Unmeasured Confounders Research Articles

Are the Relationships of Physical Activity and Television Viewing Time With Mortality Robust to Confounding? A Study, Utilizing E-Values, From the Melbourne Collaborative Cohort Study.

Physical activity and sedentary behavior are associated with health outcomes. However, evidence may be affected by confounding bias. This study aimed to examine the relationships of physical activity and television (TV) viewing time with all-cause, cardiovascular, and cancer mortality in a cohort of Australian adults, and determine the robustness of these relationships to residual and unmeasured confounding. Data from 27,317 Melbourne Collaborative Cohort Study participants (mean age = 66) were used. Physical activity was assessed using the International Physical Activity Questionnaire-Short Form and categorized as insufficient, sufficient, or more than sufficient. TV viewing time was categorized as low, moderate, or high. Multivariable Cox regression models were used to evaluate associations of interest. E-values were calculated to assess the strength of unmeasured confounders required to negate the observed results. For highest versus lowest physical activity category, the hazard ratio was 0.67 (95% confidence interval, 0.56-0.81) for all-cause mortality; E-values ranged between 1.79 and 2.44. Results were similar for cardiovascular mortality; however, hazard ratios were lower (0.72; 95% confidence interval, 0.51-1.01) and E-values much smaller (1.00-2.12) for cancer mortality. For highest versus lowest TV viewing time category, the hazard ratio was 1.08 (1.01-1.15) for all-cause mortality; E-values ranged between 1.00 and 1.37. Results were similar for cardiovascular and cancer mortality. Physical activity and TV viewing time were associated with mortality. The robustness to unmeasured/residual confounding was moderate for physical activity (all-cause and cardiovascular mortality), but weaker for physical activity (cancer mortality) and TV viewing time in this study of Australian adults.

Semiparametric Causal Mediation Analysis with Unmeasured Mediator-Outcome Confounding

Although the exposure can be randomly assigned in studies of mediation effects, any form of direct intervention on the mediator is often infeasible. As a result, unmeasured mediator-outcome confounding can seldom be ruled out. We propose semiparametric identification of natural direct and indirect effects in the presence of unmeasured mediator-outcome confounding by leveraging heteroskedasticity restrictions on the observed data law. For inference, we develop semiparametric estimators that remain consistent under partial misspecifications of the observed data model. We illustrate the proposed estimators through both simulations and an application to evaluate the effect of self-efficacy on fatigue among health care workers during the COVID-19 outbreak.

Heart rate/temperature ratio: A practical prognostic indicator for critically ill patients with sepsis

BackgroundWe hypothesize that the heart rate/temperature ratio can predict intensive care unit (ICU) mortality in critical ill patients with sepsis. We aimed to explore the association between the heart rate/temperature ratio and ICU mortality in patients with sepsis. MethodsWe conducted this study utilizing a comprehensive critical care medicine database. The primary endpoint assessed was ICU mortality. A multivariable logistic regression model was employed to determine the independent impact of the heart rate to temperature ratio on ICU mortality. ResultsThe study included 12,321 patients. A nonlinear relationship was observed between the heart rate/temperature ratio and ICU mortality, with an inflection point identified at 2.22. The results from the Multivariable logistic regression analysis revealed that the heart rate/temperature ratio independently contributed to the risk of ICU mortality. In model II, there was a 55 % higher ICU mortality rate with a heart rate/temperature ratio greater than 2.22 than with that less than 2.22 (odds ratio [OR] = 1.55, 95 % confidence interval [CI] 1.35–1.77). Moreover, an elevated heart rate/temperature ratio as a continuous variable showed a positive association with ICU mortality (OR = 2.14; 95 % CI: 1.87–2.45). The impact of the heart rate/temperature ratio on ICU mortality remained consistent across all subgroup variables. The sensitivity analysis results consistently supported the primary outcome, with an E value of 2.47. This suggests that the influence of unmeasured confounders on the observed outcomes was minimal, thereby confirming the robustness of the findings. ConclusionsThe heart rate/temperature ratio is a readily available and convenient indicator in a clinical setting. Elevated heart rate/temperature ratios, particularly those exceeding 2.22, are strongly linked to a high ICU mortality rate among critically ill sepsis patients.

