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BACKGROUND: Coronary artery calcium (CAC) has been widely recognized as an important predictor of cardiovascular disease (CVD). Given the finite resources, it is important to identify individuals who would receive the most benefit from detecting positive CAC by screening. However, the evidence is limited as to whether the burden of positive CAC on CVD differs by multidimensional individual characteristics. We sought to investigate the heterogeneity in the association between positive CAC and incident CVD. METHODS: This cohort study included adults from MESA (Multi-Ethnic Study of Atherosclerosis) ages ≥45 years and free of cardiovascular disease. After propensity score matching in a 1:1 ratio, we applied a machine learning causal forest model to (1) evaluate the heterogeneity in the association between positive CAC and incident CVD, and (2) predict the increase in CVD risk at 10-years when CAC>0 (versus CAC=0) at the individual level. We then compared the estimated increase in CVD risk when CAC>0 to the absolute 10-year atherosclerotic CVD (ASCVD) risk calculated by the 2013 American College of Cardiology/American Heart Association pooled cohort equations. RESULTS: Across 3328 adults in our propensity score-matched analysis, our causal forest model showed the heterogeneity in the association between CAC>0 and incident CVD. We found a dose-response relationship of the estimated increase in CVD risk when CAC>0 with higher 10-year ASCVD risk. Almost all individuals (2293 of 2428 [94.4%]) with borderline risk of ASCVD or higher showed ≥2.5% increase in CVD risk when CAC>0. Even among 900 adults with low ASCVD risk, 689 (69.2%) showed ≥2.5% increase in CVD risk when CAC>0; these individuals were more likely to be male, Hispanic, and have unfavorable CVD risk factors than others. CONCLUSIONS: The expected increases in CVD risk when CAC>0 were heterogeneous across individuals. Moreover, nearly 70% of people with low ASCVD risk showed a large increase in CVD risk when CAC>0, highlighting the need for CAC screening among such low-risk individuals. Future studies are needed to assess whether targeting individuals for CAC measurements based on not only the absolute ASCVD risk but also the expected increase in CVD risk when CAC>0 improves cardiovascular outcomes.
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Aterosclerose , Doenças Cardiovasculares , Doença da Artéria Coronariana , Calcificação Vascular , Adulto , Estados Unidos/epidemiologia , Humanos , Masculino , Pessoa de Meia-Idade , Feminino , Doença da Artéria Coronariana/diagnóstico por imagem , Doença da Artéria Coronariana/epidemiologia , Doenças Cardiovasculares/diagnóstico , Doenças Cardiovasculares/epidemiologia , Cálcio , Estudos de Coortes , Vasos Coronários/diagnóstico por imagem , Vasos Coronários/química , Medição de Risco/métodos , Fatores de Risco , Calcificação Vascular/diagnóstico por imagem , Calcificação Vascular/epidemiologiaRESUMO
BACKGROUND: Hypertension imposes substantial health and economic burden worldwide. Primary aldosteronism (PA) is one of the most common causes of secondary hypertension, causing cardiovascular events at higher risk compared with essential hypertension. However, the germline genetic contribution to the susceptibility of PA has not been well elucidated. METHOD: We conducted a genome-wide association analysis of PA in the Japanese population and a cross-ancestry meta-analysis combined with UK Biobank and FinnGen cohorts (816 PA cases and 425 239 controls) to identify genetic variants that contribute to PA susceptibility. We also performed a comparative analysis for the risk of 42 previously established blood pressure-associated variants between PA and hypertension with the adjustment of blood pressure. RESULTS: In the Japanese genome-wide association study, we identified 10 loci that presented suggestive evidence for the association with the PA risk (P<1.0×10-6). In the meta-analysis, we identified 5 genome-wide significant loci (1p13, 7p15, 11p15, 12q24, and 13q12; P<5.0×10-8), including 3 of the suggested loci in the Japanese genome-wide association study. The strongest association was observed at rs3790604 (1p13), an intronic variant of WNT2B (odds ratio, 1.50 [95% CI, 1.33-1.69]; P=5.2×10-11). We further identified 1 nearly genome-wide significant locus (8q24, CYP11B2), which presented a significant association in the gene-based test (P=7.2×10-7). Of interest, all of these loci were known to be associated with blood pressure in previous studies, presumably because of the prevalence of PA among individuals with hypertension. This assumption was supported by the observation that they had a significantly higher risk effect on PA than on hypertension. We also revealed that 66.7% of the previously established blood pressure-associated variants had a higher risk effect for PA than for hypertension. CONCLUSIONS: This study demonstrates the genome-wide evidence for a genetic predisposition to PA susceptibility in the cross-ancestry cohorts and its significant contribution to the genetic background of hypertension. The strongest association with the WNT2B variants reinforces the implication of the Wnt/ß-catenin pathway in the PA pathogenesis.
