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Systematic review and meta-analysis of lean mass and mortality: Rationale and study description. Osteoporos Sarcopenia 2021; 7:S3-S12. [PMID: 33997303 PMCID: PMC8088993 DOI: 10.1016/j.afos.2021.01.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 11/26/2020] [Accepted: 01/26/2021] [Indexed: 01/03/2023] Open
Abstract
Objectives Muscle mass is one of the key components in defining sarcopenia and is known to be important for locomotion and body homeostasis. Lean mass is commonly used as a surrogate of muscle mass and has been shown to be associated with increased mortality. However, the relationship of lean mass with mortality may be affected by different clinical conditions, modalities used, cut-off point to define low or normal lean mass, and even types of cancer among cancer patients. Thus, we aim to perform a comprehensive meta-analysis of lean mass with mortality by considering all these factors. Methods Systematic search was done in PubMed, Cochrane Library and Embase for articles related to lean mass and mortality. Lean mass measured by dual X-ray absorptiometry, bioelectrical impedance analysis, and computerized tomography were included. Results The number of relevant studies has increased continuously since 2002. A total of 188 studies with 98 468 people were included in the meta-analysis. The association of lean mass with mortality was most studied in cancer patients, followed by people with renal diseases, liver diseases, elderly, people with cardiovascular disease, lung diseases, and other diseases. The meta-analysis can be further conducted in subgroups based on measurement modalities, site of measurements, definition of low lean mass adopted, and types of cancer for studies conducted in cancer patients. Conclusions This series of meta-analysis provided insight and evidence on the relationship between lean mass and mortality in all directions, which may be useful for further study and guideline development.
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Kammar-García A, Hernández-Hernández ME, López-Moreno P, Ortíz-Bueno AM, Martínez-Montaño MDL. Relation of body composition indexes to cardiovascular disease risk factors in young adults. Semergen 2018; 45:147-155. [PMID: 30327259 DOI: 10.1016/j.semerg.2018.07.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 06/08/2018] [Accepted: 07/06/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND To evaluate the relationship of body composition indexes with altered metabolic analytical parameters that show higher risk of cardiovascular disease in young adults. MATERIAL AND METHODS A cross-sectional study. Sample of 1351 young adults, different body composition parameters were obtained such as Waist Circumference (WC), Hip Circumference (HC), Body Mass Index (BMI), Body Fat% (BF%), Waist-to-height Ratio (WHtR), and Waist-Hip Ratio (WHR), conicity index (C-Index), body surface area (BSA), abdominal volume index (AVI) and deep abdominal adipose-tissue (AT). Areas under receiver operating characteristic curves (AUCs) and odds ratios for the parameters were analyzed and their optimal cut-offs. Separately a MANOVA was applied to altered metabolic analytical parameters and two body composition indexes (BMI and BSA) and their interaction. RESULTS BMI correlate significantly with metabolic analytical parameters (FPG r=0.08, TCh r=0.14, TGL r=0.23, HDL-C r=-0.23, LDL-C r=0.2, UA r=0.22, All P<0.01), BSA correlate with all (All P<0.001) except FPG. BMI and BSA correlate significantly with all metabolic analytical parameters (All P<0.001). The BMI individually predicts the changes of the six metabolic analytical parameters as a set [Wilk's λ=0.89, F(18,1570)=3.4, P<0.0001], but not BSA [Wilk's λ=0.98, F(6,555)=1.4, P=0.18], the interaction between these two indexes (BMI and BSA altered in the same individual) significantly predicts changes of the six metabolic analytical parameters of cardiovascular disease risk [Wilk's λ=0.97, F(6,555)=2.3, P=0.03]. CONCLUSIONS BMI and BSA correlate with cardiovascular disease risk factor. They are superior to WC, WHtR, WHR, BF%, C-index, AVI and AT.
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Affiliation(s)
- A Kammar-García
- Biochemistry Department, School of Medicine, Benemérita Universidad Autónoma de Puebla, Mexico.
| | | | - P López-Moreno
- Biochemistry Department, School of Medicine, Benemérita Universidad Autónoma de Puebla, Mexico
| | - A María Ortíz-Bueno
- Biochemistry Department, School of Medicine, Benemérita Universidad Autónoma de Puebla, Mexico
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Velez-Cubian FO, Zhang WW, Rodriguez KL, Thau MR, Ng EP, Moodie CC, Garrett JR, Fontaine JP, Toloza EM. Effect of small body habitus on peri-operative outcomes after robotic-assisted pulmonary lobectomy: retrospective analysis of 208 consecutive cases. J Thorac Dis 2016; 8:1245-9. [PMID: 27293843 DOI: 10.21037/jtd.2016.04.67] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Patients with smaller body surface area (BSA) have smaller pleural cavities, which limit visualization and instrument mobility during video-assisted thoracoscopic surgery (VATS). We investigated the effects of BSA on outcomes with robotic-assisted VATS lobectomy. METHODS We analyzed 208 consecutive patients who underwent robotic-assisted lobectomy over 34 months. Patients were separated into group A (BSA ≤1.65 m(2)) and group B (BSA >1.65 m(2)). Operative times, estimated blood loss (EBL), conversions to thoracotomy, complications, hospital length of stay (LOS), and in-hospital mortality were compared. RESULTS Group A had 40 patients (BSA 1.25-1.65 m(2)), and group B had 168 patients (BSA 1.66-2.86 m(2)). Median skin-to-skin operative times [± standard error of the mean (SEM)] were 169±16 min for group A and 176±6 min for group B (P=0.34). Group A had median EBL of 150±96 mL compared to 200±24 mL for group B (P=0.37). Overall conversion rate to thoracotomy was 8/40 (20.0%) in group A versus 12/168 (7.1%) in group B (P=0.03); while emergent conversion for bleeding was 2/40 (5.0%) in group A versus 5/168 (3.0%) in group B (P=0.62). Postoperative complications occurred in 12/40 (30.0%) in group A, compared to 66/168 (39.3%) in group B (P=0.28). Patients from both groups had median hospital LOS of 5 days (P=0.68) and had similar in-hospital mortality. CONCLUSIONS Patients with BSA ≤1.65 m(2) have similar perioperative outcomes and complication risks as patients with larger BSA. Patients with BSA ≤1.65 m(2) have a higher overall conversion rate to thoracotomy, but similar conversion rate for bleeding as patients with larger BSA. Robotic-assisted pulmonary lobectomy is feasible and safe in patients with small body habitus.
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Affiliation(s)
- Frank O Velez-Cubian
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Wei-Wei Zhang
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Kathryn L Rodriguez
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Matthew R Thau
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Emily P Ng
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Carla C Moodie
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Joseph R Garrett
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Jacques-Pierre Fontaine
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Eric M Toloza
- 1 Department of Surgery, University of South Florida, Tampa, FL, USA ; 2 Morsani College of Medicine, University of South Florida, Tampa, FL, USA ; 3 Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA ; 4 Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
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