984 resultados para LIKELIHOOD RATIO TESTS
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Developments in the statistical analysis of compositional data over the last two decades have made possible a much deeper exploration of the nature of variability, and the possible processes associated with compositional data sets from many disciplines. In this paper we concentrate on geochemical data sets. First we explain how hypotheses of compositional variability may be formulated within the natural sample space, the unit simplex, including useful hypotheses of subcompositional discrimination and specific perturbational change. Then we develop through standard methodology, such as generalised likelihood ratio tests, statistical tools to allow the systematic investigation of a complete lattice of such hypotheses. Some of these tests are simple adaptations of existing multivariate tests but others require special construction. We comment on the use of graphical methods in compositional data analysis and on the ordination of specimens. The recent development of the concept of compositional processes is then explained together with the necessary tools for a staying- in-the-simplex approach, namely compositional singular value decompositions. All these statistical techniques are illustrated for a substantial compositional data set, consisting of 209 major-oxide and rare-element compositions of metamorphosed limestones from the Northeast and Central Highlands of Scotland. Finally we point out a number of unresolved problems in the statistical analysis of compositional processes
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Phylogenetic comparative methods are increasingly used to give new insights into the dynamics of trait evolution in deep time. For continuous traits the core of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the properties of these models are often poorly understood, which can lead to the misinterpretation of results. Here we focus on one of these models – the Ornstein Uhlenbeck (OU) model. We show that the OU model is frequently incorrectly favoured over simpler models when using Likelihood ratio tests, and that many studies fitting this model use datasets that are small and prone to this problem. We also show that very small amounts of error in datasets can have profound effects on the inferences derived from OU models. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model. We conclude by making recommendations for best practice in fitting OU models in phylogenetic comparative analyses, and for interpreting the parameters of the OU model.
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We review some issues related to the implications of different missing data mechanisms on statistical inference for contingency tables and consider simulation studies to compare the results obtained under such models to those where the units with missing data are disregarded. We confirm that although, in general, analyses under the correct missing at random and missing completely at random models are more efficient even for small sample sizes, there are exceptions where they may not improve the results obtained by ignoring the partially classified data. We show that under the missing not at random (MNAR) model, estimates on the boundary of the parameter space as well as lack of identifiability of the parameters of saturated models may be associated with undesirable asymptotic properties of maximum likelihood estimators and likelihood ratio tests; even in standard cases the bias of the estimators may be low only for very large samples. We also show that the probability of a boundary solution obtained under the correct MNAR model may be large even for large samples and that, consequently, we may not always conclude that a MNAR model is misspecified because the estimate is on the boundary of the parameter space.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Informações de genealogia e produção, cedidas pela Associação Brasileira de Criadores da Raça Simental (ABCRS), relativas aos pesos desde o nascimento até um ano de idade, foram utilizadas para estimar, sob modelos alternativos, os componentes de variância e os parâmetros genéticos em animais da raça Simental no Brasil. A matriz de parentesco incluiu 25.812 animais dos quais 7587 com dados de produção. O modelo 1 contém, além do erro, o efeito genético direto. Os modelos seguintes contêm os componentes do modelo 1, mais o efeito permanente de ambiente materno (modelo 2), ou o componente genético materno (modelo 3), ambos os componentes (modelo 5), os componentes do modelo 3 mais a covariância entre os efeitos genéticos direto e materno (modelo 4) e todos os componentes citados (modelo 6). Os modelos foram comparados pelo teste de razão de verossimilhança pelo chi² (P<0,01). Os componentes de variância e os valores de herdabilidades, estimados para os efeitos direto e materno, foram decrescentes, desde o modelo 1 até o modelo 6, na razão direta em que o modelo incorpora mais efeitos aleatórios. Para a fase de aleitamento foi encontrada variância genética nula, entretanto, alto valor para a variância de ambiente permanente. Os efeitos maternos, genético e de ambiente permanente são importantes para a raça Simental no Brasil e devem ser considerados em programas de seleção. Entretanto, os valores mais elevados de herdabilidade materna, encontrados com modelos sem efeito de ambiente permanente, sugerem que o método utilizado não discrimina apropriadamente esses efeitos, oriundos de mesma fonte de variação.