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Hiperaldosteronismo , Hipertensão , Humanos , Estudo de Associação Genômica Ampla , Hipertensão/epidemiologia , Hipertensão/genética , Pressão Sanguínea/genética , Fatores de Risco , Predisposição Genética para Doença , Hiperaldosteronismo/diagnóstico , Hiperaldosteronismo/epidemiologia , Hiperaldosteronismo/genética , Polimorfismo de Nucleotídeo Único , Loci GênicosRESUMO
Assessing heterogeneous treatment effects (HTEs) is an essential task in epidemiology. The recent integration of machine learning into causal inference has provided a new, flexible tool for evaluating complex HTEs: causal forest. In a recent paper, Jawadekar et al (Am J Epidemiol. 2023;192(7):1155-1165) introduced this innovative approach and offered practical guidelines for applied users. Building on their work, this commentary provides additional insights and guidance to promote the understanding and application of causal forest in epidemiologic research. We start with conceptual clarifications, differentiating between honesty and cross-fitting, and exploring the interpretation of estimated conditional average treatment effects. We then delve into practical considerations not addressed by Jawadekar et al, including motivations for estimating HTEs, calibration approaches, and ways to leverage causal forest output with examples from simulated data. We conclude by outlining challenges to consider for future advancements and applications of causal forest in epidemiologic research.
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Causalidade , Aprendizado de Máquina , Humanos , Estudos Epidemiológicos , Métodos Epidemiológicos , Modelos EstatísticosRESUMO
In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study the effects of Medicaid coverage using a randomized controlled design (Oregon Health Insurance Experiment). Analysis showed that Medicaid coverage lowered the risk of depression. However, this effect may vary between individuals, and the identification of individuals likely to benefit the most has the potential to improve the effectiveness and efficiency of the Medicaid program. By applying the machine learning causal forest to data from this experiment, we found substantial heterogeneity in the effect of Medicaid coverage on depression; individuals with high predicted benefit were older and had more physical or mental health conditions at baseline. Expanding coverage to individuals with high predicted benefit generated greater reduction in depression prevalence than expanding to all eligible individuals (21.5 vs 8.8 percentage-point reduction; adjusted difference = +12.7 [95% CI, +4.6 to +20.8]; P = 0.003), at substantially lower cost per case prevented ($16 627 vs $36 048; adjusted difference = -$18 598 [95% CI, -156 953 to -3120]; P = 0.04). Medicaid coverage reduces depression substantially more in a subset of the population than others, in ways that are predictable in advance. Targeting coverage on those most likely to benefit could improve the effectiveness and efficiency of insurance expansion. This article is part of a Special Collection on Mental Health.
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Depressão , Cobertura do Seguro , Aprendizado de Máquina , Medicaid , Humanos , Medicaid/estatística & dados numéricos , Estados Unidos , Feminino , Masculino , Adulto , Oregon , Pessoa de Meia-Idade , Cobertura do Seguro/estatística & dados numéricos , Adulto JovemRESUMO
BACKGROUND: We evaluated whether participants in the landmark Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial represent US adults aged ≥40 with diabetes. METHODS: Using the nationally representative 2017-2020 prepandemic National Health and Nutrition Examination Survey data, we made operational definitions of ACCORD eligibility criteria. We calculated the percentage of individuals aged ≥40 with diabetes and HbA1c ≥ 6.0% or ≥ 7.5% who met operational ACCORD eligibility criteria. RESULTS: Applying survey sampling weights to 715 National Health and Nutrition Examination Survey participants aged ≥40 with diabetes and HbA1c ≥ 6.0% (representing 29,717,406 individuals), 12% (95% confidence interval [CI] = 8%, 18%) met the operational ACCORD eligibility criteria. Restricting to HbA1c ≥ 7.5%, 39% (95% CI = 28%, 51%) of respondents met the operational ACCORD eligibility criteria. CONCLUSIONS: ACCORD represented a minority of US middle-aged and older adults with diabetes. Given the differential risk profile between ACCORD participants and the general population with diabetes, extrapolating the trial findings may not be appropriate.
