Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

CT scan-derived pectoralis muscle parameters are closely associated with COVID-19 outcomes: A systematic review and meta-analysis

  • Zhang Wen,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China

    ⨯
  • Tao Wang,

    Roles Data curation, Formal analysis, Software, Writing – original draft

    Affiliation Department of Pediatric Intensive Care Unit, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    ⨯
  • Sha Luo,

    Roles Investigation, Methodology, Resources, Software

    Affiliation Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China

    ⨯
  • Yiwen Liu

    Roles Data curation, Formal analysis, Supervision, Writing – review & editing

    18781906752@163.com

    Affiliation Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China

    ⨯

Abstract

Background

The relationships between pectoralis muscle parameters and outcomes in patients with coronavirus disease 2019 (COVID-19) remain uncertain.

Methods

We systematically searched PubMed, Embase, Web of Science and the Cochrane Library from 1 January 2019 to 1 May 2024 to identify non-overlapping studies evaluating pectoralis muscle-associated index on chest CT scan with clinical outcome in COVID-19 patients. Random-effects and fixed-effects meta-analyses were performed, and heterogeneity between studies was quantified using the I2 statistic. The risk of study bias was assessed using the Newcastle-Ottawa scale. Funnel plots for detecting small-study effects.

Results

A total of 9 studies with 4109 COVID-19 patients were included. The meta-analysis findings revealed a correlation between pectoralis muscle parameters and COVID-19 prognosis. Specifically, patients with higher pectoralis muscle density (PMD) exhibited a lower mortality risk, with an odds ratio (OR) of 0.95 (95% CI: 0.92–0.99). The rate of intubation was lower in COVID-19 patients with a high pectoralis muscle index (PMI) (OR =  0.96, 95% CI: 0.92–1.00).

Conclusion

In summary, a low PMD is associated with a marginally elevated risk of mortality, whereas a decreased PMI represents a risk factor for intubation in COVID-19 patients. These findings suggest that pectoralis muscle parameters on chest CT may be a useful prognostic tool for COVID-19 patients.

Citation: Wen Z, Wang T, Luo S, Liu Y (2025) CT scan-derived pectoralis muscle parameters are closely associated with COVID-19 outcomes: A systematic review and meta-analysis. PLoS ONE 20(1): e0316893. https://doi.org/10.1371/journal.pone.0316893

Editor: Claudia Brogna, Fondazione Policlinico Universitario Gemelli IRCCS, ITALY

Received: September 22, 2024; Accepted: December 17, 2024; Published: January 28, 2025

Copyright: © 2025 Wen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The ongoing community-wide spread of COVID-19 and its ensuing pandemic ushered in a myriad of unprecedented clinical dilemmas. COVID-19 symptoms range from mild respiratory infections to severe manifestations such as pneumonia, ARDS, hypoxia, multiorgan failure, and fatality. Various COVID-19 vaccines have demonstrated efficacy in preventing SARS-CoV-2 infections and mitigating COVID-19 severity [1–3]. Although various COVID-19 vaccines have played pivotal roles in reducing the COVID-19 pandemic to an endemic state [4], the emergence of SARS-CoV-2 variants has complicated the situation, potentially significantly diminishing the efficacy of existing vaccines [5]. In addition to vaccines, various therapeutic options, including monoclonal antibodies and antiviral agents, have emerged, yet the strategy for risk stratification among symptomatic individuals to prioritize these treatments remains a matter of ongoing discourse [6,7].

Studies have demonstrated that comorbidities, particularly diabetes, hypertension, and chronic obstructive pulmonary disease, substantially influence the postoperative prognosis of patients with COVID-19, with these patients having a poorer prognosis than those without comorbidities [8,9]. A reduction in muscle mass is closely associated with the progression of multiple diseases [10,11]. Septic patients with muscle mass depletion and dysfunction frequently experience adverse outcomes during their intensive care unit (ICU) stay [12,13]. Recent research has revealed the incidence of acute sarcopenia among COVID-19 survivors [14], yet the long-term ramifications of both COVID-19 and acute sarcopenia remain unknown. In addition, critically ill SARS-CoV-2-infected patients necessitating mechanical ventilation exhibit reduced muscle mass, strength, and mobility during intensive care unit (ICU) confinement [15].

