Survival Factors and Metabolic Pathogenesis in Elderly Patients (≥65) with COVID-19 : A multi-center study of 223 Cases
bioinformatics clinical diagnostics
Authors: Mei et al.
Link to paper: https://www.researchsquare.com/article/rs-23199/v1
Journal/ Pre-Print: Research Square.
Key Words: Clinical, bioinformatics, metabolism, diagnostics, Aging
1. The potential survival factors of COVID-19 were the decreased levels of D- Dimer, the decreased immune-related metabolic index and a decrease of neutrophil-to-lymphocyte ratio in the elderly.
2. Elderly COVID-19 patients receiving interferon atmotherapy showed an increased probability of survival.
3. A 12 metabolic pathways including phenylalanine, fatty acid and pyruvate showed a consistently lower flux in the surviving versus the deceased group.
Mortality in the elderly population remains high. However, the factors supporting survival in elderly COVID-19 patients remains under investigation. In this multi-centre study, potential survival factors were analysed in an elderly cohort of 223 patients suffering from COVID–19 (age ≥65 years old). Although high mortality has been reported for these patients (59.2%), several potential survival factors were identified in this study, such as decreased D-Dimer, decreased immune-related metabolic index, decreased neutrophil-to-lymphocyte ratio and reduced metabolic activity. Further, the authors describe a positive correlation with interferon atmotherapy in terms of survival whereas immunoglobulin, corticosteroids and antibiotic treatment were associated with decreased probability of survival. The study suggest that abnormal metabolic activity associated with a weakened immune function during COVID–19 infection, contributed to the higher risk of mortality.
Impact for SARS-CoV2/COVID19 research efforts
Clinical symptoms and pathogenesis of SARS-Cov2/COVID19
The paper identifies several clinical factors which might be relevant to improving survival among elderly patients with COVID–19. Based on the clinical data available, they developed an algorithm AlgSurv, which could be helpful to apply upon hospital admission for clinical risk stratification.
Treat of SARS-CoV2/COVID19 positive individuals
In their study, interferon atmotherapy treatment showed a positive correlation with survival, whereas other drug treatments including antibiotics, corticosteroids and immunoglobin showed a negatively influenced on the survival in this cohort.
· Clinical Cohort study (Retrospective study).
Strengths and limitations of the paper
Novelty: Given the high mortality rate of elderly patients, the novelty of this study is the development of an algorithm (AlgSurv) for the prediction of survival in the in elderly Patients with COVID–19. The novelty may be questionable, as there was another group who built a prognostic prediction model able to predict the mortality risk. This model is based on three different clinicals features, lactic dehydrogenase (LDH), lymphocyte and High-sensitivity C-reactive protein (hs-CRP). (https://www.medrxiv.org/content/10.1101/2020.02.27.20028027v2.full.pdf)
Standing in the field: There are some studies supporting the data about the alterations of the metabolic activity and the immune function during COVID–19 infection. On the other hand, the paper has few contradictory data with the field. Interestingly, they claim that the age and not the comorbidities is the main risk of mortality during COVID-19.
Appropriate statistics: Appropriate statistics (particular multivariant testing)
Viral model used: Elderly patients with positive SARS-CoV2.
Translatability: The data shown here have the potential to be translated into a clinical trial. Using the AlgSurv to predict the clinical risk and the survival of the COVID-19 may help the clinician to change their therapeutic strategy, thus potentially reducing mortality.
Main limitations: The study was overall well conducted and we appreciated that the author cited the limitation of their study.
The main concern is that the study includes only elderly patients. Adding young patients would have provided conclusive evidence for the data especially for the validation of the AlgSurv and the alerted metabolic pathway related to COVID-19.
- Authors don’t go it detail about center differences in disease outcome and patient recruitment among the different hospitals recruited to the study
- According to their statistical test age was clearly altered between survivors and deceased and a major confounding factor
- The study does not delineate between cause and consequence (e.g. LDH and urea are signs of kidney damage and second to infection), it also remains unclear when the presented data has been raised
- Metabolic flux is lower but association with viral burden was not measured and could not be correlated.