 for which there is a "current or discontinued" risk evaluation and mitigation strategy) or a potential teratogenic risk. We evaluated secular trends and modeled the effects of age, preconception exposure, and state healthcare quality rankings on prenatal exposure, adjusting for demographic factors and clinical conditions. RESULTS: The cohort included 3,445,612 pregnancies (2,532,444 live deliveries). Prenatal exposures to definite teratogens decreased slightly during the study years from 1.86 to 1.24 per 100 pregnancies between 2006 and 2017, whereas exposure increased for potential teratogens from 3.40% to 5.33%. Prenatal exposure prevalences were higher during the first trimester and for pregnancies that ended in nonlive outcomes. Drugs subject to Risk Evaluation and Mitigation Strategies had low background utilization and contributed to a small proportion of prenatal exposures (15.1 per 100,000 pregnancies). We also observed fewer prenatal exposures to risk evaluation and mitigation strategy drugs among women of childbearing age who used these treatments (0.14% vs 0.36% for any definite teratogen). Age extremes and low state-level healthcare quality rankings were independent predictors of prenatal exposure. CONCLUSION: Fetuses in more than 1 in 16 pregnancies continued to be exposed to teratogenic drugs during the past decade. Drugs with Risk Evaluation and Mitigation Strategies imposed a small burden of prenatal exposure because of the low background utilization rates and lower pregnancy prevalence among women of childbearing age who used these drugs. Although the declining exposure rates to teratogenic drugs with definite risk are encouraging, the rising prenatal exposure to drugs with potential risk calls for more assessments. Future research is needed to elucidate the health outcomes of fetuses exposed to potential risk drugs, understand the effectiveness of risk evaluation and mitigation strategy programs, and prioritize teratogenic drugs for advanced risk mitigation.

Impact of the Transition from ICD-9-CM to ICD-10-CM on the Identification of Pregnancy Episodes in US Health Insurance Claims Data.

BACKGROUND: Before October 2015, pregnancy cohorts assembled from US health insurance claims have relied on medical encounters with International Classification of Diseases-ninth revision-clinical modification (ICD-9-CM) codes. We aimed to extend existing pregnancy identification algorithms into the ICD-10-CM era and evaluate performance. METHODS: We used national private insurance claims data (2005-2018) to develop and test a pregnancy identification algorithm. We considered validated ICD-9-CM diagnosis and procedure codes that identify medical encounters for live birth, stillbirth, ectopic pregnancy, abortions, and prenatal screening to identify pregnancies. We then mapped these codes to the ICD-10-CM system using general equivalent mapping tools and reconciled outputs with literature and expert opinion. Both versions were applied to the respective coding period to identify pregnancies. We required 45 weeks of health plan enrollment from estimated conception to ensure the capture of all pregnancy endpoints. RESULTS: We identified 7,060,675 pregnancy episodes, of which 50.1% met insurance enrollment requirements. Live-born deliveries comprised the majority (76.5%) of episodes, followed by abortions (20.3%). The annual prevalence for all pregnancy types was stable across the ICD transition period except for postterm pregnancies, which increased from 0.5% to 3.4%. We observed that ICD codes indicating gestational age were available for 86.8% of live-born deliveries in the ICD-10 era compared to 23.5% in the ICD-9 era. Patterns of prenatal tests remained stable across the transition period. CONCLUSION: Translation of existing ICD-9-CM pregnancy algorithms into ICD-10-CM codes provided reasonable consistency in identifying pregnancy episodes across the ICD transition period. New codes for gestational age can potentially improve the precision of conception estimates and minimize measurement biases.

Risk of pregnancy loss in patients exposed to mycophenolate compared to azathioprine: A retrospective cohort study.

PURPOSE: To evaluate the relative risk of pregnancy loss associated with mycophenolate (MPA) vs azathioprine (AZA) use. METHODS: We conducted a retrospective cohort study using the IBM MarketScan Research Databases (2005-2015). Patients with ≥1 MPA or AZA prescription claim during the first trimester were included. The study outcome was pregnancy loss (spontaneous abortion or stillbirth). Potential confounders included age, drug indications, comorbidities, other teratogenic medication use, and gestational age at first MPA or AZA prescription fill. The risk for pregnancy loss was estimated using a generalized estimating equation model with stabilized inverse probability of treatment weighting. In sensitivity analyses, we varied the exposure definition, outcome definition, and the analytical method. RESULTS: Among 111 pregnancies exposed to MPA, 55 resulted in pregnancy loss (49.5%). Among 471 pregnancies exposed to AZA, 113 had pregnancy loss (24.0%). The unadjusted relative risk for pregnancy loss was 2.0 (95% CI 1.6, 2.6), and the adjusted relative risk was 1.9 (95% CI, 1.6, 2.3) compared to AZA. Relative risk estimates were stable in all sensitivity analyses. CONCLUSION: Exposure to MPA during early pregnancy was associated with a 2-fold increase in pregnancy loss risk.

