Which are best for successful aging prediction? Bagging, boosting, or simple machine learning algorithms?

BACKGROUND: The worldwide society is currently facing an epidemiological shift due to the significant improvement in life expectancy and increase in the elderly population. This shift requires the public and scientific community to highlight successful aging (SA), as an indicator representing the quality of elderly people's health. SA is a subjective, complex, and multidimensional concept; thus, its meaning or measuring is a difficult task. This study seeks to identify the most affecting factors on SA and fed them as input variables for constructing predictive models using machine learning (ML) algorithms. METHODS: Data from 1465 adults aged ≥ 60 years who were referred to health centers in Abadan city (Iran) between 2021 and 2022 were collected by interview. First, binary logistic regression (BLR) was used to identify the main factors influencing SA. Second, eight ML algorithms, including adaptive boosting (AdaBoost), bootstrap aggregating (Bagging), eXtreme Gradient Boosting (XG-Boost), random forest (RF), J-48, multilayered perceptron (MLP), Naïve Bayes (NB), and support vector machine (SVM), were trained to predict SA. Finally, their performance was evaluated using metrics derived from the confusion matrix to determine the best model. RESULTS: The experimental results showed that 44 factors had a meaningful relationship with SA as the output class. In total, the RF algorithm with sensitivity = 0.95 ± 0.01, specificity = 0.94 ± 0.01, accuracy = 0.94 ± 0.005, and F-score = 0.94 ± 0.003 yielded the best performance for predicting SA. CONCLUSIONS: Compared to other selected ML methods, the effectiveness of the RF as a bagging algorithm in predicting SA was significantly better. Our developed prediction models can provide, gerontologists, geriatric nursing, healthcare administrators, and policymakers with a reliable and responsive tool to improve elderly outcomes.

Establishing machine learning models to predict the early risk of gastric cancer based on lifestyle factors.

BACKGROUND: Gastric cancer is one of the leading causes of death worldwide. Screening for gastric cancer greatly relies on endoscopy and pathology biopsy, which are invasive and pose financial burdens. Thus, the prevention of the disease by modifying lifestyle-related behaviors and dietary habits or even the prevention of risk factor formation is of great importance. This study aimed to construct an inexpensive, non-invasive, fast, and high-precision diagnostic model using six machine learning (ML) algorithms to classify patients at high or low risk of developing gastric cancer by analyzing individual lifestyle factors. METHODS: This retrospective study used the data of 2029 individuals from the gastric cancer database of Ayatollah Taleghani Hospital in Abadan City, Iran. The data were randomly separated into training and test sets (ratio 0.7:0.3). Six  ML methods, including multilayer perceptron (MLP), support vector machine (SVM) (linear kernel), SVM (RBF kernel), k-nearest neighbors (KNN) (K = 1, 3, 7, 9), random forest (RF), and eXtreme Gradient Boosting (XGBoost), were trained to construct prognostic models before and after performing the relief feature selection method. Finally, to evaluate the models' performance, the metrics derived from the confusion matrix were calculated via a test split and cross-validation. RESULTS: This study found 11 important influence factors for the risk of gastric cancer, such as Helicobacter pylori infection, high salt intake, and chronic atrophic gastritis, among other factors. Comparisons indicated that the XGBoost had the best performance for the risk prediction of gastric cancer. CONCLUSIONS: The results suggest that based on simple baseline patient data, the ML techniques have the potential to start the prescreening of gastric cancer and identify high-risk individuals who should proceed with invasive examinations. Our model could also considerably lessen the number of cases that need endoscopic surveillance. Future studies are required to validate the efficacy of the models in a larger and multicenter population.

Pre-Exposure to Radiofrequency Electromagnetic Fields and Induction of Radioadaptive Response in Rats Irradiated with High Doses of X-Rays.

