Non-communicable diseases (NCDs) have become the leading cause of mortality globally, with a sharp rise in Iran due to lifestyle changes and urbanisation. Although many NCD risk factors are modifiable, limited understanding of their determinants hinders effective prevention. To address this, the Prospective Epidemiological Research Studies in Iran (PERSIAN) Cohort was established in 2014 to study NCDs nationwide. The Sabzevar PERSIAN Cohort Study (SPECS) is the first in northeastern Iran, aiming to investigate environmental and social factors influencing NCDs in a unique regional context.

SPECS enrolled 5174 adults (aged 35–70 years) in northeastern Iran between January 2018 and January 2019 through a census and an online registration process. The baseline data collection included demographic verification, informed consent, health questionnaires, anthropometric measurements and biological samples (blood, urine, hair, nails). The annual follow-up began in April 2019, with full reassessments every 5 years over a 15-year period. The data is gathered via an active and passive follow-up, supported by trained staff and registry linkages.

Of the 5174 participants, 4241 (81%) remained in the study. Among the cohort, 54.5% were female, with a mean age of 50.5 years. The majority were married (93.5%), and nearly half had at least high-school education (46.5%) and moderate socioeconomic status (49.4%). Drug abuse history (smoking/drugs) was reported by about 15% of the sample. The mean body mass index was 26.9 kg/m², and the average blood pressure was higher in males (118.1/74.0 mm Hg) than in females (111.5/70.2 mm Hg). The common conditions included hypertension (22.8%), kidney stones (22.4%), fatty liver (15.4%) and diabetes (13.8%). Cancer had the highest treatment rate (100%), while fatty liver had the lowest (70.1%). Stroke had the highest mean age of onset (51.2 years), and epilepsy the lowest (23.7 years). All health data were self-reported.

SPECS, part of the national PERSIAN cohort initiative, is the only adult NCD-focused study in Khorasan Razavi. Its 15-year follow-up aims to generate region-specific insights into the incidence of NCDs and their risk factors. The ethnically homogeneous sample enhances statistical power, and the findings may inform culturally tailored health policies. While self-reported data have limitations due to bias, high initial participation and access to free healthcare support long-term engagement, especially among lower-income groups.

Systemic sclerosis (SSc) is an autoimmune disorder causing progressive fibrosis of internal organs and skin, leading to increased thickness and rigidity. It frequently results in malnutrition, which can decrease survival rates and physical performance, while also imposing financial burdens on healthcare systems and society. Multimodal nutritional interventions may encompass various approaches, including nutritional counselling, consumption of oral nutritional supplements and disease-specific dietary regimens based on nutritional needs. The present clinical trial is designed to examine the effectiveness of multimodal nutritional intervention on nutritional status, quality of life, food intake, body composition and fatigue in patients with SSc.

This is a parallel, randomised, placebo-controlled clinical trial that will investigate the impacts of multimodal nutritional interventions in SSc patients. 46 qualified SSc participants will be chosen at random and given multimodal nutritional intervention or dietary recommendations for a period of 8 weeks. The primary outcomes of this study are changes in nutritional status and quality of life. The secondary outcomes include changes in body composition, fatigue, body weight, body mass index and calf circumference. Statistical analysis will be conducted using the SPSS software (Version 24).

The current trial received approval from the Medical Ethics Committee of Tehran University of Medical Sciences, Tehran, Iran (IR.TUMS.MEDICINE.REC.1403.345). The findings will be submitted to international, peer-reviewed publications and presented at national and international conferences.

IRCT20220208053971N4.

To enhance the quality of surgical care, complications need to be minimised. Consequently, comprehending the occurrence and risk elements for postoperative complications is essential. Subsequently, we will apply machine learning (ML) algorithms to build risk factor prediction models that will assist surgeons in identifying the risk factors associated with the development of postoperative complications after general surgery.

