Seasonal Trends of Respiratory Morbidity in Diabetic Patients

Overview

Type 2 diabetes mellitus (T2DM) poses a significant burden on the patients and the health care system. The increasing number of surgery performed in elderly population results in an increased number of perioperative T2DM-related adverse effects. T2DM has a prevalence of 30-40% in a population undergoing cardiovascular surgery. Cardiac surgery, especially cardiopulmonary bypass (CPB) is also known to deteriorate respiratory mechanics. Therefore, the study is aimed at a retrospective analysis of seasonal trends in respiratory consequences of T2DM, i.e.: i: distribution of patients with and without T2DM presenting for elective cardiac surgery during the two-year examination period; ii: characterization of respiratory co-morbidities in the patients, iii: exploring whether the respiratory mechanics at presentation and those caused by cardiac surgery exhibit different trends in T2DM and control patients.

Our study is a retrospective analysis of patient records from all patients undergoing elective cardiac surgery between January 2007 to December 2018 at the Second Department of Internal Medicine and Cardiology Centre Cardiac Surgical Unit, University of Szeged. Electronic and paper documentation will be examined and anonymously analysed for the following information: 1. date of cardiac surgery, 2. type of cardiac surgery procedure, 3. demographic data (age, height, weight), 4. presence of T2DM (previous diagnosis, fasting plasma glucose level, glycated haemoglobin \[HbA1C\]), 5. presence of respiratory co-morbidities (e.g. asthma, COPD, etc.), 6. presence of other circulatory co-mobidities (e.g. hypertension, previous stroke, vascular stenosis) 6\. respiratory mechanical parameters before and after cardiac surgery, 7. presence of perioperative respiratory complications, 8. history of smoking 9. blood gas measurements before, during and after surgery Time series statistical analysis of all data will be carried out to discover the presence of seasonal trends in both diabetic and control patients. Analysis of variance (ANOVA) will be carried out to explore global differences between diabetic and control patients.

Conditions