Oxaliplatin-associated shock in stage III colorectal cancer patients: real-world evidence in Taiwan.

Oxaliplatin-associated shock (referred to as shock) is a rare but life-threatening adverse event. This pioneering cohort study aimed to quantitatively investigate the association between oxaliplatin use and shock in patients with stage III colorectal cancer (CRC), identify potential independent risk factors for shock, and assess the cycle-to-shock during oxaliplatin treatment. The study utilized a nested case-control (NCC) design to assess the association between oxaliplatin and shock and employed a case-crossover approach to address unmeasured confounders. All newly diagnosed stage III CRC patients were identified from the CRC Health Database (2012-2016). Conditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CIs) for oxaliplatin's link to shock incidence. Among 6932 oxaliplatin recipients, 331 suffered shock. In all, 3309 controls were selected via risk-set sampling for the shock cases. Oxaliplatin use is associated with a doubled risk of shock (adjusted OR: 2.08, 95% CI: 1.23-3.52). Two independent risk factors were male sex (adjusted OR: 1.33, 95% CI: 1.05-1.69) and heart diseases (adjusted OR: 1.65, 95% CI: 1.17-2.32). The case-crossover analysis revealed a more than fourfold risk (OR: 4.4, 95% CI: 1.67-11.62). In total, 22 of 331 shock cases were exposed to oxaliplatin within 2 days of shock onset, with a median cycle-to-shock time at the seventh cycle. Oxaliplatin use significantly increased shock risk in stage III CRC patients. Male sex and heart disease are two independent risk factors.

Benzodiazepine Use During Pregnancy and Risk of Miscarriage

Benzodiazepine use during pregnancy has raised significant concerns due to the potential harmful effects of this drug class on neonates. Studies on the association between benzodiazepine use and the risk of miscarriage are limited. To quantify the risk of miscarriage associated with benzodiazepine use during pregnancy after controlling for unmeasured confounders and exposure time trends. This was a nationwide, population-based case-time-control study using Taiwan's National Birth Certificate Application database and the National Health Insurance database. Pregnancies resulting in miscarriage between 2004 and 2018 were included in the case group and were 1:1 matched with exposure time-trend control individuals using disease risk score, considering demographic characteristics and prepregnancy comorbidities. Data were analyzed from August 2022 to March 2023. Discordant exposures to benzodiazepines during risk period (1-28 days before miscarriage) and 2 reference periods (31-58 days and 181-208 days before the last menstrual period) were compared for each pregnancy. Miscarriage was defined as any pregnancy loss occurring between the first prenatal care visit (usually 8 weeks) and the 19th completed week of pregnancy. This study comprised a total of 3 067 122 pregnancies among 1 957 601 women, 136 134 of which (4.4%) resulted in miscarriage. The mean (SD) age of the study population was 30.61 (5.91) years. The use of benzodiazepines during pregnancy was associated with an increased risk of miscarriage (odds ratio [OR], 1.69; 95% CI, 1.52-1.87), and consistent findings were observed across multiple sensitivity analyses considering different time windows and accounting for misclassification. In subgroup analyses, an increased risk of miscarriage was associated with each commonly used individual benzodiazepine, ranging from case-time-control ORs of 1.39 (95% CI, 1.17-1.66) for alprazolam to 2.52 (95% CI, 1.89-3.36) for fludiazepam. This nationwide case-time-control study revealed an increased risk of miscarriage associated with benzodiazepine use during pregnancy after accounting for measurable confounders, and results were unlikely to be due to unmeasured confounding. These findings underscore the necessity for health care professionals to meticulously balance the risk-benefit ratio when considering the use of benzodiazepines to treat psychiatric and sleep disorders during pregnancy.

Analyzing risk factors for post-acute recovery in older adults with Alzheimer's disease and related dementia: A new semi-parametric model for large-scale medicare claims.

Nearly 300,000 older adults experience a hip fracture every year, the majority of which occur following a fall. Unfortunately, recovery after fall-related trauma such as hip fracture is poor, where older adults diagnosed with Alzheimer's disease and related dementia (ADRD) spend a particularly long time in hospitals or rehabilitation facilities during the post-operative recuperation period. Because older adults value functional recovery and spending time at home versus facilities as key outcomes after hospitalization, identifying factors that influence days spent at home after hospitalization is imperative. While several individual-level factors have been identified, the characteristics of the treating hospital have recently been identified as contributors. However, few methodological rigorous approaches are available to help overcome potential sources of bias such as hospital-level unmeasured confounders, informative hospital size, and loss to follow-up due to death. This article develops a useful tool equipped with unsupervised learning to simultaneously handle statistical complexities that are often encountered in health services research, especially when using large administrative claims databases. The proposed estimator has a closed form, thus only requiring light computation load in a large-scale study. We further develop its asymptotic properties with stabilized inference assisted by unsupervised clustering. Extensive simulation studies demonstrate superiority of the proposed estimator compared to existing estimators.

A NEW METHOD TO IDENTIFY MEDICARE CLAIMS-BASED FACTORS ASSOCIATED WITH POST-ACUTE RECOVERY IN OLDER ADULTS WITH ADRD

Abstract Nearly 300,000 older adults experience a hip fracture every year, the majority of which occur following a fall. Unfortunately, recovery from hip fracture is poor, where older adults diagnosed with Alzheimer’s Disease and Related Dementia (ADRD) spend a particularly long time in hospitals or rehabilitation facilities during the post-operative recuperation period. Because older adults value functional recovery and spending time at home versus facilities as key outcomes after hospitalization, identifying factors that influence days spent at home after hospitalization is imperative. However, few rigorous analytical approaches are available to help overcome potential sources of analysis bias such as hospital-level unmeasured confounders, informative hospital size, and loss to follow-up due to death. To overcome these challenges, we developed a new data science approach equipped with unsupervised learning to simultaneously handle statistical complexities that are often encountered in research using large administrative claims databases. The proposed approach is accessible and performs well in simulation studies. Analysis of 16562 Medicare beneficiaries diagnosed with ADRD who were aged 65 or older and experienced a hip fracture between 2017 and 2019 demonstrated that older age, longer length of stay in the hospital, more chronic health conditions, and less days at home before fracture are significantly associated less days spent at home in the 12-month period after hip fracture (p<.05), while existing methods fail to detect some effects. Findings demonstrate that the proposed method can overcome bias in health services research using Medicare data and can lead to findings that may inform care and resource allocation.

Understanding the impact of non-shared unmeasured confounding on the sibling comparison analysis.

The sibling comparison analysis is used to deal with unmeasured confounding. It has previously been shown that in the presence of non-shared unmeasured confounding, the sibling comparison analysis may introduce substantial bias depending on the sharedness of the unmeasured confounder and the sharedness of the exposure. We aimed to improve the awareness of this challenge of the sibling comparison analysis. First, we simulated sibling pairs with an exposure, a confounder and an outcome. We simulated sibling pairs with no effect of the exposure on the outcome and with positive confounding. For varying degrees of sharedness of the confounder and the exposure and for varying prevalence of the exposure, we calculated the sibling comparison odds ratio (OR). Second, we provided measures for sharedness of selected treatments based on Danish health data. The confounded sibling comparison OR was visualized for varying degrees of sharedness of the confounder and the exposure and for varying prevalence of the exposure. The confounded sibling comparison OR was seen to increase with increasing sharedness of the exposure and the confounded sibling comparison OR decreased with an increasing prevalence of exposure. Measures for sharedness of treatments based on Danish health data showed that treatments of chronic diseases have the highest sharedness and treatments of non-chronic diseases have the lowest sharedness. Researchers should be aware of the challenge regarding non-shared unmeasured confounding in the sibling comparison analysis, before applying the analysis in non-randomized studies. Otherwise, the sibling comparison analysis may lead to substantial bias.

Is residential exposure to oil refineries a novel contextual risk factor for coronary heart disease?

