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Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19

BACKGROUND: During the fifth wave of the coronavirus disease 2019 (COVID-19) pandemic in Japan, which took place between June and September 2021, a significant number of COVID-19 cases with deterioration occurred in unvaccinated individuals < 65 years old. However, the risk factors for COVID-19 d...

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Autores principales: Shibata, Yoko, Omae, Kenji, Minemura, Hiroyuki, Suzuki, Yasuhito, Nikaido, Takefumi, Tanino, Yoshinori, Fukuhara, Atsuro, Kanno, Ryuzo, Saito, Hiroyuki, Suzuki, Shuzo, Ishii, Taeko, Inokoshi, Yayoi, Sando, Eiichiro, Sakuma, Hirofumi, Kobayashi, Tatsuho, Kume, Hiroaki, Kamimoto, Masahiro, Aoki, Hideko, Takama, Akira, Kamiyama, Takamichi, Nakayama, Masaru, Saito, Kiyoshi, Tanigawa, Koichi, Sato, Masahiko, Kambe, Toshiyuki, Kanzaki, Norio, Azuma, Teruhisa, Sakamoto, Keiji, Nakamura, Yuichi, Ohtani, Hiroshi, Waragai, Mitsuru, Maeda, Shinsaku, Ishida, Tokiya, Sugino, Keishi, Inage, Minoru, Hirama, Noriyuki, Furuyama, Kodai, Fukushima, Shigeyuki, Saito, Hiroshi, Machiya, Jun-ichi, Machida, Hiroyoshi, Abe, Koya, Iwabuchi, Katsuyoshi, Katagiri, Yuji, Aida, Yasuko, Abe, Yuki, Ota, Takahito, Ishizawa, Yuki, Tsukada, Yasuhiko, Yamada, Ryuki, Sato, Riko, Onuma, Takumi, Tomita, Hikaru, Saito, Mikako, Watanabe, Natsumi, Rikimaru, Mami, Kawamata, Takaya, Umeda, Takashi, Morimoto, Julia, Togawa, Ryuichi, Sato, Yuki, Saito, Junpei, Kanazawa, Kenya, Kurita, Noriaki, Iseki, Ken
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463653/
https://www.ncbi.nlm.nih.gov/pubmed/37641057
http://dx.doi.org/10.1186/s12890-023-02604-3
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author Shibata, Yoko
Omae, Kenji
Minemura, Hiroyuki
Suzuki, Yasuhito
Nikaido, Takefumi
Tanino, Yoshinori
Fukuhara, Atsuro
Kanno, Ryuzo
Saito, Hiroyuki
Suzuki, Shuzo
Ishii, Taeko
Inokoshi, Yayoi
Sando, Eiichiro
Sakuma, Hirofumi
Kobayashi, Tatsuho
Kume, Hiroaki
Kamimoto, Masahiro
Aoki, Hideko
Takama, Akira
Kamiyama, Takamichi
Nakayama, Masaru
Saito, Kiyoshi
Tanigawa, Koichi
Sato, Masahiko
Kambe, Toshiyuki
Kanzaki, Norio
Azuma, Teruhisa
Sakamoto, Keiji
Nakamura, Yuichi
Ohtani, Hiroshi
Waragai, Mitsuru
Maeda, Shinsaku
Ishida, Tokiya
Sugino, Keishi
Inage, Minoru
Hirama, Noriyuki
Furuyama, Kodai
Fukushima, Shigeyuki
Saito, Hiroshi
Machiya, Jun-ichi
Machida, Hiroyoshi
Abe, Koya
Iwabuchi, Katsuyoshi
Katagiri, Yuji
Aida, Yasuko
Abe, Yuki
Ota, Takahito
Ishizawa, Yuki
Tsukada, Yasuhiko
Yamada, Ryuki
Sato, Riko
Onuma, Takumi
Tomita, Hikaru
Saito, Mikako
Watanabe, Natsumi
Rikimaru, Mami
Kawamata, Takaya
Umeda, Takashi
Morimoto, Julia
Togawa, Ryuichi
Sato, Yuki
Saito, Junpei
Kanazawa, Kenya
Kurita, Noriaki
Iseki, Ken
author_facet Shibata, Yoko
Omae, Kenji
Minemura, Hiroyuki
Suzuki, Yasuhito
Nikaido, Takefumi
Tanino, Yoshinori
Fukuhara, Atsuro
Kanno, Ryuzo
Saito, Hiroyuki
Suzuki, Shuzo
Ishii, Taeko
Inokoshi, Yayoi
Sando, Eiichiro
Sakuma, Hirofumi
Kobayashi, Tatsuho
Kume, Hiroaki
Kamimoto, Masahiro
Aoki, Hideko
Takama, Akira
Kamiyama, Takamichi
Nakayama, Masaru
Saito, Kiyoshi
Tanigawa, Koichi
Sato, Masahiko
Kambe, Toshiyuki
Kanzaki, Norio
Azuma, Teruhisa
Sakamoto, Keiji