Background: Some evidence shows that a pre-exposure to RF can mitigate the effects of subsequent exposures to high doses of ionizing radiation. Objective: We aimed to assess the effect of a pre-exposure to non-ionizing RF radiation on survival, weight changes, food consumption, and water intake of lethally irradiated rats. Material and Methods: In this case-control study, we used a commercial mobile phone (GSM, 900/1800 MHz) as well as a 2.4 GHz Wi-Fi router as the sources of pre-exposure to RF radiation. Forty-eight rats were randomly divided into six groups of control, "8 Gy X-rays", mobile phone, "mobile phone+8 Gy", Wi-Fi, and "Wi-Fi+8 Gy". Then, the survival fraction, weight loss, water, and food consumption changes were compared in different groups. Results: The survival analysis indicated that the survival rates in all of the exposed animals ("8 Gy X-rays", "mobile phone+8 Gy", "Wi-Fi+8 Gy") were significantly lower than the control, "Wi-Fi", and "mobile phone" groups. The changes in survival rates of "mobile+8 Gy", "Wi-Fi+8 Gy", and 8 Gy alone were not statistically significant. However, food and water intake were significantly affected by exposure to both RF pre-exposures and exposure to high dose ionizing radiation. Conclusion: To the best of our knowledge, the existence of a dose window for the induction of AR can be the cause of the lack of AR in our experiment. Our findings confirm that in a similar pattern with the adaptive responses induced by pre-exposure to ionizing radiation, the induction of adaptive response by RF-pre-exposures requires a minimum level of damage to trigger adaptive phenomena.

Developing the minimum data set of the corrosive ingestion registry system in Iran.

BACKGROUND: Corrosive ingestion is still a major health problem, and its outcomes are often unpredicted. The implementation of a registry system for poisoning with corrosive substances may improve the quality of patient care and might be useful to manage this type of poisoning and its complications. Therefore, our study aimed to establish a minimum data set (MDS) for corrosive ingestion. METHODS: This was an applied study performed in 2022. First, a literature review was conducted to identify the potential data items to be included in the corrosive ingestion MDS. Then, a two-round Delphi survey was performed to attain an agreement among experts regarding the MDS content, and an additional Delphi step was used for confirming the final MDS by calculating the individual item content validity index (CVI) and content validity ratio (CVR) and by using other statistical tests. RESULTS: After the literature review, 285 data items were collected and sent to a two-round Delphi survey in the form of a questionnaire. In total, 75 experts participated in the Delphi stage, CVI, kappa, and CVR calculation. Finally, the MDS of the corrosive ingestion registry system was identified in two administrative and clinical sections with 21 and 152 data items, respectively. CONCLUSIONS: The development of an MDS, as the first and most important step towards developing the corrosive ingestion registry, can become a standard basis for data collection, reporting, and analysis of corrosive ingestion. We hope this MDS will facilitate epidemiological surveys and assist policymakers by providing higher quality data capture to guide clinical practice and improve patient-centered outcomes.

Design, development, and evaluation of a surveillance system for suicidal behaviors in Iran.

BACKGROUND: Suicide is a serious cause of morbidity and mortality in Iran and worldwide. Although several organizations gather information on suicide and suicide attempts, there is substantial misperception regarding the description of the phenomenon. This study proposes the minimum data set (MDS) for suicidal behaviors surveillance. METHODS: A literature review was first conducted to achieve a thorough overview of suicide-related items and map the existing evidence supporting the development of the MDS. The data items included in the literature review were then analyzed using a two-round Delphi technique with content validation by an expert panel. The suicidal behaviors surveillance system was then established based on the confirmed MDS, and ultimately, its performance was assessed by involving the end-users. RESULTS: The panel of experts consisted of 50 experts who participated in the Delphi phase and validity content review. Of these, 46% were men, and their mean age and average work experience were (36.4, SD ± 6.4) and (12.32, SD ± 5.2) years, respectively. The final MDS platform of our study contained 108 items classified into eight main categories. A web-based system with a modular and layered architecture was developed based on the derived MDS. CONCLUSION: The developed system provides a framework for recording suicidal behaviors' data. The integration of multiple suicide-related information systems at the regional and national levels makes it possible to assess the long-term outcomes and evolutions of suicide prevention interventions.

Predictive modeling for COVID-19 readmission risk using machine learning algorithms.

INTRODUCTION: The COVID-19 pandemic overwhelmed healthcare systems with severe shortages in hospital resources such as ICU beds, specialized doctors, and respiratory ventilators. In this situation, reducing COVID-19 readmissions could potentially maintain hospital capacity. By employing machine learning (ML), we can predict the likelihood of COVID-19 readmission risk, which can assist in the optimal allocation of restricted resources to seriously ill patients. METHODS: In this retrospective single-center study, the data of 1225 COVID-19 patients discharged between January 9, 2020, and October 20, 2021 were analyzed. First, the most important predictors were selected using the horse herd optimization algorithms. Then, three classical ML algorithms, including decision tree, support vector machine, and k-nearest neighbors, and a hybrid algorithm, namely water wave optimization (WWO) as a precise metaheuristic evolutionary algorithm combined with a neural network were used to construct predictive models for COVID-19 readmission. Finally, the performance of prediction models was measured, and the best-performing one was identified. RESULTS: The ML algorithms were trained using 17 validated features. Among the four selected ML algorithms, the WWO had the best average performance in tenfold cross-validation (accuracy: 0.9705, precision: 0.9729, recall: 0.9869, specificity: 0.9259, F-measure: 0.9795). CONCLUSIONS: Our findings show that the WWO algorithm predicts the risk of readmission of COVID-19 patients more accurately than other ML algorithms. The models developed herein can inform frontline clinicians and healthcare policymakers to manage and optimally allocate limited hospital resources to seriously ill COVID-19 patients.