This research will take place at a tertiary referral medical centre located in Bandar Abbas, Hormozgan, Iran. The inclusion criteria are (1) individuals aged 18 years or older who have any type of general surgery and (2) hospitalised from September 2025 to September 2026. Individuals with insufficient data will be excluded. The main outcomes of the study are complications within 30 days of surgery. Patients will be divided into two groups based on whether they develop complications or not. The predictors are classified as (1) patient-related factors, (2) surgery-related factors and (3) postoperative factors. We intend to detect postoperative complications following general surgery using four distinct supervised ML techniques: (1) logistic regression, (2) decision trees, (3) random forests and (4) extreme gradient boosting. Accuracy, precision, recall and F1 score will be used to evaluate the performance of ML models.

With approval from the Hormozgan University of Medical School Research Ethics Board (IR.HUMS.REC.1404.137), we will carry out a forward-looking analysis of the medical records of patients undergoing general surgery. We will obtain informed consent, and all information will be collected and examined anonymously. The findings of this research will be released in appropriate scientific publications.

Prolonged QTc is a major risk factor for ventricular arrhythmias and sudden cardiac death (SCD). Anaemia’s impact on the QT interval is unclear and conflicting despite its association with increased mortality.

We investigated the association between anaemia and the prevalence of QTc prolongation, as well as potential gender differences in this relationship. Additionally, we examined whether haemoglobin levels were associated with QTc prolongation.

Observational cross-sectional study.

Sheshdeh, Fasa, Iran.

We analysed data from 5741 participants from the general population (aged 35–70 years) with no history of ischaemic heart disease; myocardial infarction; amiodarone use; multiple blood transfusions; or supplementation with iron, folic acid or cobalamin.

Anaemia was defined according to WHO guidelines (haemoglobin 450 ms in men or >470 ms in women.

Among 5741 participants, mean QTc was 427.91±24.75 ms, with QTc prolongation in 7.14%. Anaemia raised the odds of QTc prolongation by 60% (OR=1.60, 95%CI 1.12 to 2.28, p=0.010), particularly in females (OR=1.73, 95%CI 1.12 to 2.66, p=0.013), but not in males. Higher haemoglobin levels were associated with lower QTc prolongation risk (OR=0.91 per unit increase, 95% CI 0.85 to 0.97, p=0.005). No significant associations were observed between anaemia type/severity and QTc prolongation among anaemic individuals.

Anaemia was significantly associated with QTc prolongation, particularly in females. Anaemia type/severity did not affect QTc prolongation. Anaemia is associated with increased odds of QTc prolongation, particularly in women. While causality cannot be inferred from this cross-sectional analysis, the findings suggest that clinicians may consider QTc monitoring in anaemic patients, especially women and exercise caution when prescribing QT-prolonging medications. Prospective studies are needed to confirm whether anaemia directly contributes to QTc prolongation or arrhythmic risk.

Osteoporosis is a skeletal condition with decreased bone mass and structural deterioration, increasing fracture vulnerability. Several studies have found a correlation between prostate cancer in men and an increased risk of osteoporosis. This study aims to determine the prevalence of osteoporosis in patients with prostate cancer.

The primary objective of this study will be to estimate the prevalence of osteoporosis in prostate cancer survivor patients. An extensive search will be conducted on PubMed, Scopus, Embase, Web of Science, CINAHL and ProQuest databases to ensure comprehensive coverage. The search will encompass the timeframe from 1 January 1994 to 24 September 2024. Furthermore, we will not impose any limitations on the language or geographical location of the published studies. In order to assess the potential bias in the included studies, the Joanna Briggs Institute critical appraisal checklist for prevalence studies will be employed. The analysis of data will be performed using STATA V.17. The prevalence of osteoporosis or osteopenia will be calculated for each study by dividing the number of participants with these conditions by the total number of patients diagnosed with prostate cancer. A subgroup analysis will examine prevalence regarding geographical location, age groups, ethnicity, definitions and measurements of osteoporosis or osteopenia, risk of bias in the included studies, type and duration of androgen deprivation therapy, and site of osteoporosis diagnosis. We will employ multiple methods to detect publication bias, including funnel plot analysis, Begg’s and Egger’s tests, and the Trim and Fill method. If we have enough data, we will conduct a sensitivity analysis using the leave-one-out-remove method.

No ethical approval or patient consent is required as this study synthesises only published aggregate data. Results will be disseminated via a peer-reviewed publication.

CRD42024600884.