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Hemoglobinas Glicadas , Inquéritos Nutricionais , Humanos , Estados Unidos/epidemiologia , Pessoa de Meia-Idade , Idoso , Masculino , Feminino , Adulto , Hemoglobinas Glicadas/análise , Diabetes Mellitus Tipo 2/tratamento farmacológico , Diabetes Mellitus Tipo 2/epidemiologia , Doenças Cardiovasculares/epidemiologia , Diabetes Mellitus/epidemiologia , Diabetes Mellitus/tratamento farmacológico , Definição da ElegibilidadeRESUMO
In observational studies, identifying and adjusting for a sufficient set of confounders is crucial for accurately estimating the causal effect of the exposure on the outcome. Even in studies with large sample sizes, which typically benefit from small variances in estimates, there is a risk of producing estimates that are precisely inaccurate if the study suffers from systematic errors or biases, including confounding bias. To date, several approaches have been developed for selecting confounders. In this article, we first summarize the epidemiological and statistical approaches to identify a sufficient set of confounders. Particularly, we introduce the modified disjunctive cause criterion as one of the most useful approaches, which involves controlling for any pre-exposure covariate that affects the exposure, outcome, or both. It then excludes instrumental variables but includes proxies for the shared common cause of exposure and outcome. Statistical confounder selection is also useful when dealing with a large number of covariates, even in studies with small sample sizes. After introducing several approaches, we discuss some pitfalls and considerations in confounder selection, such as the adjustment for instrumental variables, intermediate variables, and baseline outcome variables. Lastly, as it is often difficult to comprehensively measure key confounders, we introduce two statistics, E-value and Robustness value, for assessing sensitivity to unmeasured confounders. Illustrated examples are provided using the National Health and Nutritional Examination Survey Epidemiologic Follow-up Study. Integrating these principles and approaches will enhance our understanding of confounder selection and facilitate better reporting and interpretation of future epidemiological studies.
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BACKGROUND: The United Nations Decade of Healthy Ageing 2021-2030 suggests nations should monitor functional ability as an indicator of healthy ageing progress. Functional ability is the attribute of people to do something they value and consists of five domains. We examined its validity in terms of a construct, cross-validation across multiple waves' data, and predictivity for subsequent well-being. METHODS: Using panel data from 35,093 community-dwelling adults aged ≥65 years from the Japan Gerontological Evaluation Study, we performed factor analyses to explore the construct of functional ability domains in both 2013 and 2016. A modified Poisson regression analysis was employed to test their associations with well-being (subjective health and happiness) in 2019. RESULTS: The mean age (standard deviation) of participants was 72.1 (5.0) years, and 52.0% were women. A total of 85.0% reported good subjective health, and 50.6% reported high happiness levels. Factor analyses with 31 logically checked candidate items from 2016 data suggested a three-factor model comprising 24 items, which were compatible with the 2013 data results. Based on the World Health Organization's original domains, we named domains as domain #1: ability to build and maintain relationships; domain #2: ability to meet basic needs + ability to move around and domain #3: ability to learn, grow and make decisions + ability to contribute. All three domains predicted both subjective health and happiness in 2019. CONCLUSIONS: Empirical data from Japan supports the functional ability concept among older individuals. Validating this concept with data from other nations is warranted.
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Geriatria , Envelhecimento Saudável , Humanos , Feminino , Idoso , Masculino , Japão , Atividades Cotidianas , Vida IndependenteRESUMO
BACKGROUND: While clinical features of KCNJ5-mutated aldosterone-producing adenoma (APA) have been reported, evidence of its clinical outcomes is lacking. We aimed to synthesize available literature about the associations between KCNJ5 mutation with cardiovascular and metabolic outcomes among patients with APA. METHODS: In this systematic review of observational studies, MEDLINE and Embase were searched through August 2022. Two independent authors screened the search results and extracted data from eligible observational studies investigating cardiovascular or metabolic outcomes between KCNJ5-mutated APAs and KCNJ5-non-mutated APAs. Risk of Bias In Non-randomized Studies of Interventions was used to assess the quality of the included studies. RESULTS: A total of 573 titles/abstracts were screened and after the expert opinion of the literature, full text was read in 20 titles/abstracts, of which 12 studies were included. Across 3 studies comparing the baseline or change in the cardiac function between KCNJ5-mutated APAs and KCNJ5-non-mutated APAs, all studies reported the association between impaired cardiac functions and KCNJ5 mutation status. Among 6 studies evaluating the cure of hypertension after surgery, all studies showed that KCNJ5 mutation was significantly associated with the cure of hypertension. In quality assessment, 7 studies were at serious risk of bias, while the remaining studies were at moderate risk of bias. CONCLUSIONS: This systematic review provided evidence of the significant association between KCNJ5 mutation and unfavorable cardiovascular outcomes in patients with primary aldosteronism. Further research is needed to improve the quality of evidence on this topic and elucidate the underlying mechanisms of the potential burden of KCNJ5 mutation.
