The Patient in Laparoscopic Colon Surgery:Impact of Comorbidities,Frailty,Malnutrition and Sarcopenia on Short-term Mortality
NCT ID: NCT04729738
Last Updated: 2021-01-28
Study Results
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Basic Information
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COMPLETED
420 participants
OBSERVATIONAL
2012-06-01
2020-12-01
Brief Summary
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Our study aimed at creating, if possible, an "identikit" of the patient who is more likely to have serious postoperative complications; in order to improve the therapeutic decision and the approach to patients with severe surgical risk since choosing the right treatment for the right patient is essential to obtain a good result.
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Detailed Description
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The following data about each patient will be collected:
* demographic variables as age at the time of surgery, sex, weight, height and BMI, weight loss in the 3-6 months prior to surgery, performance status, ASA score (American Society of Anesthesiologists score) also malnutrition scores according to MUST indexes (Malnutrition Universal Screening Tool) and NRS 2002 (Nutrition Risk Screening 2002) will be taken into account.
* Pre-existing or intercurrent comorbidities aimed at formulating the comorbidity score according to the Charlson Comorbidity Index; and frailty according to the 11 items of the Frailty Index (arterial hypertension, vascular disease, heart disease, vascular encephalopathy or previous transient ischemic attack, diabetes mellitus, inflammatory bowel disease, chronic pulmonary obstructive disease , renal or hepatic insufficiency, neurological or haematological diseases).
* Radiological characteristics of the patient (distance between the anterior-superior iliac spines, density, size and area of the psoas muscles considered at L4 vertebra level) for the constitution of indices of sarcopenia (Bilateral average density of the psoas muscles in HU, Hounsfield Unit Average Calculation , Total psoas area and Psoas Index).
* Characteristics of the surgery (date of surgery, duration in minutes, type of surgery, peri-surgical antibiotic prophylaxis, incision time, any intraoperative complications reported in the official operative document).
* Characteristics of the postoperative hospital stay (duration, complication according to the Clavien-Dindo scale and its possible treatment, date of death or follow-up and time elapsed since surgery).
* Definitive histological examination including macroscopic and microscopic description of the specimen, classification according to TNM score (Tumour, Node, Metastasis), number of lymph nodes removed).
The scales used to evaluate the malnutrition scores, comorbidity and frailty scores and the sarcopenia indices are the following:
* CCI (Charlson Comorbidity Index): score used for the assessment of comorbidities
* 11-items FI (Frailty Index): score used for the assessment of frailty
* M.U.S.T. (Malnutrition Universal Screening Tool) and NRS-2002 (Nutritional Risk Screening): scores used to define the state of malnutrition
* Scores used to define the state of sarcopenia with the aid of the PACS Carestream program.
Average density of psoas muscles = \[right psoas muscle density (HU) + left psoas muscle density (HU)\] / 2 HUAC (Hounsfield Unit Average Calculation) = \[(right psoas area \* density) + (left psoas area \* density)\] / total psoas area PI (Psoas Index) = (right psoas area in cm2 + left psoas area in cm2) / height in m2 TPA (Total Psoas Area) = (right psoas area + left psoas area) / BSA (body surface area) BSA (m2) calculated using Mosteller's formula = (height (cm) x weight (kg) / 3600) ½ RPSI (ratio of psoas and iliac spines) = ratio between the distance between the anterior-superior iliac spines in the transverse CT projection in cm and the sum of the lengths of the psoas in cm calculated at the level of the same transverse projection.
The data will be collected in a special electronic database respecting the privacy of the subjects involved; each patient will be identified by means of a unique identification code whose decryption is known only to the team involved in the study. Patient data and consent to the study will be stored in the medical office of the Surgery Unit and accessible only to health personnel involved in the study.
The person responsible for storing the collected data is identified in the figure of the promoter of the study, Professor Gabriele Anania, Medical Director of the Surgery Unit.
To improve the accuracy of data entry, standard automated control processes will be implemented (verifying that the data is in the correct format or within an expected range of values and consistency checks).
The Shapiro-Wilk test will be used to verify the distributive normality of continuous variables. In the presence of symmetry of the distributions, the variables will be represented with mean and standard deviation (sd) or, in the case of non-symmetric distribution, with the median value and the interquantile range \[1Q-3Q\]; categorical data will be expressed with absolute and percentage values.
For the analysis of short-term mortality, the Kaplan Meier estimator will be used to identify the survival curves and a Cox regression model will be estimated to identify predictive factors and evaluate the impact of comorbidities, frailty, state of malnutrition and sarcopenia.
All analyzes will be performed using Stata 15.1 SE (Stata Corporation, College Station, Texas, USA). The value \<0.05 was defined as statistically significant.
In conclusion, the study will be performed in compliance with the protocol and international guidelines (Good Clinical Practice) and in compliance with the regulations in force on clinical trials. Each Investigator is therefore responsible for conducting the study in accordance with these guidelines.
The current version of the Declaration of Helsinki (2013) is a reference for the ethical aspects of this clinical trial and will be respected by all those engaged in this research.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* colorectal surgery with laparoscopic technique according to the following surgical procedures: right hemicolectomy, left hemicolectomy, segmental resection of the transverse colon, sigmoidectomy.
* elective surgery
Exclusion Criteria
* emergency surgery
* surgical equipe different from the one operating in the U.O Chirurgia 1 at Sant'Anna University Hospital in Ferrara
18 Years
ALL
No
Sponsors
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University Hospital of Ferrara
OTHER
Responsible Party
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Gabriele Anania
Associate Professor
Locations
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Istituto di chirurgia generale 1
Ferrara, , Italy
Countries
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References
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Sandini M, Pinotti E, Persico I, Picone D, Bellelli G, Gianotti L. Systematic review and meta-analysis of frailty as a predictor of morbidity and mortality after major abdominal surgery. BJS Open. 2017 Nov 9;1(5):128-137. doi: 10.1002/bjs5.22. eCollection 2017 Oct.