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The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.
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Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.
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Background Where malaria endemicity is low, control programmes need increasingly sensitive tools for monitoring malaria transmission intensity (MTI) and to better define health priorities. A cross-sectional survey was conducted in a low endemicity area of the Peruvian north-western coast to assess the MTI using both molecular and serological tools. Methods Epidemiological, parasitological and serological data were collected from 2,667 individuals in three settlements of Bellavista district, in May 2010. Parasite infection was detected using microscopy and polymerase chain reaction (PCR). Antibodies to Plasmodium vivax merozoite surface protein-119 (PvMSP119) and to Plasmodium falciparum glutamate-rich protein (PfGLURP) were detected by ELISA. Risk factors for exposure to malaria (seropositivity) were assessed by multivariate survey logistic regression models. Age-specific antibody prevalence of both P. falciparum and P. vivax were analysed using a previously published catalytic conversion model based on maximum likelihood for generating seroconversion rates (SCR). Results The overall parasite prevalence by microscopy and PCR were extremely low: 0.3 and 0.9%, respectively for P. vivax, and 0 and 0.04%, respectively for P. falciparum, while seroprevalence was much higher, 13.6% for P. vivax and 9.8% for P. falciparum. Settlement, age and occupation as moto-taxi driver during previous year were significantly associated with P. falciparum exposure, while age and distance to the water drain were associated with P. vivax exposure. Likelihood ratio tests supported age seroprevalence curves with two SCR for both P. vivax and P. falciparum indicating significant changes in the MTI over time. The SCR for PfGLURP was 19-fold lower after 2002 as compared to before (λ1 = 0.022 versus λ2 = 0.431), and the SCR for PvMSP119 was four-fold higher after 2006 as compared to before (λ1 = 0.024 versus λ2 = 0.006). Conclusion Combining molecular and serological tools considerably enhanced the capacity of detecting current and past exposure to malaria infections and related risks factors in this very low endemicity area. This allowed for an improved characterization of the current human reservoir of infections, largely hidden and heterogeneous, as well as providing insights into recent changes in species specific MTIs. This approach will be of key importance for evaluating and monitoring future malaria elimination strategies.
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Obiettivo Valutare l’ipotesi secondo cui la movimentazione manuale di carichi possa essere un fattore di rischio per il di distacco di retina. Metodi Si è condotto uno studio caso-controllo ospedaliero multicentrico, a Bologna, (reparto di Oculistica del policlinico S. Orsola Malpighi, Prof. Campos), e a Brescia (reparto di oculistica “Spedali Civili” Prof. Semeraro). I casi sono 104 pazienti operati per distacco di retina. I controlli sono 173 pazienti reclutati tra l’utenza degli ambulatori del medesimo reparto di provenienza dei casi. Sia i casi che i controlli (all’oscuro dall’ipotesi in studio) sono stati sottoposti ad un’intervista, attraverso un questionario strutturato concernente caratteristiche individuali, patologie pregresse e fattori di rischio professionali (e non) relativi al distacco di retina. I dati relativi alla movimentazione manuale di carichi sono stati utilizzati per creare un “indice di sollevamento cumulativo―ICS” (peso del carico sollevato x numero di sollevamenti/ora x numero di anni di sollevamento). Sono stati calcolati mediante un modello di regressione logistica unconditional (aggiustato per età e sesso) gli Odds Ratio (OR) relativi all’associazione tra distacco di retina e vari fattori di rischio, tra cui la movimentazione manuale di carichi. Risultati Oltre alla chirurgia oculare e alla miopia (fattori di rischio noti), si evidenzia un trend positivo tra l’aumento dell’ICS e il rischio di distacco della retina. Il rischio maggiore si osserva per la categoria di sollevamento severo (OR 3.6, IC 95%, 1.5–9.0). Conclusione I risultati, mostrano un maggiore rischio di sviluppare distacco di retina per coloro che svolgono attività lavorative che comportino la movimentazione manuale di carichi e, a conferma di quanto riportato in letteratura, anche per i soggetti miopi e per coloro che sono stati sottoposti ad intervento di cataratta. Si rende quindi evidente l’importanza degli interventi di prevenzione in soggetti addetti alla movimentazione manuale di carichi, in particolare se miopi.
