著者

Yuta Taniguchi Masao Iwagami Nobuo Sakata Taeko Watanabe Kazuhiro Abe Nanako Tamiya

出版者

Japan Epidemiological Association

雑誌

Journal of Epidemiology (ISSN:09175040)

巻号頁・発行日

pp.JE20200057, (Released:2020-06-13)

参考文献数

22

被引用文献数

10

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Background: With increasing age globally, more people may become vulnerable to food choking. We investigated the nationwide epidemiology of food choking deaths in Japan.Methods: Using Japanese Vital Statistics death data between 2006 and 2016, we identified food choking deaths based on the 10th revision of the International Statistical Classification of Diseases code W79 (Inhalation and ingestion of food causing obstruction of respiratory tract) as a primary diagnosis. We assessed the demographics of people with food choking deaths; temporal trends of food choking deaths by the year (overall and by age group), the day of year; and prefecture variations.Results: Overall, 52,366 people experienced food choking deaths (median age, 82 years, 53% were male, and 57% occurred at home). The highest numbers occurred January 1–3, and were lowest in June. Despite a stable total number of cases at around 4,000 yearly, from 2006 to 2016 the incidence proportion declined from 16.2 to 12.1 per 100,000 population among people aged 75–84 years. Among people ≥85 years, the incidence proportion peaked at 53.5 in 2008 and decreased to 43.6 in 2016. The number of food choking deaths varied by prefecture.Conclusions: There are temporal and regional variations of food choking deaths in Japan, possibly due to the consumption of Japanese rice cake (mochi), particularly over the New Year’s holiday.

著者

Yuta Taniguchi Masao Iwagami Nobuo Sakata Taeko Watanabe Kazuhiro Abe Nanako Tamiya

出版者

Japan Epidemiological Association

雑誌

Journal of Epidemiology (ISSN:09175040)

巻号頁・発行日

vol.31, no.5, pp.356-360, 2021-05-05 (Released:2021-05-05)

参考文献数

22

被引用文献数

10

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Background: With increasing age globally, more people may become vulnerable to food choking. We investigated the nationwide epidemiology of food choking deaths in Japan.Methods: Using Japanese Vital Statistics death data between 2006 and 2016, we identified food choking deaths based on the 10th revision of the International Statistical Classification of Diseases code W79 (Inhalation and ingestion of food causing obstruction of respiratory tract) as a primary diagnosis. We assessed the demographics of people with food choking deaths; temporal trends of food choking deaths by the year (overall and by age group), the day of year; and prefecture variations.Results: Overall, 52,366 people experienced food choking deaths (median age, 82 years, 53% were male, and 57% occurred at home). The highest numbers occurred January 1–3, and were lowest in June. Despite a stable total number of cases at around 4,000 yearly, from 2006 to 2016 the incidence proportion declined from 16.2 to 12.1 per 100,000 population among people aged 75–84 years. Among people ≥85 years, the incidence proportion peaked at 53.5 in 2008 and decreased to 43.6 in 2016. The number of food choking deaths varied by prefecture.Conclusions: There are temporal and regional variations of food choking deaths in Japan, possibly due to the consumption of Japanese rice cake (mochi), particularly over the New Year’s holiday.

著者

Masao Iwagami Tomohiro Shinozaki

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

vol.4, no.2, pp.33-40, 2022 (Released:2022-04-04)

参考文献数

27

被引用文献数

21

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Matching is a technique through which patients with and without an outcome of interest (in case-control studies) or patients with and without an exposure of interest (in cohort studies) are sampled from an underlying cohort to have the same or similar distributions of some characteristics. This technique is used to increase the statistical efficiency and cost efficiency of studies. In case-control studies, besides time in risk set sampling, controls are often matched for each case with respect to important confounding factors, such as age and sex, and covariates with a large number of values or levels, such as area of residence (e.g., post code) and clinics/hospitals. In the statistical analysis of matched case-control studies, fixed-effect models such as the Mantel-Haenszel odds ratio estimator and conditional logistic regression model are needed to stratify matched case-control sets and remove selection bias artificially introduced by sampling controls. In cohort studies, exact matching is used to increase study efficiency and remove or reduce confounding effects of matching factors. Propensity score matching is another matching method whereby patients with and without exposure are matched based on estimated propensity scores to receive exposure. If appropriately used, matching can improve study efficiency without introducing bias and could also present results that are more intuitive for clinicians.

