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Response to "Analysis of possible risk predictors in patients with coronavirus disease 2019: a retrospective cohort study"

Dear Editor,

I have read with great sincerity the article entitled "Analysis of possible risk predictors in patients with coronavirus disease 2019: a retrospective cohort study" by Beatriz Nienkotter et al11 Nienkotter B, Gambetta MV, Rocha FRD, Medeiros ED, Schweitzer I, Prado F, et al. Analysis of possible risk predictors in patients with coronavirus disease 2019: a retrospective cohort study. Rev Assoc Med Bras (1992). 2023;69(5):e20220917. https://doi.org/10.1590/1806-9282.20220917
https://doi.org/10.1590/1806-9282.202209...
. It was a pleasure for me to read the concisely written article, and I congratulate the authors for their excellent efforts. I agree with the ultimate findings of the study that age older than 65 years and a lung involvement extension greater than 50% are predictors of a poor prognosis for coronavirus disease 2019 (COVID-19), as well as the need for high-flow oxygen therapy.

Based on varied research22 Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. https://doi.org/10.1136/bmj.m1966
https://doi.org/10.1136/bmj.m1966...
,33 Chon Y, Kim JY, Suh YJ, Lee JY, Park JS, Moon SM, et al. Adverse initial CT findings associated with poor prognosis of coronavirus disease. J Korean Med Sci. 2020;35(34):e316. https://doi.org/10.3346/jkms.2020.35.e316
https://doi.org/10.3346/jkms.2020.35.e31...
, I agree that different clinical and computed tomography (CT) findings are associated with critical illness and a poor prognosis in patients with COVID-19. However, it seemed noteworthy to mention a few more points that would enhance the quality of this article and enrich its conclusion.

The retrospective sort of study has drawn numerous concerns due to the possibility of recall bias, which could be addressed if authors had included present cases of that time. The author could use a larger population to supplement the results. For instance, a 2020 prospective cohort study describes the characteristics of 5,279 patients with COVID-19 treated at a large quaternary academic health system22 Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. https://doi.org/10.1136/bmj.m1966
https://doi.org/10.1136/bmj.m1966...
. Also, conducting a study at a particular location could create bias due to different socio-economic, health, and environmental conditions. As in this study, patients were all from a single geographical region and treated within a single health system; factors associated with poor prognosis might differ elsewhere. In the 2022 cohort study, patients were included in a multicenter international registry that had data from 31 centers in 7 countries44 Espejo-Paeres C, Espliguero RA, Uribarri A, Antón-Huguet B, Romero R, Fernández-Rozas I, et al. Predictors of poor prognosis in healthy, young, individuals with SARS-CoV-2 infections. Clin Microbiol Infect. 2022;28(2):273-8. https://doi.org/10.1016/j.cmi.2021.09.021
https://doi.org/10.1016/j.cmi.2021.09.02...
.

As it is entrenched that patients with a positive diagnosis of COVID-19 were included, laboratory confirmation of the cases could also be addressed. Numerous studies22 Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. https://doi.org/10.1136/bmj.m1966
https://doi.org/10.1136/bmj.m1966...
,44 Espejo-Paeres C, Espliguero RA, Uribarri A, Antón-Huguet B, Romero R, Fernández-Rozas I, et al. Predictors of poor prognosis in healthy, young, individuals with SARS-CoV-2 infections. Clin Microbiol Infect. 2022;28(2):273-8. https://doi.org/10.1016/j.cmi.2021.09.021
https://doi.org/10.1016/j.cmi.2021.09.02...
confirmed cases of COVID-19 using genetic sequencing or real-time reverse transcriptase polymerase chain reaction (RT-PCR). Additionally, the author should have analyzed further laboratory test findings, including blood urea nitrogen, serum creatinine, low-density lipoprotein levels (LDL), and liver function tests. A 2021 study concluded that elevated levels of aspartate aminotransferase (AST), creatinine, blood urea nitrogen, and bilirubin were significantly associated with unfavorable outcomes, and these parameters can be used to predict disease prognosis55 Ghaith MM, Albanghali MA, Aldairi AF, Iqbal MS, Almaimani RA, Quthami K, et al. Potential predictors of poor prognosis among severe COVID-19 patients: a single-center study. Can J Infect Dis Med Microbiol. 2021;2021:6656092. https://doi.org/10.1155/2021/6656092
https://doi.org/10.1155/2021/6656092...
. The author should also have briefed about different chronic conditions such as dyslipidemia, heart disease, chronic kidney disease, cancer, cerebrovascular disease, Parkinson's disease, and dementia since these comorbidities can influence mortality66 Becerra-Muñoz VM, Núñez-Gil IJ, Eid CM, García Aguado M, Romero R, Huang J, et al. Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19. Age Ageing. 2021;50(2):326-34. https://doi.org/10.1093/ageing/afaa258
https://doi.org/10.1093/ageing/afaa258...
. Dyslipidemia plays an important role in the pathological development of COVID-19. LDL levels are inversely correlated with disease severity, which could be a predictor of disease progress and poor prognosis77 Fan J, Wang H, Ye G, Cao X, Xu X, Tan W, et al. Letter to the editor: low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019. Metabolism. 2020;107:154243. https://doi.org/10.1016/j.metabol.2020.154243
https://doi.org/10.1016/j.metabol.2020.1...
.

