著者

Hidehiro Someko Yuki Kataoka Taku Obara

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

pp.23013, (Released:2023-05-18)

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Drug fever is an adverse drug reaction accompanied by a febrile response and is a common problem among clinicians, hence an updated knowledge of drug fever is important. A consensus regarding the definition of drug fever is lacking. Thus, descriptions of drug fever in previous literature are often inconsistent. In this narrative review, we summarized various features of drug fever, including its definition, epidemiology, risk factors, clinical presentation, diagnosis, treatment and prognosis, based on the earliest literature. Recent advances in information technology have encouraged researchers to use pharmacovigilance databases for clinical and pharmacological research. We outlined how a pharmacovigilance database, along with recently developed research methods, could be used to research drug fever.

著者

Takeshi Unoki Hideaki Sakuramoto Shunsuke Taito Yuki Kataoka

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.78-87, 2021 (Released:2021-07-01)

参考文献数

24

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BACKGROUNDAlthough the majority of medical professionals recognize unplanned extubation as a critical accident, its relationship with the clinical outcomes of ventilated patients is controversial. The purpose of this study was to understand whether unplanned extubation, including self-extubation and accidental extubation, is a prognostic factor for clinical outcomes of mechanically ventilated adult patients.METHODSA pre-specified protocol was registered on PROSPERO (CRD42019120976). EMBASE, MEDLINE, CINAHL, and the ICTRP were searched on December 25, 2018 and February 5, 2020. The primary outcome was hospital mortality, and the secondary outcomes were ICU mortality, ICU and hospital length of stay, duration of mechanical ventilation, proportion of reintubation, and cost.RESULTSOf the 3216 articles retrieved, 11 were selected for the systematic review, and 9 met the criteria for the meta-analysis. Self-extubation was significantly associated with lower hospital mortality (OR = 0.49, 95% CI 0.30–0.81; certainty of evidence: moderate) and unplanned extubation was associated with ICU mortality (OR = 0.34, 95% CI 0.17–0.69; certainty of evidence: moderate). There were no significant between-group differences in lengths of hospital or ICU stay, with mean differences of 1.71 days (95% CI −7.68 to 11.69; certainty of evidence: very low) and 1.26 days (95% CI −3.58 to 6.10; certainty of evidence: very low), respectively.CONCLUSIONSSelf-extubation is associated with lower patient mortality, but a definitive conclusion cannot be made due to methodological limitations.

著者

Yuki Kataoka Shunkichi Ikegaki Daisuke Kato Toshihiko Takada Yasushi Tsujimoto Sho Sasaki Sei Takahashi

出版者

The Japanese Society of Internal Medicine

雑誌

Internal Medicine (ISSN:09182918)

巻号頁・発行日

pp.2312-18, (Released:2019-03-28)

参考文献数

21

被引用文献数

3

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Objective To describe the clinical research support systems in Japanese board certification programs of internal medicine and to assess the relationship between these support systems and the scholarly activities of residents. Methods In 2018, a 26-item web questionnaire was mailed to 542 points of contact of hospitals listed as certified residency programs of internal medicine in order to obtain information about the presence of a research support system and scholarly activity from 2016. We used hospital characteristic data from the Japanese Diagnostic Procedure Combination database, a national inpatient database, and the annual report of the Japanese Society of Internal Medicine. Results A total of 228 hospitals (42%) responded to the survey. There were regular research lectures in 129 hospitals (57%), protected time (time to perform research during working hours) in 53 hospitals (23%), research consultations in 175 hospitals (77%), regular journal clubs in 213 hospitals (77%), regular research conferences in 151 hospitals (66%), data warehouses in 139 hospitals (61%), and financial research support from the hospital budget in 140 hospitals (61%). A multivariate analysis showed that none of the research support systems were related to the number of conference presentations. In contrast, protected time (odds ratio [OR] 3.66, 95% confidence interval [CI] 1.43-9.39) and regular research conferences (OR 2.20, 95% CI 1.14-4.23) were related to the presence of clinical research presentations in scientific conferences hosted by residents. Conclusion Protected time and regular research conferences were related to the scholarly activity of residents in Japanese teaching hospitals.