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Aldosterona , Canais de Potássio Corretores do Fluxo de Internalização Acoplados a Proteínas G , Mutação , Humanos , Canais de Potássio Corretores do Fluxo de Internalização Acoplados a Proteínas G/genética , Aldosterona/metabolismo , Aldosterona/biossíntese , Doenças Cardiovasculares/genética , Neoplasias do Córtex Suprarrenal/genética , Hiperaldosteronismo/genética , Adenoma Adrenocortical/genética , Adenoma Adrenocortical/metabolismo , Adenoma/genética , Adenoma/metabolismoRESUMO
With the rapid development of computer science, there is an increasing demand for the use of causal inference methods and machine learning in the research of endocrine disorders and their long-term health outcomes. However, studies on the effective and appropriate applications of these approaches in real-world data and clinical settings are still limited. This review will illustrate the use of causal inference and machine learning in epidemiological research within the field of endocrinology and metabolism. It will examine each concept of causal inference and machine learning through application examples of endocrine disorders. Subsequently, the paper will discuss the integration of machine learning within the causal inference framework, including (i) the estimation of treatment effects or the causal relationship between exposure and outcomes, and (ii) the evaluation of heterogeneity in such treatment effects (or exposure-outcome causal relationship) based on individuals' characteristics. Accurately assessing causal relationships and their heterogeneity across different individuals is crucial not only for determining effective interventions, but also for the appropriate allocation of medical resources and reducing healthcare disparities. By illustrating some application examples in endocrinology, this review aims to enhance readers' understanding and application of causal inference and machine learning in future epidemiological studies focusing on endocrine disorders.
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Agranulocytosis is a serious adverse effect of methimazole (MMI) and propylthiouracil (PTU), and although there have been reports suggesting a dose-dependent incidence in relation to both drugs, the evidence has not been conclusive. The objective of our study was to determine whether the incidences of agranulocytosis induced by MMI and PTU exhibit dose-dependency. The subjects were 27,784 patients with untreated Graves' disease, 22,993 of whom were on an antithyroid drug treatment regimen for more than 90 days. Within this subset, 18,259 patients had been treated with MMI, and 4,734 had been treated with PTU. The incidence of agranulocytosis according to dose in the MMI group was 0.13% at 10 mg/day, 0.20% at 15 mg/day, 0.32% at 20 mg/day, and 0.47% at 30 mg/day, revealing a significant dose-dependent increase. In the PTU group, there were 0 cases of agranulocytosis at doses of 125 mg/day and below, 0.33% at 150 mg/day, 0.31% at 200 mg/day, and 0.81% at 300 mg/day, also revealing a significant dose-dependent increase. The incidence of agranulocytosis at MMI 15 mg and PTU 300 mg, i.e., at the same potency in terms of hormone synthesis inhibition, was 0.20% and 0.81%, respectively, and significantly higher in the PTU group. Our findings confirm a dose-dependent increase in the incidence of agranulocytosis with both drugs, but that at comparable thyroid hormone synthesis inhibitory doses PTU has a considerably higher propensity to induce agranulocytosis than MMI does.
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Agranulocitose , Antitireóideos , Relação Dose-Resposta a Droga , Doença de Graves , Metimazol , Propiltiouracila , Humanos , Metimazol/efeitos adversos , Propiltiouracila/efeitos adversos , Agranulocitose/induzido quimicamente , Agranulocitose/epidemiologia , Antitireóideos/efeitos adversos , Feminino , Masculino , Doença de Graves/tratamento farmacológico , Adulto , Incidência , Pessoa de Meia-Idade , Idoso , Adulto Jovem , AdolescenteRESUMO
BACKGROUND: Although many conventional healthcare services to prevent postpartum depression are provided face-to-face, physical and psychosocial barriers remain. These barriers may be overcome by using mobile health services (mHealth). To examine the effectiveness of mHealth professional consultation services in preventing postpartum depressive symptoms in real-world settings, we conducted this randomized controlled trial in Japan, where universal free face-to-face perinatal care is available. METHODS: This study included 734 pregnant women living in Yokohama city who could communicate in Japanese, recruited at public offices and childcare support facilities. The participants were randomized to the mHealth group (intervention, n = 365), where they could use a free app-based mHealth consultation service with gynecologists/obstetricians, pediatricians, and midwives whenever and as many times as they wanted between 6 p.m. and 10 p.m. on weekdays throughout their pregnancy and postpartum periods (funded by the City of Yokohama government) or the usual care group (control, n = 369). The primary outcome was the risk of elevated postpartum depressive symptoms, defined as Edinburgh Postnatal Depression Scale score ≥ 9. Secondary outcomes were self-efficacy, loneliness, perceived barriers to healthcare access, number of clinic visits, and ambulance usage. All outcomes were collected three months post-delivery. We also conducted subgroup analyses assessing the differences in the treatment effect by sociodemographic status. RESULTS: Most women completed all questionnaires (n = 639 of 734, response rate: 87%). The mean baseline age was 32.9 ± 4.2 years, and 62% were primipara. Three months post-delivery, women in the mHealth group had a lower risk of elevated postpartum depressive symptoms (47/310 [15.2%]) compared to the usual care group (75/329 [22.8%], risk ratio: 0.67 [95% confidence interval: 0.48-0.93]). Compared with the usual care group, women in the mHealth group had higher self-efficacy, less loneliness, and fewer perceived barriers to healthcare access. No differences were observed in the frequency of clinic visits or ambulance usage. Furthermore, in the subgroup analyses, we did not find differences in the treatment effect by sociodemographic status. CONCLUSIONS: Local government-funded mHealth consultation services have a preventive effect on postpartum depressive symptoms, removing physical and psychological barriers to healthcare access in real-world settings. TRIAL REGISTRATION: UMIN-CTR identifier: UMIN000041611. Registered 31 August 2021.