Previous studies have demonstrated that parameters for assessing chest skeletal muscle mass can be derived from the analysis of patients’ chest CT scans [16]. The chest skeletal muscle area can be calculated from CT images at the level of the twelfth thoracic vertebra. Studies have reported no significant correlation between the chest skeletal muscle area and mortality in patients with COVID-19 [17]. The relationships between indicators derived from chest CT-assessed pectoral muscle parameters and prognosis in COVID-19 patients remain unclear and warrant further exploration and investigation. This review aims to assess the correlation between pectoral muscle parameters derived from chest CT and the prognosis of patients with COVID-19.

Materials and methods

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements [18].

Data sources and search

We searched PubMed, Embase, Web of Science and the Cochrane Library for eligible studies with no language restrictions. The following search terms were used: “covid-19” or “sars-cov-2” or “severe acute respiratory syndrome coronavirus 2” or “NCOV” or “2019 NCOV” and “pectoralis” or “muscle, pectoralis” or “pectoralis muscle” or “pectoral muscle” or “pectoral muscles” or “pectoralis major” or “pectoralis minor”. The search was updated on 1 May 2024.

Selection criteria

The focus of this meta-analysis was on the prognostic value of CT-derived pectoralis muscle parameters in COVID-19 patients. Studies were considered eligible for inclusion if they were observational cohort studies (prospective, retrospective cohort or case‒cohort); reported hazard ratios or odds ratios with 95% confidence intervals; and enrolled patients who tested positive for COVID-19 via PCR and underwent either chest or thoracic CT scans without the use of intravenous contrast medium.

Studies were excluded if relevant data on COVID-19 disease outcomes were not available. Publications without original data, such as reviews, editorials and commentaries, were also excluded. Abstracts and conference proceedings were excluded because of incomplete data.

Data extraction

Two authors independently extracted data for each of the eligible studies. The extracted data included the first author, year of publication, country, setting, study design, country, sample size, personal and clinical characteristics of the participants, and other outcome variables of interest. Where relevant, attempts were made to contact the authors for missing data.

In accordance with the methods of previous studies [19], a line is drawn along the contours of both the pectoralis major and pectoralis minor muscles on chest CT images, delineating the bilateral areas to define the PMA. The PMD was assessed bilaterally on all contrast-enhanced scans, with the mean value then calculated. The PMI was calculated by dividing the PMA by the patient’s height. The skeletal muscle gauge (SMG) is determined by multiplying the PMI by the average muscle density.

Quality assessment

For the included studies, the Newcastle‒Ottawa Scale (NOS) was used to assess the quality of the studies included in the meta-analysis. This scale evaluates bias risk across three domains: study group selection, group comparability, and exposure/outcome ascertainment. Studies scoring below 4 indicate high risk of bias, those scoring 4–6 suggest intermediate risk, and those scoring 7 or above imply low risk of bias. An article was considered to be of high quality if its quality score was greater than or equal to 6 out of a total score of 9. Funnel plots were used to assess publication bias.

Statistical analysis

Statistical analyses were conducted via RevMan 5.3 software (Copenhagen: Nordic Cochrane Centre, Cochrane Collaboration, 2011). For every study, ORs and 95% CIs were used to assess the relationships between pectoralis muscle parameters and the prognosis of patients with COVID-19. We pooled ORs for pectoral parameters employing fixed-effects models, transitioning to random-effects models in instances where heterogeneity was observed. Between-study heterogeneity was evaluated via the Q statistic, and inconsistency was quantified via the I2 statistic (0–25% indicates no significant heterogeneity, 26–50% indicates low heterogeneity, 51–75% indicates moderate heterogeneity, and >75% indicates high heterogeneity).

