Prognostic value of clinical and microbiological parameters in COVID-19: the COMEPA study

From Top Italian Scientists Journal
Published
January 12, 2024
Title
Prognostic value of clinical and microbiological parameters in COVID-19: the COMEPA study
Authors
Nicola Veronese, Marianna Noale, Anna La Carrubba, Luca Carruba, Stefano Ciriminna, Francesco Pollicino, Dario Saguto, Simona De Grazia, Federica Cacioppo, Giovanni M. Giammanco, Claudio Costantino, Francesco Vitale, Marco Affronti, Maria Chiara Morgante, Giusi Randazzo, Ligia J. Dominguez, Stefania Maggi, Mario Barbagallo and the COMEPA study authors
DOI
10.62684/XHIY3899
Keywords
COVID-19; clusters; long COVID; prognosis
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Nicola Veronese(a), Marianna Noale(b), Anna La Carrubba(a), Luca Carruba(a), Stefano Ciriminna(a), Francesco Pollicino(a), Dario Saguto(a), Simona De Grazia(a), Federica Cacioppo(a), Giovanni M. Giammanco(a), Claudio Costantino(a), Francesco Vitale(a), Marco Affronti(c), Maria Chiara Morgante(c), Giusi Randazzo(c), Ligia J. Dominguez(a,d), Stefania Maggi(b), Mario Barbagallo(a), and the COMEPA study authors

(a) Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties "G. D'Alessandro", University of Palermo, 90127 Palermo, Italy.

(b) Consiglio Nazionale delle Ricerche, Neuroscience Institute, Padova, 35100, Italy.

(c) Geriatric Unit, Azienda Ospedaliera Universitaria Policlinico Paolo Giaccone, Palermo, Italy.

(d) School of Medicine and Surgery, University of Enna "Kore", 94100, Enna, Italy;

Correspondence to: Nicola Veronese. Geriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, Via del Vespro, 141, 90127 Palermo, Italy. Email: nicola.veronese@unipa.it

Abstract

Purpose

Clusters’ analysis may indicate distinct phenotypes and symptom profiles potentially due to differing pathophysiology and needing different clinical approaches in COVID-19. However, the research about clusters combining clinical and microbiological information is still limited. The purpose of our study was to examine the prognostic role of clusters, including clinical and microbiological parameters in terms of severity of lung involvement, in-hospital mortality, and the occurrence of long COVID.

Methods

Information regarding COVID-19, mortality, severity of lung involvement derived from medical records; long COVID symptomatology was ascertained using phone calls. A k-means clustering method was considered to partition data into clusters considering typical symptoms of COVID-19 present at hospital admission and SarsCov2 variants.

Results

Our analysis identified among 414 patients (mean age: 65 years; males: 59.9%) four different clusters. Cluster 1: higher prevalence of respiratory COVID symptoms at hospital admission; Cluster 2: higher frequency of non-respiratory COVID symptoms and a higher prevalence of the Alpha variant; Cluster 3: older subjects and more frequently men, reporting more severe medical conditions and with a higher prevalence of Wild type variant; Cluster 4: patients that more often reported general and gastrointestinal COVID symptoms at the admission. From a prognostic point of view, patients in cluster 3 more frequently died and were admitted in a nursing home, with significantly lower presence of long COVID symptomatology.

Conclusions

Clusters combining clinical and microbiological information in individuals hospitalized with COVID-19 that had different not only different profiles, but also different prognostic values, also in terms of long COVID.

Declarations

Acknowledgements

The COMEPA group includes (alphabetical order): Affronti Marco, Amodeo Simona, Barbagallo Mario, Briganò Vincenza Maria, Cacioppo Federica, Capitano Walter M., Carruba Luca, Cavaleri Francesco, Catanese Giuseppina, Citarrella Roberto, Di Bella Giovanna, Di Franco Giuseppina, Di Prazza Agnese, Dominguez Ligia Juliana, Giannitrapani Lydia, Grasso Giulia, Immordino Federico, Licata Anna, La Carruba Anna, Mansueto Pasquale, Mirarchi Luigi, Morgante Maria Chiara, Parinello Alessandra, Pecoraro Emanuela, Peralta Marco, Polizzotto Carla, Pollicino Francesco, Quartetti Federico, Randazzo Giusi, Rizzo Angelo, Rizzo Giuseppina, Sanfilippo Valeria, Soresi Maurizio, Malerba Valentina, Vernuccio Laura, Veronese Nicola, Zerbo Maddalena.