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Depressão Pós-Parto , Depressão , Feminino , Gravidez , Humanos , Adulto , Depressão/prevenção & controle , Depressão Pós-Parto/prevenção & controle , Período Pós-Parto , Gestantes/psicologia , Encaminhamento e ConsultaRESUMO
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that induce oxidative inflammatory responses and disrupt the endocrine and central nervous systems, all of which can influence sleep. OBJECTIVE: To investigate the association between PFAS exposure and sleep health measures in U.S. adults. METHODS: We analyzed serum concentration data of four PFAS [perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] reported for 8913 adults in NHANES 2005-2014. Sleep outcomes, including trouble sleeping, having a diagnosis of sleep disorder, and recent daily sleep duration classified as insufficient or excessive sleep (<6 or >9 h/day) were examined. Weighted logistic regression was used to estimate the association between the sleep outcomes and each PFAS modeled continuously (log2) or in exposure tertiles. We applied quantile g-computation to estimate the effect of the four PFAS as a mixture on the sleep outcomes. We conducted a quantitative bias analysis to assess the potential influence of self-selection and uncontrolled confounding. RESULTS: We observed some inverse associations between serum PFAS and trouble sleeping or sleep disorder, which were more consistent for PFOS (e.g., per log2-PFOS (ng/ml) and trouble sleeping OR = 0.93, 95%CI: 0.89, 0.98; sleep disorder OR = 0.89, 95%CI: 0.83, 0.95). Per quartile increase of the PFAS mixture was inversely associated with trouble sleeping and sleep disorder. No consistent associations were found for sleep duration across analyses. Our bias analysis suggests that the finding on sleep disorder could be explained by a moderate level of self-selection and negative confounding effects. CONCLUSIONS: We found no evidence to suggest exposure to four legacy PFAS worsened self-reported sleep health among U.S. adults. While some inverse associations between specific PFAS and sleep disorder were observed, self-selection and uncontrolled confounding biases may play a role in these findings.
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OBJECTIVE: Income is a major social determinant of cardiovascular health. However, individual-level evidence regarding the trends in cardiovascular risk factors by income level among young working-age adults is limited. We thus aimed to examine the trends in cardiovascular risk factors among men and women aged 30-49 years by their income levels. METHODS: This nationwide longitudinal study included Japanese adults aged 30-49 years, who annually participated in the national health screening program from 2017 to 2020. Modified Poisson regression models were used to investigate trends in the prevalence of cardiovascular risk factors (obesity, hypertension, diabetes, and dyslipidemia) according to tertiles of individuals' annual income, adjusting for potential confounders. RESULTS: Among 58 814 adults, 50 024 (85%) were men; the mean (SD) age was 42.1 (5.4) years. Over the study period, the low-income group consistently showed a higher prevalence of obesity, hypertension, and diabetes than the high-income group. The difference in the prevalence of these diseases, particularly hypertension, across income groups increased from 2017 to 2020 among both men (low-income vs high-income: +5.73% [95% CI, 4.72-6.73] in 2017 and +8.26% [95% CI, 7.11-9.41] in 2020) and women (low-income vs high-income: +2.53% [95% CI, 0.99-4.06] in 2017 and +3.83% [95% CI, 1.93-5.73] in 2020). CONCLUSION: Among adults aged 30-49 years in Japan, a country with a universal healthcare coverage system, we found an increase in the gap of cardiovascular risk factors by income levels over the last 4 years. Careful monitoring of the increasing social disparities is needed to achieve cardiovascular health equity at this life stage.
