Chest X-ray Score and Frailty as Predictors of In-Hospital Mortality in Older Adults with COVID-19

Round 1

Reviewer 1 Report

Thank you for sending your work for consideration in JCM. This piece is highly pertinent at the moment and should be in the minds of the readership.
There are a few points that ought to be considered to improve what is fundamentally a good article. If you can address these, the work will be highly useful.
The ideas are given below:

• expand the bibliography a little by introducing the following articles:

-Borakati, A.; Perera, A.; Johnson, J.; Sood, T. Diagnostic accuracy of X-ray versus CT in COVID-19: A propensity-matched database study. BMJ Open 2020, 10, e042946. [CrossRef]

-Brogna B, Bignardi E, Brogna C, Volpe M, Lombardi G, Rosa A, Gagliardi G, Capasso PFM, Gravino E, Maio F, Pane F, Picariello V, Buono M, Colucci L, Musto LA. A Pictorial Review of the Role of Imaging in the Detection, Management, Histopathological Correlations, and Complications of COVID-19 Pneumonia. Diagnostics (Basel). 2021 Mar 4;11(3):437. doi: 10.3390/diagnostics11030437. PMID: 33806423; PMCID: PMC8000129.

-Maroldi, R.; Rondi, P.; Agazzi, G.M.; Ravanelli, M.; Borghesi, A.; Farina, D. Which role for chest x-ray score in predicting the outcome in COVID-19 pneumonia? Eur. Radiol. 2020, 2, 1–7. [CrossRef]

-Cozzi, A.; Schiaffino, S.; Arpaia, F.; Della Pepa, G.; Tritella, S.; Bertolotti, P.; Menicagli, L.; Monaco, C.G.; Carbonaro, L.A.; Spairani, R.; et al. Chest x-ray in the COVID-19 pandemic: Radiologists’ real-world reader performance. Eur. J. Radiol. 2020, 132, 109272. [CrossRef]

-Brogna, B.; Bignardi, E.; Brogna, C.; Alberigo, M.; Grappone, M.; Megliola, A.; Salvatore, P.; Fontanella, G.; Mazza, E.; Musto, L. Typical CT findings of COVID-19 pneumonia in patients presenting with repetitive negative RT-PCR. Radiography 2020. [CrossRef]

-Warren, M.A.; Zhao, Z.; Koyama, T.; Bastarache, J.A.; Shaver, C.M.; Semler, M.W.; Rice, T.W.; Matthay, M.A.; Calfee, C.S.; Ware, L.B. Severity scoring of lung oedema on the chest radiograph is associated with clinical outcomes in ARDS. Thorax 2018, 73, 840–846. [CrossRef]

-Schiaffino, S.; Tritella, S.; Cozzi, A.; Carriero, S.; Blandi, L.; Ferraris, L.; Sardanelli, F. Diagnostic Performance of Chest X-Ray for COVID-19 Pneumonia During the SARS-CoV-2 Pandemic in Lombardy, Italy. J. Thorac. Imaging 2020, 35, W105–W106. [CrossRef] [PubMed

      2) briefly clarify why the RALE Score was used and not other CXRs Scores

       3) stress the limits of the Chest X-ray , even briefly and the reasons that led the authors to use Chest x-ray and not Chest CT

      4) Introduce some x-ray images, illustrating how the CXR Score is calculated

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Thank you for the opportunity to review the manuscript titled “Chest X-ray Score and Frailty as predictors of in-hospital mortality in older adults with COVID-19”. This cross-sectional study aimed to evaluate the association between potential predictive factors and COVID-19-related in-hospital mortality. The manuscript is generally well written and clearly presented. I only offer a few minor suggestions to further improve readability of the manuscript (see below).

1. Line 27 & Line 29: Please ensure that abbreviations (i.e. RT-PCR and CFS) are defined on first use in the abstract.
2. Line 83 & Line 93 & Line 96 & Line 102 & Line 120 & Line 250: To improve readability, I suggest removing abbreviations (i.e. RT-PCR, CO, GGO, RO, RALE, AUROC, AI) that are used infrequently, especially given that this manuscript features a relatively large number of abbreviations
3. Line 115 & Line 121: The letter ‘C’ is missing in the abbreviation ‘CRX’.
4. Lines 117-118: It is not made clear why five separate multivariable models were built. I think it will suffice to simply present the final fitted model following the forward selection process (presumably the current Model 1). If there is a particular interest in evaluating the change in predictive accuracy from adding a particular variable to the final fitted model, then that needs a clear justification.
5. Line 128: For Table 1, please ensure the column heading for non-survivors is consistent with the terminology used in the manuscript text. That is the terms ‘dead’, ‘deceased’, and ‘non-survivor’ are used interchangeably at different time. To improve readability, select one term and use it consistently throughout the manuscript.
6. Line 128: Why present hazard ratios (HS) adjusted for age and gender in Table 1? I suggest presenting univariable unadjusted HRs and leave the adjustments for the subsequent multivariable model fitting. In any event, it does not make sense to present a HR ratio for gender that is adjusted for gender, nor a HR for age that is adjusted for age.
7. Line 128: The p-value for CXR score cannot be 0.000, please use inequality symbols for very low p-vales instead (e.g. p < 0.001).
8. Lines 139-151: Please ensure that all proportions are reported consistently in terms of number of decimal places and with or without space before the percentage symbol.

Author Response

Please see the attachment

Author Response File: Author Response.docx