Correction to: Suboptimal oral health and the risk of cardiovascular disease in the presence of competing death: a data linkage analysis.
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ABSTRACT:
SUBMITTER: Aldossri M
PROVIDER: S-EPMC9849495 | biostudies-literature | 2023 Feb
REPOSITORIES: biostudies-literature
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Correction to: Suboptimal oral health and the risk of cardiovascular disease in the presence of competing death: a data linkage analysis.
Aldossri Musfer M Saarela Olli O Rosella Laura L Quiñonez Carlos C
Canadian journal of public health = Revue canadienne de sante publique 20230201 1
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Project description:ObjectiveThe objective of this study is to simultaneously assess the associations between suboptimal oral health (SOH) and cardiovascular disease (CVD) and competing death (CD).MethodsOntario residents aged 40 years and over who participated in the Canadian Community Health Survey 2003 and 2007-2008 were followed until December 31, 2016 for the incidence of CVD or CD. SOH was assessed based on self-rated oral health and inability to chew. Multivariable competing risk analysis was adjusted for socioeconomic characteristics, behavioural factors and intermediate health outcomes.ResultsThe study sample included 36,176 participants. Over a median follow-up of 9.61 years, there were 2077 CVD events and 3180 CD events. The fully adjusted models indicate 35% (HR = 1.35, 95% CI: 1.12-1.64) increase in the risk of CVD and 57% (HR = 1.57, 95% CI: 1.33-1.85) increase in the risk of CD among those who reported poor oral health as compared to those who reported excellent oral health. The fully adjusted models also indicate 11% (HR = 1.11, 95% CI: 0.97-1.27) increase in the hazard of CVD and 37% (HR = 1.37, 95% CI: 1.24-1.52) increase in the hazard of CD among those who reported inability to chew.ConclusionThis study provides important information to contextualize CVD risk among those with SOH. The competing risk analysis indicates that those with SOH may benefit from additional interventions to prevent CVD and CD. Accordingly, managing the risk of CVD among those with SOH should fall under a more comprehensive approach that aims at improving their overall health and well-being.
| S-EPMC9849623 | biostudies-literature
Project description:PurposeTo identify the optimal statistical approach for predicting the risk of fragility fractures in the presence of competing event of death.MethodsWe used real-world data from the Dubbo Osteoporosis Epidemiology Study that has monitored 3035 elderly participants for bone health and mortality. Fragility fractures were ascertained radiologically. Mortality was confirmed by the State Registry. We considered four statistical models for predicting fracture risk: (i) conventional Cox's proportional hazard model, (ii) cause-specific model, (iii) Fine-Gray sub-distribution model, and (iv) multistate model. These models were fitted and validated in the development (60% of the original sample) and validation (40%) subsets, respectively. The model performance was assessed by discrimination and calibration analyses.ResultsDuring a median follow-up of 11.3 years (IQR: 7.2, 16.2), 628 individuals (34.5%) in the development cohort fractured, and 630 (34.6%) died without a fracture. Neither the discrimination nor the 5-year prediction performance was significantly different among the models, though the conventional model tended to overestimate fracture risk (calibration-in-the-large index = - 0.24; 95% CI: - 0.43, - 0.06). For 10-year risk prediction, the multistate model (calibration-in-the-large index = - 0.05; 95% CI: - 0.20, 0.10) outperformed the cause-specific (- 0.23; - 0.30, - 0.08), Fine-Gray (- 0.31; - 0.46, - 0.16), and conventional model (- 0.54; - 0.70, - 0.39) which significantly overestimated fracture risk.ConclusionAdjustment for competing risk of death has minimum impact on the short-term prediction of fracture. However, the multistate model yields the most accurate prediction of long-term fracture risk and should be considered for predictive research in the elderly, who are also at high mortality risk. Fracture risk assessment might be compromised by the competing event of death. This study, using real-world data found a multistate model was superior to the current competing risk methods in fracture risk assessment. A multistate model is considered an optimal statistical method for predictive research in the elderly.
| S-EPMC11499430 | biostudies-literature
Project description:Cardiovascular diseases (CVDs) encompass various conditions affecting the heart and its blood vessels and are often linked with oral microbes. Our data analysis aimed to identify oral bacteria from other non-oral sites (i.e., gut, arterial plaque and cultured blood) that could be linked with CVDs. Taxonomic profiling identified bacteria to the species level and compared with the Human Oral Microbiome Database (HOMD). The oral bacteria in the gut, cultured blood and arterial plaque samples were catalogued, with their average frequency calculated for each sample. Additionally, data were filtered by comparison with the Human Microbiome Project (HMP) database. We identified 17,243 microbial species, of which 410 were present in the HOMD database and further denominated as "oral", and were found in at least one gut sample, but only 221 and 169 species were identified in the cultured blood and plaque samples, respectively. Of the 410 species, 153 were present solely in oral-associated environments after comparison with the HMP database, irrespective of their presence in other body sites. Our results suggest a potential connection between the presence of specific species of oral bacterial and occurrence of CVDs. Detecting these oral bacterial species in non-oral sites of patients with CVDs could help uncover the link between oral health and general health, including cardiovascular conditions via bacterial translocation.