Despite a multi-decade decrease in cardiovascular disease, geographic disparities have widened, with excess mortality concentrated within the United States (U.S.) South. Petroleum production and refining, a major contributor to climate change, is concentrated within the U.S. South and emits multiple classes of atherogenic pollutants. We investigated whether residential exposure to oil refineries could explain variation in self-reported coronary heart disease (CHD) prevalence among adults in southern states for the year 2018, where the majority of oil refinery activity occurs (Alabama, Mississippi, Louisiana, Arkansas, Texas, New Mexico, and Oklahoma). We examined census tract-level association between oil refineries and CHD prevalence. We used a double matching method to adjust for measured and unmeasured spatial confounders: one-to-n distance matching and one-to-one generalized propensity score matching. Exposure metrics were constructed based on proximity to refineries, activities of refineries, and wind speed/direction. For all census tracts within 10 km of refineries, self-reported CHD prevalence ranged from 1.2% to 17.6%. Compared to census tracts located at ≥5 km and <10 km, one standard deviation increase in the exposure within 5 km of refineries was associated with a 0.33 (95% confidence interval: 0.04, 0.63) percentage point increase in the prevalence. A total of 1119.0 (123.5, 2114.2) prevalent cases or 1.6% (0.2, 3.1) of CHD prevalence in areas within 5 km from refineries were potentially explained by exposure to oil refineries. At the census tract-level, the prevalence of CHD explained by exposure to oil refineries ranged from 0.02% (0.00, 0.05) to 47.4% (5.2, 89.5). Thus, although we cannot rule out potential confounding by other personal risk factors, CHD prevalence was found to be higher in populations living nearer to oil refineries, which may suggest that exposure to oil refineries can increase CHD risk, warranting further investigation.

Addressing unmeasured confounders in cohort studies: Instrumental variable method for a time-fixed exposure on an outcome trajectory.

Instrumental variable methods, which handle unmeasured confounding by targeting the part of the exposure explained by an exogenous variable not subject to confounding, have gained much interest in observational studies. We consider the very frequent setting of estimating the unconfounded effect of an exposure measured at baseline on the subsequent trajectory of an outcome repeatedly measured over time. We didactically explain how to apply the instrumental variable method in such setting by adapting the two-stage classical methodology with (1) the prediction of the exposure according to the instrumental variable, (2) its inclusion into a mixed model to quantify the exposure association with the subsequent outcome trajectory, and (3) the computation of the estimated total variance. A simulation study illustrates the consequences of unmeasured confounding in classical analyses and the usefulness of the instrumental variable approach. The methodology is then applied to 6224 participants of the 3C cohort to estimate the association of type-2 diabetes with subsequent cognitive trajectory, using 42 genetic polymorphisms as instrumental variables. This contribution shows how to handle endogeneity when interested in repeated outcomes, along with a R implementation. However, it should still be used with caution as it relies on instrumental variable assumptions hardly testable inpractice.

Uncovering a causal connection between the Lachnoclostridium genus in fecal microbiota and non-alcoholic fatty liver disease: a two-sample Mendelian randomization analysis.

