Threshold Haemoglobin Levels and the Prognosis of Stable Coronary Disease: Two New Cohorts and a Systematic Review and Meta-Analysis

Background: Low haemoglobin concentration has been associated with adverse prognosis in patients with angina and myocardial infarction (MI), but the strength and shape of the association and the presence of any threshold has not been precisely evaluated.Methods and findings: A retrospective cohort study was carried out using the UK General Practice Research Database. 20,131 people with a new diagnosis of stable angina and no previous acute coronary syndrome, and 14,171 people with first MI who survived for at least 7 days were followed up for a mean of 3.2 years. Using semi-parametric Cox regression and multiple adjustment, there was evidence of threshold haemoglobin values below which mortality increased in a graded continuous fashion. For men with MI, the threshold value was 13.5 g/dl (95% confidence interval [CI] 13.2-13.9); the 29.5% of patients with haemoglobin below this threshold had an associated hazard ratio for mortality of 2.00 (95% CI 1.76-2.29) compared to those with haemoglobin values in the lowest risk range. Women tended to have lower threshold haemoglobin values (e. g, for MI 12.8 g/dl; 95% CI 12.1-13.5) but the shape and strength of association did not differ between the genders, nor between patients with angina and MI. We did a systematic review and meta-analysis that identified ten previously published studies, reporting a total of only 1,127 endpoints, but none evaluated thresholds of risk.Conclusions: There is an association between low haemoglobin concentration and increased mortality. A large proportion of patients with coronary disease have haemoglobin concentrations below the thresholds of risk defined here. Intervention trials would clarify whether increasing the haemoglobin concentration reduces mortality

Search Filters for Finding Prognostic and Diagnostic Prediction Studies in Medline to Enhance Systematic Reviews

Background: The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter. Methodology/Principal Findings: Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next -using word frequency methods - we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85. Conclusions/Significance: Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studie

Neighbourhood Socioeconomics Status Predicts Non-Cardiovascular Mortality in Cardiac Patients with Access to Universal Health Care

BACKGROUND: Although the Canadian health care system provides essential services to all residents, evidence suggests that socioeconomic gradients in disease outcomes still persist. The main objective of our study was to investigate whether mortality, from cardiovascular disease or other causes, varies by neighbourhood socioeconomic gradients in patients accessing the healthcare system for cardiovascular disease management. METHODS AND FINDINGS: A cohort of 485 patients with angiographic evidence of coronary artery disease (CAD) and neighbourhood socioeconomic status information was followed for 13.3 years. Survival analyses were completed with adjustment for potentially confounding risk factors. There were 64 cases of cardiovascular mortality and 66 deaths from non-cardiovascular chronic diseases. No socioeconomic differentials in cardiovascular mortality were observed. However, lower neighbourhood employment, education, and median family income did predict an increased risk of mortality from non-cardiovascular chronic diseases. For each quintile decrease in neighbourhood socioeconomic status, non-cardiovascular mortality risk rose by 21-30%. Covariate-adjusted hazard ratios (95% confidence interval) for non-cardiovascular mortality were 1.21 (1.02-1.42), 1.21 (1.01-1.46), and 1.30 (1.06-1.60), for each quintile decrease in neighbourhood education, employment, and income, respectively. These patterns were primarily attributable to mortality from cancer. Estimated risks for mortality from cancer rose by 42% and 62% for each one quintile decrease in neighbourhood median income and employment rate, respectively. Although only baseline clinical information was collected and patient-level socioeconomic data were not available, our results suggest that environmental socioeconomic factors have a significant impact on CAD patient survival. CONCLUSIONS: Despite public health care access, CAD patients who reside in lower-socioeconomic neighbourhoods show increased vulnerability to non-cardiovascular chronic disease mortality, particularly in the domain of cancer. These findings prompt further research exploring mechanisms of neighbourhood effects on health, and ways they may be ameliorated

An analysis of sickness absence in chronically ill patients receiving Complementary and Alternative Medicine: A longterm prospective intermittent study

BACKGROUND: The popularity of complementary and alternative medicine (CAM) has led to a growing amount of research in this area. All the same little is known about the effects of these special treatments in every-day practice of primary care, delivered by general practitioners within the health insurance system. From 1994 to 2000 more than 20 German Company health insurances initiated the first model project on CAM according to the German social law. Aim of this contribution is to investigate the effectiveness of multi-modal CAM on chronic diseases within primary health care. METHODS: A long-term prospective intermittent study was conducted including 44 CAM practitioners and 1221 self-selected chronically ill patients (64% women) of whom 441 were employed. Main outcome measure is sick-leave, controlled for secular trends and regression-to-the mean and self-perceived health status. RESULTS: Sick-leave per year of 441 patients at work increased from 22 (SD ± 45.2) to 31 (± 61.0) days within three years prior to intervention, and decreased to 24 (± 55.6) in the second year of treatment, sustaining at this level in the following two years. Detailed statistical analysis show that this development exceeds secular trends and the regression-toward-the-mean effect. Sick-leave reduction was corroborated by data on self-reported improvement of patients' health status. CONCLUSION: Results of this longterm observational study show a reduction of sick leave in chronically ill patients after a complex multimodal CAM intervention. However, as this is an uncontrolled observational study efficacy of any specific CAM treatment can not be proven. The results might indicate an general effectiveness of CAM in primary care, worthwhile further investigations. Future studies should identify the most suitable patients for CAM practices, the most appropriate and safe treatments, provide information on the magnitude of the effects to facilitate subsequent definitive randomised controlled studies that will help to position complementary and alternative medicine in health care

The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the <it>An. gambiae </it>complex. <it>Anopheles gambiae </it>is one of four DVS within the <it>An. gambiae </it>complex, the others being <it>An. arabiensis </it>and the coastal <it>An. merus </it>and <it>An. melas</it>. There are a further three, highly anthropophilic DVS in Africa, <it>An. funestus</it>, <it>An. moucheti </it>and <it>An. nili</it>. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed.</p> <p>Results</p> <p>A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method.</p> <p>Conclusions</p> <p>The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: <it>Anopheles </it>(<it>Cellia</it>) <it>arabiensis</it>, <it>An. </it>(<it>Cel.</it>) <it>funestus*</it>, <it>An. </it>(<it>Cel.</it>) <it>gambiae</it>, <it>An. </it>(<it>Cel.</it>) <it>melas</it>, <it>An. </it>(<it>Cel.</it>) <it>merus</it>, <it>An. </it>(<it>Cel.</it>) <it>moucheti </it>and <it>An. </it>(<it>Cel.</it>) <it>nili*</it>, and in the European and Middle Eastern Region: <it>An. </it>(<it>Anopheles</it>) <it>atroparvus</it>, <it>An. </it>(<it>Ano.</it>) <it>labranchiae</it>, <it>An. </it>(<it>Ano.</it>) <it>messeae</it>, <it>An. </it>(<it>Ano.</it>) <it>sacharovi</it>, <it>An. </it>(<it>Cel.</it>) <it>sergentii </it>and <it>An. </it>(<it>Cel.</it>) <it>superpictus*</it>. These maps are presented alongside a bionomics summary for each species relevant to its control.</p