Psoas Muscle Index Defined by Computer Tomography Predicts the Presence of Postoperative Complications in Colorectal Cancer Surgery
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Data Collection
2.2. Patient and Perioperative Factors
2.3. Radiological Measurements
2.4. Postoperative Follow-Up and Complications by Clavien-Dindo Classification
2.5. Statistical Analyses
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [Green Version]
- Mármol, I.; Sánchez-de-Diego, C.; Dieste, A.P.; Cerrada, E.; Yoldi, M.J.R. Colorectal Carcinoma: A General Overview and Future Perspectives in Colorectal Cancer. Int. J. Mol. Sci. 2017, 18, 197. [Google Scholar] [CrossRef] [Green Version]
- Ratto, C.; Sofo, L.; Ippoliti, M.; Merico, M.; Doglietto, G.B.; Crucitti, F. Prognostic factors in colorectal cancer. Literature review for clinical application. Dis. Colon Rectum. 1998, 41, 1033–1049. [Google Scholar] [CrossRef] [PubMed]
- Santilli, V.; Bernetti, A.; Mangone, M.; Paoloni, M. Clinical definition of sarcopenia. Clin. Cases Miner. Bone Metab. Off. J. Ital. Soc. Osteoporos. Miner. Metab. Skelet. Dis. 2014, 11, 177–180. [Google Scholar] [CrossRef]
- Morrell, G.R.; Ikizler, T.A.; Chen, X.; Heilbrun, M.E.; Wei, G.; Boucher, R.; Beddhu, S. Psoas Muscle Cross-sectional Area as a Measure of Whole-body Lean Muscle Mass in Maintenance Hemodialysis Patients. J. Ren. Nutr. Off. J. Counc. Ren. Nutr. Natl. Kidney Found. 2016, 26, 258–264. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Park, S.E.; Choi, J.H.; Park, J.Y.; Kim, B.J.; Kim, J.G.; Kim, J.W.; Park, J.-M.; Chi, K.-C.; Hwang, I.G. Loss of skeletal muscle mass during palliative chemotherapy is a poor prognostic factor in patients with advanced gastric cancer. Sci. Rep. 2020, 10, 17683. [Google Scholar] [CrossRef]
- Zhang, G.; Li, X.; Sui, C.; Zhao, H.; Zhao, J.; Hou, Y.; DU, Y. Incidence and risk factor analysis for sarcopenia in patients with cancer. Oncol. Lett. 2016, 11, 1230–1234. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cruz-Jentoft, A.J.; Baeyens, J.P.; Bauer, J.M.; Boirie, Y.; Cederholm, T.; Landi, F.; Martin, F.C.; Michel, J.-P.; Rolland, Y.; Schneider, S.M.; et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010, 39, 412–423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Levolger, S.; van Vugt, J.L.A.; de Bruin, R.W.F.; Ijzermans, J.N.M. Systematic review of sarcopenia in patients operated on for gastrointestinal and hepatopancreatobiliary malignancies. Br. J. Surg. 2015, 102, 1448–1458. [Google Scholar] [CrossRef] [PubMed]
- Vergara-Fernandez, O.; Trejo-Avila, M.; Salgado-Nesme, N. Sarcopenia in patients with colorectal cancer: A comprehensive review. World J. Clin. Cases 2020, 8, 1188–1202. [Google Scholar] [CrossRef]
- Jones, K.I.; Doleman, B.; Scott, S.; Lund, J.N.; Williams, J.P. Simple psoas cross-sectional area measurement is a quick and easy method to assess sarcopenia and predicts major surgical complications. Colorectal Dis. Off. J. Assoc. Coloproctol. Great Br. Irel. 2015, 17, O20–O26. [Google Scholar] [CrossRef] [Green Version]
- Prashanthi, P.L.; Ramachandran, R.; Adhilakshmi, A.; Radhan, P.; Sai, V. Standardization of PSOAS Muscle Index Measurements Using Computed Tomography. Int. J. Contemp. Med. Surg. Radiol. 2020, 5. [Google Scholar] [CrossRef]