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QUESTIONS UNDER STUDY: To assess whether the prevalence of HIV positive tests in clients at five anonymous testing sites in Switzerland had increased since the end of the 1990s, and ascertain whether there had been any concurrent change in the proportions of associated risk factors. METHODS: Baseline characteristics were analysed, by groups of years, over the eleven consecutive years of data collected from the testing sites. Numbers of HIV positive tests were presented as prevalence/1000 tests performed within each category. Multivariable analyses, stratified by African nationality and risk group of heterosexuals or men who have sex with men (MSM), were done controlling simultaneously for a series of variables. Odds ratios (ORs) were reported together with their 95% confidence intervals (CI). P values were calculated from likelihood ratio tests. RESULTS: There was an increase in the prevalence of positive tests in African heterosexuals between 1996-1999 and 2004-2006, rising from 54.2 to 86.4/1000 and from 5.6 to 25.2/1000 in females and males respectively. The proportion of MSM who knew that one or more of their sexual partners was infected with HIV increased from 2% to 17% and the proportion who reported having more than five sexual partners in the preceding two years increased from 44% to 51%. CONCLUSIONS: Surveillance data from anonymous testing sites continue to provide useful information on the changing epidemiology of HIV and thus inform public health strategies against HIV.
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Coronary heart disease remains the leading cause of death in the United States and increased blood cholesterol level has been found to be a major risk factor with roots in childhood. Tracking of cholesterol, i.e., the tendency to maintain a particular cholesterol level relative to the rest of the population, and variability in blood lipid levels with increase in age have implications for cholesterol screening and assessment of lipid levels in children for possible prevention of further rise to prevent adulthood heart disease. In this study the pattern of change in plasma lipids, over time, and their tracking were investigated. Also, within-person variance and retest reliability defined as the square root of within-person variance for plasma total cholesterol, HDL-cholesterol, LDL-cholesterol, and triglycerides and their relation to age, sex and body mass index among participants from age 8 to 18 years were investigated. ^ In Project HeartBeat!, 678 healthy children aged 8, 11 and 14 years at baseline were enrolled and examined at 4-monthly intervals for up to 4 years. We examined the relationship between repeated observations by Pearson's correlations. Age- and sex-specific quintiles were calculated and the probability of participants to remain in the uppermost quintile of their respective distribution was evaluated with life table methods. Plasma total cholesterol, HDL-C and LDL-C at baseline were strongly and significantly correlated with measurements at subsequent visits across the sex and age groups. Plasma triglyceride at baseline was also significantly correlated with subsequent measurements but less strongly than was the case for other plasma lipids. The probability to remain in the upper quintile was also high (60 to 70%) for plasma total cholesterol, HDL-C and LDL-C. ^ We used a mixed longitudinal, or synthetic cohort design with continuous observations from age 8 to 18 years to estimate within person variance of plasma total cholesterol, HDL-C, LDL-C and triglycerides. A total of 5809 measurements were available for both cholesterol and triglycerides. A multilevel linear model was used. Within-person variance among repeated measures over up to four years of follow-up was estimated for total cholesterol, HDL-C, LDL-C and triglycerides separately. The relationship of within-person and inter-individual variance with age, sex, and body mass index was evaluated. Likelihood ratio tests were conducted by calculating the deviation of −2log (likelihood) within the basic model and alternative models. The square root of within-person variance provided the retest reliability (within person standard deviation) for plasma total cholesterol, HDL-C, LDL-C and triglycerides. We found 13.6 percent retest reliability for plasma cholesterol, 6.1 percent for HDL-cholesterol, 11.9 percent for LDL-cholesterol and 32.4 percent for triglycerides. Retest reliability of plasma lipids was significantly related with age and body mass index. It increased with increase in body mass index and age. These findings have implications for screening guidelines, as participants in the uppermost quintile tended to maintain their status in each of the age groups during a four-year follow-up. The magnitude of within-person variability of plasma lipids influences the ability to classify children into risk categories recommended by the National Cholesterol Education Program. ^