Although it was stated that pulmonary involvement at the first chest tomography was considered a risk factor for an unfavorable outcome, it can also be mentioned that pleural effusion and a higher CT score on the CT scan at the time of admission are imaging predictors of poor prognosis in COVID-19 patients33 Chon Y, Kim JY, Suh YJ, Lee JY, Park JS, Moon SM, et al. Adverse initial CT findings associated with poor prognosis of coronavirus disease. J Korean Med Sci. 2020;35(34):e316. https://doi.org/10.3346/jkms.2020.35.e316
https://doi.org/10.3346/jkms.2020.35.e31...
. Finally, these findings lead to the conclusion that different parameters can be used to predict disease prognosis. Monitoring disease progression from the early stages will help in reducing unfavorable outcomes and allow more targeted lines of treatment, leading to a reduction in the rate of mortality.

ETHICS

The study was conducted in accordance with the Declaration of Helsinki and followed ethical standards.

  • Funding: none.

REFERENCES

  • 1
    Nienkotter B, Gambetta MV, Rocha FRD, Medeiros ED, Schweitzer I, Prado F, et al. Analysis of possible risk predictors in patients with coronavirus disease 2019: a retrospective cohort study. Rev Assoc Med Bras (1992). 2023;69(5):e20220917. https://doi.org/10.1590/1806-9282.20220917
    » https://doi.org/10.1590/1806-9282.20220917
  • 2
    Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. https://doi.org/10.1136/bmj.m1966
    » https://doi.org/10.1136/bmj.m1966
  • 3
    Chon Y, Kim JY, Suh YJ, Lee JY, Park JS, Moon SM, et al. Adverse initial CT findings associated with poor prognosis of coronavirus disease. J Korean Med Sci. 2020;35(34):e316. https://doi.org/10.3346/jkms.2020.35.e316
    » https://doi.org/10.3346/jkms.2020.35.e316
  • 4
    Espejo-Paeres C, Espliguero RA, Uribarri A, Antón-Huguet B, Romero R, Fernández-Rozas I, et al. Predictors of poor prognosis in healthy, young, individuals with SARS-CoV-2 infections. Clin Microbiol Infect. 2022;28(2):273-8. https://doi.org/10.1016/j.cmi.2021.09.021
    » https://doi.org/10.1016/j.cmi.2021.09.021
  • 5
    Ghaith MM, Albanghali MA, Aldairi AF, Iqbal MS, Almaimani RA, Quthami K, et al. Potential predictors of poor prognosis among severe COVID-19 patients: a single-center study. Can J Infect Dis Med Microbiol. 2021;2021:6656092. https://doi.org/10.1155/2021/6656092
    » https://doi.org/10.1155/2021/6656092
  • 6
    Becerra-Muñoz VM, Núñez-Gil IJ, Eid CM, García Aguado M, Romero R, Huang J, et al. Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19. Age Ageing. 2021;50(2):326-34. https://doi.org/10.1093/ageing/afaa258
    » https://doi.org/10.1093/ageing/afaa258
  • 7
    Fan J, Wang H, Ye G, Cao X, Xu X, Tan W, et al. Letter to the editor: low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019. Metabolism. 2020;107:154243. https://doi.org/10.1016/j.metabol.2020.154243
    » https://doi.org/10.1016/j.metabol.2020.154243

Publication Dates

  • Publication in this collection
    22 Apr 2024
  • Date of issue
    2024

History

  • Received
    16 Oct 2023
  • Accepted
    29 Oct 2023
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