Psoas Muscle Index as a Predictor of Postoperative Outcomes in Gastrointestinal Cancer Surgery

doi:10.21203/rs.3.rs-3979769/v1

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Psoas Muscle Index as a Predictor of Postoperative Outcomes in Gastrointestinal Cancer Surgery

https://doi.org/10.21203/rs.3.rs-3979769/v1

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Purpose

Psoas muscle index as an index of sarcopenia has a notable role in anticipating the outcome of various disorders. This prospective study aims to explore the efficacy of psoas muscle index in predicting the surgical outcomes of patients with gastrointestinal tumors.

Methods

All gastrointestinal cancer patients hospitalized for surgical treatment at our hospital between 2020 and 2023 were studied. Linear regression analysis compared psoas muscle index, age, and body mass index regarding hospitalization time and hand grip strength. Pearson's correlation test determined the strength and direction of the correlation between psoas muscle index and hospitalization duration.

Results

A total of 64 patients with a mean age of 57 years were included in our study to examine the potential association between psoas muscle index and length of hospital stay. Only psoas muscle index, compared to body mass index and age, demonstrates a statistically significant correlation with hospitalization time (r=-0.444, p < 0.001, CI -0.333 to -0.103). In addition, the impact of gender on this association is not substantial. The study also explored the correlation between hand grip strength and psoas muscle index in 62 participants. There is a significant association between age and psoas muscle index with right-hand grip strength (p = 0.000 and p = 0.014) and left-hand grip strength (p = 0.002 and p = 0.013).

Conclusion

Psoas muscle index potently predicts surgical consequences in gastrointestinal cancer patients and is essential in identifying high-risk patients and considering the risk-benefit ratio of surgical interventions.

Sarcopenia

Gastrointestinal malignancies

Psoas muscle index

Hand grip strength

Postoperative complications

Cancer causes the most clinical burden compared to other diseases regarding the impact on disability-adjusted life year (1). Even though the incidence of some kinds of gastrointestinal(GI) cancer has decreased, this group of malignancies continues to cause significant problems to public health (2). Patients with GI malignancies typically undergo surgical interventions as a means of curative or palliative management. After accomplishing surgical interventions in these patients, vulnerabilities such as age, obesity, and muscle strength may contribute to unfavorable prognosis and adverse postoperative outcomes (3–6). One of the beneficial estimates for muscle strength in cancer patients is to determine sarcopenia. Sarcopenia refers to the decrease in the quality and quantity of psoas muscle; it also has a decisive role in the outcome of various cancerous and non-cancerous(7–10).

Computed tomography (CT) is presumably the best method for examining muscle mass and the standard method of analyzing body structures; However, due to the high radiation exposure, its role in screening for sarcopenia in individuals who do not require a CT scan for another purpose is questionable. The cross-sectional area obtained by CT has to be corrected by the square of height, and the result is measured to determine the psoas muscle index (PMI) as an indicator of sarcopenia(11). Low PMI is associated with poor prognosis in solid tumors (12).

Aside from evaluating muscle stability, examining physical abilities helps determine the outcome of patients. The hand grip strength (HGS) test simultaneously evaluates muscle strength and nutritional status. A low HGS rate highly relates to cancer mortality and is recommended for pre-surgical assessments (13–15).

The relationship between sarcopenia as a potential predictive method and postoperative complications in patients with GI tumors needs a comprehensive investigation so that it can be integrated into surgical guidelines to enable more informed decisions regarding mortality and morbidity risks. We hypothesize that the adjusted sarcopenia index obtained by CT of patient candidates for GI tumor resection could consider a qualified predictive factor for the outcome of surgery. Thus, in this study, muscle mass and its association with the length of hospital stay of patients after surgery as an indication of the recovery rate and HGS rate have been analyzed and compared with other variable factors such as age and body mass index (BMI) to challenge the acceptability of this index in initial evaluations.

Patients

In this prospective cross-sectional study, patients with pathological findings for gastrointestinal cancers (such as gastric, colon, hepatic, or gallbladder) were hospitalized for surgical treatment at Ayatollah Taleghani University Hospital between 2020 to 2023 and had abdominopelvic CT scans were included. Informed consent was obtained from the participants, and the privacy rights of individuals were respected according to the principles of the Declaration of Helsinki. Patients who refused to participate were not selected. The study was approved by the ethics committee of Shahid Beheshti University of Medical Sciences, Tehran, Iran (IR.SBMU.MSP.REC.1401.376).