Establishing a minimum data set for suicide and attempted suicide registry system in Iran.

BACKGROUND: Suicidal behavior is a major cause of mortality and disability worldwide. Accurate and consistent collection of data on suicide, suicide ideation, and suicide attempts presents many challenges for public health practitioners, policymakers, and researchers. This study aimed to establish a minimum data set (MDS) for integrating data across suicide registries and other data sources. METHODS: The MDS proposed in this study was developed in two-stepwise stages. First, an extensive literature review was performed in order to identify the potential data items. Then, we conducted a two-round Delphi stage to reach a consensus among experts regarding essential data items and a supplementary one-round Delphi stage for validating the content of the final MDS by calculating the individual item content validity index (CVI) and content validity ratio (CVR) and using other statistical tests. RESULTS: After the literature review, 189 data items were extracted and sent to a panel of experts in the form of a questionnaire. In the Delphi stage and CVI calculation, 55 and 10 experts participated in kappa and CVR calculation, respectively. Finally, the MDS of the suicide registry was finalized with 84 data elements that were classified into four categories, including patient profile, socio-economic status, clinical and psychopathological status, and suicide circumstances. CONCLUSIONS: The suicide MDS can become a standardized and consistent infrastructure for meaningful evaluations, reporting, and benchmarking of suicidal behaviors across regions and countries. We hope this MDS will facilitate epidemiological surveys and support policymakers by providing higher quality data capture to guide clinical practice and improve patient-centered outcomes.

Development and evaluation of an electronic nursing documentation system.

BACKGROUND: Nursing documentation is a critical aspect of the nursing care workflow. There is a varying degree in how detailed nursing reports are described in scientific literature and care practice, and no uniform structured documentation is provided. This study aimed to describe the process of designing and evaluating the content of an electronic clinical nursing documentation system (ECNDS) to provide consistent and unified reporting in this context. METHODS: A four-step sequential methodological approach was utilized. The Minimum Data Set (MDS) development process consisted of two phases, as follows: First, a literature review was performed to attain an exhaustive overview of the relevant elements of nursing and map the available evidence underpinning the development of the MDS. Then, the data included from the literature review were analyzed using a two-round Delphi study with content validation by an expert panel. Afterward, the ECNDS was developed according to the finalized MDS, and eventually, its performance was evaluated by involving the end-users. RESULTS: The proposed MDS was divided into administrative and clinical sections; including nursing assessment and the nursing diagnosis process. Then, a web-based system with modular and layered architecture was developed based on the derived MDS. Finally, to evaluate the developed system, a survey of 150 registered nurses (RNs) was conducted to identify the positive and negative impacts of the system. CONCLUSIONS: The developed system is suitable for the documentation of patient care in nursing care plans within a legal, ethical, and professional framework. However, nurses need further training in documenting patient care according to the nursing process, and in using the standard reporting templates to increase patient safety and improve documentation.

Case report: Diagnosis and emergency surgery on a young patient with extensive aortic dissection without any risk factors.

BACKGROUND: Type A aortic dissection is a very dangerous, fatal, and emergency condition for surgery. Acute aortic dissection is a rare condition, such that many patients will not survive without reconstructive surgery. CASE PRESENTATION: We present a case 24-year-old male who came with symptoms of shortness of breath and cough. The patient underwent ECG, chest radiology, and ultrasound, where the patient was found to have right pleural effusion while his ECG was normal. In the history taken from the patient, he had no underlying disease, no history of heart diseases in his family. For a better diagnosis, ETT and aortic CT angiography was performed on the patient which confirmed the evidence of dissection. Immediately after the diagnosis, necessary arrangements were made for open heart surgery and the patient was prepared for surgery. The patient was admitted in the cardiac surgery ICU for 5 days and his medication was carefully administered. After the conditions were stabilized, the patient was transferred to the post-cardiac surgery ICU ward. The patient was discharged from the hospital one week after the surgery and returned to the office as an OPD one week after his discharge. CONCLUSION: Various risk factors can play a role in creating aortic dissection. Therefore, it is necessary to pay attention to patients' history for achieving a quick and definitive diagnosis. Therefore, to control the complications of placing the cannula as well as the duration of the surgery, it is very important to reduce the duration of pumping on the patient and to be very careful during the cannula placement.

