Commutability assessment of a certified reference material (CRM) intended for use as a secondary calibrator should be performed by the CRM producer at the time the material is originally prepared. Assessment typically includes several in-vitro diagnostic (IVD) measurement procedures (MPs) in common use in medical laboratories. Due to logistical constraints, it is usually not possible to include all existing IVD-MPs in a commutability assessment. In addition, a new IVD-MP (IVD-MP(n)) may be introduced into the market after a commutability assessment was performed for a given CRM. Here we provide a recommendation how to assess commutability of an existing CRM for use with an IVD-MP(n) that was not included in the original commutability assessment. The study design follows the same principles as a full commutability assessment, but it includes only the IVD-MP(n) and fewer additional comparator MP(s) for which the CRM's commutability with clinical samples was previously demonstrated. When no reference measurement procedure (RMP) is available, or when the logistics make an RMP difficult to use, other IVD-MP(s) that were part of the original commutability assessment for the CRM should be used as comparator MP(s). When selecting a comparator IVD-MP, its performance must be carefully considered and its selectivity for the measurand should be equivalent to that of the IVD-MP(n). The CRM should have had negligible noncommutability bias with the comparator IVD-MP in the original commutability assessment. When the existing CRM meets the commutability criterion for IVD-MP(n), the CRM can be used in the calibration hierarchy of the IVD-MP(n).

BACKGROUND: Alcohol use during pregnancy might be a risk factor for some congenital heart defects (CHDs), but CHD prevalence among children with fetal alcohol spectrum disorders (FASDs) is not well understood. We used two administrative databases to explore CHD prevalence among U.S. children with and without FASDs. METHODS: We limited 2016-2022 Merative™ MarketScan® Multi-State Medicaid and Commercial data to children ≤ 17 years old with ≥ 1 year of continuous enrollment with complete data on mental health and substance use services. CHD prevalence was calculated by FASD status, overall and by age group, using log-binomial prevalence ratios (PRs) and 95 % confidence intervals (CIs). Analyses were repeated after matching on enrollment length, and age and year at the start of enrollment. In the Medicaid sample, we also stratified by demographic characteristics and analyzed severe and non-severe CHD diagnoses separately. Multidimensional bias analysis considered the influence of unmeasured prenatal tobacco exposure. RESULTS: Among 8732,345 children in the Medicaid sample, 5.2 % with FASDs and 1.0 % without FASDs had CHDs (matched cohort PR = 3.4 [CI: 2.8, 4.1]). PRs were similar when stratified by sex and race and ethnicity, and when looking at exclusively severe or non-severe CHDs. Among 10,567,765 children in the commercial claims sample, 3.0 % with FASDs and 0.6 % without FASDs had CHDs (matched cohort PR= 4.6 [CI: 3.3, 6.4]). CONCLUSION: CHDs were more common among children with FASDs compared to those without FASDs in two administrative database samples. Increased provider awareness about CHDs as a potential FASD comorbidity may improve timely CHD care.

BACKGROUND: Hormonal contraceptive use by women with inflammatory bowel disease (IBD) might affect risk of adverse outcomes or contraceptive effectiveness. Our objective was to update a previous systematic review on the safety and effectiveness of contraceptive use among women with IBD. METHODS: We searched multiple databases from inception through July 15, 2024 for articles on contraception and IBD. Outcomes were IBD disease activity or relapse, other adverse health outcomes, and oral contraceptive (OC) effectiveness. We assessed risk of bias for each study and certainty of evidence for most outcomes. RESULTS: Fifteen articles met our inclusion criteria; 8 were new. Twelve had high risk of bias and three moderate risk. One cohort study found lower odds of IBD symptoms among hormonal contraceptive users compared with non-hormonal users, but higher odds of intestinal inflammation over one year. Nine cohort studies found inconsistent results regarding OC use and disease activity or relapse, with increased and decreased associations; most were not statistically significant. Two cohort studies found no statistically significant associations between OC use and VTE among IBD patients. One study found no statistically significant association between OC use and abnormal cervical smears. Two pharmacokinetic studies suggested no differences in plasma concentrations of steroid hormones after oral ingestion among participants with and without IBD. We found no evidence examining risk of osteoporosis or osteopenia among women with IBD using contraception. CONCLUSIONS: Limited evidence suggested inconsistent findings for increased risk of disease activity or relapse among women with IBD using hormonal contraception (very low certainty of evidence), no differences in other adverse events (very low certainty of evidence), and no differences in contraceptive hormone concentrations.

Data-to-Care (D2C) is a strategy that uses HIV surveillance data or other data sources to identify out-of-care (OOC) persons with HIV (PWH) and link or re-engage them in care to improve viral suppression (VS). While some evidence suggests D2C is effective, no comprehensive systematic review has been published. This review aims to determine the effectiveness of D2C. A systematic search in five databases (i.e., MEDLINE, EMBASE, PsycINFO, CINAHL, sociological abstracts) identified 3868 U.S. studies published between January 2009 and January 2021 that described D2C interventions and measured HIV care outcomes. Two reviewers screened titles/abstracts, reviewed full reports for eligibility, and abstracted data. Risk of bias was assessed using the Mixed Methods Appraisal Tool, and included studies were synthesized quantitatively and qualitatively (Protocol registered on PROSPERO ID = CRD42020173095). Thirty-four studies with 30 unique interventions were identified. Two different meta-analyses, each with six interventions, found that D2C approached significance in improving engagement in care (Relative Risk (RR) 95% CI 1.18 [0.99 to 1.41]) and VS (RR 95% CI 1.44 [0.99 to 2.09]). Studies that could not be incorporated into the meta-analyses, also showed improvements in engagement in care (median percent [IQI]: 63% [45% to 81%], 18 interventions) and VS (median percent [IQI]: 39% [25% to 57%], 14 interventions). Overall, this systematic review suggests that D2C may enhance HIV care outcomes, emphasizing the need for effective strategies to identify and engage OOC persons in care.