Data extraction

The following demographic data for all of the patients were collected by trained physicians: age, sex, height, weight, past medical history, BMI, cancer types, surgical methods, comorbidities (diabetes mellitus, hypertension, renal diseases, coronary heart disease, respiratory diseases), hospital stay length, psoas muscle index content acquired by abdominopelvic CT scan and HGS test results. The hand grip test was measured by the strength of muscles in total. In hand grip strength, patients were seated and flexed their elbows at 90 degrees when other joints were neutral. The dominant hand determined maximum strength by holding and squeezing the dynamometer as hard as possible. After three times with 30 seconds of recovery between each exam, the highest score was recorded as HGS.

Psoas Muscle Index Measurement

Preoperative abdominopelvic computed tomography scans without intravascular contrast injection by a Zimanth 16-slice CT scanner were used to measure the sarcopenic index. Using a threshold of -29 to + 150 Hounsfield units, the cross-sectional area (CSA) of all abdominal wall and paraspinal muscles was measured on axial CT scan at the level of L3 vertebra by Slice-O-Matic version 5.0 software (TomoVision). The following formula was used to calculate the psoas muscle index: psoas muscle index = Abdominal wall and paraspinal muscles CSA/(height)² expressed in mm²/m². Data extraction and determination of muscle and fat areas were carried out by two blinded physicians. Following the image acquisition described above, figurative CT scan images were selected to represent the method of PMI measurement (Fig. 1).

Statistical analysis

All data were divided into categorical variables or continuous variables (mean ± standard deviation). The variables examined in the patients include the type of malignant disorder, gender, hand grip strength test, and PMI as a quantitative muscle mass index. Pearson's correlation test was accomplished to establish the magnitude and direction of the correlation between PMI and hospitalization duration. Multiple linear regression analysis was conducted to compare PMI, age, and BMI regarding the length of hospitalization and HGS test results of both hands. SPSS statistics version 27.0.1.0 (IBM Corp., Armonk, NY, USA) was used for all the statistical analyses. In statistical results, P < 0.05 was meant as a significant difference.

Study population

In total, considering inclusion criteria, both PMI and length of hospitalization can be calculated in 64 patients with a mean age of 57.85 years (SD = 11.09), which includes 36 (56.2%) men and 28 (43.7%) women. The statistical analysis did not examine the remaining patients because of the immeasurable psoas muscle diameter at the level of the L3 vertebra in imaging, the uncertainty of their precise height required to specify PMI and the unclearness of the start or end time of hospitalization. In this study population, pancreatic cancer, with 15 (23.4%) patients, is the most frequent cancer, followed by colon cancer, with 13 (20.3%) patients; hepatobiliary cancer, with 13 (20.3%) patients; gastric cancer, with 12 (18.7%) patients; and esophageal cancer, with 11 (17.1%) patients.

PMI Impact on Hospitalization Length

A strong negative correlation between PMI and length of hospitalization was found, r (62) = -0.59, P < 0.001. The expression of a linear correlation between PMI and hospitalization length is displayed with a scatterplot (Fig. 2). A simple linear regression analysis was conducted to predict hospital stay length based on PMI, and a significant regression equation was discovered (F (1,62) = 33.94, P < 0.001). The results of regression revealed that one unit of PMI justified 35.4% of the variation in hospitalization length and is significantly determinative (t = -5.83, P < 0.001). The homoscedasticity and normal distribution of residuals were established within the data without any outliers beyond ± 3 standard deviations, as illustrated by a normal p-plot of standardized residuals (Fig. 3). The data also met the assumption of independent errors (Durbin-Watson value = 1.61). The estimated duration days of patients' post-operative hospital stay is equivalent to 19.094–0.267 multiplied by the PMI measured with $\raisebox{1ex}{${mm}^{2}$}\!\left/ \!\raisebox{-1ex}{${m}^{2}$}\right.$. To inspect the inclusiveness of the predictive value of PMI in both genders, linear regression analysis was conducted in both populations separately, and there is no influential difference between them (Table 1). PMI predicted hospital stay time in men (R² = 0.27, F (1,34) = 12.89, P = 0.001) and women (R² = 0.51, F (1, 26) = 28.06, P < 0.001).