Combined Effects of Radiofrequency Electromagnetic Fields and X-Ray in Renal Tissue and Function.

PURPOSE: Biochemical and histopathological properties of renal tissues were reported to be affected by both radiofrequency electromagnetic fields (RF-EMF) and ionizing radiation. The radiation-induced changes in the kidney, including the serum levels of blood urea nitrogen (BUN) and creatinine (Cr), could lead to adverse health outcomes such as chronic kidney disease. These complications signify the importance of the research in this field. Thus, in this study, the effects of ionizing and non-ionizing radiations, as well as their combination, were assessed by evaluating the alteration in BUN, Cr, and histopathological changes in kidney tissue. MATERIALS AND METHODS: Ninety-six male Wistar rats were randomly divided into six groups and were exposed to either 900/1800MHz (mobile phone) or 2.4 GHz RF-EMF (Wi-Fi) radiation for 14 days, 8Gy x-ray, or their combination. Sera were collected from 2 mL of rat blood, then BUN and Cr levels were determined. Also, renal samples were stained with hematoxylin and eosin and evaluated histopathologically. RESULTS: Both BUN and Cr levels raised non-significantly after exposure to 8 Gy x-rays. Moreover, all measurements in the samples of x-ray groups were in borderline or higher than normal values. The BUN levels of control, Wi-Fi, x-ray, and Wi-Fi+x-ray groups were not significantly different. However, Cr levels in the Wi-Fi group were significantly higher than those of the controls, and BUN to Cr ratio levels were significantly lower than those of the controls. Also, tubular atrophy and vessel wall thickening were associated with these exposures. CONCLUSION: Exposure to 900/1800MHz, 2400 MHz EMF can alter the kidney function. However, pre-exposure to 900/1800MHz EMF could modulate the acute adverse effects of lethal x-ray dose, which addresses the adaptive response in the kidney.

Assessment of function, histopathological changes, and oxidative stress in liver tissue due to ionizing and non-ionizing radiations.

BACKGROUND: Compared to past decades, humans are exposed to rapidly increasing levels of radiofrequency electromagnetic radiations (RF-EMF). Despite numerous studies, the biological effects of human exposure to different levels of RF-EMF are not fully understood yet. This study aimed to evaluate the bioeffects of exposure to "900/1800 MHz" and "2.4 GHz" RF-EMFs, and x-rays alone as well as their potential interactions, i.e. inducing simple additive, adaptive, or synergistic effects. METHODS: 120 Wistar rats were randomly divided into ten groups of 12 each. The rats were exposed to RF-EMF, 10 cGy, and 8 Gy x-rays, a combination of these exposures, or only sham-exposed. The levels of liver enzymes were determined in serum samples by an auto-analyzer. Moreover, the histopathological changes, and the levels of malondialdehyde (MDA), nitric oxide, ferric reducing antioxidant power, total thiols, and protein carbonyl (PCO) were measured. RESULTS: Among the markers of liver function, gamma-glutamyltransferase was not associated with irradiation but, aspartate transaminase, alanine transaminase, and alkaline phosphatase showed some levels of association. MDA and PCO levels after 8 Gy irradiation increased, but pre-exposure to RF-EMF could modulate their changes. At the cellular level, the frequency of lobular inflammation was associated with the type of intervention. CONCLUSION: The exposure to both ionizing and non-ionizing radiations could alter some liver function tests. A short term pre-exposure to RF-EMF before exposure to an 8 Gy challenging dose of x-rays caused the alterations in oxidative stress markers and liver function tests, which indicate that oxidative stress is possibly involved in the adaptive response.

A study to assess the knowledge and practice of medical professionals on radiation protection in interventional radiology.