Introduction: The 2022 Behavioral Risk Factor Surveillance System introduced an optional module called social determinants and health equity to address health-related social needs, thereby supporting studies of social determinants of health. There were nonignorable nonresponses to the social determinants and health equity module. Methods: Nonresponse referred to an interviewee who completed the Behavioral Risk Factor Surveillance System core survey but chose not to answer any of the social determinants and health equity module questions. The study included 2022 Behavioral Risk Factor Surveillance System participants from 39 states; Washington, DC; and 2 territories. The sequential multiple imputation approach was used to impute the household income. Multivariable logistic regression was used to estimate the propensity of not answering any questions in social determinants and health equity. A nonresponse adjustment factor was developed for each state using a propensity score estimated from the logistic regression model. Results: Florida, California, and New Jersey had the highest nonresponse rates at 29.3%, 26.4%, and 25.6%, respectively. After excluding the outlier Puerto Rico, the median value of nonresponse adjustment factors for states ranged from 1.09 in Idaho to 1.67 in Florida. Conclusions: The nonresponse adjustment will mitigate the nonresponse bias in the analysis of social determinants and health equity data. The adjustment factor developed by the authors will be useful for analysts from various states, programs, and institutions studying social determinants and health equity. © 2025

Artificial intelligence (AI) holds significant potential to transform HIV prevention and treatment through the application of advanced technologies such as machine learning (ML), deep learning (DL), and generative AI (Gen AI). These technologies can enhance the monitoring, management, and analysis of vast and complex HIV-related datasets, enabling more timely predictions of potential risks and improving HIV care strategies. AI is poised to streamline HIV prevention interventions by increasing workforce efficiency, supporting expanded accessibility and sustainability of preexposure prophylaxis (PrEP) care in nontraditional settings, and supporting clinical decision-making. Additionally, when utilized within HIV care systems, AI can help close gaps in diagnosis, treatment, and continuous care engagement. However, to optimize AI's potential in HIV prevention, careful implementation is crucial. Challenges such as reducing bias, ensuring ethical standards (including health privacy standards) are maintained, and mitigating risks like AI hallucinations must be addressed. Thoughtful integration, community consultation, and continuous evaluation will be critical to ensuring that AI plays a beneficial role in HIV prevention and drives innovations that lead to more equitable health outcomes. This editorial review explores AI's transformative potential, focusing on the US CDC's key public health strategies for HIV prevention. When aligning with public health strategies - particularly in countries supported by initiatives like President's Emergency Plan for AIDS Relief (PEPFAR) - AI can contribute significantly to global efforts to end the HIV epidemic. It offers a vision for AI's future application in HIV prevention, emphasizing the need for a holistic and syndemic approach to improving HIV prevention worldwide.

OBJECTIVE: We sought to assess whether, among women with liver disease, there is an increased risk of adverse health effects with use of hormonal contraception (HC). METHODS: We conducted a systematic review of six databases from database inception through December 13, 2022. We searched for articles that examined changes in liver lesions and acute and chronic liver disease with use of HC or after discontinuation of HC. We assessed risk of bias for each study and certainty of evidence for all outcomes. RESULTS: Thirteen articles met inclusion criteria, one with low risk of bias and the others with high risk of bias: three studies (four articles) were of women with focal nodular hyperplasia (FNH), five studies were of hepatocellular adenoma (HCA) and four studies were of acute or chronic hepatitis. The size and/or number of FNH lesions were generally not influenced by HC use. HCA progression was generally higher among current combined oral contraception (COC) users than those who discontinued, and lesions were stable or regressed in most women who discontinued COC or used progestin-only contraception. Studies found that viral hepatitis generally did not progress or increase in severity with use of COC. CONCLUSION: Overall, a limited body of evidence suggested changes in FNH lesions were independent of hormonal contraceptive use. Estrogen-containing contraceptive method use was associated with HCA lesion progression; lesions generally remained stable with progestin-only contraceptive use. COC use did not increase progression or severity of disease among those with viral hepatitis. The certainty of evidence for all outcomes was very low. IMPLICATIONS: Liver conditions such as liver lesions, viral hepatitis, and cirrhosis are increasingly common in women of reproductive age. Information in this review can be used by health care providers when counseling women with liver disease about safe use of contraception.

Verbal autopsy (VA) algorithms are routinely used to determine individual-level causes of death (COD) in many low-and-middle-income countries. The individual CODs are then aggregated to derive population-level cause-specific mortality fractions (CSMF), which are essential to in-forming public health policies. However, VA algorithms frequently misclas-sify COD and introduce bias in CSMF estimates. A recent method, VA-calibration, can correct for this bias using a VA misclassification rate matrix estimated from paired data on COD from both VA and minimally invasive tissue sampling (MITS) from the Child Health and Mortality Prevention Surveillance (CHAMPS) Network. Due to the limited sample size, CHAMPS data are pooled across all countries, implicitly assuming that the misclassifi-cation rates are homogeneous. In this research we show that the VA misclassification matrices are sub-stantially heterogeneous across countries, thereby biasing the VA-calibration. We develop a coherent framework for modeling country-specific VA mis-classification matrices in data-scarce settings. We first introduce a novel base model to parsimoniously characterize misclassifications via two latent mechanisms—intrinsic accuracy and systematic preference. We prove that these mechanisms are identifiable from the data and manifest as a form of in-variance in certain misclassification odds, a pattern evident in the CHAMPS data. Then we expand from this base model, adding higher complexity and country-specific heterogeneity via interpretable effect sizes. Shrinkage priors balance the bias-variance trade-off by adaptively favoring simpler models. We publish uncertainty-quantified estimates of VA misclassification rates for six countries. This effort broadens VA-calibration’s future applicability and strengthens ongoing efforts of using VA for mortality surveillance. © Institute of Mathematical Statistics, 2025.

