Hemoglobin variability is known to increase cardiovascular mortality in chronic kidney disease, but the association of hemoglobin variability with the risk of cardiovascular disease (CVD) in the general population is yet unclear. This retrospective cohort study based on 'the South Korean National Health Insurance Service database' consisted of 198,347 adults who went through all three health examinations. Hemoglobin variability is defined as the average successive variability of three separate hemoglobin values from each health screening period. Participants were followed up for 6 years to determine the risk of coronary heart disease and stroke. We used multivariate Cox proportional hazards regression to examine the adjusted hazard ratios for CVD according to hemoglobin variability. Per 1 unit increase of hemoglobin variability, the risk for CVD (aHR 1.06, 95% CI 1.02-1.09) and stroke (aHR 1.08, 95% CI 1.03-1.13) increased significantly. The risk-increasing trend was preserved in the low-to-moderate risk group of CVDs (aHR 1.07, 95% CI 1.02-1.11). This result suggests that subjects with high hemoglobin variability who would otherwise be categorized as having low-to-moderate CVD risk may have higher risk of CVD than those with low hemoglobin variability.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9905090 | PMC |
| http://dx.doi.org/10.1038/s41598-023-28029-w | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.
Eur J Med Res
December 2024
Department of Geriatric Respiratory and Critical Care, Anhui Geriatric Institute, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Background: This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.
Methods: Data were collected from two centers and categorized into development and validation cohorts. Using the development cohort, candidate variables were selected via the Recursive Feature Elimination (RFE) method.
A correlation study between blood glucose fluctuation and chronic pain in the older people with type 2 diabetes mellitus.
BMC Geriatr
December 2024
Geriatric Endocrinology, Department of Geriatric Endocrinology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Shushan District, Hefei City, Anhui Province, China.
Article Synopsis
- The study aims to explore how fluctuations in blood glucose levels relate to chronic pain in older adults (aged 60+) with type 2 diabetes mellitus (T2DM) and assess the predictive value of these fluctuations for pain severity.
- A total of 60 patients were evaluated, categorizing them into mild and severe pain groups based on their numeric pain scores, with extensive clinical data and continuous glucose monitoring used for analysis.
- Results indicated that higher pain scores correlated positively with factors like age, diabetes duration, and specific glucose parameters, while showing negative correlation with red blood cell count.
Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.
Medicine (Baltimore)
December 2024
School of Informatics, Hunan University of Chinese Medicine, Changsha, China.
In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined with machine learning technology, to study the risk factors and better risk prediction model of diabetic retinopathy (DR), and provide basis for the screening and treatment of it. Through a retrospective study of DR cases in the real world, the electronic medical records of patients who met screening criteria were collected. Moreover, Recursive Feature Elimination with Cross-Validation (RFECV) was used for feature selection.
View Article and Find Full Text PDFNeighborhood disorder and social cohesion: A longitudinal investigation of links with maternal cardiometabolic risk one year postpartum.
J Psychosom Res
December 2024
Department of Psychology, University of California, Los Angeles, USA. Electronic address:
Objective: Neighborhood characteristics can influence cardiometabolic health, including during the perinatal period. However, maternal health research has largely examined the influence of objective neighborhood measures, limiting insights into psychological and social processes. We examined associations of perceived neighborhood disorder and social cohesion with maternal cardiometabolic risk 1 year postpartum and explored potential pathways of psychological distress and physical activity.
View Article and Find Full Text PDFEvaluating the necessity of postoperative day 1 labs following laparoscopic radical nephrectomy (LRN).
Transl Androl Urol
November 2024
Department of Urology, Mayo Clinic, Jacksonville, FL, USA.
Background: Standard postoperative care following laparoscopic radical nephrectomy (LRN) typically includes routine blood tests. Recent studies have assessed the safety of omitting routine postoperative labs in minimally invasive surgeries to reduce hospital costs. Our primary objective was to evaluate if routine postoperative day 1 (POD1) labs were necessary following LRN.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!