Table 1

The comprehensiveness of PMI in both genders. This study examined the impact of gender on hospital stay duration and found no significant difference between male and female patients. df, degree of freedom; r, the correlation coefficient; CI, confidence interval.
	df	r	P-value	95% CI
Male	34	-0.52	0.001	-0.37 to -0.10
Female	26	-0.72	< 0.001	-0.47 to -0.20

Furthermore, to approximate the impact of BMI, age, and PMI on hospitalization time, multiple linear regression was run between 58 patients with a mean age of 57.82 (SD = 11.36), F (3, 54) = 12.68, P < 0.001, R² = 0.413. The results exemplify that age and BMI, unlike PMI, do not affect the duration of hospitalization after tumor resection surgery (Table 2).

Table 2

Linear regression analysis comparing the impact of independent variables (PMI and BMI and age) on dependent variable (hospital stay time). These results show that only PMI had a notable association with hospital stay time among these independent variables. Coefficients Std. Error, standard error of the beta coefficient; t, t-statistic; CI, confidence interval; PMI, psoas muscle index; BMI, body mass index.
	Coefficients Std. Error	t	P -value	95% CI
PMI	0.047	-5.77	< 0.001	-0.36 to -0.17
BMI	0.058	-0.69	0.493	-0.15 to 0.07
Age	0.029	-1.01	0.313	-0.08 to 0.02

Correlation of PMI, Age, BMI, and HGS

PMI and HGS test results were also available in 62 patients with a mean age of 58.83 (SD = 11.65), containing 36 men (58.1%) and 26 women (41.9%). The relation between PMI and right and left handgrip strength test results was inspected, and a moderate positive correlation was found with both hands, r (60) = 0.28, P = 0.025, and r (60) = 0.31, P = 0.014, respectively. The linear association between PMI and right and left HGS is represented by scatterplots (Fig. 4). The multiple linear regression analysis was calculated to predict the right- and left-hand grip test results based on comparable variables (age, PMI, BMI). For right-hand grip strength, this results in a significant model, F (3, 58) = 7.24, P < 0.001, R² = 0.273. For left-hand grip strength, a significant equation was found, F (3, 58) = 6.132, P < 0.001, R² = 0.241. In particular, PMI and age were significant predictors for both hand grip strength, but BMI was not (Table 3).

Table 3

Assessment of impacts of PMI, BMI, and age on right- and left- hand grip strength tests. The results demonstrate that age and PMI have a significant relationship with both HGS; however, BMI has not. Coefficients Std. Error, standard error of the beta coefficient; t, t-statistic; CI, confidence interval; PMI, psoas muscle index; BMI, body mass index; HGS, hand grip strength.
		Coefficients Std. Error	t	P-value	95% CI
Right HGS	PMI	0.129	2.52	0.014	0.06 to 0.58
	BMI	0.164	-1.22	0.225	-0.53 to 0.12
	Age	0.077	-3.69	< 0.001	-0.44 to -0.13
Left HGS	PMI	0.127	2.55	0.013	0.070 to 0.581
	BMI	0.163	-0.67	0.504	-0.435 to 0.216
	Age	0.076	-3.24	0.002	-0.401 to -0.095

This study aims to determine the psoas muscle index as a precise factor for surgical outcomes. Based on the obtained results, PMI is a potent predictor of hospitalization time, independent of gender. Therefore, this index promises to be a reliable indicator of post-surgery complications regardless of other clinical or demographic characteristics. The notability of PMI is that it is easily accessible and does not require dedicated attainment. Almost all patients with GI cancers have been imaged before surgery and therefore do not need additional radiation. The best site in cross-sectional imaging to determine the PMI is in the range of the L3 vertebra, which is recognizable in CT of the abdomen and pelvis of these patients(16). This index needs to adjust based on the patient's height to provide a comparable value of sarcopenia(11, 17). In this study, the relationship of PMI with a higher period of hospitalization as an indicator of poor survival compared to age and BMI has been specified. Overweight cancer people are advantaged more than other patients from the preference of PMI over BMI because weight loss, one of the well-known cancer clues, may not be observable in obese people, and the high weight of these patients conceals such losses. However, sarcopenia can efficiently be recognized in them. As a result, and based on this study, it is recommended to measure muscle quantity from the beginning of the assessment, especially in overweight people.