著者

Masahiro Banno Yasushi Tsujimoto Yuki Kataoka

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

pp.22007, (Released:2022-02-09)

被引用文献数

2

著者

Akihiro Shiroshita Norio Yamamoto Natsumi Saka Hiroshi Shiba Shinji Toki Mari Yamamoto Eisuke Doi Yuki Kataoka

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

pp.24005, (Released:2023-06-10)

著者

Keisuke Anan Yuki Kataoka Kazuya Ichikado Kodai Kawamura Takeshi Johkoh Kiminori Fujimoto Kazunori Tobino Ryo Tachikawa Hiroyuki Ito Takahito Nakamura Tomoo Kishaba Minoru Inomata Yosuke Yamamoto

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

pp.22008, (Released:2022-02-09)

被引用文献数

4

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Background: This study aimed to develop criteria for identifying patients with acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) from Japanese administrative data and validate the pre-existing criteria.Methods: This retrospective, multi-center validation study was conducted at eight institutes in Japan to verify the diagnostic accuracy of the disease name for AE-IPF. We used the Japanese Diagnosis Procedure Combination data to identify patients with a disease name that could meet the diagnostic criteria for AE-IPF, who were admitted to the eight institutes from January 2016 to February 2019. As a reference standard, two respiratory physicians performed a chart review to determine whether the patients had a disease that met the diagnostic criteria for AE-IPF. Furthermore, two radiologists interpreted the chest computed tomography findings of cases considered AE-IPF and confirmed the diagnosis. We calculated the positive predictive value (PPV) for each disease name and its combination. Results: We included 830 patients; among them, 216 were diagnosed with AE-IPF through the chart review. We combined the groups of disease names and yielded two criteria: the criteria with a high PPV (0.72 [95% confidence interval 0.62 to 0.81]) and that with a slightly less PPV (0.61 [0.53 to 0.68]) but more true positives. Pre-existing criteria showed a PPV of 0.40 (0.31 to 0.49).Conclusion: The criteria derived in this study for identifying AE-IPF from Japanese administrative data show a fair PPV. Although these criteria should be carefully interpreted according to the target population, our findings could be utilized in future database studies on AE-IPF.

著者

Yuki Kataoka Tomohisa Baba Tatsuyoshi Ikenoue Yoshinori Matsuoka Junichi Matsumoto Junji Kumasawa Kentaro Tochitani Hiraku Funakoshi Tomohiro Hosoda Aiko Kugimiya Michinori Shirano Fumiko Hamabe Sachiyo Iwata Yoshiro Kitamura Tsubasa Goto Tomohiro Handa Shoji Kido Shingo Fukuma Noriyuki Tomiyama Toyohiro Hirai Takashi Ogura Japan COVID-19 AI team

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

pp.22014, (Released:2022-07-08)

被引用文献数

2

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Background: We aimed to develop and externally validate a novel machine learning model that can classify CT image findings as positive or negative for SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR).Methods: We used 2,928 images from a wide variety of case-control type data sources for the development and internal validation of the machine learning model. A total of 633 COVID-19 cases and 2,295 non-COVID-19 cases were included in the study. We randomly divided cases into training and tuning sets at a ratio of 8:2. For external validation, we used 893 images from 740 consecutive patients at 11 acute care hospitals suspected of having COVID-19 at the time of diagnosis. The dataset included 343 COVID-19 patients. The reference standard was RT-PCR.Results: In external validation, the sensitivity and specificity of the model were 0.869 and 0.432, at the low-level cutoff, 0.724 and 0.721, at the high-level cutoff. Area under the receiver operating characteristic was 0.76.Conclusions: Our machine learning model exhibited a high sensitivity in external validation datasets and may assist physicians to rule out COVID-19 diagnosis in a timely manner at emergency departments. Further studies are warranted to improve model specificity.