IMPORTANCE: The test-negative design (TND) has been widely used to assess postmarketing COVID-19 vaccine effectiveness but requires further evaluation for this application. OBJECTIVE: To determine whether the TND reliably evaluates vaccine effectiveness against symptomatic COVID-19 using placebo-controlled vaccine efficacy randomized clinical trials (RCTs). DESIGN, SETTING, AND PARTICIPANTS: This secondary cross-protocol analysis constructed TND study datasets from study sites in 16 countries across 5 continents using the blinded phase cohorts of 5 harmonized phase 3 COVID-19 Prevention Network RCTs: COVE (Coronavirus Vaccine Efficacy and Safety), AZD1222, ENSEMBLE, PREVENT-19 (Prefusion Protein Subunit Vaccine Efficacy Novavax Trial COVID-19), and VAT00008. Participants included adults who received the intended number of doses, experienced COVID-19-like symptoms, and obtained SARS-CoV-2 testing. Start dates ranged from July 27, 2020, to October 19, 2021; data cutoff dates ranged from March 26, 2021, to March 15, 2022. Statistical analysis was performed from May 11, 2023, to February 25, 2025. INTERVENTIONS: Participants received vaccines consisting of messenger RNA-1273 (COVE; 2 doses 28 days apart), ChAdOx1 nCoV-19 (AZD1222; 2 doses 28 days apart), Ad26.COV2.S (ENSEMBLE; 1 dose), NVX-CoV2373 (PREVENT-19; 2 doses 21 days apart), CoV2 preS dTM-AS03 (VAT00008; D614) (2 doses 21 days apart), or CoV2 preS dTM-AS03 (D614 plus B.1.351) (VAT00008; 2 doses 21 days apart) or placebo. MAIN OUTCOMES AND MEASURES: Main outcomes were symptomatic COVID-19 according to each trial's primary efficacy definition and the Centers for Disease Control and Prevention definition. Vaccine effectiveness was estimated using targeted maximum likelihood estimation under a semiparametric logistic regression model and ordinary logistic regression. Noncase exchangeability, a core TND assumption for unbiased estimation, was also assessed by estimating vaccine efficacy against non-COVID-19 illness. RESULTS: Among the 12 157 participants included in the analysis, mean (SD) age was 45 (15) years, 6414 were female (53%), 5858 were vaccinated (48%), 2835 experienced primary COVID-19 (23%), and 2992 experienced Centers for Disease Control and Prevention-defined COVID-19 (25%). TND vaccine effectiveness estimates were concordant with RCT vaccine efficacy estimates (concordance correlation coefficient, 0.86 [95% CI, 0.58-0.96] for both outcomes). The semiparametric method had 48% smaller variance estimates than ordinary logistic regression. Noncase exchangeability was generally supported with a median vaccine efficacy against non-COVID-19 illness of 7.7% (IQR, 2.7%-16.8%) across trial cohorts and most 95% CIs including 0. CONCLUSIONS AND RELEVANCE: In this cross-protocol analysis, the TND provided reliable inferences on COVID-19 vaccine effectiveness in health care-seeking populations for multiple vaccines and symptom definitions when confounding and selection bias were absent. A machine-learning approach for robust confounding control in postmarketing TND studies was also introduced.

PURPOSE: Studies of influenza vaccination during pregnancy and major birth defects generally provide reassuring findings. To maintain public confidence, it is important to continue evaluating the safety of maternal vaccination using well characterized, population-based data. This study extended previous research to examine associations between maternal influenza vaccination and selected birth defects using data from the Birth Defects Study To Evaluate Pregnancy exposureS, a US, multisite case-control study. METHODS: Mothers of case children (diagnosed with a birth defect) and control children (without a birth defect diagnosis) were identified from population-based birth defect surveillance programs and recruited to complete a telephone interview. Data from 2675 case and 1575 control mothers (participants) with deliveries during 2014-2019 were analyzed. Influenza vaccination exposure during the critical exposure period (one month before pregnancy through the first pregnancy month [B1P1] for spina bifida or through the third pregnancy month [B1P3] for other selected birth defects) was assessed controlling for several participant covariates. Logistic regression with propensity score adjustment was used to estimate adjusted odds ratios (aORs) and 95 % confidence intervals (CIs). Several secondary analyses were conducted. A probabilistic bias analysis examined the effect of exposure misclassification. RESULTS: The aOR observed between B1P1 influenza vaccination exposure and spina bifida was 0.9 (95 % CI: 0.4-2.0). The aORs for B1P3 exposure and other selected birth defects examined ranged from 0.4 to 1.3, with 95 % CIs including the null except those for cleft lip ± cleft palate (aOR: 0.6; 95 % CI: 0.4-0.9) and gastroschisis (aOR: 0.4; 95 % CI: 0.2-0.7). Results from secondary analyses were similar to the primary analyses, and those from probabilistic bias analysis were similar to respective primary and secondary analyses. CONCLUSION: Findings showed no statistically significant positive associations between influenza vaccination and the selected birth defects, supporting public health efforts to promote optimal vaccination coverage among pregnant women.