OBJECTIVE: Ionizing radiation has been extensively used in medical procedures throughout the world. Such interventional radiological procedures could result in occupational exposure that needs urgent control. Therefore, MPs (medical professionals) should receive education and appropriate training on occupational radiation protection. In this context, the present study is aimed to investigate the MPs' knowledge and practice regarding radiation protection principles during interventional radiological procedures. MATERIAL AND METHODS: A descriptive questionnaire-based study was carried out among 215 MPs involved in interventional fluoroscopy procedures. The practice of 31 MPs was studied using a checklist based on ALARA principles and ICRP guidelines. RESULTS: A total of 43.3% and 45.1% answered correctly for knowledge and practice. However, the difference between radiation protection knowledge and practice between the physicians and nurses was statistically significant. The knowledge and practice survey of MPs demonstrated that nurses rarely adhered to radiation-protection measures. CONCLUSION: The present study reflects the lack of knowledge and practice concerning radiation protection concepts among the nurses. This deficiency needs to be resolved by periodic practical radiation protection courses in the curriculum of medicine.

Exploring Changes in Thalamus Metabolites as Diagnostic Biomarkers in Idiopathic Generalised Epilepsy Patients Using Magnetic Resonance Spectroscopy.

INTRODUCTION: Idiopathic generalised epilepsy (IGE) refers to a group of epilepsies resulting from the activation of neurons in the whole brain. This study aimed to evaluate the metabolite changes in thalamus as diagnostic biomarkers in IGE patients compared to healthy individuals using magnetic resonance spectroscopy (MRS) technique. METHODS: The MRS was performed on 35 IGE patients (26 women and 11 men) with average age of 32 (ranged from 18 to 43) and 35 healthy individuals (13 women and 22 men) with average age of 31 (ranged from 21 to 50) as the control group. The levels of N-acetylaspartate (NAA), creatine (Cr) and choline (Cho) were measured using MRS. The NAA/Cr and NAA/Cho ratios were calculated for all participants. These values were statistically compared using t-test between the groups. RESULTS: The NAA had significant lower values in IGE patients, 9.6 (SD = 0.8) and 9.9 (SD = 0.7) for right and left thalamus, respectively, compared to 10.9 (SD = 0.9) and 10.7 (SD = 0.9) in control group. The Cr values in the left side of thalamus were significantly higher in IGE patients (6.7 [SD = 0.8] versus 5.8 [SD = 0.5]); however, there was no difference in right thalamus. Measurements showed no difference for amounts of Cho between the groups in both sides of thalamus. The NAA/Cr ratio was 1.48 (SD = 0.14) and 1.48 (SD = 0.16) for right and left thalamus, respectively, in IGE patients in comparison with 1.83 (SD = 0.2) and 1.86 (SD = 0.26) in controls. There was no meaningful variation between the NAA/Cho ratio of the right and left thalamus among the groups. CONCLUSION: Thalamic NAA, Cr and NAA/Cr ratio values in IGE patients showed statistical differences compared to healthy individuals. Evaluating metabolites variations in thalamus using MRS is suggested for differentiating IGE patients from healthy individuals.

Chromosomal aberrations in C-arm fluoroscopy, CT-scan, lithotripsy, and digital radiology staff.

We have assessed chromosome-type aberrations and micronuclei in the peripheral lymphocytes of personnel working with C-arm fluoroscopy, multi-slice CT-scan, lithotripsy, and digital radiology medical procedures. The study population comprised of 46 exposed workers and 35 controls matched for age, gender, and other confounding factors. Chromosome-type aberrations and micronuclei were analyzed and compared with occupational dosimetry data. The highest frequency of both chromosome aberrations (1.62 CA/100 cells) and MN (MN = 7.47 ± 2.55) was observed in the operating room group. According to occupational dosimetry, surgeons and medical staff received 0-2.99 mSv over the previous year, well below the limit established by the International Committee on Radiation Protection. An increased level of chromosomal aberrations was observed among workers exposed in the operating rooms. We recommend that operating room radiation safety programs be improved and better supervised, in particular for orthopedic surgeons and personnel performing fluoroscopically guided procedures.

Can healthy life style predict successful aging among Iranian older adults?