- Dindo, D.; Demartines, N.; Clavien, P.-A. Classification of surgical complications: A new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann. Surg. 2004, 240, 205–213. [Google Scholar] [CrossRef]
- Clavien, P.A.; Barkun, J.; de Oliveira, M.L.; Vauthey, J.N.; Dindo, D.; Schulick, R.D.; de Santibañes, E.; Pekolj, J.; Slankamenac, K.; Bassi, C.; et al. The Clavien-Dindo Classification of Surgical Complications: Five-Year Experience. Ann. Surg. 2009, 250, 187–196. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Malietzis, G.; Johns, N.; Al-Hassi, H.O.; Knight, S.C.; Kennedy, R.H.; Fearon, K.C.H.; Aziz, O.; Jenkins, J.T. Low Muscularity and Myosteatosis Is Related to the Host Systemic Inflammatory Response in Patients Undergoing Surgery for Colorectal Cancer. Ann. Surg. 2015, 263. Available online: https://cyberleninka.org/article/n/643217 (accessed on 19 January 2021). [CrossRef]
- McSorley, S.T.; Ramanathan, M.L.; Horgan, P.G.; McMillan, D.C. Postoperative C-reactive protein measurement predicts the severity of complications following surgery for colorectal cancer. Int. J. Colorectal Dis. 2015, 30, 913–917. [Google Scholar] [CrossRef]
- McMillan, D.C. Systemic inflammation, nutritional status and survival in patients with cancer. Curr. Opin. Clin. Nutr. Metab. Care 2009, 12, 223–226. [Google Scholar] [CrossRef] [Green Version]
- Chen, L.-K.; Liu, L.-K.; Woo, J.; Assantachai, P.; Auyeung, T.-W.; Bahyah, K.S.; Chou, M.-Y.; Hsu, P.-S.; Krairit, O.; Lee, J.S.; et al. Sarcopenia in Asia: Consensus report of the Asian Working Group for Sarcopenia. J. Am. Med. Dir. Assoc. 2014, 15, 95–101. [Google Scholar] [CrossRef]
- Beaudart, C.; Zaaria, M.; Pasleau, F.; Reginster, J.-Y.; Bruyère, O. Health Outcomes of Sarcopenia: A Systematic Review and Meta-Analysis. PLoS ONE 2017, 12, e0169548. [Google Scholar] [CrossRef] [Green Version]
- Bano, G.; Trevisan, C.; Carraro, S.; Solmi, M.; Luchini, C.; Stubbs, B.; Manzato, E.; Sergi, G.; Veronese, N. Inflammation and sarcopenia: A systematic review and meta-analysis. Maturitas 2017, 96, 10–15. [Google Scholar] [CrossRef]
- Bhandari, T.R.; Shahi, S.; Bhandari, R.S.; Lakhey, P.J. Preoperative serum albumin level as a predictor of perioperative outcome in patient undergoing major gastrointestinal surgery. J. Soc. Surg. Nepal 2016, 19. [Google Scholar] [CrossRef]
- Galata, C.; Busse, L.; Birgin, E.; Weiß, C.; Hardt, J.; Reißfelder, C.; Otto, M. Role of Albumin as a Nutritional and Prognostic Marker in Elective Intestinal Surgery. Can. J. Gastroenterol. Hepatol. 2020, 2020, 7028216. [Google Scholar] [CrossRef]
- Kim, Y.W.; Kim, I.Y. Factors associated with postoperative complications and 1-year mortality after surgery for colorectal cancer in octogenarians and nonagenarians. Clin. Interv. Aging 2016, 11, 689–697. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pak, H.; Maghsoudi, L.H.; Soltanian, A.; Gholami, F. Surgical complications in colorectal cancer patients. Ann. Med. Surg. 2020, 55, 13–18. [Google Scholar] [CrossRef]
- Dasarathy, S.; Merli, M. Sarcopenia from mechanism to diagnosis and treatment in liver disease. J. Hepatol. 2016, 65, 1232–1244. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Izumi, T.; Watanabe, J.; Tohyama, T.; Takada, Y. Impact of psoas muscle index on short-term outcome after living donor liver transplantation. Turk. J. Gastroenterol. Off. J. Turk. Soc. Gastroenterol. 2016, 27, 382–388. [Google Scholar] [CrossRef]