This radiological index is also related to the physical potency of patients before performing tumor resection surgery; and is a more accurate factor than BMI and age in the quantity of the hand grip strength test. HGS is directly related to the mortality of cancer patients and is used to identify the nutritional situation of patients who are candidates for gastrointestinal surgery(18). This low-price and accessible test refers to the maximum strength of each hand in kilograms. Our investigation revealed that PMI correlates to HGS of both hands and increases the validity of preoperative exercise testing.

The prevalence of sarcopenia in all types of GI cancers is clarified, which indicates that it is caused by a similar mechanism of malignancies, regardless of its kind(19–21). There are various factors involved in creating alterations in muscle fibers leading to sarcopenia, such as increased apoptotic activity due to the down-regulation of certain hormones like growth hormone and insulin, proteolysis of muscle tissue by increasing the levels of pro-inflammatory mediators like tumor necrosis factor-alpha and interleukin 6, and Mitochondria instability due to the increase of oxygen-containing reactive species (ROS). Decreased intake of adequate nutrients due to inflammatory substances causing diminished appetite also leads to muscle changes visible on imaging(22, 23). Accordingly, the decrease in muscle volume could be a practical guide toward understanding the transformation at the cellular and molecular level of these patients. In addition to the microscopic interactions due to malignancies, various types of cancer treatment can also accelerate the occurrence of sarcopenia. Antineoplastic drugs are of particular importance. Several anti-cancer drugs worsen sarcopenia and exacerbate its adverse effects, which cause toxicity induced by chemotherapy and reduce the response to treatment. Therefore, the association between chemotherapy and sarcopenia is two-way, and each aggravates the unfavorable effect of the other(24, 25). Radiotherapy is another treatment option for GI cancers, including pancreatic and rectal cancer. The impact of sarcopenia on survival after radiotherapy of head and neck cancer patients is well known(26–28). The prognostic value of PMI in radiotherapy of GI cancers requires further research. Also, an additional investigation needs to determine radiotherapy-induced changes in the process of sarcopenia.

After estimating the PMI and distinguishing the high-risk people, treatment approaches for improving the patient's life expectancy recommend. Different processes have been investigated to reclaim muscle mass in individuals with cancer. Proper nutrition is one of the considerable ways to gain adequate muscle capacity(29). For instance, anti-inflammatory materials such as Eicosapentaenoic acid (EPA) found in fish or separately; are beneficial to gain weight and appetite in patients at risk of body composition changes without remarkable side effects. Vitamin D supplements with whey protein and adequate exercise also recommend for low muscle mass treatment(30). In addition, contractile protein mass can enhance by resistance training. These exercises diminish sarcopenia by reducing body fat, increasing muscle strength, and building muscle through protein(31, 32). It is recommended that validated therapeutic modalities be considered for individuals with sarcopenia who are scheduled to undergo tumor resection surgery. Such interventions should be performed under the recommendation of a qualified nutritionist and exercise specialist to decrease the risk of post-surgical morbidity.

Previous research has explored the influence of sarcopenia on the prognosis of patients with GI malignancies and its impact on chemotherapy response and physical strength. The present study seeks to clarify the importance of the defined PMI as an indicator of sarcopenia regarding postoperative complications in this population. Under its accessibility before surgery, PMI becomes a crucial factor in surgical decision-making. This study represents the first study demonstrating the validity of sarcopenia in all forms of GI cancer, thereby proposing surgical approaches to these tumors. Additionally, our investigation confirms the correlation between PMI and HGS, emphasizing this index's importance.

The limitations of this investigation may affect the results to some extent. For instance, despite the high statistical population, due to the limited availability of all variables required for evaluating the correlation in this study, the number of patients whose both PMI and length of stay in the hospital were investigated was restricted, which can undermine the statistical power of the analysis and challenge the comprehensiveness of these statistics in larger communities underscoring the requirement for more extensive studies. Furthermore, the length of hospitalization of postoperative patients can be influenced by previous underlying conditions and medications.

Future studies should aim to determine effectual and precise guidelines for retrieving sarcopenia, including physical therapy or dietary regimens in subjects affected with GI tumors. Additionally, identifying pharmacological agents with a minimal adverse impact on muscle mass during chemotherapy is suggested. In addition, for better practical use of PMI, a precise quantitative level as a cut-off of sarcopenia is highly recommended, which can be easily attended to in managing patients before surgery.

