Evaluation of sarcopenia and sarcopenic obesity in patients affected by oral squamous cell carcinoma: A retrospective single-center study

Bonavolontà, Paola; Improta, Giovanni; Orabona, Giovanni Dell’Aversana; Goglia, Federica; Abbate, Vincenzo; Sorrentino, Alfonso; Piloni, Sara; Salzano, Giovanni; Iaconetta, Giorgio; Califano, Luigi

doi:10.1016/j.jcms.2023.01.014

Cited by 5 publications

(1 citation statement)

References 48 publications

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“…Researchers and practitioners are focused on developing models and methodologies for estimating LOS [5,6], and models have been proposed to decrease LOS for other surgeries [7][8][9][10][11][12]. The implementations presented actually adopt all those data analysis strategies already successfully used in the health sector for the analysis of biomedical data [13][14][15] but also from a management point of view for the analysis of hospital resources [16][17][18] and pathways [19,20]. The main aim of the proposed work is to design and develop the most suitable ML model able to estimate the LOS for patients undergoing mastectomy in order to optimize the healthcare management process.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Hospital Length Stay for Patients Undergoing Mastectomy

Donofrío

D’Amore

Onofaro

et al. 2023

Studies in Health Technology and Informatics

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The prolonged length of stay is an important aspect to be considered for the healthcare management since this affect both the health-related expenditure of the hospital and the quality of the offered service. In the light of these consideration is important for hospitals to be able to predict the LOS of patients and to work on the principal aspect affecting it in order to reduce LOS as much as possible. In this work we focus on patients undergoing mastectomy. The data were collected form 989 patients who underwent mastectomy surgery in the Surgery Department of the AORN “A. Cardarelli” of Naples. Different models have been tested and characterized and the one with the best performance was identified.

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Section: Introductionmentioning

confidence: 99%

Prediction of Hospital Length Stay for Patients Undergoing Mastectomy

Donofrío

D’Amore

Onofaro

et al. 2023

Studies in Health Technology and Informatics

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Sarcopenic obesity in patients with head and neck cancer is predictive of critical weight loss during radiotherapy

Vangelov,

Smee,

Bauer

2024

Br J Nutr

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The impact of computed tomography-defined sarcopenia on outcomes in head and neck cancer has been well described. Sarcopenic obesity (SO) (depleted muscle mass combined with obesity) may pose a more serious risk than either condition alone. We investigated SO and its impact on survival and critical weight loss (≥ 5 %) in patients with head and neck cancer who received curative radiotherapy (± other modalities). Retrospective analysis of computed tomography cross-sectional muscle at cervical (C3), thoracic (T2) and lumbar (L3) regions was conducted. Patients were grouped by BMI and sarcopenia status based on established thresholds. A total of 413 patients were included for analysis, the majority having oropharyngeal carcinoma (52 %), and 56 % received primary concurrent chemoradiotherapy. The majority of the cohort (65 %) was overweight or obese (BMI ≥ 25 kg/m2). Sarcopenia was found in 43 %, with 65 % having SO (n 116), equating to 28 % of the whole cohort. Critical weight loss was experienced by 58 % (n 238). A significantly higher proportion of patients with SO experienced critical weight loss (n 70 v. 19, P < 0·001) and were four times more likely to do so during treatment (OR 4·1; 95 % CI 1·5, 7·1; P = 0·002). SO was not found to impact on overall or cancer-specific survival; however, in patients with sarcopenia, those with SO had better overall survival (median 9·1 v. 7·0 years; 95 % CI 5·2, 16·8; P = 0·021). SO at the time of presentation in patients with head and neck cancer is predictive of critical weight loss during treatment, and muscle evaluation can be useful in identifying patients at nutritional risk regardless of BMI and obvious signs of wasting.

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