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Doenças Cardiovasculares , Diabetes Mellitus , Hipertensão , Adulto , Feminino , Humanos , Masculino , Doenças Cardiovasculares/epidemiologia , Estudos de Coortes , Diabetes Mellitus/epidemiologia , População do Leste Asiático , Fatores de Risco de Doenças Cardíacas , Hipertensão/epidemiologia , Estudos Longitudinais , Obesidade/complicações , Prevalência , Fatores de Risco , Pessoa de Meia-IdadeRESUMO
Appropriate administration of anti-inflammatory and immunosuppressive treatment (AIIST) is important for patients with Graves' orbitopathy (GO). This study aimed to clarify the incidence and risk factors for GO treated with AIIST and propose a predictive score, among newly diagnosed Graves' disease (GD) patients in Japan. A total of 1,553 GD patients who were newly diagnosed during the year 2011 were investigated. AIIST included local and/or systemic glucocorticoid administration and retrobulbar irradiation. A multivariable Cox proportional hazards model was used to investigate the risk factors for GO underwent AIIST during medical treatment, including at diagnosis, of GD. Then, a GO score was created by summing each point assigned to risk factors based on their coefficient obtained in the Cox model. AIIST was administered to 107 patients (6.9%). The risk factors and hazard ratios for GO underwent AIIST were: age (per 10 years), 1.32 (95% confidence interval: 1.16-1.50), p < 0.0001; TSH binding inhibitory immunoglobulin (TBII) (per 10 IU/L), 1.33 (1.15-1.54), p = 0.0001; and thyroglobulin antibody (TgAb) negativity, 2.98 (1.96-4.59), p < 0.0001. The GO score, ranging from 0 to 8 points, showed moderate performance (area under the curve: 0.71, cut-off value: 5 points, sensitivity: 0.76, specificity: 0.59, positive predictive value: 0.12, negative predictive value: 0.97). AIIST was performed for patients with active manifestations of GO in 6.9% of newly diagnosed GD patients. The risk factors for GO underwent AIIST were higher age, higher TBII, and TgAb negativity. The GO score based on these factors may be useful in managing GO.
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Doença de Graves , Oftalmopatia de Graves , Humanos , Criança , Oftalmopatia de Graves/diagnóstico , Oftalmopatia de Graves/tratamento farmacológico , Oftalmopatia de Graves/epidemiologia , Incidência , Autoanticorpos , Doença de Graves/diagnóstico , Doença de Graves/tratamento farmacológico , Doença de Graves/epidemiologia , Fatores de Risco , Anti-Inflamatórios/uso terapêuticoRESUMO
BACKGROUND: Although remote communication technologies have been widely used to maintain connections with others against interpersonal contact restrictions and exacerbated loneliness during the COVID-19 pandemic, it is unclear whether and what types of remote communication technologies are effective in mitigating loneliness. OBJECTIVE: This study aimed to investigate the association between remote communication and loneliness when face-to-face meetings with others were strongly prohibited and whether this association varied across types of communication tools, age, and gender. METHODS: We used cross-sectional data from the Japan COVID-19 and Society Internet Survey conducted from August to September 2020. From registered panelists of the research agency, 28,000 randomly sampled participants completed the survey on the website. We created 2 study cohorts who stopped meeting with family members living apart and friends during the pandemic. We categorized whether participants had technology-based remote communication (voice calling, text messaging, and video calling) with family and friends. Loneliness was assessed using the 3-item University of California, Los Angeles Loneliness Scale. We used a modified Poisson regression model to investigate the association between loneliness and remote communication with family members living apart or friends. We also conducted subgroup analyses based on age and gender. RESULTS: A total of 4483 participants stopped meeting with family members living apart, and 6783 participants stopped meeting with friends during the COVID-19 pandemic. Remote communication with family members living apart did not show an association with loneliness, whereas remote communication with friends was associated with a low prevalence of loneliness (family: adjusted prevalence ratio [aPR]=0.89, 95% CI 0.74-1.08; P=.24 and friends: aPR=0.82, 95% CI 0.73-0.91; P<.001). From analyses by tools, voice calling was associated with low loneliness (family: aPR=0.88, 95% CI 0.78-0.98; P=.03 and friends: aPR=0.87, 95% CI 0.80-0.95; P=.003). Similarly, text messaging was associated with low loneliness (family: aPR=0.82, 95% CI 0.69-0.97; P=.02 and friends: aPR=0.81, 95% CI 0.73-0.89; P<.001). However, we did not find an association between video calling and loneliness (family: aPR=0.88, 95% CI 0.75-1.02; P=.09 and friends: aPR=0.94, 95% CI 0.85-1.04; P=.25). Text messaging with friends was associated with low loneliness regardless of age, whereas voice calling with family or friends was associated with low loneliness only among participants aged ≥65 years. An association between remote communication with friends and low loneliness was found regardless of the type of remote communication tool among men, whereas it was found only for text messaging with friends among women. CONCLUSIONS: In this cross-sectional study of adults in Japan, remote communication, especially via voice calling and text messaging, was associated with low loneliness. Promoting remote communication may reduce loneliness when face-to-face contact is restricted, which should be the subject of future research.