Results

Study selection

Fifty-two records were identified after removing duplicates in our initial systematic search. After title and abstract screening, the full texts of 10 articles were reviewed. One study was excluded because of incomplete data. Finally, 9 retrospective studies that included 3997 COVID-19 patients were included in the systematic review [19–27]. The flow diagram is shown in Fig 1.

thumbnail
Download:
Fig 1. Flow diagram of literature searching and study selection.

https://doi.org/10.1371/journal.pone.0316893.g001

Study characteristics

Among the included studies, 3 were identified from Turkey across three time periods: Period 1 (March 2020April 2020) [25], period 2 (December 2020March 2021) [26], and Period 3 (October 2021 to November 2021) [24]. All COVID-19 cases were confirmed by reverse-transcription polymerase chain reaction testing or highly suspected clinically with a COVID-19 Reporting and Data System (CO-RADS) score ≥4, ruling out other diagnoses [28].

For all patients with an initial admission diagnosis of COVID-19, a chest CT scan was administered within the first 1 to 2 days of their hospital stay as part of the diagnostic workup. In eight studies [19–21,23–27], a chest CT scan was performed within 1–2 days of hospital admission for all patients with an initial diagnosis of COVID-19. In a multicenter study by Nakagawara et al., the associations between changes in muscle parameters and decreased CT density at 3 months and patient prognosis were analyzed in 167 patients [22]. The baseline characteristics of the patients in the included studies are presented in Table 1.

thumbnail
Download:
Table 1. The descriptive characteristics of the study population.

https://doi.org/10.1371/journal.pone.0316893.t001

Primary outcome: mortality

Pectoralis muscle area.

The PMA was defined as the total bilateral area encompassing the pectoralis major and minor muscles, as described previously [29]. Five studies [19,23,25–27] that reported on the association between the PMA and mortality risk of COVID-19 patients were included in the synthesis, totaling 2104 individuals.

The meta-analysis results revealed no relationship between PMA and mortality (OR 0.99, 95% CI 0.95–1.02), with high heterogeneity (I2  =  64%; P  =  0.02) (Fig 2A). Furthermore, Tekin ZN et al [24]. found that a PMA ≤  2800 was an independent risk factor for death in COVID-19 patients.

thumbnail
Download:
Fig 2. Relationship between mortality and pectoralis muscle parameters in patients with COVID-19.

(A) pectoralis muscle area; (B) pectoralis muscle index; (C) pectoralis muscle density; (D) pectoralis muscle gauge.

https://doi.org/10.1371/journal.pone.0316893.g002

Pectoralis muscle index.

PMI is calculated by dividing the cross-sectional area of the pectoral muscle by the square of the individual’s height. This metric provides a standardized way to assess the relative size and development of the chest muscles, taking into account the individual’s overall height [30].

A meta-analysis of 3 studies [19,23,25] revealed that the PMI had no significant effect on the mortality risk of COVID-19 patients (OR 0.89, 95% CI 0.67–1.17), with high heterogeneity (I2  =  75%; P  =  0.02) (Fig 2B).

Liu Y et al [21]. evaluated the relationship between high and low PMIs and COVID-19 mortality risk and reported that a low PMI was an independent risk factor for death in COVID-19 patients. As the provided OR value could not be combined with the data from the other included studies, it is described separately here.

Pectoral muscle density.

Teigen LM et al. reported that the quantity of the pectoralis muscle is associated with mortality after implantation of a left ventricular assist device [31]. Therefore, four studies reporting the relationship between pectoral muscle density (PMD) and mortality were included in this subgroup analysis.

The meta-analysis results indicated that PMD was associated with mortality (OR 0.95, 95% CI 0.92–0.99), with high heterogeneity (I2  =  71%; P  =  0.01). A summary of the findings is shown in Fig 2C. Nakagawara K et al [22]. found that regardless of sex, a lower CT density of the pectoralis muscle was associated with a greater risk of death.

Skeletal muscle gauge.

Furthermore, the PMI was multiplied by the average muscle density, as described in the two included studies [19,23], to derive the SMG. The pooled outcome results revealed that decreasing SMG was independent of mortality (OR 1.00, 95% CI 0.99–1.00), with high heterogeneity (I2  =  91%; P  =  0.00007) (Fig 2D).

Secondary outcome: Intubation

PMA.