| S-EPMC10794416 | biostudies-literature
Project description:Electronic health records (EHRs) contain rich clinical information for millions of patients and are increasingly used for public health research. However, non-random inclusion of subjects in EHRs can result in selection bias, with factors such as demographics, socioeconomic status, healthcare referral patterns, and underlying health status playing a role. While this issue has been well documented, little work has been done to develop or apply bias-correction methods, often due to the fact that most of these factors are unavailable in EHRs. To address this gap, we propose a series of Heckman type bias correction methods by incorporating social determinants of health selection covariates to model the EHR non-random sampling probability. Through simulations under various settings, we demonstrate the effectiveness of our proposed method in correcting biases in both the association coefficient and the outcome mean. Our method augments the utility of EHRs for public health inferences, as we show by estimating the prevalence of cardiovascular disease and its correlation with risk factors in the New York City network of EHRs.
| S-EPMC10941326 | biostudies-literature
Project description:AimCardiovascular mortality risk evolves over the lifespan of kidney failure (KF), as patients develop comorbid disease and transition between treatment modalities. Absolute cardiovascular death rates would help inform clinical practice and health-care provision, but are not well understood across a continuum of dialysis and transplant states. We aimed to characterize cardiovascular death across the natural history of KF using a lifespan approach.MethodsWe performed a population-based cohort study of incident patients commencing kidney replacement therapy in Australia and New Zealand. Cardiovascular deaths were identified using data linkage to national death registers. We estimated the probability of death and kidney transplant using multi-state models, and calculated rates of graft failure and cardiovascular death across demographic factors and comorbidities.ResultsAmong 60 823 incident patients followed over 381 874 person-years, 25% (8492) of deaths were from cardiovascular disease. At 15 years from treatment initiation, patients had a 15.2% probability of cardiovascular death without being transplanted, but only 2.3% probability of cardiovascular death post-transplant. Females had a 3% lower probability of cardiovascular death at 15 years (15.3% vs. 18.6%) but 4% higher probability of non-cardiovascular death (54.5% vs. 50.8%). Within the first year of dialysis, cardiovascular mortality peaked in the second month and showed little improvement across treatment era.ConclusionDespite improvements over time, cardiovascular death remains common in KF, particularly among the dialysis population and in the first few months of treatment. Multi-state models can provide absolute measures of cardiovascular mortality across both dialysis and transplant states.
| S-EPMC9306651 | biostudies-literature
Project description:Analyses of viral genetic linkage can provide insight into HIV transmission dynamics and the impact of prevention interventions. For example, such analyses have the potential to determine whether recently-infected individuals have acquired viruses circulating within or outside a given community. In addition, they have the potential to identify characteristics of chronically infected individuals that make their viruses likely to cluster with others circulating within a community. Such clustering can be related to the potential of such individuals to contribute to the spread of the virus, either directly through transmission to their partners or indirectly through further spread of HIV from those partners. Assessment of the extent to which individual (incident or prevalent) viruses are clustered within a community will be biased if only a subset of subjects are observed, especially if that subset is not representative of the entire HIV infected population. To address this concern, we develop a multiple imputation framework in which missing sequences are imputed based on a model for the diversification of viral genomes. The imputation method decreases the bias in clustering that arises from informative missingness. Data from a household survey conducted in a village in Botswana are used to illustrate these methods. We demonstrate that the multiple imputation approach reduces bias in the overall proportion of clustering due to the presence of missing observations.