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COVID-19 , Pandemias , Adulto , Masculino , Feminino , Humanos , Idoso , Estudos Transversais , COVID-19/epidemiologia , Solidão , ComunicaçãoRESUMO
BACKGROUND: Chronic pain is the leading cause of disability worldwide and is strongly associated with the epidemic of opioid overdosing events. However, the causal links between chronic pain, opioid prescriptions, and mortality remain unclear. METHODS: This study included 13,884 US adults aged ≥20 years who provided data on chronic pain in the National Health and Nutrition Examination Survey 1999-2004 with linkage to mortality databases through 2015. We employed the generalized form of the front-door formula within the structural causal model framework to investigate the causal effect of chronic pain on all-cause mortality mediated by opioid prescriptions. RESULTS: We identified a total of 718 participants at 3 years of follow-up and 1260 participants at 5 years as having died from all causes. Opioid prescriptions increased the risk of all-cause mortality with an estimated odds ratio (OR) (95% confidence interval) = 1.5 (1.1, 1.9) at 3 years and 1.3 (1.1, 1.6) at 5 years. The front-door formula revealed that chronic pain increased the risk of all-cause mortality through opioid prescriptions; OR = 1.06 (1.01, 1.11) at 3 years and 1.03 (1.01, 1.06) at 5 years. Our bias analysis showed that our findings based on the front-door formula were likely robust to plausible sources of bias from uncontrolled exposure-mediator or mediator-outcome confounding. CONCLUSIONS: Chronic pain increased the risk of all-cause mortality through opioid prescriptions. Our findings highlight the importance of careful guideline-based chronic pain management to prevent death from possibly inappropriate opioid prescriptions driven by chronic pain.
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Analgésicos Opioides , Dor Crônica , Adulto , Analgésicos Opioides/uso terapêutico , Dor Crônica/tratamento farmacológico , Dor Crônica/epidemiologia , Humanos , Inquéritos Nutricionais , Razão de Chances , PrescriçõesRESUMO
BACKGROUND: A study has shown that industry payments to physicians for drugs are associated not only with higher drug prescriptions but also with higher non-drug costs due to additional utilization of healthcare services. However, the association between industry payments to cardiologists for antiplatelet drugs and the costs and number of percutaneous coronary interventions they perform has not been investigated. OBJECTIVE: To examine the association between industry payments to cardiologists for antiplatelet drugs and the costs and number of percutaneous coronary interventions they perform. DESIGN: Using the 2016 Open Payments Database linked to the 2017 Medicare Provider Utilization and Payment Data, we examined the association between the value of industry payments related to the antiplatelet drugs prasugrel and ticagrelor and healthcare spending and volume for cardiovascular procedures, adjusted for potential cofounders. SUBJECTS: A total of 7456 cardiologists who performed diagnostic cardiac catheterizations on Medicare beneficiaries in 2017. MAIN MEASURES: Primary outcomes included (1) healthcare spending on cardiac procedures, (2) diagnostic cardiac catheterization volumes, and (3) rates of coronary stenting. Secondary outcomes were total expenditures for all drugs and for antiplatelet drugs. KEY RESULTS: Industry payments for antiplatelet drugs were associated with higher healthcare spending on cardiac procedures (adjusted difference, +$50.9 for additional $100 industry payments; 95% CI, +$25.5 to +$76.2; P < 0.001), diagnostic cardiac catheterizations (+0.1 procedures per cardiologist; 95% CI, +0.03 to +0.1; P=0.001), and stent use (+0.5 per 1000 diagnostic cardiac catheterizations per cardiologist; 95% CI, +0.2 to +0.9; P=0.002). Industry payments for antiplatelet drugs were associated with higher total costs for all drugs and antiplatelet drugs. CONCLUSIONS: Industry payments to cardiologists for antiplatelet drugs were associated with both prescribing of antiplatelet drugs and the use of cardiac procedures and stents. Further research is warranted to understand whether the observed associations are causal or reflect a greater propensity for higher volume proceduralists to have relationships with industry.
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Medicare Part D , Médicos , Medicamentos sob Prescrição , Idoso , Indústria Farmacêutica , Humanos , Inibidores da Agregação Plaquetária/uso terapêutico , Padrões de Prática Médica , Stents , Estados UnidosRESUMO
BACKGROUND: An inappropriately low frequency of healthcare utilization has been reported to be associated with poor control of chronic diseases, accelerating healthcare disparities. However, the evidence is limited regarding the association between no healthcare utilization and mortality. OBJECTIVES: To examine whether individuals without healthcare utilization have the increased risks of mortality among the US general population. DESIGN: Prospective cohort study PARTICIPANTS: Adults aged ≥ 20 years (n = 39,067) in the National Health and Nutrition Examination Survey (NHANES)1999-2014 linked to national mortality data through December 2015. MAIN MEASURES: The exposure was the number of visits to healthcare providers during the past year (healthcare utilization): none, 1-3 times (referent), 4-9 times, or ≥ 10 times. Cox hazard regression models were employed to estimate the adjusted hazard ratios (aHR) of all-cause, cardiovascular, and cancer mortality adjusting for socio-demographic characteristics and comorbidities. KEY RESULTS: During a median follow-up of 7.4 years, participants without visit over the past year showed higher risks of all-cause mortality (aHR [95% CI] = 1.16 [1.04-1.30]) and cardiovascular mortality (aHR [95% CI] = 1.62 [1.28-2.05]) than those who visited the office 1-3 times. We found no evidence of the association between no visit and cancer mortality. The association between no providers' office visit and all-cause mortality was stronger among males (aHR [95% CI] = 1.22 [1.06-1.40]) than females (aHR [95% CI] = 0.97 [0.79-1.19]; p-for-interaction = 0.01) and among uninsured individuals (aHR [95% CI] = 1.22 [0.98-1.51]) than insured individuals (aHR [95% CI] = 1.09 [0.95-1.25]; p-for-interaction = 0.04). CONCLUSION: No providers' office visit over a year was associated with increased risks of all-cause and cardiovascular mortality. Further investigations are warranted to identify the underlying reasons for the elevated mortality risks due to no healthcare utilization.