A meta-analysis of 3 studies [23,25,26] investigated the association between the PMA and the need for intubation in COVID-19 patients. The present study revealed no correlation between PMA and intubation (OR 0.96, 95% CI 0.92–1.00), with high heterogeneity observed (I2  =  85%; P  =  0.03) (Fig 3A).

thumbnail
Download:
Fig 3. Relationship between intubation rate and pectoralis muscle parameters in patients with COVID-19.

(A) pectoralis muscle area; (B) pectoralis muscle index; (C) pectoralis muscle density.

https://doi.org/10.1371/journal.pone.0316893.g003

PMI.

Two articles [23,25] investigated the relationship between the PMI and the need for mechanical ventilation in COVID-19 patients. The meta-analysis results indicated that the PMI was associated with the need for intubation (OR 0.87, 95% CI 0.80–0.95), with low heterogeneity (I2 =  0%; P =  0.002) (Fig 3B).

PMD.

Combined data from the two studies [23,26] indicated that the PMD was independent of the need for intubation in COVID-19 patients (OR 0.90, 95% CI 0.79–1.03), with high heterogeneity (I2 =  91%; P =  0.00007) (Fig 3C).

Publication bias.

The publication bias in this meta-analysis was assessed via funnel plots, and a summary of the funnel plots is presented in Fig 4. Visual inspection of the funnel plots revealed no substantive evidence of publication bias.

thumbnail
Download:
Fig 4. Funnel plots: pectoralis muscle parameters (A pectoralis muscle area, B pectoralis muscle index, C pectoralis muscle density, D pectoralis muscle gauge) on mortality, and (E pectoralis muscle area, F pectoralis muscle index, G pectoralis muscle density) on intubation.

https://doi.org/10.1371/journal.pone.0316893.g004

Discussion

COVID-19, a deadly disease that led to the death of almost 1.1 million people in 2022 [32], can cause rapid respiratory failure, with no specific drug currently available for its treatment [33]. The aim of this study was to assess the associations between pectoralis muscle parameters and the prognosis of COVID-19 patients. Our research findings confirm that lower levels of PMA, PMI, and PMD are associated with an increased risk of patient mortality. Furthermore, the pooled results indicate that lower PMIs and PMDs are correlated with higher intubation rates.

ARDS induced by COVID-19 results in the need for ventilatory support and multisystem damage in critically ill patients, characterized by heightened inflammation, hypermetabolism, and hypercatabolism, primarily affecting the musculoskeletal system [34]. Research by Silva et al. revealed a significant reduction in quadriceps muscle thickness among critically ill patients with COVID-19 during their intensive care unit (ICU) stay [15]. Muscle atrophy in critically ill patients is associated with prolonged hospital stays, extended duration of mechanical ventilation, deep sedation, more severe illness at admission, delirium, and extended periods of bed rest [35]. The degree of decline in muscle mass and function can be used to assess the presence of sarcopenia. Sarcopenia has emerged as a predictive factor for both hospital duration and mortality among critically ill and trauma patients, as evidenced in studies [36,37]. However, the relationship between sarcopenia and the prognosis of patients with COVID-19 remains controversial. Kim et al. quantified the skeletal muscle index at T12 and reported that sarcopenia in COVID-19 patients prolonged hospitalization but did not significantly impact mortality [16]. Feng et al.‘s study of 116 patients revealed no discernible correlation between the paraspinal muscle index at the T12 level and clinical outcomes [38].

Patients diagnosed with COVID-19 are categorized as having mild to severe disease [39]. Thorax CT is a rapid assessment method that can aid in the evaluation of critically ill COVID-19 patients and is utilized to assess the severity and prognosis of COVID-19 [40]. Branea et al. identified alterations in diaphragm thickness through chest CT scan results in critically ill patients diagnosed with COVID-19 [41]. In two recent studies, the pectoralis musculature measured at the T4 level emerged as a prognostic indicator in COVID-19 patients [19,23]. The studies included in this meta-analysis measured pectoralis muscle parameters at the T4 level instead of at the L3 level and examined different pectoralis muscle parameters on chest CT. Chest CT is an important examination for COVID-19 patients on admission, and the PMA, PMI, and PMD can be derived from chest CT parameters. The PMA has emerged as a robust predictor of sarcopenia [42]. Furthermore, research has indicated that decreased PMA and PMI are correlated with adverse prognoses in chronic obstructive pulmonary disease [43], lung cancer [44] and unexplained lung fibrosis [45]. PMD has been employed to investigate the impact of muscular atrophy on chronic obstructive pulmonary disease in mechanically ventilated critically ill patients [43,46]. The present study revealed that COVID-19 patients with a favorable prognosis exhibit high levels of PMD.

