Dear Editor,
We read with interest the article by Innocenti et al. regarding the role of prognostic scores in predicting worse outcome in patients with COVID-19 acute respiratory failure (ARF) treated with non-invasive ventilation (NIV) [1].
The paper is extremely actual as COVID-19 management has peculiarities such as high volume of patients, limited resources, and need for rapid decision-making, that make use and validation of scores particularly appealing.
Prognostic and diagnostic scores are increasingly diffuse in the clinical practice; therefore, it is crucial to provide the clinician with insights that can guide the choice of the most appropriate score.
In this line, we consider that some aspects need to be clarified for a proper clinical extrapolation.
First, the ideal prognostic mode should be build and validated on a contemporary community-based population, including limited number of relevant, independent, and easy to retrieve variables (parsimony) [2].
The authors gathered together three contemporary scores (ROX index, HACOR, and the nomogram elaborated by Liu et al. [3]) validated on a population similar to that of the study, while Charlson score is an old prognostic model validated on a very different population (women with carcinoma of the breast) [4].
This issue might rise some concerns about generalizability of risk estimation on the population with COVID-19.
Second, another crucial point is the definition of the outcome that the specific score aims to predict [5]. We consider that, although NIV failure and mortality are conceptually linked, they have a completely different practical meaning for the physician. In other words, NIV failure prediction is a point risk estimation performed before initiating the therapy, while mortality risk prediction has less immediate operative implication and can be adjusted during ongoing observation.
To this regard, the authors have introduced a novel methodological approach contemplating the prospective longitudinal acquisition of score values. The depiction of sequential calculation of different scores allowed an interesting observation: at baseline, none of the scores is able to separate neither survivor from non-survivors nor NIV responder from not responders. On the other hand, the curve of score values diverges during the observation.
Furthermore, a striking similarity exists between the trend of scores among NIV non-responder and non-survivors, reflecting the poor prognosis of patients with COVID-19 needing endotracheal intubation.
From these data, we might conclude that scores devised to predict NIV success perform well if applied prospectically, while point estimation of risk led to a substantial overlap between patients.
Finally, we might speculate that the unsatisfactory NIV success prediction might be explained by the variability of the biological and genetic background not catched by the variables included in conventional respiratory scores.
Further evidences need to confirm the predictive capabilities of these scores.
Abbreviations
- ARF
Acute respiratory failure
- NIV
Non-invasive ventilation
- COVID-19
Coronavirus disease 2019
Declarations
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
Ethical approval
Not required.
Human and animal rights statement
This study complies with the Declaration of Helsinki.
Informed consent
Not required.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Innocenti F, Lazzari C, Paolucci E, De Paris A, Lagomarsini A, Guerra F, Alleonato P, Casalini L, Buggea M, Caldi F, Zanobetti M, Pieralli F, Guazzini G, Lastraioli L, Luise F, Milia A, Sammicheli L, Maddaluni L, Lavorini F, Pini R. Role of prognostic scores in predicting in-hospital mortality and failure of non-invasive ventilation in adults with COVID-19. Intern Emerg Med. 2022;2:1–11. doi: 10.1007/s11739-022-03058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ferrero P, Iacovoni A, D'Elia E, Vaduganathan M, Gavazzi A, Senni M. Prognostic scores in heart failure - Critical appraisal and practical use. Int J Cardiol. 2015;188:1–9. doi: 10.1016/j.ijcard.2015.03.154. [DOI] [PubMed] [Google Scholar]
- 3.Liu L, Xie J, Wu W, Chen H, Li S, He H, Yu Y, Hu M, Li J, Zheng R, Li X, Qiu H, Tong Z, Du B, Fan E, Yang Y, Slutsky AS. A simple nomogram for predicting failure of non-invasive respiratory strategies in adults with COVID-19: a retrospective multicentre study. Lancet Digit Health. 2021;3(3):e166–e174. doi: 10.1016/S2589-7500(20)30316-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8. [DOI] [PubMed] [Google Scholar]
- 5.Altman D, Royston P. What do we mean by validating a prognostic model? Stat Med. 2000;19:453–473. doi: 10.1002/(sici)1097-0258(20000229)19:4<453::aid-sim350>3.0.co;2-5. [DOI] [PubMed] [Google Scholar]