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

  1. Yoko Shibata
  2. Kenji Omae
  3. Hiroyuki Minemura
  4. Yasuhito Suzuki
  5. Takefumi Nikaido
  6. Yoshinori Tanino
  7. Atsuro Fukuhara
  8. Ryuzo Kanno
  9. Hiroyuki Saito
  10. Shuzo Suzuki
  11. Taeko Ishii
  12. Yayoi Inokoshi
  13. Eiichiro Sando
  14. Hirofumi Sakuma
  15. Tatsuho Kobayashi
  16. Hiroaki Kume
  17. Masahiro Kamimoto
  18. Hideko Aoki
  19. Akira Takama
  20. Takamichi Kamiyama
  21. Masaru Nakayama
  22. Kiyoshi Saito
  23. Koichi Tanigawa
  24. Masahiko Sato
  25. Toshiyuki Kambe
  26. Norio Kanzaki
  27. Teruhisa Azuma
  28. Keiji Sakamoto
  29. Yuichi Nakamura
  30. Hiroshi Ohtani
  31. Mitsuru Waragai
  32. Shinsaku Maeda
  33. Tokiya Ishida
  34. Keishi Sugino
  35. Minoru Inage
  36. Noriyuki Hirama
  37. Kodai Furuyama
  38. Shigeyuki Fukushima
  39. Hiroshi Saito
  40. Jun-ichi Machiya
  41. Hiroyoshi Machida
  42. Koya Abe
  43. Katsuyoshi Iwabuchi
  44. Yuji Katagiri
  45. Yasuko Aida
  46. Yuki Abe
  47. Takahito Ota
  48. Yuki Ishizawa
  49. Yasuhiko Tsukada
  50. Ryuki Yamada
  51. Riko Sato
  52. Takumi Onuma
  53. Hikaru Tomita
  54. Mikako Saito
  55. Natsumi Watanabe
  56. Mami Rikimaru
  57. Takaya Kawamata
  58. Takashi Umeda
  59. Julia Morimoto
  60. Ryuichi Togawa
  61. Yuki Sato
  62. Junpei Saito
  63. Kenya Kanazawa
  64. Noriaki Kurita
  65. Ken Iseki

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Abstract

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.

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  1. Version published to 10.1186/s12890-023-02604-3
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    SciScore for 10.1101/2021.12.13.21267698: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsConsent: Ethics statement: The need for informed consent was waived because the study is retrospective.
    IRB: This study was approved by the Ethical Committee of Fukushima Medical University (approval number 2020-118, approved on August 3, 2020, updated September 01, 2021).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There were limitations in the present study. Firstly, data regarding the exact proportion of vaccinated individuals were not available. COVID-19 vaccinations began to be administered in Japan in March 2021, and by the end of May 2021, no vaccinations had yet been administered to non-elderly people [27, 28]. Therefore, we believe that most of the population in this study had not been vaccinated. Secondly, the precise data regarding about the day of onset and deterioration or treatment before deterioration was not available for any patients. There may be some differences in treatment before deterioration between the Worsened and Stable groups. For example, treatment such as inhaled corticosteroid and favipiravir may have affected the clinical course of the patients[29-31]. In our database, information about the timing of the prescription of these medicines were not available. Thirdly, we do not know whether the risk factors identified in the present study will still be applicable to the risk stratification against COVID-19 caused by future-coming variants of SARS-CoV-2. The current vaccines are reportedly less effective against the SARS-CoV-2 Mu variant[32]. Therefore, even vaccinated individuals may still get infected[33]. The increased infectivity caused by viral mutations may prolong the COVID-19 pandemic. In situations where many individuals are vaccinated, it is possible that new risk factors for worsening COVID-19 will become apparent.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.12.13.21267698v1 on medRxiv