Nakamura, Yuichi
Ohtani, Hiroshi
Waragai, Mitsuru
Maeda, Shinsaku
Ishida, Tokiya
Sugino, Keishi
Inage, Minoru
Hirama, Noriyuki
Furuyama, Kodai
Fukushima, Shigeyuki
Saito, Hiroshi
Machiya, Jun-ichi
Machida, Hiroyoshi
Abe, Koya
Iwabuchi, Katsuyoshi
Katagiri, Yuji
Aida, Yasuko
Abe, Yuki
Ota, Takahito
Ishizawa, Yuki
Tsukada, Yasuhiko
Yamada, Ryuki
Sato, Riko
Onuma, Takumi
Tomita, Hikaru
Saito, Mikako
Watanabe, Natsumi
Rikimaru, Mami
Kawamata, Takaya
Umeda, Takashi
Morimoto, Julia
Togawa, Ryuichi
Sato, Yuki
Saito, Junpei
Kanazawa, Kenya
Kurita, Noriaki
Iseki, Ken
author_sort Shibata, Yoko
collection PubMed
description BACKGROUND: During the fifth wave of the coronavirus disease 2019 (COVID-19) pandemic in Japan, which took place between June and September 2021, a significant number of COVID-19 cases with deterioration occurred in unvaccinated individuals < 65 years old. However, the risk factors for COVID-19 deterioration in this specific population have not yet been determined. This study developed a prediction method to identify COVID-19 patients < 65 years old who are at a high risk of deterioration. METHODS: This retrospective study analyzed data from 1,675 patients < 65 years old who were admitted to acute care institutions in Fukushima with mild-to-moderate-1 COVID-19 based on the Japanese disease severity criteria prior to the fifth wave. For validation, 324 similar patients were enrolled from 3 hospitals in Yamagata. Logistic regression analyses using cluster-robust variance estimation were used to determine predictors of disease deterioration, followed by creation of risk prediction scores. Disease deterioration was defined as the initiation of medication for COVID-19, oxygen inhalation, or mechanical ventilation starting one day or later after admission. RESULTS: The patients whose condition deteriorated (8.6%) tended to be older, male, have histories of smoking, and have high body temperatures, low oxygen saturation values, and comorbidities, such as diabetes/obesity and hypertension. Stepwise variable selection using logistic regression to predict COVID-19 deterioration retained comorbidities of diabetes/obesity (DO), age (A), body temperature (T), and oxygen saturation (S). Two predictive scores were created based on the optimism-corrected regression coefficients: the DOATS score, including all of the above risk factors, and the DOAT score, which was the DOATS score without oxygen saturation. In the original cohort, the areas under the receiver operating characteristic curve (AUROCs) of the DOATS and DOAT scores were 0.81 (95% confidence interval [CI] 0.77–0.85) and 0.80 (95% CI 0.76–0.84), respectively. In the validation cohort, the AUROCs for each score were both 0.76 (95% CI 0.69–0.83), and the calibration slopes were both 0.80. A decision curve analysis confirmed the clinical practicability of both scores in the validation cohort. CONCLUSIONS: We established two prediction scores that can quickly evaluate the risk of COVID-19 deterioration in mild/moderate patients < 65 years old. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02604-3. The calculator of the DOATS and DOAT scores are available at https://shibatay8.wixsite.com/doats-score--a-simpl/post/doats-score.
