Association of Emotional Self-Regulation with Psychological Distress and Positive Functioning Dimensions in Brazilian University Students during the COVID-19 Pandemic.

Emotional self-regulation is a relevant factor for human development capable of minimizing emotional difficulties in the face of adverse events, as was particularly useful during the COVID-19 pandemic. The present study aimed to evaluate emotional self-regulation in Brazilian health science university students and its relationship with positive psychology constructs (subjective well-being, hope, optimism, spirituality, self-compassion, and self-efficacy) and psychological distress (depression, anxiety, and stress). This was a prospective, cross-sectional, observational, analytic study of 1062 Brazilian undergraduate students with data collected using self-administered online questionnaires. Students in the first years of their undergraduate degree programs had significantly higher dysregulation scores than those in the final years. Multiple linear regression yielded a model that explained 71.8% of the variation in emotion dysregulation. The correlations of emotion dysregulation were significant and strong, scoring negatively with self-compassion, optimism, and subjective well-being and positively with psychological distress.

Machine Learning-based Prediction Model for Treatment of Acromegaly With First-generation Somatostatin Receptor Ligands.

CONTEXT: Artificial intelligence (AI), in particular machine learning (ML), may be used to deeply analyze biomarkers of response to first-generation somatostatin receptor ligands (fg-SRLs) in the treatment of acromegaly. OBJECTIVE: To develop a prediction model of therapeutic response of acromegaly to fg-SRL. METHODS: Patients with acromegaly not cured by primary surgical treatment and who had adjuvant therapy with fg-SRL for at least 6 months after surgery were included. Patients were considered controlled if they presented growth hormone (GH) <1.0 ng/mL and normal age-adjusted insulin-like growth factor (IGF)-I levels. Six AI models were evaluated: logistic regression, k-nearest neighbor classifier, support vector machine, gradient-boosted classifier, random forest, and multilayer perceptron. The features included in the analysis were age at diagnosis, sex, GH, and IGF-I levels at diagnosis and at pretreatment, somatostatin receptor subtype 2 and 5 (SST2 and SST5) protein expression and cytokeratin granulation pattern (GP). RESULTS: A total of 153 patients were analyzed. Controlled patients were older (P = .002), had lower GH at diagnosis (P = .01), had lower pretreatment GH and IGF-I (P < .001), and more frequently harbored tumors that were densely granulated (P = .014) or highly expressed SST2 (P < .001). The model that performed best was the support vector machine with the features SST2, SST5, GP, sex, age, and pretreatment GH and IGF-I levels. It had an accuracy of 86.3%, positive predictive value of 83.3% and negative predictive value of 87.5%. CONCLUSION: We developed a ML-based prediction model with high accuracy that has the potential to improve medical management of acromegaly, optimize biochemical control, decrease long-term morbidities and mortality, and reduce health services costs.

Lipid profile and response to statin therapy in patients with hypopituitarism.

OBJECTIVE: Dyslipidemia is prevalent among patients with hypopituitarism, especially in those with growth hormone (GH) deficiency. This study aimed to evaluate the response to statin therapy among adult patients with dyslipidemia and hypopituitarism. METHODS: A total of 113 patients with hypopituitarism following up at a neuroendocrinology unit were evaluated for serum lipid levels. Dyslipidemia was diagnosed in 72 (63.7%) of these patients. A control group included 57 patients with dyslipidemia and normal pituitary function. The distribution of gender, age, weight, and dyslipidemia type was well balanced across both groups, and all participants were treated with simvastatin at doses adjusted to obtain normal lipid levels. RESULTS: Patients with hypopituitarism and dyslipidemia presented deficiency of TSH (69%), gonadotropins (69%), ACTH (64%), and GH (55%) and had a similar number of deficient pituitary axes compared with patients with hypopituitarism but without dyslipidemia. All patients with dyslipidemia (with and without hypopituitarism) had lipid levels well controlled with doses of simvastatin ranging from 20-40 mg/day. The mean daily dose of simvastatin was not significantly different between patients with and without hypopituitarism (26.7 versus 23.5 mg, p = 0.10). Similarly, no significant variation in simvastatin dose was observed between patients with different causes of hypopituitarism, presence or absence of GH deficiency, number of deficient pituitary axes, prior pituitary radiation therapy or not, and presence or absence of obesity. CONCLUSION: Patients with GH deficiency without GH replacement showed good response to simvastatin at a mean dose equivalent to that used in individuals with dyslipidemia and normal pituitary function.

