This is a transversal observational study of classic cardiovascular risk factors in aged patients with a confirmed diagnosis of hypopituitarism, compared to the retrospective analysis of the same parameters collected in the moment of diagnosis from the electronic registry. Data were gathered, and individuals were recruited from August 2019 to April 2020 at the Neuroendocrinology Unit of the University Hospital of Brasília, considered as a Pituitary Center of Excellence. The data concerning hypopituitary patients were compared to sex and age-matched control group, without a diagnosis of endocrine diseases or acute cardiac dysfunction, some of them recruited from a geriatric cohort from a private clinic and others from the University Hospital of Brasília (HUB).
3.1- Inclusion and Exclusion Criteria
Patients included in the study were aged >70 years, with periodical clinical follow-ups, presenting the following criteria: (i) confirmed diagnosis of hypopituitarism, considering two or multiple hormone deficiencies (MPHD), (ii) patients with thyrotrophic and adrenocorticotrophic deficiencies with adjusted replacement doses of levothyroxine and glucocorticoids. Exclusion criteria were: (i) patients with active functioning pituitary tumors (Cushing's disease, prolactinoma, acromegaly), (ii) chronic use of supraphysiological doses of corticoids or levothyroxine, (iii) use of cabergoline, bromocriptine, or somatostatin analogs during the long term follow up.
A control group was composed of 90 patients > 70 years old, with long term geriatric follow up, without endocrine diseases, hormonal replacement, or antecedents of acute cardiovascular events. The sample was composed of 40 patients 70-74 years, 31 patients 75-80 years, and 19 patients 80-99 years, followed for at least ten years regularly in a cardiologic private clinic. Comorbidities at first evaluation were hypertension in 78.1 %, Diabetes in 35.2 %, hypercholesterolemia in 60.1%, and hypertriglyceridemia in 35.8% of patients. All control subjects included were conventionally treated by anti-hypertensives and hypolipemiant drugs.
3.2- Clinical and Laboratory Evaluation
Clinical evaluation of study participants comprised weight, height, waist, and Blood Pressure (BP) measurements (mean of three independent measurements), at the moment of the last follow up medical evaluation. All patients were submitted to Magnetic Ressonance Imaging (MRI) of the sellar region by diagnosis to determine the etiology of hypopituitarism. Blood samples were drawn in the morning after overnight fast and hormonal evaluation, including GH, prolactin, IGF-1, cortisol, FSH, LH, Testosterone or estradiol, TSH, fT4. Peptides were determined by chemiluminescent immunometric assay (Immulite 2000). A solid-phase enzyme-labeled chemiluminescent immunometric assay was used to measure serum IGF-I with the sample pretreatment on an onbooard dilution step (Immulite 2000). Lipids and glucose serum measurements were determined respectively by hexokinase and IFCC without pyridoxal phosphate and compared to the same parameters by the diagnosis of hypopituitarism.
The criteria for the diagnosis of hypopituitarism were based on Endocrine Society Clinical Practice Guideline 17: adrenal insufficiency was considered when basal cortisol levels< 3 μg/dL, or in Insulin Tolerance Test (ITT), cortisol< 18 μg/dL; GH deficiency when GH peak on ITT< 3 ng/mL or IGF-1 lower than age-matched reference values; prolactin deficiency if lower than reference values; thyrotropic deficiency if fT4< 0.8 ng/dL and low or inappropriate TSH levels.
The treatment of pituitary deficiencies were: Prednisone was administered once daily in the morning, in doses ranging from 2.5-5 mg per day, because formulations of acetate hydrocortisone are not available in our country. Levothyroxin was administered in doses from 1.4-1.6 μg/kg/day. Intramuscular formulations containing testosterone enanthate or cypionate were are administered every 2 to 3 weeks, no women had estrogen therapy. No patient was submitted to GH replacement. Patients were evaluated each four months, and hemogram, glucose, lipid profile, fT4, Testosterone, PSA, hepatic and renal functions, during the follow up time. All patients were treated for comorbidities according to validated guidelines.
3.3- Cardiovascular disease risk estimation
The cardiovascular disease risk was estimated using two widely utilized risk scores using data from the period of diagnosis and the last clinical meeting from each patient, evaluated by the same team from the Unit of Endocrinology from University Hospital of Brasília (HUB).
One of the scores adopted was the 10-year General Cardiovascular Disease (CVD) Risk Prediction Score Using Lipids published by the Framingham Heart Study. 24 The considered parameters were age, Diabetes, smoking, treated and untreated systolic blood pressure, total cholesterol, HDL cholesterol. The 10-year CVD risk is considered is considered low <10%, moderate 10-20% and high> 20%. The score provides a 10-year risk prediction, prediction of the following CVDs: coronary death, myocardial infarction, coronary insufficiency, angina, ischemic stroke, hemorrhagic stroke, transient ischemic attack, peripheral artery disease, and heart failure.
The atherosclerotic cardiovascular disease (ASCVD) was estimated using the calculator provided by the ACC / AHA Guideline on the Assessment of Cardiovascular Risk in 2013 based on the Pooled Cohort Equations (25). The equation estimates a 10-year risk of coronary death or nonfatal myocardial infarction or fatal or nonfatal stroke. 25 Both calculators were derived from cohorts without previous atherosclerotic cardiovascular disease. To adapt and standardize the age range of our population, which goes beyond the age allowed by the scores, we used the age of 79 years (maximum age established by the scores) to calculate the patients' risks. The same scores were calculated for a control group age and sex-matched.
3.4- Statistical analysis
Data were analyzed using the IBM SPSS Statistics version 20.0 software (IBM Corp. released in 2011. IBM SPSS Statistics for Mac, Version 20.0. Armonk, NY: IBM Corp). Categorical variables are summarized as number and percentage, whereas numeric variables are summarized as mean ± standard deviation (SD) and median (min-max) where appropriate. Categorical variables were compared using the Chi-square test. In the comparison of numerical variables between the groups, one-way analysis of variance (ANOVA) was used when assumptions were met, and the Kruskal–Wallis test was used when assumptions were not met. Covariance analysis (ANCOVA) was done to compare the difference between Framinghan Risk Score (FRS) at diagnosis and the last clinical meeting from each patient, taking into account time's follow-up as a covariate. A p-value < 0.05 was considered to be statistically significant.
3.5- Ethics Approval
The study complied with the WMA Declaration of Helsinki and its amended versions of ethical principles for medical research involving human subjects. It was approved by the Ethical Committee on Human Subject Research from the Faculty of Health Sciences, University of Brasilia. All patients signed a proper informed consent before participating in the study.