著者

Yuki Kataoka Shunkichi Ikegaki Daisuke Kato Toshihiko Takada Yasushi Tsujimoto Sho Sasaki Sei Takahashi

出版者

The Japanese Society of Internal Medicine

雑誌

Internal Medicine (ISSN:09182918)

巻号頁・発行日

vol.58, no.13, pp.1859-1864, 2019-07-01 (Released:2019-07-01)

参考文献数

21

被引用文献数

1 3

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Objective To describe the clinical research support systems in Japanese board certification programs of internal medicine and to assess the relationship between these support systems and the scholarly activities of residents. Methods In 2018, a 26-item web questionnaire was mailed to 542 points of contact of hospitals listed as certified residency programs of internal medicine in order to obtain information about the presence of a research support system and scholarly activity from 2016. We used hospital characteristic data from the Japanese Diagnostic Procedure Combination database, a national inpatient database, and the annual report of the Japanese Society of Internal Medicine. Results A total of 228 hospitals (42%) responded to the survey. There were regular research lectures in 129 hospitals (57%), protected time (time to perform research during working hours) in 53 hospitals (23%), research consultations in 175 hospitals (77%), regular journal clubs in 213 hospitals (77%), regular research conferences in 151 hospitals (66%), data warehouses in 139 hospitals (61%), and financial research support from the hospital budget in 140 hospitals (61%). A multivariate analysis showed that none of the research support systems were related to the number of conference presentations. In contrast, protected time [odds ratio (OR) 3.66, 95% confidence interval (CI) 1.43-9.39] and regular research conferences (OR 2.20, 95% CI 1.14-4.23) were related to the presence of clinical research presentations in scientific conferences hosted by residents. Conclusion Protected time and regular research conferences were related to the scholarly activity of residents in Japanese teaching hospitals.

著者

Shunsuke Taito Yuki Kataoka Takashi Ariie Shiho Oide Yasushi Tsujimoto

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

vol.3, no.2, pp.56-58, 2021 (Released:2021-04-01)

参考文献数

6

被引用文献数

4

著者

Yuki Kataoka Shiho Oide Takashi Ariie Yasushi Tsujimoto Toshi A. Furukawa

出版者

Society for Clinical Epidemiology

雑誌

Annals of Clinical Epidemiology (ISSN:24344338)

巻号頁・発行日

vol.3, no.2, pp.46-55, 2021 (Released:2021-04-01)

参考文献数

36

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BACKGROUNDThe objective of this study was to investigate the methodological quality of coronavirus disease 2019 (COVID-19) systematic reviews (SRs) indexed in medRxiv and PubMed, compared with Cochrane COVID Reviews.METHODSThis is a cross-sectional meta-epidemiological study. We searched medRxiv, PubMed, and Cochrane Database of Systematic Reviews for SRs of COVID-19. We evaluated the methodological quality using A MeaSurement Tool to Assess systematic Reviews (AMSTAR) checklists. The maximum AMSTAR score is 11, and minimum is 0. Higher score means better quality.RESULTSWe included 9 Cochrane reviews as well as randomly selected 100 non-Cochrane reviews in medRxiv and PubMed. Compared with Cochrane reviews (mean 9.33, standard deviation 1.32), the mean AMSTAR scores of the articles in medRxiv were lower (mean difference (MD): −2.85, 98.3% confidence intervals (CI): −0.96 to −4.74), and those in PubMed were also lower (MD: −3.28, 98.3%CI: −1.40 to −5.15), with no difference between the latter two.CONCLUSIONSReaders should pay attention to the potentially low methodological quality of SRs related to COVID-19 in both PubMed and medRxiv. Evidence users might be better to search the Cochrane Library rather than medRxiv or PubMed to search SRs related to COVID-19.