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Prostate cancer (PrCa) is a leading cause of morbidity and mortality, yet the etiology remains uncertain. Meta-analyses show that PrCa risk is reduced by 16% in men with type 2 diabetes (T2D), but the mechanism is unknown. Recent genome-wide association studies and meta-analyses have found single nucleotide polymorphisms (SNPs) that consistently predict T2D risk. We evaluated associations of incident PrCa with 14 T2D SNPs in the Atherosclerosis Risk in Communities (ARIC) study. From 1987-2000, there were 397 incident PrCa cases ascertained from state or local cancer registries among 6,642 men (1,560 blacks and 5,082 whites) aged 45-64 years at baseline. Genotypes were determined by TaqMan assay. Cox proportional hazards models were used to assess the association between PrCa and increasing number of T2D risk-raising alleles for individual SNPs and for genetic risk scores (GRS) comprised of the number of T2D risk-raising alleles across SNPs. Two-way gene-gene interactions were evaluated with likelihood ratio tests. Using additive genetic models, the T2D risk-raising allele was associated with significantly reduced risk of PrCa for IGF2BP2 rs4402960 (hazard ratio [HR]=0.79; P=0.07 among blacks only), SLC2A2 rs5400 (race-adjusted HR=0.85; P=0.05) and UCP2 rs660339 (race-adjusted HR=0.84; P=0.02), but significantly increased risk of PrCa for CAPN10 rs3792267 (race-adjusted HR=1.20; P=0.05). No other SNPs were associated with PrCa using an additive genetic model. However, at least one copy of the T2D risk-raising allele for TCF7L2 rs7903146 was associated with reduced PrCa risk using a dominant genetic model (race-adjusted HR=0.79; P=0.03). These results imply that the T2D-PrCa association may be partly due to shared genetic variation, but these results should be verified since multiple tests were performed. When the combined, additive effects of these SNPs were tested using a GRS, there was nearly a 10% reduction in risk of PrCa per T2D risk-raising allele (race-adjusted HR=0.92; P=0.02). SNPs in IGF2BP2, KCNJ11 and SLC2A2 were also involved in multiple synergistic gene-gene interactions on a multiplicative scale. In conclusion, it appears that the T2D-PrCa association may be due, in part, to common genetic variation. Further knowledge of T2D gene-PrCa mechanisms may improve understanding of PrCa etiology and may inform PrCa prevention and treatment.^
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Purpose: The purpose of this paper is to analyse differences in the drivers of firm innovation performance across sectors. The literature often makes the assumption that firms in different sectors differ in their propensity to innovate but not in the drivers of innovation. The authors empirically assess whether this assumption is accurate through a series of econometric estimations and tests. Design/methodology/approach: The data used are derived from the Irish Community Innovation Survey 2004-2006. A series of multivariate probit models are estimated and the resulting coefficients are tested for parameter stability across sectors using likelihood ratio tests. Findings: The results indicate that there is a strong degree of heterogeneity in the drivers of innovation across sectors. The determinants of process, organisational, new to firm and new to market innovation varies across sectors suggesting that the pooling of sectors in an innovation production function may lead to biased inferences. Research limitations/implications: The implications of the results are that innovation policies targeted at stimulating innovation need to be tailored to particular industries. One size fits all policies would seem inappropriate given the large degree of heterogeneity observed across the drivers of innovation in different sectors. Originality/value: The value of this paper is that it provides an empirical test as to whether it is suitable to group sectoral data when estimating innovation production functions. Most papers simply include sectoral dummies, implying that only the propensity to innovate differs across sectors and that the slope of the coefficient estimates are in fact consistent across sectors.