- Nakamura, R.; Inage, Y.; Tobita, R.; Yoneyama, S.; Numata, T.; Ota, K.; Yanai, H.; Endo, T.; Inadome, Y.; Sakashita, S.; et al. Sarcopenia in Resected NSCLC: Effect on Postoperative Outcomes. J. Thorac. Oncol. Off. Publ. Int. Assoc. Study Lung Cancer 2018, 13, 895–903. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Abbass, T.; Ho, Y.T.T.; Horgan, P.G.; Dolan, R.D.; McMillan, D.C. The relationship between computed tomography derived skeletal muscle index, psoas muscle index and clinical outcomes in patients with operable colorectal cancer. Clin. Nutr. ESPEN 2020, 39, 104–113. [Google Scholar] [CrossRef]
- Murachi, Y.; Sakai, D.; Koseki, J.; Inagaki, C.; Nishida, N.; Yamaguchi, T.; Satoh, T. Impact of sarcopenia in patients with advanced or recurrent colorectal cancer treated with regorafenib. Int. J. Clin. Oncol. 2020. [Google Scholar] [CrossRef] [PubMed]
- Tee, Y.-S.; Cheng, C.-T.; Wu, Y.-T.; Kang, S.-C.; Derstine, B.A.; Fu, C.-Y.; Liao, C.-H.; Su, G.L.; Wang, S.C.; Hsieh, C.-H. The psoas muscle index distribution and influence of outcomes in an Asian adult trauma population: An alternative indicator for sarcopenia of acute diseases. Eur. J. Trauma Emerg. Surg. Off. Publ. Eur. Trauma Soc. 2020. [Google Scholar] [CrossRef]
- Yamada, R.; Todo, Y.; Kurosu, H.; Minowa, K.; Tsuruta, T.; Minobe, S.; Matsumiya, H.; Kato, H.; Mori, Y.; Osanai, T. Validity of measuring psoas muscle mass index for assessing sarcopenia in patients with gynecological cancer. Jpn. J. Clin. Oncol. 2020. [Google Scholar] [CrossRef]
- Hou, L.; Deng, Y.; Wu, H.; Xu, X.; Lin, L.; Cui, B.; Zhao, T.; Fan, X.; Mao, L.; Hou, J.; et al. Low psoas muscle index associates with long-term mortality in cirrhosis: Construction of a nomogram. Ann. Transl. Med. 2020, 8, 358. [Google Scholar] [CrossRef]
- Zager, Y.; Khalilieh, S.; Ganaiem, O.; Gorgov, E.; Horesh, N.; Anteby, R.; Kopylov, U.; Jacoby, H.; Dreznik, Y.; Dori, A.; et al. Low psoas muscle area is associated with postoperative complications in Crohn’s disease. Int. J. Colorectal Dis. 2020. [Google Scholar] [CrossRef]
- Wang, S.; Xie, H.; Gong, Y.; Kuang, J.; Yan, L.; Ruan, G.; Gao, F.; Gan, J. The value of L3 skeletal muscle index in evaluating preoperative nutritional risk and long-term prognosis in colorectal cancer patients. Sci. Rep. 2020, 10, 8153. [Google Scholar] [CrossRef] [PubMed]
- Sun, G.; Li, Y.; Peng, Y.; Lu, D.; Zhang, F.; Cui, X.; Zhang, Q.; Li, Z. Can sarcopenia be a predictor of prognosis for patients with non-metastatic colorectal cancer? A systematic review and meta-analysis. Int. J. Colorectal Dis. 2018, 33, 1419–1427. [Google Scholar] [CrossRef] [PubMed]
- Cao, Q.; Xiong, Y.; Zhong, Z.; Ye, Q. Computed Tomography-Assessed Sarcopenia Indexes Predict Major Complications following Surgery for Hepatopancreatobiliary Malignancy: A Meta-Analysis. Ann. Nutr. Metab. 2019, 74, 24–34. [Google Scholar] [CrossRef]
- Hou, J.C.; Zheng, H.; Qiang, Z.; Zhang, Y.M.; Jiang, W.T.; Gao, W.; Cai, J.Z.; Zhang, J.J.; Shen, Z.Y. Impact of psoas muscle index on early postoperative mortality and complications after liver transplantation. Zhonghua Wai Ke Za Zhi 2018, 56, 374–378. [Google Scholar] [CrossRef] [PubMed]
