Status
Conditions
About
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.
Full description
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.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Loading...
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal