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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.

Previous investigations into the cost effectiveness of direct oral anticoagulants only considered individual stroke risk but not bleed risk even though bleeding is an important and potentially fatal side effect for anticoagulated patients. This study aimed to evaluate the cost effectiveness of dabigatran, rivaroxaban, apixaban, and edoxaban vs warfarin in patients with atrial fibrillation with varying stroke/bleed risk profiles over a lifetime horizon. A Markov micro-simulation was adapted to examine the lifetime costs and quality-adjusted survival of five anticoagulants from a US private payer’s perspective. The study hypothetical cohort consisted of 10,000 patients with atrial fibrillation with age, CHA2DS2-VASc, and HAS-BLED scores similar to a commercially insured patient with atrial fibrillation cohort. Model input parameters including the efficacy and safety of each strategy, utilities, and cost were estimated from public sources, published literature, and analysis conducted in the IBM MarketScan database. Lifetime cost, quality-adjusted life-years, and incremental cost-effectiveness ratios were assessed for each treatment strategy. Subgroup analyses stratified by age, stroke risk score alone, bleed risk score alone and both were performed. Uncertainty was assessed by a deterministic sensitivity analysis and a probabilistic sensitivity analysis. The base-case analysis suggested dabigatran was the optimal treatment with an incremental cost-effectiveness ratio of $35,055 per quality-adjusted life-year relative to warfarin. Subgroup analyses stratified by age, stroke risk score, and bleed risk score alone were largely consistent with the base-case analysis. Subgroup analyses stratified by both stroke and bleed risk score showed edoxaban was the preferred treatment in patients with a low stroke and a low or medium bleed risk, and patients with a high stroke and low bleed risk. Apixaban was the preferred treatment in patients with a medium stroke and high bleed risk. Results of the deterministic sensitivity analysis indicate the model results were most sensitive to the drug cost and hazard ratio for stroke and bleeding event. Results of the probability sensitivity analysis showed dabigatran is cost effective vs. other treatments in 32.8% and 42.4% of iterations at a willingness to pay of $50,000/quality-adjusted life-year and a willingness to pay of $100,000/quality-adjusted life year, respectively. From a US private payer’s perspective, dabigatran appears cost effective compared with other anticoagulants. This study indicated risk stratification especially considering both stroke and bleed risk simultaneously is important not only in clinical practice but also in health technology assessment exercises among patients with atrial fibrillation.

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.To predict survival after IHCA with mild or moderate neurological dysfunction based on pre-arrest factors.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 with3% 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.Age85, admission CPC2, 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%.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.

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.

Background Chloroquine or hydroxychloroquine (chloroquine) plus azithromycin is considered as therapy for COVID-19. With benefit evaluations underway, safety concerns due to potential additive effects on QTc prolongation should be addressed. Objective We compared risk of cardiac adverse events between combinations of chloroquine and azithromycin and chloroquine and amoxicillin. Methods We conducted a retrospective cohort study using the IBM MarketScan Commercial Claims and Medicare Supplemental Databases, 2005–2018. We included autoimmune disease patients aged ≥18 years initiating azithromycin or amoxicillin for ≥5 days during chloroquine treatment. Patients had continuous insurance coverage ≥6 months before combination use until 5 days thereafter or inpatient death. Two outcomes were sudden cardiac arrest/ventricular arrhythmias (SCA/VA) and cardiac symptoms. We followed patients for up to 5 days to estimate hazard ratios (HR). Covariates were adjusted using stabilized inverse probability treatment weighting. Results We identified two SVC/VA events among >145,000 combination users. The adjusted incidence of cardiac symptoms among azithromycin and amoxicillin users was 276 vs 254 per 10,000 person-years with an adjusted HR of 1.10 (95%CI, 0.62–1.95). Conclusion Combination use of chloroquine and azithromycin at routine doses did not show pronounced increases in arrhythmias in this real-world population, though small sample size and outcome rates limit conclusions., Highlights • Chloroquine/hydroxychloroquine plus azithromycin is a potential therapy for COVID19. • Each of these drugs is known with an increased risk of QTc prolongation. • This combination may have potential additive effects on QTc prolongation. • This combination did not show pronounced increases in arrhythmias in our study. • We caution against using this combination for COVID-19 until further safety evidence.

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.

Introduction Both non-Group A streptococcal (non-GAS) pharyngitis and Group A streptococcal (GAS) pharyngitis are commonly found in patients with sore throat. It is not known whether or not they present with similar signs and symptoms compared to patients with non-streptococcal pharyngitis. Methods MEDLINE was searched for prospective studies that reported throat culture for both GAS and non-GAS as a reference standard, and reported at least one sign, symptom, or the Centor score. Summary estimates of sensitivity, specificity, likelihood ratios (LR+ and LR-), and diagnostic odds ratios (DOR) were calculated using a bivariate random effects model. Summary receiver operating characteristic (ROC) curves were created for key signs and symptoms. Results Eight studies met our inclusion criteria. Tonsillar exudate had the highest LR+ for both GAS and non-GAS pharyngitis (1.53 versus 1.71). The confidence intervals of sensitivity, LR+, LR-, and DOR for all signs, symptoms, and the Centor score between two groups overlapped, with the relative difference between sensitivities within 15% for arthralgia or myalgia, fever, injected throat, tonsillar enlargement, and tonsillar exudate. Larger differences in sensitivities were observed for sore throat, cervical adenopathy, and lack of a cough, although the difference for lack of a cough largely due to a single outlier. Discussion Signs and symptoms of patients with GAS and non-GAS pharyngitis are generally similar. No signs or symptoms clearly distinguish GAS from non-GAS infection. Further work is needed to determine whether Group C streptococcus is a pathogen that should be treated.

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.

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.

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.