Conflict of interest

The Authors declare that there is no conflict of interest.

Funding

None.

Data Availability

The datasets analysed during the current study are available from the corresponding author on reasonable request.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. The study was approved by the Local Ethical Committee during the session of the 28th of April 2021 (protocol number 04/2021).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

References

  1. Park, M.; Cook, A.R.; Lim, J.T.; Sun, Y.; Dickens, B.L. A systematic review of COVID-19 epidemiology based on current evidence. J. Clin. Med. 2020, 9, 967.
  2. Vasireddy, D.; Vanaparthy, R.; Mohan, G.; Malayala, S.V.; Atluri, P. Review of COVID-19 variants and COVID-19 vaccine efficacy: what the clinician should know? Journal of Clinical Medicine Research 2021, 13, 317.
  3. Parums, D.V. Revised World Health Organization (WHO) terminology for variants of concern and variants of interest of SARS-CoV-2. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research 2021, 27, e933622-933621.
  4. Organization, W.H. A clinical case definition of post COVID-19 condition by a Delphi consensus, 6 October 2021; World Health Organization: 2021.
  5. Di Gennaro, F.; Belati, A.; Tulone, O.; Diella, L.; Fiore Bavaro, D.; Bonica, R.; Genna, V.; Smith, L.; Trott, M.; Bruyere, O., et al. Incidence of long COVID-19 in people with previous SARS-Cov2 infection: a systematic review and meta-analysis of 120,970 patients. Intern. Emerg. Med. 2022, 10.1007/s11739-022-03164-w, doi:10.1007/s11739-022-03164-w.
  6. Baraniuk, C. Covid-19: How Europe is approaching long covid. bmj 2022, 376.
  7. Araf, Y.; Akter, F.; Tang, Y.d.; Fatemi, R.; Parvez, M.S.A.; Zheng, C.; Hossain, M.G. Omicron variant of SARS‐CoV‐2: genomics, transmissibility, and responses to current COVID‐19 vaccines. Journal of medical virology 2022, 94, 1825-1832.
  8. Samani, A.; Mathiassen, S.E.; Madeleine, P. Cluster-based exposure variation analysis. BMC Med Res Methodol 2013, 13, 54, doi:10.1186/1471-2288-13-54.
  9. Canas, L.D.S.; Molteni, E.; Deng, J.; Sudre, C.; Murray, B.; Kerfoot, E.; Antonelli, M.; Rjoob, K.; Pujol, J.C.; Polidori, L. Profiling post-COVID syndrome across different variants of SARS-CoV-2: a prospective longitudinal study on the unvaccinated wild-type, unvaccinated alpha, and vaccinated delta-variant populations. The Lancet Digital Health 2023.
  10. Barbagallo, M.; Citarrella, R.; Dominguez, L.; Giannitrapani, L.; Licata, A.; Mansueto, P.; Soresi, M.; Veronese, N. COMEPA (COVID-19 Medicina Policlinico Palermo): a study in hospitalized patients. Geriatric Care 2021, 7, 9895.
  11. Likas, A.; Vlassis, N.; Verbeek, J.J. The global k-means clustering algorithm. Pattern recognition 2003, 36, 451-461.
  12. Milligan, G.W.; Cooper, M.C. An examination of procedures for determining the number of clusters in a data set. Psychometrika 1985, 50, 159-179.
  13. Chen, C.; Haupert, S.R.; Zimmermann, L.; Shi, X.; Fritsche, L.G.; Mukherjee, B. Global Prevalence of Post COVID-19 Condition or Long COVID: A Meta-Analysis and Systematic Review. The Journal of Infectious Diseases 2022.