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spelling pubmed-104636532023-08-30 Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19 Shibata, Yoko Omae, Kenji Minemura, Hiroyuki Suzuki, Yasuhito Nikaido, Takefumi Tanino, Yoshinori Fukuhara, Atsuro Kanno, Ryuzo Saito, Hiroyuki Suzuki, Shuzo Ishii, Taeko Inokoshi, Yayoi Sando, Eiichiro Sakuma, Hirofumi Kobayashi, Tatsuho Kume, Hiroaki Kamimoto, Masahiro Aoki, Hideko Takama, Akira Kamiyama, Takamichi Nakayama, Masaru Saito, Kiyoshi Tanigawa, Koichi Sato, Masahiko Kambe, Toshiyuki Kanzaki, Norio Azuma, Teruhisa Sakamoto, Keiji Nakamura, Yuichi Ohtani, Hiroshi Waragai, Mitsuru Maeda, Shinsaku Ishida, Tokiya Sugino, Keishi Inage, Minoru Hirama, Noriyuki Furuyama, Kodai Fukushima, Shigeyuki Saito, Hiroshi Machiya, Jun-ichi Machida, Hiroyoshi Abe, Koya Iwabuchi, Katsuyoshi Katagiri, Yuji Aida, Yasuko Abe, Yuki Ota, Takahito Ishizawa, Yuki Tsukada, Yasuhiko Yamada, Ryuki Sato, Riko Onuma, Takumi Tomita, Hikaru Saito, Mikako Watanabe, Natsumi Rikimaru, Mami Kawamata, Takaya Umeda, Takashi Morimoto, Julia Togawa, Ryuichi Sato, Yuki Saito, Junpei Kanazawa, Kenya Kurita, Noriaki Iseki, Ken BMC Pulm Med Research BACKGROUND: During the fifth wave of the coronavirus disease 2019 (COVID-19) pandemic in Japan, which took place between June and September 2021, a significant number of COVID-19 cases with deterioration occurred in unvaccinated individuals < 65 years old. However, the risk factors for COVID-19 deterioration in this specific population have not yet been determined. This study developed a prediction method to identify COVID-19 patients < 65 years old who are at a high risk of deterioration. METHODS: This retrospective study analyzed data from 1,675 patients < 65 years old who were admitted to acute care institutions in Fukushima with mild-to-moderate-1 COVID-19 based on the Japanese disease severity criteria prior to the fifth wave. For validation, 324 similar patients were enrolled from 3 hospitals in Yamagata. Logistic regression analyses using cluster-robust variance estimation were used to determine predictors of disease deterioration, followed by creation of risk prediction scores. Disease deterioration was defined as the initiation of medication for COVID-19, oxygen inhalation, or mechanical ventilation starting one day or later after admission. RESULTS: The patients whose condition deteriorated (8.6%) tended to be older, male, have histories of smoking, and have high body temperatures, low oxygen saturation values, and comorbidities, such as diabetes/obesity and hypertension. Stepwise variable selection using logistic regression to predict COVID-19 deterioration retained comorbidities of diabetes/obesity (DO), age (A), body temperature (T), and oxygen saturation (S). Two predictive scores were created based on the optimism-corrected regression coefficients: the DOATS score, including all of the above risk factors, and the DOAT score, which was the DOATS score without oxygen saturation. In the original cohort, the areas under the receiver operating characteristic curve (AUROCs) of the DOATS and DOAT scores were 0.81 (95% confidence interval [CI] 0.77–0.85) and 0.80 (95% CI 0.76–0.84), respectively. In the validation cohort, the AUROCs for each score were both 0.76 (95% CI 0.69–0.83), and the calibration slopes were both 0.80. A decision curve analysis confirmed the clinical practicability of both scores in the validation cohort. CONCLUSIONS: We established two prediction scores that can quickly evaluate the risk of COVID-19 deterioration in mild/moderate patients < 65 years old. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02604-3. The calculator of the DOATS and DOAT scores are available at https://shibatay8.wixsite.com/doats-score--a-simpl/post/doats-score. BioMed Central 2023-08-28 /pmc/articles/PMC10463653/ /pubmed/37641057 http://dx.doi.org/10.1186/s12890-023-02604-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Shibata, Yoko
Omae, Kenji
Minemura, Hiroyuki
Suzuki, Yasuhito
Nikaido, Takefumi
Tanino, Yoshinori
Fukuhara, Atsuro
Kanno, Ryuzo
Saito, Hiroyuki
Suzuki, Shuzo
Ishii, Taeko
Inokoshi, Yayoi
Sando, Eiichiro
Sakuma, Hirofumi
Kobayashi, Tatsuho
Kume, Hiroaki
Kamimoto, Masahiro
Aoki, Hideko
Takama, Akira
Kamiyama, Takamichi
Nakayama, Masaru
Saito, Kiyoshi
Tanigawa, Koichi
Sato, Masahiko
Kambe, Toshiyuki
Kanzaki, Norio
Azuma, Teruhisa
Sakamoto, Keiji
Nakamura, Yuichi
Ohtani, Hiroshi
Waragai, Mitsuru
Maeda, Shinsaku
Ishida, Tokiya
Sugino, Keishi
Inage, Minoru
Hirama, Noriyuki
Furuyama, Kodai
Fukushima, Shigeyuki
Saito, Hiroshi
Machiya, Jun-ichi
Machida, Hiroyoshi
Abe, Koya
Iwabuchi, Katsuyoshi
Katagiri, Yuji
Aida, Yasuko
Abe, Yuki
Ota, Takahito
Ishizawa, Yuki
Tsukada, Yasuhiko
Yamada, Ryuki
Sato, Riko
Onuma, Takumi
Tomita, Hikaru
Saito, Mikako
Watanabe, Natsumi
Rikimaru, Mami
Kawamata, Takaya
Umeda, Takashi
Morimoto, Julia
Togawa, Ryuichi
Sato, Yuki
Saito, Junpei
Kanazawa, Kenya
Kurita, Noriaki
Iseki, Ken
Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19
title Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19
title_full Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19
title_fullStr Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19
title_full_unstemmed Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19
title_short Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19
title_sort development and external validation of the doat and doats scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate covid-19
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463653/
https://www.ncbi.nlm.nih.gov/pubmed/37641057
http://dx.doi.org/10.1186/s12890-023-02604-3
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