Background: The assessment of patients’ quality of life has emerged as a critical metric in evaluating healthcare services. Internationally, numerous studies have been conducted to assess the QoL of individuals diagnosed with pulmonary embolism through the development of standardized questionnaires and their association with various clinical parameters. Aim: To adapt a standardized questionnaire for assessing the quality of life following a pulmonary embolism and to evaluate the quality of life of affected patients. Materials and Methods: A total of 33 patients diagnosed with pulmonary embolism and hospitalized in the Department of Pulmonology at the Third State Central Hospital in Mongolia between August 2022 and December 2023 were included in the study. An observational cross-sectional study design was used. Inclusion criteria encompassed all patients diagnosed with PE during the study period, while exclusion criteria included individuals with severe comorbidities, those aged over 85 years, and those who declined participation. QoL was assessed using the Pulmonary Embolism Quality of Life (PEmb-QoL) questionnaire, which consists of 39 questions categorized into six domains. Higher scores indicate poorer QoL. Data analysis was performed using SPSS version 16. Results: The average age of the participants was 61±15 years, and 18 (54.5%) were female. The median duration of anticoagulant therapy was 170 days (range: 27–2555 days), and the average monthly expenditure on medication was 80,000 MNT (range: 63,000–400,000 MNT). The overall mean QoL score was 69.7±23.2. The median scores for the six domains were as follows: frequency of complaints 1.6 (IQR 1.5-1.9; max 5 score), activities of daily living limitations 1.5 (1.3–1.8; max 3 score), work-related problems 1.7 (1.5–2.0; max 2 score), social limitations 2.0 (2.0–3.0; max 5 score), intensity of complaints 3.0 (3.0–4.0; max 6 score), emotional complaints 2.0 (1.5–2.4; max 6 score). The internal consistency reliability of the questionnaire was assessed, with the symptom frequency category scoring well (α=0.74), while the other categories had excellent reliability (α>0.85). A weak positive correlation was observed between overall QoL scores and age, while a weak negative correlation was identified with body mass index (r=0.14 & r= -0.13, P>0.05). Conclusion The study findings indicate a low QoL among PE patients, emphasizing the necessity for enhancements in post-diagnosis medical care and long-term management strategies to improve patient outcomes.

Background: Hyperferritinemia, characterized by elevated serum ferritin levels, affects approximately 5–25% of the general population. Given the frequent coexistence of liver iron overload syndrome and metabolic syndrome—both of which significantly contribute to global morbidity and mortality—it is essential to investigate their interconnections. However, there is a lack of sufficient evidence, both in Mongolia and internationally, regarding the relationship between iron storage indicators, metabolic syndrome, and its components. A deeper understanding of iron’s role in disease progression is needed. Aim: This study aims to assess the association between hyperferritinemia and metabolic syndrome parameters. Materials and Methods: A cross-sectional analytical observational study was conducted on 159 male participants who met the inclusion criteria. Data were collected using a standardized questionnaire, and anthropometric measurements were taken. Blood samples were analyzed to determine glucose, triglyceride, total cholesterol, and high-density lipoprotein (HDL) levels using an automated biochemical analyzer. Serum ferritin concentrations were measured via the ELISA method (DRG Instruments GmbH, Germany), with hyperferritinemia defined as a serum ferritin level exceeding 400 ng/ ml. Metabolic syndrome was diagnosed based on the Harmonized criteria. Statistical analyses included the chi-square test and Fisher’s exact test for categorical variables, the Mann-Whitney U test for non-normally distributed data, and Spearman’s correlation test to assess relationships between glycemic levels, lipid parameters, and metabolic syndrome components. Results: The findings indicate that 59 participants (37.1%) had metabolic syndrome, while 33 (20.8%) presented with hyperferritinemia. The presence of metabolic syndrome and hyperglycemia increased the likelihood of developing hyperferritinemia by 3.4 and 3.7 times, respectively, whereas abdominal obesity raised the risk by 2.2 times. Conclusion There was a significant correlation between serum ferritin levels and certain parameters of metabolic syndrome among the male participants in this study.