  14. Stavem, K.; Ghanima, W.; Olsen, M.K.; Gilboe, H.M.; Einvik, G. Prevalence and determinants of fatigue after COVID-19 in non-hospitalized subjects: a population-based study. International Journal of Environmental Research and Public Health 2021, 18, 2030.
  15. Natarajan, A.; Shetty, A.; Delanerolle, G.; Zeng, Y.; Zhang, Y.; Raymont, V.; Rathod, S.; Halabi, S.; Elliot, K.; Phiri, P. A systematic review and meta-analysis of Long COVID symptoms. medRxiv : the preprint server for health sciences 2022.
  16. Han, Q.; Zheng, B.; Daines, L.; Sheikh, A. Long-Term sequelae of COVID-19: A systematic review and meta-analysis of one-year follow-up studies on post-COVID symptoms. Pathogens 2022, 11, 269.
  17. Blevins, C.A.; Weathers, F.W.; Davis, M.T.; Witte, T.K.; Domino, J.L. The posttraumatic stress disorder checklist for DSM‐5 (PCL‐5): Development and initial psychometric evaluation. Journal of traumatic stress 2015, 28, 489-498.
  18. Bjelland, I.; Dahl, A.A.; Haug, T.T.; Neckelmann, D. The validity of the Hospital Anxiety and Depression Scale: an updated literature review. Journal of psychosomatic research 2002, 52, 69-77.
  19. Shebl, E.; Mirabile, V.S.; Sankari, A.; Burns, B. Respiratory failure. In StatPearls [Internet], StatPearls publishing: 2022.
  20. Fan, E.; Brodie, D.; Slutsky, A.S. Acute respiratory distress syndrome: advances in diagnosis and treatment. Jama 2018, 319, 698-710.
  21. Linn, B.S.; Linn, M.W.; Gurel, L. Cumulative illness rating scale. Journal of the American Geriatrics Society 1968, 16, 622-626, doi:10.1111/j.1532-5415.1968.tb02103.x.
  22. Evans, R.A.; McAuley, H.; Harrison, E.M.; Shikotra, A.; Singapuri, A.; Sereno, M.; Elneima, O.; Docherty, A.B.; Lone, N.I.; Leavy, O.C. Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study. The Lancet Respiratory Medicine 2021, 9, 1275-1287.
  23. Davis, H.E.; Assaf, G.S.; McCorkell, L.; Wei, H.; Low, R.J.; Re'em, Y.; Redfield, S.; Austin, J.P.; Akrami, A. Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. EClinicalMedicine 2021, 38, 101019.
  24. West, E.; Moore, K.; Kupeli, N.; Sampson, E.L.; Nair, P.; Aker, N.; Davies, N. Rapid review of decision-making for place of care and death in older people: lessons for COVID-19. Age and Ageing 2021, 50, 294-306.
  25. Sadegi, K.; Soofi, D.; Mirshekarpour, H.; Pormasoumi, H. Investigating the Return Possibility of Covid-19 Mutated Strains and Role of Vaccination in Present and Future. Journal of Pharmaceutical Negative Results 2022, 2043-2047.
  26. Pedersen, M.L.; Handberg, C.; Dreyer, P. Mental health reported in adult invasive home mechanical ventilation through a tracheostomy: A scoping review. International Journal of Nursing Studies Advances 2022, 100110.
  27. Arulkumaran, N.; Brealey, D.; Howell, D.; Singer, M. Use of non-invasive ventilation for patients with COVID-19: a cause for concern? The Lancet Respiratory Medicine 2020, 8, e45.
  28. Talic, S.; Shah, S.; Wild, H.; Gasevic, D.; Maharaj, A.; Ademi, Z.; Li, X.; Xu, W.; Mesa-Eguiagaray, I.; Rostron, J. Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis. bmj 2021, 375.
  29. Venkatesan, P. Do vaccines protect from long COVID? The Lancet Respiratory Medicine 2022, 10, e30.