Background: Successful aging is a prominent and worldwide theme in gerontology. However, until recently, only few studies were conducted about successful aging in Iran. This study examined whether a healthy lifestyle could predict successful aging among older Iranians. Methods: This cross sectional and descriptive study included 975 older Iranians who were selected through a multistage cluster-quota method from the health centers of Shiraz, Iran. A 5-part questionnaire, including demographic characteristics, the Seniors' Healthy Lifestyle, Barthel Index, the Diner Life Satisfaction and Quality of Life, was used to collect the data. A logistic regression analysis was used in data analysis; data were analyzed using SPSS 21; and significance level was set at α = 0.05. Results: The prevalence of successful aging among older Iranians was calculated at 24.0%. Results of multiple logistic regression analysis revealed that age (95% CI = 1.129- 1.702 and OR = 1.352), gender (95% CI = 0.412-0.764 and OR = 0.687), education level (95% CI = 1.443 - 1.699 and OR = 1.454), job (95% CI = 1.063-1.413 and OR = 1.185), monthly income (95% CI = 1.355-4.055 and OR = 2.272), insurance (95% CI = 0.344-0.842 and OR = 0.540), source of income (95% CI = 1.014-1.298 and OR = 1.145), and healthy lifestyle (95% CI = 0.772 - 0.858 and OR = 0.814) were predictors for successful aging. Conclusion: Findings indicated that successful agers were mostly younger men, with higher education level and monthly income, who had insurance and a job and a healthy lifestyle. Thus, to age successfully, one must maintain and improve healthy lifestyle to prolong one's health.

Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software.

INTRODUCTION: Timely diagnosis of brain tumors could considerably affect the process of patient treatment. To do so, para-clinical methods, particularly MRI, cannot be ignored. MRI has so far answered significant questions regarding tumor characteristics, as well as helping neurosurgeons. In order to detect the tumor cellularity, neuro-surgeons currently have to sample specimens by biopsy and then send them to the pathology unit. The aim of this study is to determine the tumor cellularity in the brain. METHODS: In this cross-sectional study, 32 patients (18 males and 14 females from 18-77 y/o) were admitted to the neurosurgery department of Shohada-E Tajrish Hospital in Tehran, Iran from April 2012 to February 2014. In addition to routine pulse sequences, T2W Multi echo pulse sequences were taken and the images were analyzed using the MATLAB software to determine the brain tumor cellularity, compared with the biopsy. RESULTS: These findings illustrate the need for more T2 relaxation time decreases, the higher classes of tumors will stand out in the designed table. In this study, the results show T2 relaxation time with a 85% diagnostic weight, compared with the biopsy, to determine the brain tumor cellularity (p<0.05). CONCLUSION: Our results indicate that the T2 relaxation time feature is the best method to distinguish and present the degree of intra-axial brain tumors cellularity (85% accuracy compared to biopsy). The use of more data is recommended in order to increase the percent accuracy of this techniques.

Efficacy of Eye Movements Desensitization and Reprocessing on the Quality of Life of the Patients with Myocardial Infarction.

Myocardial infarction causes limitations in the physical activity and perturbation of quality of life.The aim of this study was to evaluate the effect of eye movements desensitization and reprocessing (EMDR) on the quality of life of these patients. This study was conducted in two groups as the before and after while the effect of eye movements desensitization and reprocessing on the quality of life of the patients with Myocardial infarction. Sampling was done based on the purposive sampling. Patients were randomly divided into two experimental and control groups (30 patients in each group). Samples were assigned through randomized allocation. In the experimental group, the EMDR method was carried out on the patients in five 90-minute sessions over a two week period. In the control group no intervention was received. Data of Quality of life, pre-treatment, post-treatment were analyzed using SPSS. The results showed that the quality of life increase in all its dimensions of the experimental group, after performing the EMDR therapy significantly (P=0.001). Treatment what has already been stated, was effective on the quality of life in patients. Treatment team members can use this method as an effective intervention in order to improve the quality of life of their patients.

Analysis of survival data in thalassemia patients in Shiraz, Iran.

OBJECTIVES: The survival rate of thalassemia patients has not been conclusively established, and the factors associated with survival remain unclear. This study aimed to determine the survival rate of thalassemia among patients in southern Iran and to identify the factors associated with mortality from thalassemia. METHODS: This retrospective cohort study was conducted based on a retrospective review of the medical records of 911 beta-thalassemia patients in 2014. Data analysis was conducted using the Kaplan-Meier method and Cox regression analysis. RESULTS: Overall, 212 patients (23.3%) died, and 26.8% had thalassemia intermedia. The 20-year, 40-year, and 60-year survival rates were 85%, 63%, and 54%, respectively. Both crude and adjusted analyses found that education, marital status, ferritin levels, and comorbidities were related to mortality. CONCLUSIONS: Sociodemographic and hematological factors were found to be significantly associated with the survival rate of thalassemia. Addressing these factors may help healthcare providers and physicians to provide the best possible care and to improve the survival rate.