Engelman DT, Adams DH, Byrne JG, Aranki SF, Collins JJ Jr, Couper GS, Allred EN, Cohn LH, Rizzo RJ. Impact of body mass index and albumin on morbidity and mortality after cardiac surgery. J Thorac Cardiovasc Surg. 1999 Nov;118(5):866-73. doi: 10.1016/s0022-5223(99)70056-5.
van Bokhorst-de van der Schueren MA, van Leeuwen PA, Sauerwein HP, Kuik DJ, Snow GB, Quak JJ. Assessment of malnutrition parameters in head and neck cancer and their relation to postoperative complications. Head Neck. 1997 Aug;19(5):419-25. doi: 10.1002/(sici)1097-0347(199708)19:53.0.co;2-2.
Dannhauser A, Van Zyl JM, Nel CJ. Preoperative nutritional status and prognostic nutritional index in patients with benign disease undergoing abdominal operations--Part I. J Am Coll Nutr. 1995 Feb;14(1):80-90. doi: 10.1080/07315724.1995.10718477.
Fukuda Y, Yamamoto K, Hirao M, Nishikawa K, Maeda S, Haraguchi N, Miyake M, Hama N, Miyamoto A, Ikeda M, Nakamori S, Sekimoto M, Fujitani K, Tsujinaka T. Prevalence of Malnutrition Among Gastric Cancer Patients Undergoing Gastrectomy and Optimal Preoperative Nutritional Support for Preventing Surgical Site Infections. Ann Surg Oncol. 2015 Dec;22 Suppl 3:S778-85. doi: 10.1245/s10434-015-4820-9. Epub 2015 Aug 19.
Bozzetti F, Gianotti L, Braga M, Di Carlo V, Mariani L. Postoperative complications in gastrointestinal cancer patients: the joint role of the nutritional status and the nutritional support. Clin Nutr. 2007 Dec;26(6):698-709. doi: 10.1016/j.clnu.2007.06.009. Epub 2007 Aug 1.
Jones K, Gordon-Weeks A, Coleman C, Silva M. Radiologically Determined Sarcopenia Predicts Morbidity and Mortality Following Abdominal Surgery: A Systematic Review and Meta-Analysis. World J Surg. 2017 Sep;41(9):2266-2279. doi: 10.1007/s00268-017-3999-2.
Levolger S, van Vugt JL, de Bruin RW, IJzermans JN. Systematic review of sarcopenia in patients operated on for gastrointestinal and hepatopancreatobiliary malignancies. Br J Surg. 2015 Nov;102(12):1448-58. doi: 10.1002/bjs.9893. Epub 2015 Sep 16.
Mitchell WK, Williams J, Atherton P, Larvin M, Lund J, Narici M. Sarcopenia, dynapenia, and the impact of advancing age on human skeletal muscle size and strength; a quantitative review. Front Physiol. 2012 Jul 11;3:260. doi: 10.3389/fphys.2012.00260. eCollection 2012.
Herrod PJJ, Boyd-Carson H, Doleman B, Trotter J, Schlichtemeier S, Sathanapally G, Somerville J, Williams JP, Lund JN. Quick and simple; psoas density measurement is an independent predictor of anastomotic leak and other complications after colorectal resection. Tech Coloproctol. 2019 Feb;23(2):129-134. doi: 10.1007/s10151-019-1928-0. Epub 2019 Feb 21.
Yoo T, Lo WD, Evans DC. Computed tomography measured psoas density predicts outcomes in trauma. Surgery. 2017 Aug;162(2):377-384. doi: 10.1016/j.surg.2017.03.014. Epub 2017 May 24.
Makary MA, Segev DL, Pronovost PJ, Syin D, Bandeen-Roche K, Patel P, Takenaga R, Devgan L, Holzmueller CG, Tian J, Fried LP. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg. 2010 Jun;210(6):901-8. doi: 10.1016/j.jamcollsurg.2010.01.028. Epub 2010 Apr 28.
Lin HS, Watts JN, Peel NM, Hubbard RE. Frailty and post-operative outcomes in older surgical patients: a systematic review. BMC Geriatr. 2016 Aug 31;16(1):157. doi: 10.1186/s12877-016-0329-8.
Clegg A, Rogers L, Young J. Diagnostic test accuracy of simple instruments for identifying frailty in community-dwelling older people: a systematic review. Age Ageing. 2015 Jan;44(1):148-52. doi: 10.1093/ageing/afu157. Epub 2014 Oct 29.
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Farhat JS, Velanovich V, Falvo AJ, Horst HM, Swartz A, Patton JH Jr, Rubinfeld IS. Are the frail destined to fail? Frailty index as predictor of surgical morbidity and mortality in the elderly. J Trauma Acute Care Surg. 2012 Jun;72(6):1526-30; discussion 1530-1. doi: 10.1097/TA.0b013e3182542fab.
Cone MM, Herzig DO, Diggs BS, Dolan JP, Rea JD, Deveney KE, Lu KC. Dramatic decreases in mortality from laparoscopic colon resections based on data from the Nationwide Inpatient Sample. Arch Surg. 2011 May;146(5):594-9. doi: 10.1001/archsurg.2011.79.
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Other Identifiers
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Lap30d
Identifier Type: -
Identifier Source: org_study_id
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