Shahriar Siddique Ayon , Md. Ebrahim Hossain , Md. Saef Ullah Miah , B. M. Mredul Arafin , Antara Chowdhury , Nuzhat Noor Islam Prova
{"title":"地中海贫血数据集涵盖临床、社会经济和精神卫生方面","authors":"Shahriar Siddique Ayon , Md. Ebrahim Hossain , Md. Saef Ullah Miah , B. M. Mredul Arafin , Antara Chowdhury , Nuzhat Noor Islam Prova","doi":"10.1016/j.dib.2025.112082","DOIUrl":null,"url":null,"abstract":"<div><div>Thalassemia is an inherited disorder of haemoglobin formation that requires lifelong blood transfusions and iron removal and brings both medical and emotional challenges. This dataset contains detailed information on 617 patients with thalassemia treated at a leading diagnostic centre in Pabna, Bangladesh. Demographic and socioeconomic data were gathered through face-to-face interviews, including age, gender, place of residence (urban or rural), education level, monthly household income, travel time to hospital, and how thalassemia affects school or work life. Clinical details, such as the type of thalassemia, age at diagnosis, whether the spleen was removed, transfusion frequency, the iron chelation plan, and how well patients adhered to it were taken from medical records. Laboratory results from the hospital’s central lab include pre transfusion haemoglobin, serum ferritin, red blood cell indices, reticulocyte count, and foetal haemoglobin percentage. Patients also rated their recent mental health as good or bad. Each record is assigned a unique code and stored in a single CSV file with twenty-three variables. The combination of medical, laboratory, social, and psychological information can support many uses, from building machine learning models to predict transfusion needs or therapy adherence to studying factors that drive health disparities and designing more patient centred care plans.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"63 ","pages":"Article 112082"},"PeriodicalIF":1.4000,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Thalassemia dataset covering clinical, socioeconomic, and mental health aspects\",\"authors\":\"Shahriar Siddique Ayon , Md. Ebrahim Hossain , Md. Saef Ullah Miah , B. M. Mredul Arafin , Antara Chowdhury , Nuzhat Noor Islam Prova\",\"doi\":\"10.1016/j.dib.2025.112082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Thalassemia is an inherited disorder of haemoglobin formation that requires lifelong blood transfusions and iron removal and brings both medical and emotional challenges. This dataset contains detailed information on 617 patients with thalassemia treated at a leading diagnostic centre in Pabna, Bangladesh. Demographic and socioeconomic data were gathered through face-to-face interviews, including age, gender, place of residence (urban or rural), education level, monthly household income, travel time to hospital, and how thalassemia affects school or work life. Clinical details, such as the type of thalassemia, age at diagnosis, whether the spleen was removed, transfusion frequency, the iron chelation plan, and how well patients adhered to it were taken from medical records. Laboratory results from the hospital’s central lab include pre transfusion haemoglobin, serum ferritin, red blood cell indices, reticulocyte count, and foetal haemoglobin percentage. Patients also rated their recent mental health as good or bad. Each record is assigned a unique code and stored in a single CSV file with twenty-three variables. The combination of medical, laboratory, social, and psychological information can support many uses, from building machine learning models to predict transfusion needs or therapy adherence to studying factors that drive health disparities and designing more patient centred care plans.</div></div>\",\"PeriodicalId\":10973,\"journal\":{\"name\":\"Data in Brief\",\"volume\":\"63 \",\"pages\":\"Article 112082\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data in Brief\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352340925008042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340925008042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Thalassemia dataset covering clinical, socioeconomic, and mental health aspects
Thalassemia is an inherited disorder of haemoglobin formation that requires lifelong blood transfusions and iron removal and brings both medical and emotional challenges. This dataset contains detailed information on 617 patients with thalassemia treated at a leading diagnostic centre in Pabna, Bangladesh. Demographic and socioeconomic data were gathered through face-to-face interviews, including age, gender, place of residence (urban or rural), education level, monthly household income, travel time to hospital, and how thalassemia affects school or work life. Clinical details, such as the type of thalassemia, age at diagnosis, whether the spleen was removed, transfusion frequency, the iron chelation plan, and how well patients adhered to it were taken from medical records. Laboratory results from the hospital’s central lab include pre transfusion haemoglobin, serum ferritin, red blood cell indices, reticulocyte count, and foetal haemoglobin percentage. Patients also rated their recent mental health as good or bad. Each record is assigned a unique code and stored in a single CSV file with twenty-three variables. The combination of medical, laboratory, social, and psychological information can support many uses, from building machine learning models to predict transfusion needs or therapy adherence to studying factors that drive health disparities and designing more patient centred care plans.
期刊介绍:
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