Effect of age on the prognostic value of left ventricular function in patients with acute coronary syndrome:a prospective registry study

Objective: This study aims to study the prognostic impact of LV function on mortality and examine the effect of age on the prognostic value of left ventricular function.  Methods: We examined the Myocardial Ischaemia National Audit Project (MINAP) registry (2006-2010) data with a mean follow up of 2.1 years. LV function was categorized into good (ejection fraction (EF) ≥50%), moderate (EF 30-49%) and poor (EF <30%) categories. Cox-proportional hazards models were constructed to examine the prognostic significance of LV function in different age groups (<65, 65-74, 75-84 and ≥85 years) on all-cause mortality adjusting for baseline variables.  Results: Of 424,848 patients, LV function data available for 123,609. Multiple imputations were used to impute missing values of LV function and the final sample for analyses were drawn from 414,305. After controlling for confounders, 339,887 participants were included in the regression models. For any age group, mortality was higher with worsening degree of LV impairment. Increased age reduced the adverse prognosis associated with reduced LV function (hazard ratios (HRs) of death comparing poor LV function to good LV function were 2.11 95%CI 1.88-2.37 for age <65 years and 1.28 95%CI 1.20-1.36 for age ≥85 years. Older patients had a high mortality risk even in those with good LV function. HRs of mortality for ≥85 compared to <65 years (HR=1.00) within good, moderate and poor ejection fractions groups were 5.89, 4.86 and 3.43, respectively.  Conclusions: In patients with ACS, clinicians should interpret the prognostic value of LV function taking into account patient’s age

How do dataset characteristics affect the performance of propensity score methods and regression for controlling confounding in observational studies?:A simulation study

In observational studies, researchers must select a method to control for confounding. Options include propensity score methods and regression. It remains unclear how dataset characteristics (size, overlap in propensity scores, exposure prevalence) influence the relative performance of the methods, making it difficult to select the best method for a particular dataset. A simulation study to evaluate the role of dataset characteristics on the performance of propensity score methods, compared to logistic regression, for estimating a marginal odds ratio in the presence of confounding was conducted. Outcomes were simulated from logistic and complementary log-log models, and size, overlap in propensity scores, and prevalence of the exposure were varied. Regression showed poor coverage for small sample sizes, but with large sample sizes it was more robust to imbalance in propensity scores and low exposure prevalence than were propensity score methods. Propensity score methods frequently displayed suboptimal coverage, particularly as overlap in propensity scores decreased. These problems were exacerbated at larger sample sizes. Power of matching methods was particularly affected by lack of overlap, low prevalence of exposure, and small sample size. Performance of inverse probability of treatment weighting depended heavily on dataset characteristics, with poor coverage and bias with low overlap. The advantage of regression for large data size was less clear in sensitivity analysis with a complementary log-log outcome generation mechanism and unmeasured confounding, with superior bias and error but lower coverage than nearest neighbour and caliper matching

Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis

Background Primary care provides the foundation for most modern health-care systems, and in the interests of equity, it should be resourced according to local need. We aimed to describe spatially the burden of chronic conditions and primary medical care funding in England at a low geographical level, and to measure how much variation in funding is explained by chronic condition prevalence and other patient and regional factors. Methods We used multiple administrative data sets including chronic condition prevalence and management data (2014/15), funding for primary-care practices (2015-16), and geographical and area deprivation data (2015). Data were assigned to a low geographical level (average 1500 residents). We investigated the overall morbidity burden across 19 chronic conditions and its regional variation, spatial clustering and association with funding and area deprivation. A linear regression model was used to explain local variation in spending using patient demographics, morbidity, deprivation and regional characteristics. Results Levels of morbidity varied within and between regions, with several clusters of very high morbidity identified. At the regional level, morbidity was modestly associated with practice funding, with the North East and North West appearing underfunded. The regression model explained 39% of the variability in practice funding, but even after adjusting for covariates, a large amount of variability in funding existed across regions. High morbidity and, especially, rural location were very strongly associated with higher practice funding, while associations were more modest for high deprivation and older age. Conclusions Primary care funding in England does not adequately reflect the contemporary morbidity burden. More equitable resource allocation could be achieved by making better use of routinely available information and big data resources. Similar methods could be deployed in other countries where comparable data are collected, to identify morbidity clusters and to target funding to areas of greater need

Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study

OBJECTIVE: Clinically applicable diabetes severity measures are lacking, with no previous studies comparing their predictive value with glycated hemoglobin (HbA1c). We developed and validated a type 2 diabetes severity score (the DIabetes Severity SCOre, DISSCO) and evaluated its association with risks of hospitalization and mortality, assessing its additional risk information to sociodemographic factors and HbA1c. RESEARCH DESIGN AND METHODS: We used UK primary and secondary care data for 139 626 individuals with type 2 diabetes between 2007 and 2017, aged ≥35 years, and registered in general practices in England. The study cohort was randomly divided into a training cohort (n=111 748, 80%) to develop the severity tool and a validation cohort (n=27 878). We developed baseline and longitudinal severity scores using 34 diabetes-related domains. Cox regression models (adjusted for age, gender, ethnicity, deprivation, and HbA1c) were used for primary (all-cause mortality) and secondary (hospitalization due to any cause, diabetes, hypoglycemia, or cardiovascular disease or procedures) outcomes. Likelihood ratio (LR) tests were fitted to assess the significance of adding DISSCO to the sociodemographics and HbA1c models. RESULTS: A total of 139 626 patients registered in 400 general practices, aged 63±12 years were included, 45% of whom were women, 83% were White, and 18% were from deprived areas. The mean baseline severity score was 1.3±2.0. Overall, 27 362 (20%) people died and 99 951 (72%) had ≥1 hospitalization. In the training cohort, a one-unit increase in baseline DISSCO was associated with higher hazard of mortality (HR: 1.14, 95% CI 1.13 to 1.15, area under the receiver operating characteristics curve (AUROC)=0.76) and cardiovascular hospitalization (HR: 1.45, 95% CI 1.43 to 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to sociodemographic variables significantly improved the predictive value of survival models, outperforming the added value of HbA1c for all outcomes. Findings were consistent in the validation cohort. CONCLUSIONS: Higher levels of DISSCO are associated with higher risks for hospital admissions and mortality. The new severity score had higher predictive value than the proxy used in clinical practice, HbA1c. This reproducible algorithm can help practitioners stratify clinical care of patients with type 2 diabetes

