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There are many factors involved in outlining the patient's profile and in defining which factors can be configured as risks related to the surgical act; for the modern surgeon it is no longer possible to identify the patient at risk of complications based on the mere age or some comorbidities historically considered more influential on the surgical outcome, but each patient must be evaluated in its entirety including age, fragility, comorbidity, state nutritional and sarcopenia and, if necessary, implementing preoperative therapeutic strategies aimed at minimizing the impact of some of these factors on the outcome of surgery.
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.
The data and information collected for each patient will initially be extracted through the setting of filters that are specific for date and type of surgical procedure, on the data management system for surgery of the Arcispedale S.Anna (Ormaweb). Subsequently, for patients who meet the inclusion criteria, the data collection will be implemented by evaluating discharge letters, radiological and pathological reports relating to the analysis of the surgical specimen, contained in the management program of the data (SAP network) of the Arcispedale S.Anna di Cona and, if necessary, the digitized archive of the medical records of the Archispedale S.Anna will be queried to analyze the medical records relating to the hospitalization during which the patient underwent surgery. The radiological examinations of the patients, in particular the Computed Tomography of the abdomen, will be further analyzed using specific software for the analysis of the density and muscle conformation of the psoas muscles in order to evaluate the state of sarcopenia and extrapolate the indices related to psoas muscle density, psoas index, and total psoas area.
The following data about each patient will be collected:
The scales used to evaluate the malnutrition scores, comorbidity and frailty scores and the sarcopenia indices are the following:
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.
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| Measure | Description | Time Frame |
|---|---|---|
| short-term mortality rates within 30 days from surgery | short-term (30 days after surgery) mortality rate in patients undergoing resective colorectal surgery | Within 30 days from surgery |
| correlation between the development of a postoperative complication within 30 days from surgery and patient-related characteristics (comorbidity, frailty, malnutrition and sarcopenia) | presence of a proportional correlation between the development of postoperative complications and its the extent within 30 days from surgery assessed according to the Clavien Dindo scale (mild complications 1-2; severe complications 3-4-5) and patient-related factors that may have influenced the occurrence of postoperative complications. For assessing the pre-existing comorbidities we used the Charlson Comorbidity Index (CCI), the level of frailty will be assessed by the 11-items Frailty Index, malnutrition is assessed by two scores (M.U.S.T. and NRS-2002) allowing a stratification of the patient's risk of malnutrition. In addition, the level of preoperative sarcopenia present on computed tomography will also be assessed using specific software to calculate the average density of the psoas muscles, Psoas Index (PI) and Total Psoas Area (TPA). | Preoperative assessment of pre-existing comorbidities, the frailty, malnutrition and sarcopenia status and within 30 days from surgery for Clavien Dindo complication score |
| Measure | Description | Time Frame |
|---|---|---|
| Assessing comorbidity status in patients undergoing colon laparoscopic surgery | To calculate the indices of comorbidity using the CCI (Charlson Comorbidity Index) which reports an overall score between 1 and 37 according to the extent of comorbidities (cardiorespiratory history, renal or hepatic pathologies, spread of tumor disease, lympho-myeloproliferative pathologies and age) and how these impact on the estimated 10-year survival (clearly the greater the patient's comorbidities the lower the estimated 10-year survival rate). |
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Inclusion Criteria:
Exclusion Criteria:
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All patients over 18 y.o undergoing elective laparoscopic colo-rectal surgery.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Istituto di chirurgia generale 1 | Ferrara | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29951615 | Background | 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. | |
| 10534692 | Background | 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. |
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| Type | Date | Date Unknown |
|---|---|---|
| Release | Dec 3, 2021 | |
| Reset | Feb 18, 2022 |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Dec 3, 2021 | Feb 18, 2022 |
| ID | Term |
|---|---|
| D003110 | Colonic Neoplasms |
| D044342 | Malnutrition |
| D055948 | Sarcopenia |
| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
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| Prior to surgery |
| Assessing the malnutrition status in patients undergoing colon laparoscopic surgery | To calculate malnutrition status using the Malnutrition Universal Screening Tool or M.U.S.T. (score between 0 and 6) and Nutritional Risk Screening or NRS-2002 (score between 0 and 7) considering BMI, percentage of weight loss and probability of caloric intake reduction, severity of the disease and age, thus obtaining a stratification of the patient's risk of malnutrition in low risk, medium risk and high risk resulting in different strategies for preventing and cure the malnutrition status. | Prior to surgery |
| Assessing the sarcopenia status in patients undergoing colon laparoscopic surgery | To calculate the indices of sarcopenia by extrapolating from CT-scan images the data relating to bilateral mean density of psoas muscles in HU and the Hounsfield Unit Average Calculation (HUAC) which is adapted for the area of the psoas muscles at L4 level. We calculate also the Psoas Index (PI) using the following formula: "right psoas area in cm2+ left psoas area in cm2)/height in m2" and the Total Psoas Area(TPA) calculate as: "right psoas area+left psoas area)/BSA (=body surface area with Mosteller formula). We assume that a higher level of sarcopenia may be related to a worse surgical outcome for the patient. | Prior to surgery |
| Assessing the frailty index in patients undergoing colon laparoscopic surgery | To calculate the index of fragility using the 11-items FI (Frailty Index) considered as a summary of medical history (cardiorespiratory, neurological, insulin resistance, vascular) and performance status resulting in an increasing score according to the extent of patient frailty ranging from 1 to 11 (the maximum ranking is related with worse outcome for the patients) | Prior to surgery |
| relatedness between the average density sarcopenia indices, HUAC, PI, TPA and the distance between the anterior-superior iliac spines and the size of the psoas muscles (RPSI) | to evaluate the link between the average density sarcopenia indices already mentioned above such as HUAC, PI, TPA and the distance between the anterior-superior iliac spines and the size of the psoas muscles (RPSI) | prior to surgery |
| 9243270 | Background | 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. |
| 7706616 | Background | 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. |
| 26286199 | Background | 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. |
| 17683831 | Background | 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. |
| 28386715 | Background | 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. |
| 26375617 | Background | 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. |
| 22934016 | Background | 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. |
| 30790102 | Background | 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. |
| 28551380 | Background | 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. |
| 20510798 | Background | 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. |
| 27580947 | Background | 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. |
| 25355618 | Background | 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. |
| 18826625 | Background | Searle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr. 2008 Sep 30;8:24. doi: 10.1186/1471-2318-8-24. |
| 22695416 | Background | 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. |
| 21576611 | Background | 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. |
| 17681780 | Background | Janssen-Heijnen ML, Maas HA, Houterman S, Lemmens VE, Rutten HJ, Coebergh JW. Comorbidity in older surgical cancer patients: influence on patient care and outcome. Eur J Cancer. 2007 Oct;43(15):2179-93. doi: 10.1016/j.ejca.2007.06.008. Epub 2007 Aug 2. |
| 17198496 | Background | Gross CP, Guo Z, McAvay GJ, Allore HG, Young M, Tinetti ME. Multimorbidity and survival in older persons with colorectal cancer. J Am Geriatr Soc. 2006 Dec;54(12):1898-904. doi: 10.1111/j.1532-5415.2006.00973.x. |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D009133 | Muscular Atrophy |
| D020879 | Neuromuscular Manifestations |
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D001284 | Atrophy |
| D020763 | Pathological Conditions, Anatomical |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D012816 | Signs and Symptoms |