Previous observational studies have indicated that an imbalance in gut microbiota may contribute to non-alcoholic fatty liver disease (NAFLD). However, given the inevitable bias and unmeasured confounders in observational studies, the causal relationship between gut microbiota and NAFLD cannot be deduced. Therefore, we employed a two-sample Mendelian randomization (TSMR) study to assess the causality between gut microbiota and NAFLD. The gut microbiota-related genome-wide association study (GWAS) data of 18,340 individuals were collected from the International MiBioGen consortium. The GWAS summary data for NAFLD from the Anstee cohort (1,483 cases and 17,781 controls) and the FinnGen consortium (894 cases and 217,898 controls) were utilized in the discovery and verification phases, respectively. The inverse variance weighted (IVW) method was used as the principal method in our Mendelian randomization (MR) study, with sensitivity analyses using the MR-Egger, weighted median, simple mode, and weighted mode methods. The MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were conducted to identify heterogeneity and pleiotropy. Moreover, a fixed-effect meta-analysis was conducted to verify the robustness of the results. The gene prediction results showed that at the genus level, four gut microbiota were causally associated with NAFLD in the GWAS conducted by Anstee et al. The relative abundance of Intestinimonas (OR: 0.694, 95%CI: 0.533-0.903, p = 0.006, IVW), Lachnoclostridium (OR: 0.420, 95%CI: 0.245-0.719, p = 0.002, IVW), and Senegalimassilia (OR: 0.596, 95%CI: 0.363-0.978, p = 0.041, IVW) was negatively associated with NAFLD. The relative abundance of Ruminococcus1 (OR: 1.852, 95%CI: 1.179-2.908, p = 0.007, IVW) was positively correlated with NAFLD. Among them, the Lachnoclostridium genus was validated in FinnGen GWAS (OR: 0.53, 95%CI: 0.304-0.928, p = 0.026, IVW). The Lachnoclostridium genus was also significantly associated with NAFLD risk in the meta-analyses (OR: 0.470, 95%CI: 0.319-0.692, p = 0.0001, IVW). No heterogeneity or pleiotropy was observed. This study provided new evidence of the relationship between the Lachnoclostridium genus and NAFLD, suggesting that augmentation of the relative abundance of the Lachnoclostridium genus through the oral administration of probiotics or fecal microbiota transplantation could be an effective way to reduce the risk of NAFLD.

MSR130 Current Trends in Quantitative Bias Analysis for Unmeasured Confounders: A Targeted Literature Review

MSR130 Current Trends in Quantitative Bias Analysis for Unmeasured Confounders: A Targeted Literature Review

Childhood personality and academic performance: A sibling fixed-effects study.

This study investigated the associations between personality traits at age 8 and academic performance between ages 10 and 14, controlling for family confounds. Many studies have shown links between children's personality traits and their school performance. However, we lack evidence on whether these associations remain after genetic and environmental confounders are accounted for. Sibling data from the Norwegian Mother and Child Cohort Study (MoBa) were used (n = 9701). First, we estimated the overall associations between Big Five personality traits and academic performance, including literacy, numeracy, and foreign language. Second, we added sibling fixed effects to remove unmeasured confounders shared by siblings as well as rating bias. Openness to Experience (between-person β = 0.22 [95% CI: 0.21-0.24]) and Conscientiousness (between-person β = 0.18 [95% CI 0.16-0.20]) were most strongly related to educational performance. Agreeableness (between-person β = 0.06 [95% CI -0.08-0.04]) and Extraversion (between-person β = 0.02 [95% CI 0.00-0.04]) showed small associations with educational performance. Neuroticism had a moderate negative association (between-person β = -0.14 [95% CI -0.15-0.11]). All associations between personality and performance were robust to confounding: the within-family estimates from sibling fixed-effects models overlapped with the between-person effects. Finally, childhood personality was equally predictive of educational performance across ages and genders. Although family background is influential for academic achievement, it does not confound associations with personality. Childhood personality traits reflect unbiased and consistent individual differences in educational potential.

User-generated content affects urban park use: Analysis of direct and moderating effects

Urban parks contribute to sustainable urban development by bringing various social and environmental benefits; understanding the factors influencing park use is important for informing evidence-based park design and intervention. Although there are increasing number of studies using user-generated content (UGC) as a proxy of park use, few studies have examined how UGC influences park use. Therefore, we selected 221 urban parks in Guangzhou and Shenzhen, China, with multisource geographic data and collected 153,479 UGC from influential social media platforms. We discovered that UGC sentiment and park use were positively correlated, which was moderated by UGC exposure. In addition, park shape, vegetation and water coverage, land cover mix, parking lot density, and surrounding socioeconomic status, had indirect effects on park use via UGC sentiment. Solid evidence supports that UGC may affect park use because the spurious relationship arising from unmeasured confounders may not be moderated by UGC exposure. We recommend that UGC should be more carefully used as a proxy; its effect should be considered in future studies. In addition, we propose a tentative theoretical framework associating park use, UGC, and other key factors. This research provides a reference for future research and optimizing park use in the modern digital society.