著者

Masao Iwagami Hiroki Matsui

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

vol.4, no.3, pp.72-80, 2022 (Released:2022-07-01)

参考文献数

38

被引用文献数

5

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Clinical prediction models include a diagnostic prediction model to estimate the probability of an individual currently having a disease (e.g., pulmonary embolism) and a prognostic prediction model to estimate the probability of an individual developing a specific health outcome over a specific time period (e.g., myocardial infarction and stroke in 10 years). Clinical prediction models can be developed by applying traditional regression models (e.g., logistic and Cox regression models) or emerging machine learning models to real-world data, such as electronic health records and administrative claims data. For derivation, researchers select candidate variables based on a literature review and clinical knowledge, and predictor variables in the final model based on pre-defined criteria (e.g., thresholds for the size of relative risk and p-values) or strategies such as the stepwise regression and the least absolute shrinkage and selection operator (LASSO) regression. For validation, the clinical prediction model’s performance is evaluated in terms of goodness of fit (e.g., R2), discrimination (e.g., area under the receiver operating characteristic curve or c-statistics), and calibration (e.g., calibration plot and Hosmer-Lemeshow test). Performance of a new variable added to an existing clinical prediction model is evaluated in terms of reclassification (e.g., net reclassification improvement and integrated discrimination improvement). The model should be validated using the original data to examine internal validity through methods such as resampling (e.g., cross-validation and bootstrapping) and using other participants’ data to examine external validity. For successful implementation of a clinical prediction model in actual clinical practice, presentation methods such as paper-based (nomogram) or web-based calculator and an easy-to-use risk score should be considered.

著者

Jun Komiyama Masao Iwagami Takahiro Mori Naoaki Kuroda Xueying Jin Tomoko Ito Nanako Tamiya

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

vol.4, no.1, pp.11-19, 2022 (Released:2022-01-07)

参考文献数

36

被引用文献数

1

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BACKGROUNDAlthough outpatient cardiac rehabilitation has been shown to be effective, the participation status of older cardiac patients is unclear in real-world settings. We investigated the proportion and associated factors of outpatient cardiac rehabilitation participation among older patients with heart diseases after cardiac intervention.METHODSWe analyzed data from medical and long-term care insurance claims data from two municipalities in Japan. The data coverage period was between April 2014 and March 2019 in City A and between April 2012 and November 2016 in City B. We identified patients aged ≥65 years with post-operative acute myocardial infarction, angina pectoris, or heart valve disease. We estimated the proportion of cardiac rehabilitation participation and conducted logistic regression to identify factors (age, sex, type of cardiac disease, open-heart surgery, Charlson comorbidity index, long-term care need level, catecholamine use, inpatient cardiac rehabilitation, and hospital volume for cardiac rehabilitation) associated with outpatient cardiac rehabilitation participation.RESULTSA total of 690 patients were included in this study. The proportion of patients receiving outpatient cardiac rehabilitation was 9.0% overall. Multivariable logistic regression analysis suggested that men (adjusted OR 3.98; 95% CI 1.69–9.37), acute myocardial infarction (adjusted OR 2.76; 95% CI 1.20–6.36; reference angina pectoris), inpatient cardiac rehabilitation (adjusted OR 17.01; 95% CI 5.33–54.24), and “hospital volume” for cardiac rehabilitation (adjusted OR 4.35; 95% CI 1.14–16.57 for high-volume hospitals; reference low-volume hospital) were independently associated with outpatient cardiac rehabilitation.CONCLUSIONSThe participation rate of outpatient cardiac rehabilitation among older post-operative cardiac patients was suboptimal. Further studies are warranted to examine its generalizability and whether a targeted approach to a group of patients who are less likely to receive outpatient cardiac rehabilitation could improve the participation rate.

著者

Jun Komiyama Takehiro Sugiyama Masao Iwagami Miho Ishimaru Yu Sun Hiroki Matsui Keitaro Kume Masaru Sanuki Teruyuki Koyama Genta Kato Yukiko Mori Hiroaki Ueshima Nanako Tamiya

出版者

The Japanese Circulation Society

雑誌

Circulation Reports (ISSN:24340790)

巻号頁・発行日

pp.CR-22-0113, (Released:2023-04-12)

参考文献数

30

被引用文献数

1

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Background: Cardiac rehabilitation (CR) is an evidence-based medical service for patients with acute myocardial infarction (AMI); however, its implementation is inadequate. We investigated the provision status and equality of CR by hospitals in Japan using a comprehensive nationwide claims database.Methods and Results: We analyzed data from the National Database of Health Insurance Claims and Specific Health Checkups in Japan for the period April 2014–March 2016. We identified patients aged ≥20 years with postintervention AMI. We calculated hospital-level proportions of inpatient and outpatient CR participation. The equality of hospital-level proportions of inpatient and outpatient CR participation was evaluated using the Gini coefficient. We included 35,298 patients from 813 hospitals for the analysis of inpatients and 33,328 patients from 799 hospitals for the analysis of outpatients. The median hospital-level proportions of inpatient and outpatient CR participation were 73.3% and 1.8%, respectively. The distribution of inpatient CR participation was bimodal; the Gini coefficients of inpatient and outpatient CR participation were 0.37 and 0.73, respectively. Although there were statistically significant differences in the hospital-level proportion of CR participation for several hospital factors, CR certification status for reimbursement was the only visually evident factor affecting the distribution of CR participation.Conclusions: The distributions of inpatient and outpatient CR participation by hospitals were suboptimal. Further research is warranted to determine future strategies.