The clinical manifestations of COVID-19 range from asymptomatic to mild to severe. Myalgia and generalized weakness have been documented in 25% to 50% of symptomatic COVID-19 patients [47]. Among 214 hospitalized COVID-19 patients in Wuhan, China, 19% exhibited creatine kinase (CK) levels exceeding 200 U/L (a clinically established threshold for elevation), with a maximum value reaching 12,216 U/L [48]. Patients with abnormal imaging findings demonstrate more pronounced clinical manifestations and laboratory abnormalities [49]. There are also case reports regarding rhabdomyolysis associated with COVID-19 [50]. The mechanisms underlying the effects of COVID-19 on skeletal muscle are not fully understood, and several mechanisms have been proposed. COVID-19 is associated with substantial systemic inflammation, with a subset of patients exhibiting a severe cytokine response. Elevated serum levels of inflammatory cytokines, such as TNF-α, have been observed in critically ill COVID-19 patients [51]. TNF-α adversely impacts muscle protein synthesis by reducing mRNA translational efficiency via alterations in eIF-4E availability [52]. In addition, many hospitalized COVID-19 patients experience extended periods of bedrest and limited physical activity. Research indicates that bed rest is associated with decreases in muscle mass, strength, and aerobic exercise capacity [53]. These underlying mechanisms suggest that exploring the potential associations between body composition and COVID-19 outcomes is reasonable.

We acknowledge that this meta-analysis has several limitations. First, the current evidence is limited by the small number of included studies. Second, there was significant heterogeneity between the included studies, which could be due to the quality of the limited number of studies, but further subgroup analysis did not identify the source of heterogeneity. Third, the results are driven by one study with a large sample size.

Conclusion

In summary, a low PMD is associated with a marginally elevated risk of mortality, whereas a decreased PMI represents a risk factor for intubation in COVID-19 patients. These findings suggest that pectoralis muscle parameters on chest CT may be a useful prognostic tool for COVID-19 patients.