Lipid profile and response to statin therapy in patients with hypopituitarism

ABSTRACT Objective: Dyslipidemia is prevalent among patients with hypopituitarism, especially in those with growth hormone (GH) deficiency. This study aimed to evaluate the response to statin therapy among adult patients with dyslipidemia and hypopituitarism. Subjects and methods: A total of 113 patients with hypopituitarism following up at a neuroendocrinology unit were evaluated for serum lipid levels. Dyslipidemia was diagnosed in 72 (63.7%) of these patients. A control group included 57 patients with dyslipidemia and normal pituitary function. The distribution of gender, age, weight, and dyslipidemia type was well balanced across both groups, and all participants were treated with simvastatin at doses adjusted to obtain normal lipid levels. Results: Patients with hypopituitarism and dyslipidemia presented deficiency of TSH (69%), gonadotropins (69%), ACTH (64%), and GH (55%) and had a similar number of deficient pituitary axes compared with patients with hypopituitarism but without dyslipidemia. All patients with dyslipidemia (with and without hypopituitarism) had lipid levels well controlled with doses of simvastatin ranging from 20-40 mg/day. The mean daily dose of simvastatin was not significantly different between patients with and without hypopituitarism (26.7 versus 23.5 mg, p = 0.10). Similarly, no significant variation in simvastatin dose was observed between patients with different causes of hypopituitarism, presence or absence of GH deficiency, number of deficient pituitary axes, prior pituitary radiation therapy or not, and presence or absence of obesity. Conclusions: Patients with GH deficiency without GH replacement showed good response to simvastatin at a mean dose equivalent to that used in individuals with dyslipidemia and normal pituitary function.

The acromegalic spine: fractures, deformities and spinopelvic balance.

INTRODUCTION: Axial skeleton arthropathy and osteoporotic vertebral fractures are common findings in acromegalic patients and can result in severe spinal deformity. OBJECTIVE: To investigate the presence of spinal fractures and deformities, sagittal imbalances, and spinopelvic compensatory mechanisms in acromegalics. PATIENTS AND METHODS: 58 patients with acromegaly from a referral neuroendocrinology center were prospectively evaluated by panoramic spine radiographs to detect the presence of fractures and scoliosis, to measure thoracic kyphosis, lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT) and sagittal vertical axis (SVA). Sagittal imbalance criteria were considered: thoracic kyphosis > 50°, PI-LL > 10°, PT > 20° and SVA > 5 cm. Their medical records were analyzed for clinical and laboratorial data. RESULTS: The prevalence of fractures was 13.8%, predominantly in the thoracic spine, with mild and anterior wedge compressions. Scoliosis was present in 34.5% of the cases, all with degenerative lumbar curve apex. Thoracic kyphosis > 50º occurred in 36.8% of patients, PI-LL > 10° in 48.3%, PT > 20° in 41.4% and SVA > 5 cm in 12.1%. CONCLUSION: Increased number of vertebral fractures and high prevalence of spinal deformities related to sagittal imbalance were detected, indicating the importance of monitoring bone comorbidities in acromegaly, with radiological evaluation of the spine as part of the follow up.

Evaluation of the potential of the Ki67 index to predict tumor evolution in patients with pituitary adenoma.

The aggressive course of a number of pituitary adenomas requires the investigation of potential predictors. This study aimed to investigate the proliferation marker Ki67 as a predictor of postoperative outcome in patients with pituitary adenoma regarding recurrence and regrowth of the tumor, using a Ki67 cut-off value of 3%. This retrospective study included 52 patients with pituitary adenoma who had undergone adenomectomy and had a pituitary image taken at least 1 year after surgery. Patients were divided according to Ki67 expression into high (≥3%) vs. low (<3%) levels of Ki67. The two groups were similar regarding the preoperative tumor invasion grade. The Ki67 index ranged from 0 to 30%; in 23 cases, Ki67 was ≥3%. The two groups were similar regarding tumor recurrence and regrowth: 4 cases (28%) of recurrence in the Ki67<3% group vs. none in the Ki67≥3% group (P=0.26); and 2 cases (13%) of regrowth in the Ki67<3% group vs. 7 cases (43%) in the Ki67≥3% group (P=0.11). A subgroup analysis was performed for nonfunctioning adenomas. Recurrence rates remained similar between groups (Ki67<3% group: 1 case [20%]; Ki67≥3% group: none; P>0.99), whereas regrowth rates were higher in the Ki67≥3% group (6 cases [67%] vs. 2 cases [17%] in the Ki67<3% group; P=0.03). The patient with the highest Ki67 index (30%) developed pituitary carcinoma. The results allow us to suggest the adoption of a stricter control of image monitoring in nonfunctioning adenomas with incomplete resection associated with a Ki67 index ≥3%.