Assuntos
Doenças Cardiovasculares , Neoplasias , Adulto , Doenças Cardiovasculares/epidemiologia , Feminino , Humanos , Masculino , Neoplasias/terapia , Inquéritos Nutricionais , Aceitação pelo Paciente de Cuidados de Saúde , Estudos Prospectivos , Fatores de RiscoRESUMO
BACKGROUND: It is often challenging to determine which variables need to be included in the g-computation algorithm under the time-varying setting. Conditioning on instrumental variables (IVs) is known to introduce greater bias when there is unmeasured confounding in the point-treatment settings, and this is also true for near-IVs which are weakly associated with the outcome not through the treatment. However, it is unknown whether adjusting for (near-)IVs amplifies bias in the g-computation algorithm estimators for time-varying treatments compared to the estimators ignoring such variables. We thus aimed to compare the magnitude of bias by adjusting for (near-)IVs across their different relationships with treatments in the time-varying settings. METHODS: After showing a case study of the association between the receipt of industry payments and physicians' opioid prescribing rate in the US, we demonstrated Monte Carlo simulation to investigate the extent to which the bias due to unmeasured confounders is amplified by adjusting for (near-)IV across several g-computation algorithms. RESULTS: In our simulation study, adjusting for a perfect IV of time-varying treatments in the g-computation algorithm increased bias due to unmeasured confounding, particularly when the IV had a strong relationship with the treatment. We also found the increase in bias even adjusting for near-IV when such variable had a very weak association with unmeasured confounders between the treatment and the outcome compared to its association with the time-varying treatments. Instead, this bias amplifying feature was not observed (i.e., bias due to unmeasured confounders decreased) by adjusting for near-IV when it had a stronger association with the unmeasured confounders (≥0.1 correlation coefficient in our multivariate normal setting). CONCLUSION: It would be recommended to avoid adjusting for perfect IV in the g-computation algorithm to obtain a less biased estimate of the time-varying treatment effect. On the other hand, it may be recommended to include near-IV in the algorithm unless their association with unmeasured confounders is very weak. These findings would help researchers to consider the magnitude of bias when adjusting for (near-)IVs and select variables in the g-computation algorithm for the time-varying setting when they are aware of the presence of unmeasured confounding.
Assuntos
Analgésicos Opioides , Padrões de Prática Médica , Algoritmos , Analgésicos Opioides/uso terapêutico , Viés , Humanos , PrescriçõesRESUMO
BACKGROUND AND AIM: Although endoscopic resection with careful surveillance instead of total proctocolectomy become to be permitted for visible low-grade dysplasia, it is unclear how accurately endoscopists can differentiate these lesions, as classifying neoplasias occurring in inflammatory bowel disease (IBDN) is exceedingly challenging due to background chronic inflammation. We evaluated a pilot model of an artificial intelligence (AI) system for classifying IBDN and compared it with the endoscopist's ability. METHODS: This study used a deep convolutional neural network, the EfficientNet-B3. Among patients who underwent treatment for IBDN at two hospitals between 2003 and 2021, we selected 862 non-magnified endoscopic images from 99 IBDN lesions and utilized 6 375 352 images that were increased by data augmentation for the development of AI. We evaluated the diagnostic ability of AI using two classifications: the "adenocarcinoma/high-grade dysplasia" and "low-grade dysplasia/sporadic adenoma/normal mucosa" groups. We compared the diagnostic accuracy between AI and endoscopists (three non-experts and four experts) using 186 test set images. RESULTS: The diagnostic ability of the experts/non-experts/AI for the two classifications in the test set images had a sensitivity of 60.5% (95% confidence interval [CI]: 54.5-66.3)/70.5% (95% CI: 63.8-76.6)/72.5% (95% CI: 60.4-82.5), specificity of 88.0% (95% CI: 84.7-90.8)/78.8% (95% CI: 74.3-83.1)/82.9% (95% CI: 74.8-89.2), and accuracy of 77.8% (95% CI: 74.7-80.8)/75.8% (95% CI: 72-79.3)/79.0% (95% CI: 72.5-84.6), respectively. CONCLUSIONS: The diagnostic accuracy of the two classifications of IBDN was higher than that of the experts. Our AI system is valuable enough to contribute to the next generation of clinical practice.