OBJECTIVES: To systematically review evidence on whether medications with smooth muscle relaxant properties improve patient and provider outcomes for intrauterine device (IUD) placement. STUDY DESIGN: We searched multiple databases through August 2022 for randomized clinical trials assessing smooth muscle relaxants for IUD placement. Primary outcomes were pain experienced with IUD placement, provider ease of placement, need for adjunctive placement measures, placement success, patient satisfaction with procedure, medication side effects occurring before clinic discharge, and adverse events occurring before clinic discharge. We extracted data from included articles, assessed risk of bias for each trial, narratively summarized results, and determined certainty of evidence for all outcomes. RESULTS: Five trials met inclusion criteria; four trials had low risk of bias and one had moderate risk. Two trials of topical nitroprusside gel or nitroglycerin ointment found no differences in patient pain, provider ease of placement, patient satisfaction, placement success, side effects, or adverse events. One trial suggested that drotaverine plus mefenamic acid reduced patient pain but did not improve placement success. Two trials suggested that isonicotinic acid hydrazide reduced patient pain, improved provider ease of placement and patient satisfaction, reduced need for analgesia and for cervical dilation (in one trial) and did not increase side effects; neither trial reported improved placement success. CONCLUSIONS: Evidence on smooth muscle relaxants for IUD placement remains sparse with inconsistent findings across specific medications. Certainty of evidence for all outcomes was low for topical nitroprusside gel and nitroglycerin ointment, very low for drotaverine plus mefenamic acid, and mostly high for isonicotinic acid hydrazide. IMPLICATIONS: Before IUD placement, healthcare providers can counsel patients on the potential for pain during placement and options for pain management. However, more evidence is needed on specific smooth muscle relaxants to determine their effectiveness as an intervention for IUD placement.

Disease burden studies commonly use data from electronic health records (EHRs) or community surveys. Quantitative bias assessments of these study designs are needed. We compared two studies on acute gastroenteritis (AGE) burden conducted in an integrated healthcare system in Oregon and Washington, USA. EHRs were used to identify AGE patients who sought care during July 2014 - June 2016 and determine the incidence of medically attended AGE (MAAGE). Members from the same health care system were surveyed during September 2016 - September 2017 to estimate community AGE incidence. MAAGE incidence was calculated using the rate of reported healthcare seeking among survey respondents and compared to the estimate derived from the EHR study. Survey respondents' EHR data were used to conduct a bias analysis. MAAGE incidence from survey respondents was 6.1 times higher than the EHR derived MAAGE estimate. Among survey respondents who self-reported contacting KPNW for an AGE episode, 36.3% had an AGE-coded encounter in the EHR during the same timeframe, and among those who reported no contact (either no AGE or AGE without medical attention), 2.6% did have an AGE-coded encounter. Potential noninfectious explanations for symptoms were reported by 35% of ill survey respondents. We quantify misclassification bias in both studies and discuss other potential sources of bias. Researchers should consider these biases when designing disease burden studies and consider including sensitivity analyses in published work.

OBJECTIVES: Thrombophilia is associated with an elevated risk of thrombosis, which may be further elevated with use of hormonal contraception. Our objective was to update a previously published systematic review on thrombosis risk with use of hormonal contraception among women with thrombophilia. STUDY DESIGN: We conducted a systematic review of five databases from database inception through December 8, 2022. We searched for articles that examined risk of venous thromboembolism (VTE) or arterial thromboembolism (ATE) in women with thrombophilia using hormonal contraception compared with women using non-hormonal or no contraception. We assessed risk of bias for each study and certainty of evidence for all outcomes. RESULTS: Eighteen articles met inclusion criteria; four had moderate risk of bias and 14 had high risk of bias. Odds of VTE in women with factor V Leiden (FVL) mutation or prothrombin (PT) gene mutation were elevated in combined oral contraception (COC) users vs non-users. Odds of VTE were elevated in COC users with FVL mutation, PT gene mutation, both FVL and PT mutations, antithrombin (AT) deficiency, or protein C deficiency compared with non-users without the mutation. Odds of stroke were elevated in COC users with FVL mutation compared with non-users without the mutation. Evidence was mixed on whether risk was elevated in women with protein S deficiency using COC compared with non-use. One study found elevated odds of VTE in women with FVL mutation but not women with PT gene mutation using progestin-only contraception (POC), compared with non-users without the mutation. CONCLUSIONS: Overall, studies found elevated odds of VTE and ATE in women with thrombophilia using COC compared with non-users without thrombophilia. The certainty of evidence for all outcomes is low. Evidence is also limited by small numbers of women and minimal evidence on use of patch, ring, or POC, and is insufficient to assess differential risk by all thrombophilia types. IMPLICATIONS: Use of estrogen-containing hormonal contraception might further elevate risk of thrombosis among women with thrombophilia. Further study is needed on safety of POC use in women with thrombophilia.

Background: Performance of thyroid function assays can vary significantly. To address this issue, the Centers for Disease Control and Prevention (CDC) Clinical Standardization Programs conducted an interlaboratory comparison of free thyroxine (fT4) immunoassays (IAs) and laboratory-developed tests (LDTs). This assessment aimed to determine the current performance characteristics of these assays as a first step toward measurement standardization. Thyrotropin (TSH) IAs were also evaluated. Methods: Assays measured 41 blinded individual-donor sera, including a sample from a pregnant woman (for fT4 analysis only) and three serum pools, with 11.3-32.1 pmol/L (0.881-2.49 ng/dL) fT4 and 0.337-21.6 mIU/L TSH in duplicate over 2 days. Passing-Bablok regression analysis performed pre-recalibration compared assays performance to the CDC fT4 reference measurement procedure (RMP) or TSH all-lab mean (ALM). Additionally, the impact of linear regression-based recalibration of assays to the CDC fT4 RMP or TSH ALM was estimated. Inter-assay agreement of sample classification according to the assay-specific reference interval (RI) was assessed pre- and post-recalibration. Results: A total of 21 fT4 and 17 TSH assays participated. Pre-recalibration, median biases of TSH measurements to the ALM were -1.2% [confidence interval or CI -1.8% to -0.4%], and good classification agreement among TSH assays was observed. fT4 assays all showed a negative median bias to the RMP, with higher bias among IAs (median: -20.3%, CI [-21.5% to -19.4%]) than LDTs (median: -4.5%, [CI -6.1% to -3.2%]). Of the individual-donor sera, only 21 out of 40 samples were classified uniformly by all fT4 assays, indicating poor inter-assay agreement. Post-recalibration, agreement improved to 33 out of 40 individual-donor sera correctly classified by all tested IAs and LDTs. Similar improvement in post-recalibration median percent bias was observed for fT4 IAs (median: -0.2, [CI -1.2% to 0.6%]) and LDTs (median: -0.3%, [CI -2.5% to 1.4%]). Conclusions: The comparison among fT4 assays emphasizes the need for measurement standardization to improve accuracy and comparability. This and previous studies demonstrate the possibility to develop common fT4 RIs via standardization, enabling the use of evidence-based clinical guidelines universally in patient care. Recalibration can effectively address high variability in fT4 assays, ensuring consistent diagnostic classification.