| S-EPMC4547719 | biostudies-literature
Project description:BackgroundTo study the risk of cardiovascular disease (CVD) and other competing causes of death in older kidney cancer patients.MethodsData on older patients (aged 65 and above) diagnosed with kidney cancer between 1975 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We delved into the distribution of CVD and other competing causes of death across the entire cohort and in various patient subgroups. The competing risk analysis was used to produce cumulative mortality curves based on cumulative mortality for the primary outcomes by follow-up period. Utilizing the standardized mortality ratios (SMRs) and absolute excess risks (AERs), we contrasted the risk of CVD and other competing causes of death in older kidney cancer patients to that observed in the general population.ResultsThe analysis included 29,349 older kidney cancer patients, of which included 4563 CVD deaths. As survival time extended, the proportion of non-cancer deaths increased in older kidney cancer patients, with CVD accounting for the largest share of non-cancer deaths. At 10-15 years after diagnosis, cumulative non-cancer mortality exceeded primary kidney cancer as the predominant cause of death, and cumulative CVD mortality is higher among all non-cancer causes. Older kidney cancer patients exhibited a greater risk of CVD and other non-cancer deaths than their counterparts in the general older population did (SMR: 1.38-2.81; AER: 1.1-143.69).ConclusionsAs survival time increases, the risk of non-cancer death in older kidney cancer patients gradually surpassed that of primary cancer, and CVD death accounted for the majority of non-cancer deaths. Among older kidney cancer patients, the risk of CVD mortality was higher than in the general population. Managing non-cancer deaths, especially CVD deaths, should be a focus in the care of older kidney cancer patients.
| S-EPMC11759974 | biostudies-literature
Project description:Digital health is increasingly promoting open health data. Although this open approach promises a number of benefits, it also leads to tensions with Indigenous data sovereignty movements led by Indigenous peoples around the world who are asserting control over the use of health data as a part of self-determination. Digital health has a role in improving access to services and delivering improved health outcomes for Indigenous communities. However, we argue that in order to be effective and ethical, it is essential that the field engages more with Indigenous peoples´ rights and interests. We discuss challenges and possible improvements for data acquisition, management, analysis, and integration as they pertain to the health of Indigenous communities around the world.
| S-EPMC11224364 | biostudies-literature
Project description:IntroductionContemporary care of congenital heart disease (CHD) is largely standardised, however there is heterogeneity in post-surgical outcomes that may be explained by genetic variation. Data linkage between a CHD biobank and routinely collected administrative datasets is a novel method to identify outcomes to explore the impact of genetic variation.ObjectiveUse data linkage to identify and validate patient outcomes following surgical treatment for CHD.MethodsData linkage between clinical and biobank data of children born from 2001-2014 that had a procedure for CHD in New South Wales, Australia, with hospital discharge data, education and death data. The children were grouped according to CHD lesion type and age at first cardiac surgery. Children in each 'lesion/age at surgery group' were classified into 'favourable' and 'unfavourable' cardiovascular outcome groups based on variables identified in linked administrative data including; total time in intensive care, total length of stay in hospital, and mechanical ventilation time up to 5 years following the date of the first cardiac surgery. A blind medical record audit of 200 randomly chosen children from 'favourable' and 'unfavourable' outcome groups was performed to validate the outcome groups.ResultsOf the 1872 children in the dataset that linked to hospital or death data, 483 were identified with a 'favourable' cardiovascular outcome and 484 were identified as having a 'unfavourable' cardiovascular outcome. The medical record audit found concordant outcome groups for 182/192 records (95%) compared to the outcome groups categorized using the linked data.ConclusionsThe linkage of a curated biobank dataset with routinely collected administrative data is a reliable method to identify outcomes to facilitate a large-scale study to examine genetic variance. These genetic hallmarks could be used to identify patients who are at risk of unfavourable cardiovascular outcomes, to inform strategies for prevention and changes in clinical care.
| S-EPMC10897946 | biostudies-literature
Project description:BackgroundCardiovascular disease (CVD) is the leading cause of death for all non-cancer deaths among breast cancer (BC) patients. The aim of this study was to investigate the risk of cardiovascular mortality (CVM) in patients with BC.MethodsPatients diagnosed with primary BC between 2010 and 2018 were identified through the Surveillance, Epidemiology and End Results (SEER) database. The standardized mortality ratio (SMR) for CVD was calculated to compare the CVM of BC patients with that of the general population. Multivariate competing risk models were performed to identify predictors of CVM in BC patients.ResultsOverall, 399,014 BC patients were included from the SEER database, of whom 7,023 (1.8%) suffered death from CVD. The significantly higher overall SMR of CVM was observed in BC patients [SMR =4.84, 95% confidence interval (CI): 4.72-4.95]. Multivariate competing risk regression analysis revealed that age, race, American Joint Committee on Cancer (AJCC) stage, year of diagnosis, estrogen receptor (ER) status, progesterone receptor (PR) status, human epidermal growth factor receptor 2 (HER2) status, BC subtype, surgery, chemotherapy, radiation therapy, and median household income as independent predictors of CVM in BC patients.ConclusionsCompared to the general population, BC patients have a higher risk of experiencing CVM during the follow-up period after diagnosis. Early detection and intervention of cardiovascular risk factors would improve overall survival (OS) of BC patients.
| S-EPMC10774043 | biostudies-literature