- Herrod, P.J.J.; Boyd-Carson, H.; Doleman, B.; Trotter, J.; Schlichtemeier, S.; Sathanapally, G.; Somerville, J.; Williams, J.P.; Lund, J.N. Quick and simple; psoas density measurement is an independent predictor of anastomotic leak and other complications after colorectal resection. Technol. Coloproctol. 2019, 23, 129–134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tevis, S.E.; Kennedy, G.D. Postoperative Complications: Looking Forward to a Safer Future. Clin. Colon Rectal Surg. 2016, 29, 246–252. [Google Scholar] [CrossRef] [Green Version]
- Lo, W.D.; Evans, D.C.; Yoo, T. CT Measured Psoas Density Predicts Outcomes After Enterocutaneous Fistula Repair. JPEN J. Parenter. Enter. Nutr. 2018, 42, 176–185. [Google Scholar] [CrossRef]
- Kitagawa, M.; Haji, S.; Amagai, T. Elevated Serum AA/EPA Ratio as a Predictor of Skeletal Muscle Depletion in Cachexic Patients with Advanced Gastro-intestinal Cancers. In Vivo 2017, 31, 1003–1009. [Google Scholar] [CrossRef] [PubMed]
- Ojima, Y.; Harano, M.; Sumitani, D.; Okajima, M. Impact of Preoperative Skeletal Muscle Mass and Quality on the Survival of Elderly Patients After Curative Resection of Colorectal Cancer. J. Anus Rectum Colon 2019, 3, 143–151. [Google Scholar] [CrossRef] [Green Version]
- Kobayashi, A.; Kaido, T.; Hamaguchi, Y.; Okumura, S.; Shirai, H.; Kamo, N.; Yagi, S.; Taura, K.; Okajima, H.; Uemoto, S. Impact of Visceral Adiposity as Well as Sarcopenic Factors on Outcomes in Patients Undergoing Liver Resection for Colorectal Liver Metastases. World J. Surg. 2018, 42, 1180–1191. [Google Scholar] [CrossRef]
- Lodewick, T.M.; van Nijnatten, T.J.; van Dam, R.M.; van Mierlo, K.; Dello, S.A.W.G.; Neumann, U.P.; Damink, S.W.M.O.; Dejong, C.H.C. Are sarcopenia, obesity and sarcopenic obesity predictive of outcome in patients with colorectal liver metastases? HPB 2015, 17, 438–446. [Google Scholar] [CrossRef] [Green Version]
- Liu, Y.-W.; Lu, C.-C.; Chang, C.-D.; Lee, K.-C.; Chen, H.H.; Yeh, W.S.; Hu, W.-H.; Tsai, K.-L.; Yeh, C.-H.; Wee, S.-Y.; et al. Prognostic value of sarcopenia in patients with colorectal liver metastases undergoing hepatic resection. Sci. Rep. 2020, 10. [Google Scholar] [CrossRef] [Green Version]
- Gislason, M.; Edmunds, K.; Gargiulo, P. Behind an Image: Advanced Quantitative Methods of Clinical Imaging for Sarcopenic Muscle. Biol. Eng. Med. 2018, 3, 4. [Google Scholar] [CrossRef]
- Edmunds, K.J.; Gíslason, M.K.; Arnadottir, I.D.; Marcante, A.; Piccione, F.; Gargiulo, P. Quantitative Computed Tomography and Image Analysis for Advanced Muscle Assessment. Eur. J. Transl. Myol. 2016, 26. [Google Scholar] [CrossRef]
- Edmunds, K.J.; Árnadóttir, Í.; Gíslason, M.K.; Carraro, U.; Gargiulo, P. Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration. Comput. Math. Methods Med. 2016, 2016, e8932950. [Google Scholar] [CrossRef] [Green Version]
- Recenti, M.; Ricciardi, C.; Edmunds, K.; Gislason, M.K.; Sigurdsson, S.; Carraro, U.; Gargiulo, P. Healthy Aging Within an Image: Using Muscle Radiodensitometry and Lifestyle Factors to Predict Diabetes and Hypertension. IEEE J. Biomed. Health Inform. 2020. [Google Scholar] [CrossRef] [PubMed]
- Ricciardi, C.; Jónsson, J.H.; Jacob, D.; Improta, G.; Recenti, M.; Gíslason, M.K.; Cesarelli, G.; Esposito, L.; Minutolo, V.; Bifulco, P.; et al. Improving Prosthetic Selection and Predicting BMD from Biometric Measurements in Patients Receiving Total Hip Arthroplasty. Diagnostics 2020, 10, 815. [Google Scholar] [CrossRef] [PubMed]
