Active or latent tuberculosis increases susceptibility to COVID-19 and disease severity

  1. Yu Chen
  2. Yaguo Wang
  3. Joy Fleming
  4. Yanhong Yu
  5. Ye Gu
  6. Chang Liu
  7. Lichao Fan
  8. Xiaodan Wang
  9. Moxin Cheng
  10. Lijun Bi
  11. Yongyu Liu

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Abstract

Importance

Risk factors associated with COVID-19, the viral pneumonia originating in Wuhan, China, in Dec 2019, require clarification so that medical resources can be prioritized for those at highest risk of severe COVID-19 complications. Infection with M. tuberculosis (MTB), the pathogen that causes TB and latently infects ∼25% of the global population, may be a risk factor for SARS-CoV-2 infection and severe COVID-19 pneumonia.

Objective

To determine if latent or active TB increase susceptibility to SARS-COV-19 infection and disease severity, and lead to more rapid development of COVID-19 pneumonia.

Design

An observational case-control study of 36 confirmed COVID-19 cases from Shenyang, China, conducted in Feb 2020. Final date of follow-up: Feb 29, 2020. Cases were grouped according to COVID-19 pneumonia severity (mild/moderate, severe/critical), and MTB infection status compared. Comparisons were made with MTB infection data from another case-control study on bacterial/viral pneumonia at Shenyang Chest Hospital.

Setting

Multi-center study involving three primary care hospitals in Shenyang, China.

Participants

86 suspected COVID-19 cases from participating primary-care hospitals in Shenyang. All 36 SARS-CoV-2 +ve cases (based on RT-PCR assay) were included. Disease severity was assessed using the Diagnostic and Treatment Guidelines of the National Health Commission of China (v6). Mean age, 47 years (range: 25-79), gender ratio, 1:1.

Exposures

Confirmed COVID-19 pneumonia. Interferon-gamma Release Assays (IGRA) were performed using peripheral blood to determine MTB infection.

Main Outcome and Measures

Epidemiological, demographic, clinical, radiological, and laboratory data were collected. Comparison of MTB infection status between patients with mild/moderate and severe/critical COVID-19 pneumonia.

Results

Mean age of 36 COVID-19 patients: 47 (range: 25-79); M/F: 18/18; Wuhan/Hubei connection: 42%. Mild/moderate cases: 27 (75%); severe/critical: 9 (25%). MTB infection (IGRA+ve): 13 cases (36.11%), including 7 of 9 severe/critical cases. MTB infection rate: higher in COVID-19 (36.11%) than bacterial pneumonia (20%; p=0.0047) and viral pneumonia patients (16.13%; p=0.024). MTB infection more common than other co-morbidities (36.11% vs diabetes: 25%; hypertension: 22.2%; coronary heart disease: 8.33%; COPD: 5.56%). MTB co-infection linked with disease severity (severe/critical 78% vs mild/moderate cases 22%; p=0.0049), and rate of disease progression: infection to development of symptoms (MTB+SARS-CoV-2: 6.5±4.2 days vs SARS-COV-2: 8.9±5.2 days; p=0.073); from symptom development to diagnosed as severe (MTB+SARS-CoV-2: 3.4±2.0 days vs SARS-COV-2: 7.5±0.5 days; p=0.075).

Conclusions and Relevance

MTB infection likely increases susceptibility to SARS-CoV-2, and increases COVID-19 severity, but this requires validation in a larger study. MTB infection status of COVID-19 patients should be checked routinely at hospital admission.

Key Points

Question

Is latent or active tuberculosis (TB) a risk factor for SARS-CoV-19 infection and progression to severe COVID-19 pneumonia?

Findings

In this observational case-control study of 36 COVID-19 cases from Shenyang, China, we found tuberculosis history (both of active TB and latent TB) to be an important risk factor for SARS-CoV-2 infection. Patients with active or latent TB were more susceptible to SARS-CoV-2, and COVID-19 symptom development and progression were more rapid and severe.

Meaning

Tuberculosis status should be assessed carefully at patient admission and management and therapeutic strategies adjusted accordingly to prevent rapid development of severe COVID-19 complications.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.10.20033795: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: These studies were approved by the Ethics Committee of Shenyang Chest Hospital, and informed written consent was obtained from each of the study participants.
    Consent: These studies were approved by the Ethics Committee of Shenyang Chest Hospital, and informed written consent was obtained from each of the study participants.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    IFN-γ IGRA assays: IFN-γ IGRA assays were performed using X.DOT-TB kits (TB Healthcare, Foshan, China) according to the manufacturer’s instructions8.
    TB Healthcare
    suggested: (Clinical Data Interchange Standards Consortium, RRID:SCR_000219)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.03.10.20033795 on medRxiv