References

  1. 1. Voysey M, Clemens SAC, Madhi SA, Weckx LY, Folegatti PM, Aley PK, et al. Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK. Lancet. 2021;397(10269):99–111. pmid:33306989
  2. 2. Heath PT, Galiza EP, Baxter DN, Boffito M, Browne D, Burns F, et al. Safety and efficacy of the NVX-CoV2373 coronavirus disease 2019 vaccine at completion of the placebo-controlled phase of a randomized controlled trial. Clin Infect Dis. 2023;76(3):398–407. pmid:36210481
  3. 3. Wu X, Xu K, Zhan P, Liu H, Zhang F, Song Y, et al. Comparative efficacy and safety of COVID-19 vaccines in phase III trials: a network meta-analysis. BMC Infect Dis. 2024;24(1):234. pmid:38383356
  4. 4. Yazdanpanah N, Sedikides C, Ochs H, et al. Global challenges after a global challenge: lessons learned from the COVID-19 pandemic. Adv Exp Med Biol. 2024;1457:1–31.
  5. 5. Zhou Z, Zhu Y, Chu M. Role of COVID-19 vaccines in SARS-CoV-2 variants. Front Immunol. 2022;13:898192. pmid:35669787
  6. 6. Quitián LM, Rodríguez-Martinez CE, Sossa-Briceño MP, et al. Disease burden and vaccination priorities in Colombia. Vaccine. 2022;40(12):1717–21.
  7. 7. Wen W, Chen C, Tang J, et al. Efficacy and safety of three new oral antiviral treatment (molnupiravir, fluvoxamine and Paxlovid) for COVID-19: a meta-analysis. Ann Med. 2022;54(1):516–23.
  8. 8. Pepera G, Tribali M-S, Batalik L, Petrov I, Papathanasiou J. Epidemiology, risk factors and prognosis of cardiovascular disease in the coronavirus disease 2019 (COVID-19) pandemic era: a systematic review. Rev Cardiovasc Med. 2022;23(1):28. pmid:35092220
  9. 9. Alqahtani JS, Oyelade T, Aldhahir AM, Alghamdi SM, Almehmadi M, Alqahtani AS, et al. Prevalence, severity and mortality associated with COPD and smoking in patients with COVID-19: a rapid systematic review and meta-analysis. PLoS One. 2020;15(5):e0233147. pmid:32392262
  10. 10. Ferreira AP, Machado MV. Impact of pretransplant frailty and sarcopenia on the post-transplant prognosis of patients with liver cirrhosis: a systematic review. Eur J Gastroenterol Hepatol. 2021;33(1S Suppl 1):e883–97. pmid:35048655
  11. 11. Huq S, Khalafallah AM, Ruiz-Cardozo MA, Botros D, Oliveira LAP, Dux H, et al. A novel radiographic marker of sarcopenia with prognostic value in glioblastoma. Clin Neurol Neurosurg. 2021;207:106782. pmid:34186275
  12. 12. Lee Z, Ong S, Ng C, et al. Association between ultrasound quadriceps muscle status with premorbid functional status and 60-day mortality in mechanically ventilated critically ill patient: a single-center prospective observational study. Clin Nutr. 2021;40(3):1338–47.
  13. 13. Cavayas YA, Eljaiek R, Rodrigue É, Lamarche Y, Girard M, Wang HT, et al. Preoperative diaphragm function is associated with postoperative pulmonary complications after cardiac surgery. Crit Care Med. 2019;47(12):e966–74. pmid:31609771
  14. 14. Welch C, Greig C, Masud T, et al. COVID-19 and acute sarcopenia. Aging Dis. 2020;11(6):1345–51.
  15. 15. Silva-Gutiérrez A, Artigas-Arias M, Alegría-Molina A, Guerra-Vega P, Navarrete P, Venegas Á, et al. Characterization of muscle mass, strength and mobility of critically ill patients with SARS-CoV-2 pneumonia: distribution by sex, age, days on mechanical ventilation, and muscle weakness. Front Physiol. 2023;14:1095228. pmid:36846316
  16. 16. Kim JW, Yoon JS, Kim EJ, et al. Prognostic implication of baseline Sarcopenia for length of hospital stay and survival in patients with coronavirus disease 2019. J Gerontol A Biol Sci Med Sci. 2021, 76(8):e110–6.
  17. 17. Moctezuma-Velázquez P, Miranda-Zazueta G, Ortiz-Brizuela E, González-Lara MF, Tamez-Torres KM, Román-Montes CM, et al. Low thoracic skeletal muscle area is not associated with negative outcomes in patients with COVID-19. Am J Phys Med Rehabil. 2021;100(5):413–8. pmid:33587451