Measurement invariance and differential item functioning of the PHQ-9 and GAD-7 between working age and older adults seeking treatment for common mental disorders

BackgroundThe nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalised Anxiety Disorder (GAD-7) scale are widely used clinically and within research, and so it is important to determine how the measures, and individual items within the measures, are answered by adults of differing ages. This study sought to evaluate measurement invariance and differential item functioning (DIF) of the PHQ-9 and GAD-7 between working age and older adults seeking routine psychological treatment. MethodsData of working age (18–64 years old) and older (≥65) adults in eight Improving Access to Psychological Therapies (IAPT) services were used. Confirmatory factor analysis (CFA) was used to establish unidimensionality of the PHQ-9 and GAD-7, with multiple-group CFA to test measurement invariance and The Multiple Indicators, Multiple Causes Models approach to assess DIF. The employed methods were applied to a propensity score matched (PSM) sample in sensitivity analyses to control for potential confounding. ResultsData from 166,816 patients (159,325 working age, 7491 older) were used to show measurement invariance for the PHQ-9 and GAD-7, with limited evidence of DIF and similar results found with a PSM sample (n = 5868). LimitationsThe localised sample creates an inability to detect geographical variance, and the potential effect of unmeasured confounders cannot be ruled out. ConclusionsThe findings support the use of the PHQ-9 and GAD-7 measures for working age and older adults, both clinically and in research settings. This study validates using the measures for these age groups to assess clinically significant symptom thresholds, and monitor treatment outcomes between them.

Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort

Many psychiatric outcomes share a common etiologic pathway reflecting behavioral disinhibition, generally referred to as externalizing (EXT) disorders. Recent genome-wide association studies (GWASs) have demonstrated the overlap between EXT disorders and important aspects of veterans' health, such as suicide-related behaviors and substance use disorders (SUDs). To explore correlates of risk for EXT disorders within the Veterans Health Administration (VA) Million Veteran Program (MVP). A series of phenome-wide association studies (PheWASs) of polygenic risk scores (PGSs) for EXT disorders was conducted using electronic health records. First, ancestry-specific PheWASs of EXT PGSs were conducted in the African, European, and Hispanic or Latin American ancestries. Next, a conditional PheWAS, covarying for PGSs of comorbid psychiatric problems (depression, schizophrenia, and suicide attempt; European ancestries only), was performed. Lastly, to adjust for unmeasured confounders, a within-family analysis of significant associations from the main PheWAS was performed in full siblings (European ancestries only). This study included the electronic health record data from US veterans from VA health care centers enrolled in MVP. Analyses took place from February 2022 to August 2023 covering a period from October 1999 to January 2020. PGSs for EXT, depression, schizophrenia, and suicide attempt. Phecodes for diagnoses derived from the International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification, codes from electronic health records. Within the MVP (560 824 patients; mean [SD] age, 67.9 [14.3] years; 512 593 male [91.4%]), the EXT PGS was associated with 619 outcomes, of which 188 were independent of risk for comorbid problems or PGSs (from odds ratio [OR], 1.02; 95% CI, 1.01-1.03 for overweight/obesity to OR, 1.44; 95% CI, 1.42-1.47 for viral hepatitis C). Of the significant outcomes, 73 (11.9%) were significant in the African results and 26 (4.5%) were significant in the Hispanic or Latin American results. Within-family analyses uncovered robust associations between EXT PGS and consequences of SUDs, including liver disease, chronic airway obstruction, and viral hepatitis C. Results of this cohort study suggest a shared polygenic basis of EXT disorders, independent of risk for other psychiatric problems. In addition, this study found associations between EXT PGS and diagnoses related to SUDs and their sequelae. Overall, this study highlighted the potential negative consequences of EXT disorders for health and functioning in the US veteran population.