Introduction: Diabetes is the seventh leading cause of death in the United States, impacting over 37 million people. Accurate glucose measurements are critical for effective diabetes management. A reliable candidate reference measurement procedure (cRMP) for assessing the analytical performance of glucose tests performed in patient care is essential for ensuring measurement accuracy. Methods: We have developed a gas chromatography-mass spectrometry (GC–MS)-based cRMP for glucose in human serum. In this procedure, glucose is measured as the aldononitrile acetate derivative and quantitated using a 13C6-glucose internal standard. Results: Analytical selectivity was achieved through chromatographic separation and monitoring the quantitation ion/confirmation ion ratios in samples. With bias ranging from −0.79 % to 0.67 % for eight levels of serum-based certified reference materials from the National Institute of Standards and Technology (NIST) and Laboratoire national de métrologie et d'essais (LNE) and total CVs of 1.11 %, 0.68 % and 0.74 % at the low, medium, and high glucose concentration levels, respectively, the cRMP provided excellent accuracy and precision. The calibration curve was linear throughout the 13.51–378.21 mg/dL [0.75–21 mmol/L] measurement range (R2 = 0.9999), with a mean slope of 270.73 (95 % CI, 270.19 to 271.27) and an intercept of 0.021 (95 % CI, −0.157 to 0.199). The limit of detection was 0.25 mg/dL (0.014 mmol/L) and the limit of quantitation was 0.83 mg/dL (0.046 mmol/L). Conclusion: The described GC–MS method, with metrological traceability to the International System of Units (SI), provides highly accurate and precise measurements of glucose in human serum. © 2025

OBJECTIVES: To systematically review literature on whether hormonal contraception following ulipristal acetate (UPA) for emergency contraception decreases the effectiveness of either drug. STUDY DESIGN: We searched multiple databases through December 2022 for studies assessing the interaction between UPA and hormonal contraception. The primary outcome was contraceptive effectiveness, measured by pregnancy rates or proxy measures (e.g., ovarian activity). We extracted and summarized findings from identified studies, assessed risk of bias for each study, and determined certainty of evidence for all outcomes. RESULTS: Four studies met inclusion criteria; all had low risk of bias. Two studies assessed whether UPA use affected the ability of oral contraceptives (OCs) to inhibit ovulation; no differences were observed in ovarian activity when starting OCs one day after UPA compared with starting OCs one day after placebo. Two studies assessed whether OC use affected the ability of UPA to delay ovulation; both studies observed higher proportions of ovulation when UPA was followed by OC use versus delayed or no OC use. One study assessed ovulation risk when UPA was taken after missed OCs, followed by immediate versus delayed OC resumption; no ovulations occurred within the first five days after UPA administration in either group, but there was greater risk of ovulation beyond five days with delayed versus immediate OC resumption. CONCLUSIONS: While there is no evidence that UPA affects the ability of hormonal contraception to inhibit ovulation, hormonal contraception use immediately or soon after UPA may decrease UPA's ability to delay ovulation. The certainty of evidence ranged from moderate to very low. IMPLICATIONS: If a patient desires hormonal contraception after UPA, an interaction with UPA can be avoided by delaying initiation or resumption of hormonal contraception. The risk of pregnancy due to decreased effectiveness of UPA with immediate hormonal contraception should be balanced against the risk of subsequent pregnancy due to delay or non-start of hormonal contraception.

OBJECTIVES: To explore how artificial intelligence (AI) can enhance infodemiology, which distributes and scans information in the electronic medium, to process social media posts for HIV pre-exposure prophylaxis (PrEP). DESIGN: Systematic Review. METHODS: We searched in the U.S. Centers for Disease Control and Prevention's Prevention Research Synthesis database through June 2024 (PROSPERO: CRD42023458870). We included infodemiology studies published in English and reported using AI to process social media posts on PrEP. Two reviewers independently screened citations, extracted data, and conducted a risk of bias assessment using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. Findings are narratively summarized. RESULTS: Of the 135 citations screened, eight infodemiology studies were identified, analyzing over 58.9 million posts. Infodemiology studies found the PrEP topics commonly discussed in communities (e.g., barriers of uptake), rumors that may raise public health concerns (e.g., PrEP is a prevention method against COVID-19 infection), geographic locations where concerns regarding risk of acquiring HIV were raised (e.g., most HIV-related posts were from the 10 states with the highest numbers of new HIV diagnoses), and predicted HIV trends (e.g., HIV-related tweets were negatively correlated with the county-level HIV incidence rate in the following year). CONCLUSIONS: Despite the limitations of this review including a small number of studies reviewed, our review suggests social media posts may provide information on real-time PrEP-related concerns, and AI can accelerate and enhance the processing of mass data to identify the information that communities need and the areas/locations that may need HIV prevention intervention.