In conclusion, this study highlights the significance of the psoas muscle index (PMI) as a determinant factor for surgical outcomes in patients with GI cancers. PMI is easily obtainable and more precise than BMI and age in determining physical potency and hand grip strength, making this index a practical tool in preoperative assessments. These findings are essential in identifying high-risk patients and choosing proper approaches to enhance their life expectancy, especially considering surgical interventions' risk-benefit ratio.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Nima Shokrollahi, Mohammad Nouri, Alireza Movahedi and Mehdi Eshaghzadeh. The first draft of the manuscript was written by Nima Shokrollahi, Mohammad Nouri, Amirhassan Rabbani and Hesammedin Eghlimi and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data Availability

The datasets analysed during the current study are available from the corresponding author on reasonable request.

Mattiuzzi C, Lippi G. Current cancer epidemiology. Journal of epidemiology and global health. 2019;9(4):217.
Arnold M, Abnet CC, Neale RE, Vignat J, Giovannucci EL, McGlynn KA, Bray F. Global burden of 5 major types of gastrointestinal cancer. Gastroenterology. 2020;159(1):335-49. e15.
Chindapasirt J. Sarcopenia in cancer patients. Asian Pacific Journal of Cancer Prevention. 2016;16(18):8075-7.
Hursting SD, DiGiovanni J, Dannenberg AJ, Azrad M, LeRoith D, Demark-Wahnefried W, et al. Obesity, energy balance, and cancer: new opportunities for prevention. Cancer prevention research. 2012;5(11):1260-72.
Pandya C, Magnuson A, Flannery M, Zittel J, Duberstein P, Loh KP, et al. Association between symptom burden and physical function in older patients with cancer. Journal of the American Geriatrics Society. 2019;67(5):998-1004.
Xue D-d, Cheng Y, Wu M, Zhang Y. Comprehensive geriatric assessment prediction of postoperative complications in gastrointestinal cancer patients: a meta-analysis. Clinical Interventions in Aging. 2018:723-36.
Dent E, Morley J, Cruz-Jentoft A, Arai H, Kritchevsky S, Guralnik J, et al. International clinical practice guidelines for sarcopenia (ICFSR): screening, diagnosis and management. The journal of nutrition, health & aging. 2018;22:1148-61.
Giglio J, Kamimura MA, Lamarca F, Rodrigues J, Santin F, Avesani CM. Association of sarcopenia with nutritional parameters, quality of life, hospitalization, and mortality rates of elderly patients on hemodialysis. Journal of Renal Nutrition. 2018;28(3):197-207.
Moisey LL, Mourtzakis M, Cotton BA, Premji T, Heyland DK, Wade CE, et al. Skeletal muscle predicts ventilator-free days, ICU-free days, and mortality in elderly ICU patients. Critical care. 2013;17(5):1-8.
Pamoukdjian F, Bouillet T, Lévy V, Soussan M, Zelek L, Paillaud E. Prevalence and predictive value of pre-therapeutic sarcopenia in cancer patients: a systematic review. Clinical Nutrition. 2018;37(4):1101-13.
Tagliafico AS, Bignotti B, Torri L, Rossi F. Sarcopenia: how to measure, when and why. La radiologia medica. 2022;127(3):228-37.
Shachar SS, Williams GR, Muss HB, Nishijima TF. Prognostic value of sarcopenia in adults with solid tumours: a meta-analysis and systematic review. European journal of cancer. 2016;57:58-67.
Kim H, Yoo S, Kim H, Park SG, Son M. Cancer survivors with low hand grip strength have decreased quality of life compared with healthy controls: The Korea National Health and Nutrition Examination Survey 2014–2017. Korean journal of family medicine. 2021;42(3):204.
Song M, Zhang Q, Tang M, Zhang X, Ruan G, Zhang X, et al. Associations of low hand grip strength with 1 year mortality of cancer cachexia: a multicentre observational study. Journal of cachexia, sarcopenia and muscle. 2021;12(6):1489-500.