  18. 18. Moher D, Liberati A, Tetzlaff J, et al. Reprint--preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Phys Ther. 2009;89(9):873–80.
  19. 19. Kardas H, Thormann M, Bär C, Omari J, Wienke A, Pech M, et al. Impact of pectoral muscle values on clinical outcomes in patients with severe Covid-19 disease. In Vivo. 2022;36(1):375–80. pmid:34972737
  20. 20. Besutti G, Pellegrini M, Ottone M, Cantini M, Milic J, Bonelli E, et al. The impact of chest CT body composition parameters on clinical outcomes in COVID-19 patients. PLoS One. 2021;16(5):e0251768. pmid:33989341
  21. 21. Liu Y, Qi Z, Bai M, Kang J, Xu J, Yi H, et al. Combination of chest computed tomography value and clinical laboratory data for the prognostic risk evaluation of patients with COVID-19. Int J Gen Med. 2023;16:3829–42. pmid:37662505
  22. 22. Nakagawara K, Shiraishi Y, Chubachi S, Tanabe N, Maetani T, Asakura T, et al. Integrated assessment of computed tomography density in pectoralis and erector spinae muscles as a prognostic biomarker for coronavirus disease 2019. Clin Nutr. 2024;43(3):815–24. pmid:38350289
  23. 23. Surov A, Kardas H, Besutti G, Pellegrini M, Ottone M, Onur MR, et al. Prognostic role of the pectoralis musculature in patients with COVID-19. A multicenter study. Acad Radiol. 2023;30(1):77–82. pmid:35667979
  24. 24. Tekin ZN, Dogruoz Karatekin B, Dogan MB, Bilgi Z, et al. Pectoralis muscle area measured at T4 level is closely associated with adverse COVID-19 outcomes in hospitalized patients. J Musculoskelet Neuronal Interact. 2023;23(2):196–204. pmid:37259659
  25. 25. Ufuk F, Demirci M, Sagtas E, et al. The prognostic value of pneumonia severity score and pectoralis muscle area on chest CT in adult COVID-19 patients. Eur J Radiol. 2020;131:109271.
  26. 26. Ufuk F, Utebey AR, Yavas HG, Baser Oncel S, Akbudak IH, Sari T, et al. Which body composition parameters on computed tomography are more successful in predicting the prognosis of COVID-19 patients? J Comput Assist Tomogr. 2023;47(1):58–66. pmid:36219743
  27. 27. van Bakel SIJ, Gietema HA, Stassen PM, et al. CT scan-derived muscle, but not fat, area independently predicts mortality in COVID-19. Chest. 2023;164(2):314–22.
  28. 28. Prokop M, van Everdingen W, van Rees Vellinga T, Quarles van Ufford H, Stöger L, Beenen L, et al. CO-RADS: a categorical CT assessment scheme for patients suspected of having COVID-19-definition and evaluation. Radiology. 2020;296(2):E97–104. pmid:32339082
  29. 29. Diaz A, Martinez C, Harmouche R, et al. Pectoralis muscle area and mortality in smokers without airflow obstruction. Respi Res. 2018;19(1):62.
  30. 30. Shin HS, Choi DS, Na JB, Choi HY, Kim J-E, Choi HC, et al. Low pectoralis muscle index, cavitary nodule or mass and segmental to lobar consolidation as predictors of primary multidrug-resistant tuberculosis: a comparison with primary drug sensitive tuberculosis. PLoS One. 2020;15(10):e0239431. pmid:33017424
  31. 31. Teigen LM, John R, Kuchnia AJ, Nagel EM, Earthman CP, Kealhofer J, et al. Preoperative pectoralis muscle quantity and attenuation by computed tomography are novel and powerful predictors of mortality after left ventricular assist device implantation. Circ Heart Fail. 2017;10(9):e004069. pmid:28912261
  32. 32. Looi MK, Mahase E. Has covid-19 become milder? BMJ. 2022;379:o2516.
  33. 33. Yang S, Cao P, Du P, Wu Z, Zhuang Z, Yang L, et al. Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis. Ann Transl Med. 2020;8(4):128. pmid:32175421
  34. 34. Li H, Liu L, Zhang D, Xu J, Dai H, Tang N, et al. SARS-CoV-2 and viral sepsis: observations and hypotheses. Lancet. 2020;395(10235):1517–20. pmid:32311318
  35. 35. Schefold JC, Wollersheim T, Grunow JJ, Luedi MM, Z’Graggen WJ, Weber-Carstens S, et al. Muscular weakness and muscle wasting in the critically ill. J Cachexia Sarcopenia Muscle. 2020;11(6):1399–412. pmid:32893974