BACKGROUND: Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. However, they lack specimen collection and diagnosis dates to assign location of onset. Algorithms to classify CDI onset location using claims data have been published, but the degree of misclassification is unknown. METHODS: We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016-2021 to Medicare beneficiaries with fee-for-service Part A/B coverage. We calculated sensitivity of ICD-10-CM codes in claims within ±28 days of EIP specimen collection. CDI was categorized as hospital, long-term care facility, or community-onset using three different Medicare claims-based algorithms based on claim type, ICD-10-CM code position, duration of hospitalization, and ICD-10-CM diagnosis code presence-on-admission indicators. We assessed concordance of EIP case classifications, based on chart review and specimen collection date, with claims case classifications using Cohen's kappa statistic. RESULTS: Of 12,671 CDI cases eligible for linkage, 9,032 (71%) were linked to a single, unique Medicare beneficiary. Compared to EIP, sensitivity of CDI ICD-10-CM codes was 81%; codes were more likely to be present for hospitalized patients (93.0%) than those who were not (56.2%). Concordance between EIP and Medicare claims algorithms ranged from 68% to 75%, depending on the algorithm used (κ = 0.56-0.66). CONCLUSION: ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

INTRODUCTION: Non-survey-based data sources (e.g. electronic health records, administrative claims) have been used to estimate vaccination coverage among US adults. However, these data sources were not collected for research or surveillance purposes and may have substantial limitations. The objectives of this narrative review were to: 1) identify published studies that used non-survey-based data sources to estimate adult vaccination coverage for one or more routinely recommended vaccines; and 2) summarize the strengths and limitations of these data sources for coverage assessments. AREAS COVERED: Thirty-four publications derived from 9 data sources were reviewed: 16 publications were in a general population (i.e. defined by age), 12 were among pregnant women, and 6 were among individuals with chronic health conditions. While several data sources used continuous health insurance enrollment to define the study population, doing so limited generalizability to stably insured populations. Methods for obtaining race and ethnicity data were complex and potentially subject to bias. None of the reviewed studies presented any formal assessment of vaccine data validity. EXPERT OPINION: While multiple non-survey-based data sources have been used to assess adult vaccination coverage in the United States, important limitations exist, including related to generalizability, data validity, and risk of bias.

Objectives This report describes the development and operations of the 2016 National Culturally and Linguistically Appropriate Services Survey for Office-based Physicians (National CLAS Physician Survey). The survey was developed to understand awareness, adoption, and implementation of the National CLAS Standards in health and health care among office-based physicians. Methods Survey development included a literature review of survey and assessment instruments that evaluated cultural and linguistic appropriateness in health care. Survey questions were pretested during a cognitive interview study of 20 office-based physicians in the District of Columbia metropolitan area. The cognitive interviews were analyzed using a grounded theory approach. The final survey was administered via web, mail, and computer-assisted telephone interview to 2, 400 sampled physicians between August 2016 and December 2016. A nonresponse bias assessment was conducted. Results The literature review identified five survey and assessment instruments. Collectively, survey content included: cultural competency training, cultural awareness, and adoption of the National CLAS Standards. Cognitive interviews showed respondent difficulty in question interpretation and survey completion of some items. Survey revisions addressed these issues. The final overall weighted survey response rate was 33.8%. Final weights produced a lower standardized bias than base weights. Conclusions The National CLAS Physician Survey is the first nationally representative survey to describe the use and implementation of culturally and linguistically appropriate services by office-based physicians. Data can serve as a baseline for future studies and as a benchmark for meeting the key objectives of the National CLAS Standards. © 2025, null. All rights reserved.

BACKGROUND: Parent-reported surveys are commonly used in child health research. However, few national surveys have examined concordance between parent- and teen-reported Adverse Childhood Experiences (ACEs). OBJECTIVE: To examine concordance between parent- and teen-reported ACEs among a nationally representative sample of teens and understand sociodemographic correlates of concordance. PARTICIPANTS AND SETTING: Data were collected as part of the National Health Interview Survey (NHIS), an annual nationally representative survey of the United States, with parent-reported interviews and its follow-back survey, the National Health Interview Survey-Teen (NHIS-Teen), a self-administered web survey of youth aged 12-17 years. METHODS: Parent- and teen-reported ACEs, and several measures of concordance (e.g. weighted Cohen's kappa, prevalence adjusted bias adjusted kappa (PABAK)) are presented. Unadjusted logistic regressions tested associations between sociodemographic characteristics and likelihood of concordance for each ACE. RESULTS: ACEs prevalence based on parent report were lower compared to teen report (e.g. victim of or witnessed violence in the neighborhood, 6.5 % parent-reported vs. 15.5 %, teen-reported). Weighted Cohen's kappa statistics showed fair to moderate agreement (ks ranging from 0.27 to 0.53), with PABAK statistics showing slightly higher levels (ks ranging from 0.41 to 0.88). CONCLUSIONS: There is discordance in ACEs reporting between teens and their parents, with parents less likely to report that their teen experience an ACE than teens are. This emphasizes the importance of collecting information directly from teenagers, which may help inform intervention work.

BACKGROUND: Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial. OBJECTIVE: This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design. METHODS: Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets. RESULTS: Bias in VE estimates from multivariable models ranged from -5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from -2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups. CONCLUSIONS: Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.