Zhuang CL, Zhang FM, Li W, Wang KH, Xu HX, Song CH, et al. Associations of low handgrip strength with cancer mortality: a multicentre observational study. Journal of Cachexia, Sarcopenia and Muscle. 2020;11(6):1476-86.
Kazemi-Bajestani SMR, Mazurak VC, Baracos V, editors. Computed tomography-defined muscle and fat wasting are associated with cancer clinical outcomes. Seminars in cell & developmental biology; 2016: Elsevier.
Boutin RD, Yao L, Canter RJ, Lenchik L. Sarcopenia: current concepts and imaging implications. American Journal of Roentgenology. 2015;205(3):W255-W66.
Silveira TMG, SOUSA JBd, Stringhini MLF, FREITAS ATVdS, Melo PG. Nutritional assessment and hand grip strength of candidates for surgery of the gastrointestinal tract. ABCD Arquivos Brasileiros de Cirurgia Digestiva (São Paulo). 2014;27:104-8.
O'brien S, Twomey M, Moloney F, Kavanagh RG, Carey BW, Power D, et al. Sarcopenia and post-operative morbidity and mortality in patients with gastric cancer. Journal of gastric cancer. 2018;18(3):242-52.
Pessia B, Giuliani A, Romano L, Bruno F, Carlei F, Vicentini V, Schietroma M. The role of sarcopenia in the pancreatic adenocarcinoma. Eur Rev Med Pharmacol Sci. 2021;25(10):3670-8.
Yang J, Chen K, Zheng C, Chen K, Lin J, Meng Q, et al. Impact of sarcopenia on outcomes of patients undergoing liver resection for hepatocellular carcinoma. Journal of Cachexia, Sarcopenia and Muscle. 2022;13(5):2383-92.
Peixoto da Silva S, Santos JM, Costa e Silva MP, Gil da Costa RM, Medeiros R. Cancer cachexia and its pathophysiology: links with sarcopenia, anorexia and asthenia. Journal of cachexia, sarcopenia and muscle. 2020;11(3):619-35.
Vega MCMD, Laviano A, Pimentel GD. Sarcopenia and chemotherapy-mediated toxicity. Einstein (Sao Paulo). 2016;14:580-4.
Bozzetti F. Forcing the vicious circle: sarcopenia increases toxicity, decreases response to chemotherapy and worsens with chemotherapy. Annals of oncology. 2017;28(9):2107-18.
Chan MY, Chok KSH. Sarcopenia in pancreatic cancer–effects on surgical outcomes and chemotherapy. World Journal of Gastrointestinal Oncology. 2019;11(7):527.
Karavolia E, van Rijn-Dekker MI, Van den Bosch L, van den Hoek JG, Oldehinkel E, Meijer TW, et al. Impact of sarcopenia on acute radiation-induced toxicity in head and neck cancer patients. Radiotherapy and Oncology. 2022;170:122-8.
Medici F, Bazzocchi A, Buwenge M, Zamagni A, Macchia G, Deodato F, et al. Impact and Treatment of Sarcopenia in Patients Undergoing Radiotherapy: A Multidisciplinary, AMSTAR-2 Compliant Review of Systematic Reviews and Metanalyses. Frontiers in Oncology. 2022;12.
Thureau S, Lebret L, Lequesne J, Cabourg M, Dandoy S, Gouley C, et al. Prospective evaluation of sarcopenia in head and neck cancer patients treated with radiotherapy or radiochemotherapy. Cancers. 2021;13(4):753.
Ravasco P. Nutrition in cancer patients. Journal of clinical medicine. 2019;8(8):1211.
Prado CM, Purcell SA, Laviano A. Nutrition interventions to treat low muscle mass in cancer. Journal of cachexia, sarcopenia and muscle. 2020;11(2):366-80.
Davis MP, Panikkar R. Sarcopenia associated with chemotherapy and targeted agents for cancer therapy. Ann Palliat Med. 2019;8(1):86-101.
Papa EV, Dong X, Hassan M. Resistance training for activity limitations in older adults with skeletal muscle function deficits: a systematic review. Clinical interventions in aging. 2017:955-61.

No competing interests reported.

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Psoas Muscle Index as a Predictor of Postoperative Outcomes in Gastrointestinal Cancer Surgery

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Abstract

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Introduction

Method

Statistical analysis

Result

Study population

PMI Impact on Hospitalization Length

Correlation of PMI, Age, BMI, and HGS

Discussion

Declarations

References

Additional Declarations

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