Predicting the probability of survival with mild or moderate neurological dysfunction after in-hospital cardiopulmonary arrest: The GO-FAR 2 score.

BACKGROUND: The Good Outcome Following Attempted Resuscitation (GO-FAR) Score uses pre-arrest factors to predict survival after In-Hospital Cardiac Arrest (IHCA) with minimal neurological dysfunction, (cerebral performance category (CPC) ≤1). Moderate neurological dysfunction (CPC ≤2) may be a more acceptable outcome. OBJECTIVE: To predict survival after IHCA with mild or moderate neurological dysfunction based on pre-arrest factors. METHODS: 52,468 patients with IHCA from 2012-2017. Data was divided into training (44%), testing (22%), and validation (34%) sets. Univariate analysis was used to identify variables with >3% difference in survival with CPC ≤2. These variables carried forward to the multivariate logistic regression model. The most parsimonious model that best classified patients as having a very poor (≤5%), below average (≤10%), average (11%-30%), or above average (>30%) likelihood of survival with CPC ≤2 was chosen. RESULTS: Age >85, admission CPC <2, and non-surgical admission were strongly association with poor survival (-12.1%, -14.4%, and -18%, respectively). Nine variables were included in the logistic regression analysis. The final updated model, GO FAR 2, categorized 6.2% of patients with a very poor predicted survival, 24.8% of patients with a below average predicted survival, and 11.3% with above average predicted survival. The observed survival among those with very poor predicted survival was 4.5%. CONCLUSION: The GO FAR 2 score provides clinicians with a prognostic estimate of the likelihood of a good outcome after IHCA based on pre-arrest patient factors. Future research is required to validate the GO-FAR 2 score.

Prospective validation of the Good Outcome Following Attempted Resuscitation (GO-FAR) score for in-hospital cardiac arrest prognosis.

AIM: We aimed to prospectively validate the Good Outcome Following Attempted Resuscitation (GO-FAR) score, which predicts the likelihood of survival to discharge neurologically intact or with minimal deficits (conscious, alert, and able to work) after in-hospital cardiac arrest (IHCA). METHODS: Inpatients experiencing an index episode of IHCA between 2010 and 2016 in hospitals participating in the Get With the Guidelines® - Resuscitation (GWTG-R) Registry were included. The score's performance was prospectively validated in both all GWTG-R hospitals and in a subset of hospitals not part of the GWTG-R registry when the score was originally developed using prospective data. Score performance was stratified by hospital size, presence of residency training programs, and type of hospital ownership. Discrimination was measured by the c-statistic, calibration using a Hosmer-Lemeshow plot, and classification accuracy by the survival rates in each risk group. RESULTS: A total of 62,131 inpatients in 386 hospital were included. The GO-FAR score had similar discrimination (c-statistic 0.75, 95% CI 0.748-0.758), calibration, and classification accuracy as in the original study. Survival rates were somewhat higher due to a secular increase in survival of IHCA. In hospitals that were not part of the derivation population, the score performed as well as in the hospitals used to derive the score (c-statistic 0.75). The score performed similarly in hospitals of different sizes (c-statistic of 0.80 and 0.75 for hospital with ≤100 and >100 beds, respectively), with and without residency training programs (c-statistics of 0.76 and 0.75, respectively), and with different ownership structures (c-statistic of 0.79 for private, 0.74 for military government, and 0.76 for nonprofit hospital). CONCLUSIONS: The GO-FAR score accurately classifies patients into risk groups based on their likelihood of survival to discharge with a good neurologic outcome following an episode of IHCA. Recalibration may be necessary using different point score cutoffs as IHCA survival increases.

Cancer screening recommendations: an international comparison of high income countries.

BACKGROUND: Recommendations regarding cancer screening vary from country to country, and may also vary within countries depending on the organization making the recommendations. The goal of this study was to summarize the cancer screening recommendations from the 21 countries with the highest per capita spending on healthcare. MAIN BODY: Cancer screening guidelines were identified for each country based on a review of the medical literature, internet searches, and contact with key informants in most countries. The highest level recommendation was identified for each country, in the order of national recommendation, cancer society recommendation, or medical specialty society recommendation. Breast cancer screening recommendations were generally consistent across countries, most commonly recommending mammography biennially from ages 50 to 69 or 70 years. In the USA, specialty societies generally offered more intensive screening recommendations. All countries also recommend cervical cancer screening, although there is some heterogeneity regarding the test (cytology or HPV or both) and the age of initiation and screening interval. Most countries recommend colorectal cancer screening using fecal immunochemical (FIT) testing, while only seven countries recommend general or selective screening for prostate cancer, and a similar number explicitly recommend against screening for prostate cancer. Screening for lung and skin cancer is only recommended by a few countries. Greater per capita healthcare expenditures are not associated with greater screening intensity, with the possible exception of prostate cancer. CONCLUSIONS: Guidelines for cancer screening differ between countries, with areas of commonality but also clear differences. Recommendations have important commonalities for well-established cancer screening programs such as breast and cervical cancer, with greater variation between countries regarding prostate, colorectal, lung, and skin cancer screening. Ideally, recommendations should be made by a professionally diverse, independent panel of experts that make evidence-based recommendations regarding screening based on the benefits, harms, and available resources in that country's context.