Data science is an emerging field that provides new analytical methods. It incorporates novel data sources (eg, internet data) and methods (eg, machine learning) that offer valuable and timely insights into public health issues, including injury and violence prevention. The objective of this research was to describe ethical considerations for public health data scientists conducting injury and violence prevention-related data science projects to prevent unintended ethical, legal, and social consequences, such as loss of privacy or loss of public trust. We first reviewed foundational bioethics and public health ethics literature to identify key ethical concepts relevant to public health data science. After identifying these ethics concepts, we held a series of discussions to organize them under broad ethical domains. Within each domain, we examined relevant ethics concepts from our review of the primary literature. Lastly, we developed questions for each ethical domain to facilitate the early conceptualization stage of the ethical analysis of injury and violence prevention projects. We identified 4 ethical domains: privacy, responsible stewardship, justice as fairness, and inclusivity and engagement. We determined that each domain carries equal weight, with no consideration bearing more importance than the others. Examples of ethical considerations are clearly identifying project goals, determining whether people included in projects are at risk of reidentification through external sources or linkages, and evaluating and minimizing the potential for bias in data sources used. As data science methodologies are incorporated into public health research to work toward reducing the effect of injury and violence on individuals, families, and communities in the United States, we recommend that relevant ethical issues be identified, considered, and addressed.

Annual surveys of refugees in Gambella, Ethiopia suggest that anemia is a persistent public health problem among non-pregnant women of reproductive age (NP-WRA, 15-49 years). Measurement of anemia in most refugee camp settings is conducted using an invasive HemoCue 301. We assessed the accuracy and precision of a non-invasive, pulse CO-oximeter in measuring anemia among NP-WRA in four Gambella refugee camps. We conducted a population-representative household survey between November 7 and December 4, 2022. Hemoglobin (Hb) concentration was measured by HemoCue 301, using capillary blood, and Rad-67, a novel non-invasive device. We collected four measurements per participant: two per device. We calculated Rad-67 bias and precision of Hb measurements and sensitivity and specificity of detecting anemia. Of the 812 NP-WRAs selected, 807 (99%) participated in the study. Anemia was detected in 39% of NP-WRA as classified by the Rad-67 compared with 47% of NP-WRA as classified by the HemoCue 301. Average bias of Rad-67 measurements was 1.1 ± 1.0 SD g/dL, using HemoCue 301 as a comparator. Absolute mean difference between the first and second measurements was 0.9 g/dL (95% CI 0.8, 0.9) using the Rad-67, compared with 0.6 g/dL (95% CI 0.5, 0.6) using the HemoCue 301. The Rad-67 had 49% sensitivity and 70% specificity for detecting anemia, compared with the HemoCue 301. The Rad-67 can be a useful tool for anemia screening; however, lower accuracy and precision, and poor sensitivity suggest it cannot immediately replace the HemoCue 301 in the study area.

Commutability is where the measurement response for a reference material (RM) is the same as for an individual patient sample with the same concentration of analyte measured using two or more measurement systems. Assessment of commutability is essential when the RM is used in a calibration hierarchy or to ensure that clinical measurements are comparable across different measurement procedures and at different times. The commutability of three new Standard Reference Materials(®) (SRMs) for determining serum total 25-hydroxyvitamin D [25(OH)D], defined as the sum of 25-hydroxyvitamin D(2) [25(OH)D(2)] and 25-hydroxyvitamin D(3) [25(OH)D(3)], was assessed through an interlaboratory study. The following SRMs were assessed: (1) SRM 2969 Vitamin D Metabolites in Frozen Human Serum (Total 25-Hydroxyvitamin D Low Level), (2) SRM 2970 Vitamin D Metabolites in Frozen Human Serum (25-Hydroxyvitamin D(2) High Level), and (3) SRM 1949 Frozen Human Prenatal Serum. These SRMs represent three clinically relevant situations including (1) low levels of total 25(OH)D, (2) high level of 25(OH)D(2), and (3) 25(OH)D levels in nonpregnant women and women during each of the three trimesters of pregnancy with changing concentrations of vitamin D-binding protein (VDBP). Twelve laboratories using 17 different ligand binding assays and eight laboratories using nine commercial and custom liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays provided results in this study. Commutability of the SRMs with patient samples was assessed using the Clinical and Laboratory Standards Institute (CLSI) approach based on 95% prediction intervals or a pre-set commutability criterion and the recently introduced International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) approach based on differences in bias for the clinical and reference material samples using a commutability criterion of 8.8%. All three SRMs were deemed as commutable with all LC-MS/MS assays using both CLSI and IFCC approaches. SRM 2969 and SRM 2970 were deemed noncommutable for three and seven different ligand binding assays, respectively, when using the IFCC approach. Except for two assays, one or more of the three pregnancy levels of SRM 1949 were deemed noncommutable or inconclusive using different ligand binding assays and the commutability criterion of 8.8%. Overall, a noncommutable assessment for ligand binding assays is determined for these SRMs primarily due to a lack of assay selectivity related to 25(OH)D(2) or an increasing VDBP in pregnancy trimester materials rather than the quality of the SRMs. With results from 17 different ligand binding and nine LC-MS/MS assays, this study provides valuable knowledge for clinical laboratories to inform SRM selection when assessing 25(OH)D status in patient populations, particularly in subpopulations with low levels of 25(OH)D, high levels of 25(OH)D(2), women only, or women who are pregnant.

Rotavirus vaccine appears to perform sub-optimally in countries with higher rotavirus burden. We hypothesized that differences in the magnitude of rotavirus exposures may bias vaccine efficacy (VE) estimates, so true differences in country-specific rotavirus VE would be exaggerated without accommodating differences in exposure. We estimated VE against any-severity and severe rotavirus gastroenteritis (RVGE) using Poisson regression models fit to pooled individual-level data from Phase II and III monovalent rotavirus vaccine trials conducted between 2000 and 2012. The standard approach model included terms for vaccination, country, and a vaccination-country interaction. Other models used proxies for exposure magnitude like severe RVGE rate or age at severe RVGE instead of country. Country-specific proxies were calculated from placebo group data or extracted from an external meta-analysis. Analyses included 83,592 infants from 23 countries in the Americas, Europe, Africa, and Asia. Using the standard approach, VE against severe RVGE substantially varied (10-100%). Using the severe RVGE rate proxy brought VE from all but two countries between 80% and 86%. Heterogeneity for VE against any-severity RVGE was similarly attenuated. Adjusting for exposure proxies reduced heterogeneity in country-specific rotavirus VE estimates. This phenomenon may extend to other vaccines against partially immunizing pathogens with global disparities in burden.