Relationship between anemia and mortality outcomes in a national acute coronary syndrome cohort: Insights from the UK Myocardial Ischemia National Audit Project registry

Background: We aim to determine the prevalence of anemia in ACS patients and compared their clinical characteristics, management and clinical outcomes to those without anemia in an unselected national ACS cohort. Methods and Results: The Myocardial Ischemia National Audit Project (MINAP) registry collects data on all adults admitted to hospital trusts in England and Wales with diagnosis of an ACS. We conducted a retrospective cohort study by analyzing patients in this registry between January 2006 and December 2010 and followed them up until August 2011. Multiple logistic regressions were used to determine factors associated with anemia and the adjusted odds of 30-day mortality with 1 g/dl incremental hemoglobin increase and the 30-days and 1-year mortality for anemic compared to non-anemic groups. Analyses were adjusted for covariates. Our analysis of 422,855 patients with ACS showed that 27.7% of patients presenting with ACS are anemic, and that these patients are older, have a greater prevalence renal disease, peripheral vascular disease, diabetes mellitus and previous acute myocardial infarction and are less likely to receive evidence based therapies shown to improve clinical outcomes. Finally our analysis suggests that anemia is independently associated with 30-day (OR 1.28, 95%CI 1.22-1.35) and 1-year mortality (OR 1.31, 95%CI 1.27-1.35) and we observed a reverse J-shaped relationship between hemoglobin levels and mortality outcomes. Conclusion: The prevalence of anemia in a contemporary national ACS cohort is clinically significant. Patients with anemia are older and multi-morbid, and less likely to receive evidence-based therapies shown to improve clinical outcomes with the presence of anemia independently associated mortality outcomes

Excess mortality in England and Wales during the first wave of the COVID-19 pandemic

Background: Deaths during the COVID-19 pandemic result directly from infection and exacerbation of other diseases and indirectly from deferment of care for other conditions, and are socially and geographically patterned. We quantified excess mortality in regions of England and Wales during the pandemic, for all causes and for non-COVID-19-associated deaths. Methods: Weekly mortality data for 1 January 2010 to 1 May 2020 for England and Wales were obtained from the Office of National Statistics. Mean-dispersion negative binomial regressions were used to model death counts based on pre-pandemic trends and exponentiated linear predictions were subtracted from: (i) all-cause deaths and (ii) all-cause deaths minus COVID-19 related deaths for the pandemic period (week starting 7 March, to week ending 8 May). Findings: Between 7 March and 8 May 2020, there were 47 243 (95% CI: 46 671 to 47 815) excess deaths in England and Wales, of which 9948 (95% CI: 9376 to 10 520) were not associated with COVID-19. Overall excess mortality rates varied from 49 per 100 000 (95% CI: 49 to 50) in the South West to 102 per 100 000 (95% CI: 102 to 103) in London. Non-COVID-19 associated excess mortality rates ranged from −1 per 100 000 (95% CI: −1 to 0) in Wales (ie, mortality rates were no higher than expected) to 26 per 100 000 (95% CI: 25 to 26) in the West Midlands. Interpretation: The COVID-19 pandemic has had markedly different impacts on the regions of England and Wales, both for deaths directly attributable to COVID-19 infection and for d

Hand dysfunction after transradial artery catheterization for coronary procedures

AIM To sythesize the available literature on hand dysfunction after transradial catheterization. METHODS We searched MEDLINE and EMBASE. The search results were reviewed by two independent judicators for studies that met the inclusion criteria and relevant reviews. We included studies that evaluated any transradial procedure and evaluated hand function outcomes post transradial procedure. There were no restrictions based on sample size. There was no restriction on method of assessing hand function which included disability, nerve damage, motor or sensory loss. There was no restriction based on language of study. Data was extracted, these results were narratively synthesized. RESULTS Out of 555 total studies 13 studies were finally included in review. A total of 3815 participants with mean age of 62.5 years were included in this review. A variety of methods were used to assess sensory and motor dysfunction of hand. Out of 13 studies included, only 3 studies reported nerve damage with a combined incidence of 0.16%, 5 studies reported sensory loss, tingling and numbness with a pooled incidence of 1.52%. Pain after transradial access was the most common form of hand dysfunction (6.67%) reported in 3 studies. The incidence of hand dysfunction defined as disability, grip strength change, power loss or any other hand complication was incredibly low at 0.26%. Although radial artery occlusion was not our primary end point for this review, it was observed in 2.41% of the participants in total of five studies included. CONCLUSION Hand dysfunction may occur post transradial catheterisation and majority of symptoms resolve without any clinical sequel