- 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
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
- Kensaku Aihara Tomohiro Handa Sonoko Nagai Kiminobu Tanizawa Kizuku Watanabe Yuka Harada Yuichi Chihara Takefumi Hitomi Toru Oga Tomomasa Tsuboi Kazuo Chin Michiaki Mishima
- 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.11, pp.1157-1162, 2011 (Released:2011-06-01)
- 参考文献数
- 32
- 被引用文献数
- 8 37
Objective We identified the prognostic relevance of pneumothorax in interstitial lung disease (ILD) patients and evaluated the efficacy and safety of autologous blood-patch pleurodesis. Methods We retrospectively reviewed 59 occurrences of pneumothorax in 34 ILD patients identified over a 12-year period. Results Air leakage ceased in 16 of 22 (72.7%) episodes after blood pleurodesis and in 11 of 14 (78.6%) episodes after chemical pleurodesis. Both the cure ratio and recurrence ratio in the cure episodes were comparable with those in the chemical pleurodesis group (p=0.99 and 0.99, respectively). In addition, there were no harmful events associated with blood pleurodesis. The median survival time after the first episode of pneumothorax was less than 9 months in patients with idiopathic interstitial pneumonia (IIP) and only around 3 years in the patients with other types of ILD, which have essentially favorable outcomes. Kaplan-Meier survival estimates were significantly worse in the patients with concomitant pneumomediastinum than in those without (p<0.05). A multivariate Cox regression analysis identified that the number of episodes of pneumothorax, IIP diagnosis and concomitant pneumomediastinum were independent predictors of death. Conclusion Autologous blood-patch pleurodesis is safe and worth considering as a first-line treatment for pneumothorax secondary to ILD. However, despite treatments, the prognosis after the onset of pneumothorax in ILD patients was found to be poor. In addition, concomitant pneumomediastinum may further worsen the prognosis.