Abstract 13825: Post-PCI Outcomes in Patients on SGLT2 Inhibitor Therapy

Introduction: Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been shown to improve cardiorenal outcomes among patients with and without diabetes mellitus. Hypothesis: We aimed to investigate their impact on the risk of acute kidney injury (AKI) and major adverse cardiac events (MACE) after percutaneous coronary intervention (PCI). Methods: Consecutive patients undergoing PCI at a high-volume PCI center between 2015 and 2022 were analyzed. Patients on SGLT2 inhibitors prior to PCI were compared to those not on SGLT2 inhibitors. The primary outcome was AKI, as defined as serum creatinine increase of ≥0.5 mg/dL or ≥25% from baseline within 30 days of PCI. MACE was defined as death or myocardial infarction (MI) and was assessed at 1 year post PCI. Results: There were significant differences in baseline clinical characteristics between patients on (n = 347) vs. not on (n = 16,594) SGLT2 inhibitors. Patients on SGLT2 inhibitors had higher prevalence of diabetes (90.5% vs. 45.5%), hypertension (96.8% vs. 92.1%), hyperlipidemia (95.7% vs. 90.5%), and prior CABG (21.0% vs 15.8%). SGLT2 inhibitor use was associated with a decreased rate of post-PCI AKI (3.3% vs. 6.6%; adjusted odds ratio [OR] 0.33; 95% confidence interval [CI] 0.08-0.89, P=0.025). At one year after PCI, patients on SGLT2 inhibitors had increased rates of MACE (8.2% vs. 3.9%; adjusted hazard ratio [HR] 1.74, 95% CI 0.99-3.06, P=0.052), driven by an increased risk of MI (6.9% vs. 2.1%; HR 2.63, 95% CI 1.42-4.90, P=0.002). Conclusions: SGLT2 inhibitor use was associated with lower post-PCI AKI, but was associated with an increased risk of MACE. The latter finding was driven by increased risk of MI, which may be explained by unmeasured confounders in these heterogeneous groups of patients.

A Study to Evaluate the Effectiveness and Safety of Prephase Steroid Treatment before Remission Induction Chemotherapy in Patients with Pediatric Acute Lymphoblastic Leukemia Using Common Data Model-Based Real World Data

Introduction: Remission induction chemotherapy (RIC) is a primary treatment strategy for pediatric acute lymphoblastic leukemia (ALL), aiming to rapidly reduce leukemic cells in the bone marrow. However, this swift reduction can lead to significant complications such as tumor lysis syndrome (TLS). Pretreatment with steroids such as prednisolone or dexamethasone a week before initiating multi-agent RIC can potentially prevent TLS, but the effectiveness and utility of this approach remains unclear. We investigated whether steroid pretreatment before RIC can decrease TLS incidence and improve overall survival. Methods: We utilized clinical databases from two university-affiliated tertiary-care hospitals in Seoul, South Korea, constructed according to the OMOP Common Data Model (CDM) specifications. Eligible patients were children with ALL aged &amp;lt;18 who received RIC consisting of vincristine, prednisolone, L-asparaginase with or without daunorubicin between 2012 and 2021. Patients who received steroid pretreatment ≥7 days before RIC constituted the treated group, whereas those who didn't receive any steroid pretreatment or received it &amp;lt;7 days before were the untreated group. We used propensity score (PS) matching to make baseline characteristics comparable between the groups, based on logistic regression model that incorporated the following covariates: age at ALL diagnosis, sex, presence of Down syndrome, risk group, and baseline laboratory measurements including white blood cell count, hemoglobin, platelet count, absolute neutrophil count, uric acid, phosphorus, potassium, calcium, blood urea nitrogen, creatinine, and lactate dehydrogenase. The primary and secondary outcomes were the incidence of TLS within 14 days of starting RIC and overall survival (OS), respectively. Sensitivity analyses were performed to evaluate if unmeasured confounders resulted in any difference in the main results. Likewise, a rule-out approach and a negative control method was applied to adjust for confounders like immunophenotype and genetic alterations and for other residual confounding, respectively. Results: The study included 574 pediatric patients with ALL, with 275 in the treated group and 299 in the untreated group. After PS matching, each group included 142 patients with all baseline characteristics being comparable. Among the untreated patients, TLS was observed 32 out of 299 (10.7%), whereas in the treated group, 6 out of 275 (2.2%) developed TLS. The significant association between the treatment and reduced TLS risk persisted after adjusting for potential confounders (adjusted OR = 0.08, 95% CI: 0.01-0.31, p = 0.01). OS was numerically greater in the treated group that in the untreated group although it failed to reach statistical significance (HR 0.78, 95% CI 0.35-1.71, p=0.53). Sensitivity analyses including a rule-out approach and a negative control method indicated no substantial impact from unmeasured confounders such as immunophenotype, genetic alterations, or other residual factors. Conclusions: Steroid pretreatment ≥7 days before RIC significantly reduced the risk of TLS in pediatric patients with ALL although no significant reduction in OS was seen in the treated group than in the untreated group, partly because median OS was not reached. Because prospective randomized studies are ethically challenging to assess the efficacy and safety of steroid pretreatment before RIC, our results can provide its critical real-world evidence.