Grades | Definition |
---|---|
Grade I: | Any deviation from the normal postoperative course without the need for pharmacological treatment or surgical, endoscopic and radiological interventions. Acceptable therapeutic regimens are: drugs as antiemetics, antipyretics, analgetics, diuretics and electrolytes and physiotherapy. This grade also includes wound infections opened at the bedside |
Grade II | Requiring pharmacological treatment with drugs other than such allowed for grade I complications. Blood transfusions and total parenteral nutrition are also included. |
Grade III | Requiring surgical, endoscopic or radiological intervention |
Grade III-a | intervention not under general anesthesia |
Grade III-b | intervention under general anesthesia |
Grade IV | Life-threatening complication (including Central nervous system (CNS) complications)* requiring IC/ICU-management |
Grade IV-a | single organ dysfunction (including dialysis) |
Grade IV-b | multi organ dysfunction |
Grade V | Death of a patient |
Suffix “d” | If the patient suffers from a complication at the time of discharge, the suffix “d” (for ‘disability’) is added to the respective grade of complication. This label indicates the need for a follow-up to fully evaluate the complication |
Characteristics | N (Number of Cases) | % |
---|---|---|
Cancer localization | ||
Rectal | 29 | 56.9 |
Right colon | 13 | 25.5 |
Sigmoid | 6 | 11.8 |
Left colon | 3 | 5.9 |
Postoperative Complications | N | % |
---|---|---|
Clavien-Dindo Complication Grade | ||
No complication (0) | 30 | 58.8 |
Grade I | 12 | 23.5 |
Grade II | 4 | 7.8 |
Grade III | 2 | 3.9 |
Grade IV | 1 | 2.0 |
Grade V | 2 | 3.9 |
Characteristic | All (n = 51) | Clavien-Dindo Complication Grade | |||
---|---|---|---|---|---|
0 a (n = 30) | 1–2 b (n = 16) | 3–5 c (n = 5) | p | ||
General characteristic | |||||
Age (years) | 65 (56–71) | 62 (55–71) | 64 (59–69) | 70 (69–71) | 0.512 |
Sex, male/female, n (%) | 31 (61)/20 (39) | 24 (80)/6(20) | 5(31)/11(69) | 2(40)/3(60) | 0.003 |
BMI (kg/m2) | 26.3 (23.9–30.1) | 27.6 (24.9–30.4) | 23.7 (22.9–28.2) | 25.6 (25.5–26.9) | 0.074 |
Symptomatology | |||||
Symptom duration (days) | 3 (2–6) | 3 (2–5) | 3.5 (1–6) | 3 (2–3) | 0.517 |
Hemorrhage, n (%) | 23 (45) | 12 (40) | 8 (50) | 3 (60) | 0.637 |
Loss in weight (kg) | 5 (0–10) | 3 (0–35) | 6 (0–20) | 8 (0–30) | 0.941 |
Meteorism, n (%) | 18 (25) | 10 (33) | 5 (31) | 3 (60) | 0.490 |
Diarrhea, n (%) | 21 (41) | 15 (50) | 3 (19) | 3 (60) | 0.069 |
Constipation, n (%) | 16 (31) | 8 (27) | 4 (25) | 4 (80) | 0.059 |
Abdominal pain, n (%) | 23 (45) | 13 (43) | 7 (44) | 3 (60) | 0.780 |
Fatiguability, n (%) | 18 (35) | 8 (27) | 8 (50) | 2 (40) | 0.284 |
Preoperative laboratory | |||||
White blood cells (/μL) | 7560 (6000–8560) | 7000 (5500–8230) | 7845 (6925–8525) | 8030 (6200–8720) | 0.454 |
Hematocrit (%) | 39 (32–42) | 42 (39–45) | 33 (30–38) | 32 (29–40) | 0.002 |
Hemoglobin (g/dL) | 12.6 (9.9–14.0) | 13.5 (12.4–14.4) | 9.9 (9.5–11.5) | 10.8 (9.1–12.5) | 0.001 |
Platelet (x103/μL) | 246 (208–299) | 237 (193–267) | 255 (228–299) | 255 (208–423) | 0.192 |
ALT (U/L) | 14 (10–25) | 14 (10–25) | 15.5 (9–29.5) | 13 (12–17) | 0.915 |