Prevalence of and Risk Factors for Oral Human Papillomavirus Infection With Multiple Genotypes in the United States.

BACKGROUND: This study investigated the prevalence of and risk factors for oral human papillomavirus (HPV) infection with multiple genotypes in the United States. METHODS: Data were from the nationally representative 2009-2012 National Health and Nutrition Examination Survey. This analysis comprised 9257 participants for whom data on oral HPV (37 genotypes) and associated risk factors were available. RESULTS: The weighted prevalence of multitype (2-6 types) oral HPV infection was 1.5% (2.5% for men, 0.4% for women) in the whole sample and 19.7% (22.0% for men, 12.1% for women) in those who had any type of oral HPV positivity. Most multitype oral HPV cases (83.8%) harbored one or more oncogenic types. In the adjusted multinominal logistic regression model, being male (relative risk ratio [RRR] = 3.69; 95% confidence interval [CI], 1.57-8.65), being a current cigarette smoker (RRR = 2.57; 95% CI, 1.23-5.36), and having a new sex partner in the past year (RRR = 2.10; 95% CI, 1.03-4.28) were associated with an increased risk of multitype oral HPV infection over single-type HPV infection. CONCLUSIONS: Men, smokers, and those who had new sexual partners were at a significantly higher risk for multitype oral HPV infection.

Association Between Vaginal Douching and Genital Human Papillomavirus Infection Among Women in the United States.

The very few studies that have examined the association between vaginal douching and genital human papillomavirus (HPV) infection have found contrary results. We investigated the associations between douching and numbers of HPV genotypes infecting 1271 participants aged 20-49 years in the 2003-2004 US National Health and Nutrition Examination Survey. After controlling for relevant covariates, douching in the past 6 months was significantly associated with infection by higher numbers of all genital HPV types (relative risk ratio, 1.26; 95% confidence interval, 1.03-1.54) and HPV high-risk types (1.40; 1.09-1.80).

Prevalence of Atypical Pathogens in Patients With Cough and Community-Acquired Pneumonia: A Meta-Analysis.

PURPOSE: Community-acquired pneumonia (CAP), acute cough, bronchitis, and lower respiratory tract infections (LRTI) are often caused by infections with viruses or Streptococcus pneumoniae. The prevalence of atypical pathogens Mycoplasma pneumoniae, Chlamydophila pneumoniae, Legionella pneumophila, and Bordetella pertussis among patients with these illnesses in the ambulatory setting has not been previously summarized. We set out to derive prevalence information from the existing literature. METHODS: We performed a systematic review of MEDLINE for prospective, consecutive-series studies reporting the prevalence of M pneumoniae, C pneumoniae, L pneumophila and/or B pertussis in outpatients with cough, acute bronchitis, LRTI, or CAP. Articles were independently reviewed by 2 authors for inclusion and abstraction of data; discrepancies were resolved by consensus discussion. A meta-analysis was performed on each pathogen to calculate the pooled prevalence estimates using a random effects model of raw proportions. RESULTS: Fifty studies met our inclusion criteria. While calculated heterogeneity was high, most studies reported prevalence for each pathogen within a fairly narrow range. In patients with CAP, the overall prevalences of M pneumoniae and C pneumoniae were 10.1% (95% CI, 7.1%-13.1%) and 3.5% (95% CI, 2.2%-4.9%), respectively. Consistent with previous reports, M pneumoniae prevalence peaked in roughly 6-year intervals. Overall prevalence of L pneumophila was 2.7% (95% CI, 2.0%-3.4%), but the organism was rare in children, with only 1 case in 1,765. In patients with prolonged cough in primary care, the prevalence of B pertussis was 12.4% (95% CI, 4.9%-19.8%), although it was higher in studies that included only children (17.6%; 95% CI, 3.4%-31.8%). CONCLUSIONS: Atypical bacterial pathogens are relatively common causes of lower respiratory diseases, including cough, bronchitis, and CAP. Where surveillance data were available, we found higher prevalences in studies where all patients are tested for these pathogens. It is likely that these conditions are underreported, underdiagnosed, and undertreated in current clinical practice.