  36. 36. DeAndrade J, Pedersen M, Garcia L, et al. Sarcopenia is a risk factor for complications and an independent predictor of hospital length of stay in trauma patients. J Surg Res. 2018;221:161–6.
  37. 37. Ji Y, Cheng B, Xu Z, Ye H, Lu W, Luo X, et al. Impact of sarcopenic obesity on 30-day mortality in critically ill patients with intra-abdominal sepsis. J Crit Care. 2018;46:50–4. pmid:29677586
  38. 38. Feng Z, Zhao H, Kang W, Liu Q, Wu J, Bragazzi NL, et al. Association of paraspinal muscle measurements on chest computed tomography with clinical outcomes in patients with severe coronavirus disease 2019. J Gerontol A Biol Sci Med Sci. 2021;76(3):e78–84. pmid:33355656
  39. 39. Li X, Ma X. Acute respiratory failure in COVID-19: is it “typical” ARDS? Crit Care. 2020;24(1):198. pmid:32375845
  40. 40. Rana A, Singh H, Mavuduru R, Pattanaik S, Rana PS, et al. Quantifying prognosis severity of COVID-19 patients from deep learning based analysis of CT chest images. Multimed Tools Appl. 2022;81(13):18129–53. pmid:35282403
  41. 41. Branea OE, Copotoiu SM, Becica DA, et al. Assessment of the diaphragm thickness decrease in critically ill COVID-19 patients: could computed tomography be of aid regarding diaphragm muscle mass? Cureus. 2023;15(10):e47195.
  42. 42. Kim YS, Kim EY, Kang SM, Ahn HK, Kim HS, et al. Single cross-sectional area of pectoralis muscle by computed tomography - correlation with bioelectrical impedance based skeletal muscle mass in healthy subjects. Clin Physiol Funct Imaging. 2017;37(5):507–11. pmid:26668097
  43. 43. Bak SH, Kwon SO, Han S-S, Kim WJ. Computed tomography-derived area and density of pectoralis muscle associated disease severity and longitudinal changes in chronic obstructive pulmonary disease: a case control study. Respir Res. 2019;20(1):226. pmid:31638996
  44. 44. Cury SS, de Moraes D, Freire PP, et al. Tumor transcriptome reveals high expression of IL-8 in non-small cell lung cancer patients with low pectoralis muscle area and reduced survival. Cancers (Basel). 2019;11(9).
  45. 45. Moon SW, Choi JS, Lee SH, Jung KS, Jung JY, Kang YA, et al. Thoracic skeletal muscle quantification: low muscle mass is related with worse prognosis in idiopathic pulmonary fibrosis patients. Respir Res. 2019;20(1):35. pmid:30767787
  46. 46. Looijaard WGPM, Dekker IM, Stapel SN, Girbes ARJ, Twisk JWR, Oudemans-van Straaten HM, et al. Skeletal muscle quality as assessed by CT-derived skeletal muscle density is associated with 6-month mortality in mechanically ventilated critically ill patients. Crit Care. 2016;20(1):386. pmid:27903267
  47. 47. Nasiri MJ, Haddadi S, Tahvildari A, et al. COVID-19 clinical characteristics, and sex-specific risk of mortality: systematic review and meta-analysis. Front Med. 2020;7:459.
  48. 48. Mao L, Jin H, Wang M, Hu Y, Chen S, He Q, et al. Neurologic manifestations of hospitalized patients With coronavirus disease 2019 in Wuhan, China. JAMA Neurol. 2020;77(6):683–90. pmid:32275288
  49. 49. Zhang X, Cai H, Hu J, Lian J, Gu J, Zhang S, et al. Epidemiological, clinical characteristics of cases of SARS-CoV-2 infection with abnormal imaging findings. Int J Infect Dis. 2020;94:81–7. pmid:32205284
  50. 50. Khosla SG, Nylen ES, Khosla R. Rhabdomyolysis in patients hospitalized with COVID-19 infection: five case series. J Investig Med High Impact Case Rep. 2020;8:2324709620984603. pmid:33371733
  51. 51. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. pmid:31986264
  52. 52. Lang CH, Frost RA, Nairn AC, MacLean DA, Vary TC. TNF-alpha impairs heart and skeletal muscle protein synthesis by altering translation initiation. Am J Physiol Endocrinol Metab. 2002;282(2):E336-47. pmid:11788365
  53. 53. Kortebein P, Ferrando A, Lombeida J, Wolfe R, Evans WJ. Effect of 10 days of bed rest on skeletal muscle in healthy older adults. JAMA. 2007;297(16):1772–4. pmid:17456818