INTRODUCTION: Occupational injuries have been associated with increased suicide mortality, but prior studies have not accounted for pre-injury depression. METHODS: We linked injuries that occurred from 1994 to 2000 in the Washington State workers' compensation system with Social Security Administration data on earnings and mortality through 2018. We estimated the subdistribution hazard ratio (sHR) and 95% confidence interval using competing risks regression of suicide deaths with lost time compared with medical-only injuries separately for men and women, adjusting for age, pre-injury annual earnings, and industry. We further adjusted for pre-injury diagnosis of major depressive disorder by using a quantitative bias analysis (QBA), with the prevalence of this disorder in workers derived from an external health insurance claims data set. RESULTS: Elevated suicide mortality was observed following lost-time injuries compared with medical-only injuries for men (sHR = 1.49, 95% CI [1.14, 1.93]) and women (sHR = 1.30, 95% CI [1.00, 1.69]), adjusting for age, pre-injury earnings, and industry. Adjusted for pre-injury depression using a QBA, elevated suicide risk in men remained statistically significant (median sHR = 1.33, simulation interval [1.18, 1.47]) but not for women. DISCUSSION: Workplace injury requiring time off work appeared to remain influential in increasing suicide risk among men, even after controlling for pre-injury depression. The relationship between mental health before and after occupational injury is complex and studies should better integrate mental health pre-injury. CONCLUSIONS: Though many questions remain on the complex relationship between work, depression, injuries, and suicide, employers should work to prevent injuries and consider implementing mental health programs, which could be helpful in reducing suicide risk.

Respirable dust mass is a prevalent occupational health hazard to the mining workforce. Mineral matrices observed in the mine environment are complex, time varying, and heterogeneous. This poses a challenge to assessing dust exposure using Fourier transform infrared (FT-IR) spectrometry as calibrations for constituent dust species (e.g., crystalline silica) have historically been trained using homogeneous standards or simple mixtures therein. Investigations have considered direct-on-filter analysis, which collects FT-IR spectra directly from sampling filters for calibration, as an alternative. Direct-on-filter analysis using a partial least squares (PLS) method has gained particular interest recently due to the potential to rapidly quantify multiple species from a single filter at the mine site. By design, heterogeneity, and its presumed impact on method accuracy, cannot be addressed in the laboratory when using a direct-on-filter approach motivating the need for more advanced calibration approaches. When heterogeneity is present, mixture of experts (MoE) finite mixture models offer a promising and novel alternative to PLS direct-on-filter analysis as MoE incorporates cluster discovery, regression, and outlier identification into model fitting. Three MoE models of increasing complexity were tasked with determining respirable dust mass in 243 field samples from thirteen active coal, limestone, sandstone, and silver mines. All MoE models, including those using only "expert" spectroscopic predictors or a combination of expert and categorical "gate" variables (e.g., mine type), significantly outperform PLS in terms of accuracy (α = 0.05). Decomposing bias by mine type shows that accuracy generally improves across all types considered when MoE models are not overfitted. The MoE method's effectiveness was linked to its ability to endogenously classify outliers as well as possibly to the use of an additional cluster model for mass predictions. Overall, MoE methods appear as a capable and novel tool to addressing problems of heterogeneity for direct-on-filter quantitative analysis.

BACKGROUND: We aimed to develop a method for assessing occupational styrene exposures for application in epidemiological studies on risks of lymphohematopoietic neoplasms and other malignant and non-malignant diseases in the European and the US glass reinforced plastics industries. METHOD: We estimated a linear mixed effects model based on individual airborne personal measurements of styrene from the glass reinforced plastics industry in Denmark, Norway, Sweden, UK, and the US. The most suitable model was chosen based on its predictive power as assessed using cross validation with different combinations of predictors; and by comparing their prediction errors. RESULTS: We created a database containing 21,201 personal and area measurements but a subset of 14,440 personal measurements that spanned a period from 1962 to 2018, were used in the analysis. The selected model included fixed effects for year, sampling duration, measurement reason, product, process and random effects for country and worker. There was strong agreement between the model's predictions and actual exposure values indicating a good fit (Lin's CCC: 0.85 95% CI 0.84, 0.85). There were regional differences in exposure levels, with the UK and the US having comparable exposures that were higher than those in the Nordic countries. Higher exposures were consistent with measurements collected for inspection purposes, the lamination process, and specific products. Styrene exposure levels have decreased annually on average by 7%. CONCLUSION: Our exposure model and the resulting exposure predictions will enable estimation of lifetime occupational exposure for individual workers in the European and the US glass reinforced plastics industry and possibly related health risks among employees. The approach facilitates understanding of the uncertainty in our prediction model and can inform analysis of the bias that application of our exposure assessment approach can produce in epidemiologic analyses of exposure-response associations. Addressing systematic sources of bias can increase confidence in the conclusions of the epidemiologic analysis.

A significant portion of the work of developing and validating methods for volatile organic compound (VOC) sampling in workplace atmospheres involves the use of laboratory-generated atmospheres. The sample variability was evaluated from the dynamic atmosphere generation system used for VOC atmosphere generation and sampling. Characterization of the bias and variability of samples was done for a variety of atmospheres containing neat n-heptane and mixtures of VOCs sampled on activated coconut shell charcoal. Estimates of sampling variability ranged from 2% for neat n-heptane to 12% for a component in the 10 VOC mix. Sample variability increased for lower concentration samples and for mixtures of VOCs compared to single component atmospheres. This study can serve as a baseline for future atmosphere sampling experiments evaluating performance at lower concentrations and mixed VOC environments.