著者

Masao Iwagami Yoshinori Takeuchi

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

vol.3, no.3, pp.67-73, 2021 (Released:2021-07-01)

参考文献数

21

被引用文献数

6

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Self-controlled study designs, also known as case-only designs or Self-controlled Crossover Observational PharmacoEpidemiologic (SCOPE) studies, include case-crossover (CCO) and self-controlled case series (SCCS). These designs compare different time windows (i.e., lengths of time) within the same person. An SCCS compares the occurrence of an outcome (event) during periods with and without exposure in the same person, whereas a CCO compares periods with and without the outcome for exposure. The main strength of self-controlled study designs is that they can ignore confounding factors that do not change over time (e.g., sex, genetics, habitual healthy or unhealthy behaviors). The effect of these factors are canceled out through statistical analyses, even if they are unknown or unmeasured. However, self-controlled study designs cannot be used for all research questions. Assumptions specific to each study design are needed. In CCO, there should be no substantial changes in exposure trends during the study period, the exposure should be transient (intermittent), and the outcome should be abrupt (sudden). In SCCS, event rates should be constant within each defined period and events must be independently recurrent or rare. In addition, the occurrence of an event should not affect subsequent exposures. Self-controlled study designs may be particularly useful in studies using electronic health records, in which some (time-invariant) confounding factors may not have been recorded, provided that the research question meets the assumptions required for each study design.

著者

TAKENORI INOMATA JAEMYOUNG SUNG MASAHIRO NAKAMURA MASAO IWAGAMI YUICHI OKUMURA KENTA FUJIO YASUTSUGU AKASAKI KEIICHI FUJIMOTO AI YANAGAWA AKIE MIDORIKAWA-INOMATA KEN NAGINO ATSUKO EGUCHI HURRRAMHON SHOKIROVA JUN ZHU MARIA MIURA MIZU KUWAHARA KUNIHIKO HIROSAWA TIANXING HUANG YUKI MOROOKA AKIRA MURAKAMI

出版者

The Juntendo Medical Society

雑誌

順天堂醫事雑誌 (ISSN:21879737)

巻号頁・発行日

vol.67, no.6, pp.519-529, 2021 (Released:2021-12-31)

参考文献数

67

被引用文献数

9

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Society 5.0, a visionary human-centered societal model, fuels economic development and resolves long-standing social problems. The model establishes a technological foundation and social contract to integrate cyberspace into the physical (real) space fully. The medical infrastructure outlined by the model envisions a healthcare paradigm that revolves around preventative, lifelong patient- and population- centered care that functions seamlessly within one's daily life. In satisfying this goal, cross-hierarchical integrative data-driven biological research has received attention due to medical big data and artificial intelligence (AI) technologies, capable of highly accurate and rapid data analysis. However, the collection of big data has been a bottleneck, and the capability of AI analysis is not being utilized to its full potential. In solving this obstacle, we explore mobile health (mHealth) and multi-omics as two rich sources of medical big data. Additionally, we discuss the implications of cross-hierarchical integrative analysis that encompasses all levels of cellular function, from intracellular molecular dynamics to end-phenotypes. This is to understand ocular disease pathology and implement the pillars of P4 (predictive, personalized, preventative, participatory) medicine toward human-centered healthcare. Here, we discuss notable studies in utilizing mHealth to stratify subjective symptoms, presentations of dry eye disease, and employing multi-omics machine learning targeted at elucidating immunologic mechanisms of corneal allograft rejection and ocular inflammation. We also discuss the role of cross-hierarchical integrative data-driven research in promoting future-oriented healthcare envisioned by the Society 5.0 plan.

著者

Masao Iwagami Kanae Kubo Ryoichi Tanaka Kimito Kawahata Akiko Okamoto Noboru Hagino Kazuhiko Yamamoto

出版者

一般社団法人 日本内科学会

雑誌

Internal Medicine (ISSN:09182918)

巻号頁・発行日

vol.50, no.20, pp.2413-2416, 2011 (Released:2011-10-15)

参考文献数

14

被引用文献数

3 8

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We present the first documented case of thrombotic thrombocytopenic purpura (TTP) with severe hypertension complicated by polymyositis and systemic sclerosis sine scleroderma. TTP developed in the progressive phase of visceral fibrosis in the absence of skin thickening. ADAMTS13 activity was not useful for the diagnosis of TTP. Although TTP and scleroderma renal crisis (SRC) share similar findings of thrombotic microangiopathy, severe thrombocytopenia with multiple organ injuries and hemorrhagic manifestations suggested TTP rather than SRC. The patient's condition improved dramatically with plasmapheresis.