Impact of the COVID-19 Pandemic on Births, Vaginal Deliveries, Cesarian Sections, and Maternal Mortality in a Brazilian Metropolitan Area: A Time-Series Cohort Study.

The COVID-19 pandemic posed a worldwide challenge, leading to radical changes in healthcare. The primary objective of the study was to assess the impact of the COVID-19 pandemic on birth, vaginal delivery, and cesarian section (c-section) rates. The secondary objective was to compare the maternal mortality before and after the pandemic. Time-series cohort study including data of all women admitted for childbirth (vaginal delivery or c-section) at the maternities in the Public Health System of Federal District, Brazil, between March 2018 and February 2022, using data extracted from the Hospital Information System of Brazilian Ministry of Health (SIH/DATASUS) on September 30, 2022. Causal impact analysis was used to evaluate the impact of COVID-19 on birth, vaginal delivery, and c-section using the CausalImpact R package, and a propensity score matching was used to evaluate the effect on maternal mortality rate using the Easy R (EZR) software. There were 150,617 births, and considering total births, the effect of the COVID-19 pandemic was not statistically significant (absolute effect per week: 5.5, 95% CI: -24.0-33.4). However, there was an increase in c-sections after COVID-19 (absolute effect per week: 18.1; 95% CI: 11.9-23.9). After propensity score matching, the COVID-19 period was associated with increased maternal mortality (OR: 3.22, 95% CI: 1.53-6.81). The e-value of the adjusted OR for the association between the post-COVID-19 period and maternal mortality was 5.89, with a 95% CI: 2.43, suggesting that unmeasured confounders were unlikely to explain the entirety of the effect. Our study revealed a rise in c-sections and maternal mortality during the COVID-19 pandemic, possibly due to disruptions in maternal care. These findings highlight that implementing effective strategies to protect maternal health in times of crisis and improve outcomes for mothers and newborns is crucial.

Prevention of Hip Fractures: Trade-off between Minor Benefits to Individuals and Large Benefits to the Community.

Goeffrey Rose postulated that a population-based measure bringing a small benefit to each individual can yield large benefits to the community. We aimed to test this axiom by quantifying the relationship between change in bone mineral density (BMD) and hip fracture incidence between two prospective cohorts separated by ~10 years. In this prospective population-based Dubbo Osteoporosis Epidemiology Study (DOES), the participants aged 60+ were recruited in two waves: the initial cohort (1311 women, 842 men) in 1989 to 1992 and the second cohort (974 women, 544 men) in 1999 to 2001. The incident hip fracture was radiologically ascertained. Femoral neck BMD was measured biannually. Multivariable-adjusted Cox's proportional hazards models were adjusted for the predefined covariates such as age, BMI, lifestyle factors, falls, and prior fracture. Compared with the initial cohort, the second cohort had a higher femoral neck BMD by ~0.04 g/cm2 in women and 0.03 g/cm2 in men. However, the prevalence of osteoporosis in the second cohort was halved (prevalence ratio 0.51, 95% CI 0.36 to 0.73 in women; 0.45, 0.24 to 0.84 in men), and its hip fracture incidence was significantly reduced (hazard ratio 0.54, 95% CI, 0.38 to 0.78 in women; 0.39, 0.19 to 0.80 in men). Sensitivity analyses indicated that the "effect" was unlikely due to unmeasured confounders. These findings suggest that a population-wide strategy aimed at enhancing BMD across the entire population could lead to a substantial decrease in the incidence of hip fractures. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).