AST (U/L) | 17 (13–29) | 15 (13–24) | 17.5 (12–32.5) | 18 (17–31) | 0.563 |
Total protein (g/L) | 69 (62–73) | 69 (67–73) | 67 (58–72) | 55 (54–76) | 0.318 |
Albumin (g/L) | 40 (37–43) | 41 (39–43) | 37 (35–39) | 33 (32–42) | 0.008 |
Na+ (mEq/L) | 140 (138–142) | 141 (139–143) | 140 (138–142) | 136 (136–138) | 0.019 |
K+ (mEq/L) | 4.3 (4.0–4.6) | 4.4 (4–4.7) | 4.2 (4.1–4.5) | 4.3 (3.9–4.4) | 0.618 |
Creatinine (mg/dL) | 0.77 (0.72–0.89) | 0.78 (0.74–0.86) | 0.73 (0.66–0.84) | 1.07 (0.74–1.31) | 0.105 |
ESR (mm/h) | 37 (16–62) | 30 (8–50) | 46 (28–76) | 24 (14–50) | 0.121 |
CRP (mg/L) | 0.7 (0.3–1.7) | 0.4 (0.2–0.9) | 1.0 (0.6–2.0) | 2.7 (1.3–2.9) | 0.043 |
Radiological measurement | |||||
Right psoas area (cm2) | 10.2 (8.5–11.9) | 11.3 (10.2–12.7) | 7.9 (6.7–8.9) | 8.3 (7.8–11.1) | <0.001 |
Left psoas area (cm2) | 10.3 (8.3–12.6) | 12.3 (11.4–13.2) | 8.3 (6.5–9.4) | 8.5 (7.9–10.1) | <0.001 |
Total psoas area (cm2) | 20.9 (16.7–24.3) | 23.3 (21.1–25.8) | 15.9 (13.6–18.3) | 16.9 (15.6–21.2) | <0.001 |
Psoas muscle index (cm2/m2) | 7.2 (5.9–8.2) | 8.1 (7.3–8.6) | 5.8 (5.1–6.1) | 6.8 (5.9–7.3) | <0.001 |
Mean density (HU) | 36.0 (30.5–40.3) | 36.5 (32.0–40.5) | 34.0 (39.8–41.0) | 32.0 (28.0–37.5) | 0.343 |
Low-Grade | ||
---|---|---|
Predictors | OR(Odds Ratio) (95% CI) | p Value |
General characteristics | ||
Female gender | 8.80 (2.20–35.14) | 0.001 |
Preoperative laboratory markers | ||
Hematocrit | 0.87 (0.79–0.97) | 0.013 |
Hemoglobin | 0.55 (0.38–0.79) | 0.002 |
CRP | 1.35 (0.88–2.06) | 0.159 |
Albumin | 0.75 (0.61–0.92) | 0.006 |
Na+ | 0.91 (0.72–1.15) | 0.459 |
Radiological measurements | ||
Right psoas area | 0.11 (0.02–0.50) | 0.005 |
Left psoas area | 0.18 (0.05–0.61) | 0.006 |
Total psoas area | 0.33 (0.16–0.72) | 0.005 |
Psoas muscle index | 0.05 (0.01–0.31) | 0.002 |
High–Grade | ||
Predictors | OR (95% CI) | pValue |
General characteristics | ||
Female gender | 6.00 (0.81–44.35) | 0.076 |
Preoperative laboratory markers | ||
Hematocrit | 0.90 (0.81–1.01) | 0.080 |
Hemoglobin | 0.64 (0.42–0.98) | 0.041 |
CRP | 1.56 (0.88–2.78) | 0.125 |
Albumin | 0.78 (0.61–0.98) | 0.038 |
Na+ | 0.64 (0.44–0.93) | 0.022 |
Radiological measurements | ||
Right psoas area | 0.41 (0.19–0.88) | 0.022 |
Left psoas area | 0.45 (0.24–0.85) | 0.014 |
Total psoas area | 0.64 (0.44–0.91) | 0.016 |
Psoas muscle index | 0.26 (0.08–0.85) | 0.027 |
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Benedek, Z.; Todor-Boér, S.; Kocsis, L.; Bauer, O.; Suciu, N.; Coroș, M.F. Psoas Muscle Index Defined by Computer Tomography Predicts the Presence of Postoperative Complications in Colorectal Cancer Surgery. Medicina 2021, 57, 472. https://doi.org/10.3390/medicina57050472
Benedek Z, Todor-Boér S, Kocsis L, Bauer O, Suciu N, Coroș MF. Psoas Muscle Index Defined by Computer Tomography Predicts the Presence of Postoperative Complications in Colorectal Cancer Surgery. Medicina. 2021; 57(5):472. https://doi.org/10.3390/medicina57050472
Chicago/Turabian StyleBenedek, Zalán, Szabolcs Todor-Boér, Loránd Kocsis, Orsolya Bauer, Nicolae Suciu, and Marius Florin Coroș. 2021. "Psoas Muscle Index Defined by Computer Tomography Predicts the Presence of Postoperative Complications in Colorectal Cancer Surgery" Medicina 57, no. 5: 472. https://doi.org/10.3390/medicina57050472