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Trypanosomiasis has been identified as a neglected tropical disease in both humans and animals in many regions of sub-Saharan Africa. Whilst assessments of the biology of trypanosomes, vectors, vertebrate hosts and the environment have provided useful information about life cycles, transmission, and pathogenesis of the parasites that could be used for treatment and control, less information is available about the effects of interactions among multiple intrinsic factors on trypanosome presence in tsetse flies from different sites. It is known that multiple species of tsetse flies can transmit trypanosomes but differences in their vector competence has normally been studied in relation to individual factors in isolation, such as: intrinsic factors of the flies (e.g. age, sex); habitat characteristics; presence of endosymbionts (e.g. Wigglesworthia glossinidia, Sodalis glossinidius); feeding pattern; host communities that the flies feed on; and which species of trypanosomes are transmitted. The purpose of this study was to take a more integrated approach to investigate trypanosome prevalence in tsetse flies. In chapter 2, techniques were optimised for using the Polymerase Chain Reaction (PCR) to identify species of trypanosomes (Trypanosoma vivax, T. congolense, T. brucei, T. simiae, and T. godfreyi) present in four species of tsetse flies (Glossina austeni, G. brevipalpis, G. longipennis and G. pallidipes) from two regions of eastern Kenya (the Shimba Hills and Nguruman). Based on universal primers targeting the internal transcribed spacer 1 region (ITS-1), T. vivax was the predominant pathogenic species detected in flies, both singly and in combination with other species of trypanosomes. Using Generalised Linear Models (GLMs) and likelihood ratio tests to choose the best-fitting models, presence of T. vivax was significantly associated with an interaction between subpopulation (a combination between collection sites and species of Glossina) and sex of the flies (X2 = 7.52, df = 21, P-value = 0.0061); prevalence in females overall was higher than in males but this was not consistent across subpopulations. Similarly, T. congolense was significantly associated only with subpopulation (X2 = 18.77, df = 1, P-value = 0.0046); prevalence was higher overall in the Shimba Hills than in Nguruman but this pattern varied by species of tsetse fly. When associations were analysed in individual species of tsetse flies, there were no consistent associations between trypanosome prevalence and any single factor (site, sex, age) and different combinations of interactions were found to be significant for each. The results thus demonstrated complex interactions between vectors and trypanosome prevalence related to both the distribution and intrinsic factors of tsetse flies. The potential influence of the presence of S. glossinidius on trypanosome presence in tsetse flies was studied in chapter 3. A high number of Sodalis positive flies was found in the Shimba Hills, while there were only two positive flies from Nguruman. Presence or absence of Sodalis was significantly associated with subpopulation while trypanosome presence showed a significant association with age (X2 = 4.65, df = 14, P-value = 0.0310) and an interaction between subpopulation and sex (X2 = 18.94, df = 10, P-value = 0.0043). However, the specific associations that were significant varied across species of trypanosomes, with T. congolense and T. brucei but not T. vivax showing significant interactions involving Sodalis. Although it has previously been concluded that presence of Sodalis increases susceptibility to trypanosomes, the results presented here suggest a more complicated relationship, which may be biased by differences in the distribution and intrinsic factors of tsetse flies, as well as which trypanosome species are considered. In chapter 4 trypanosome status was studied in relation to blood meal sources, feeding status and feeding patterns of G. pallidipes (which was the predominant fly species collected for this study) as determined by sequencing the mitochondrial cytochrome B gene using DNA extracted from abdomen samples. African buffalo and African elephants were the main sources of blood meals but antelopes, warthogs, humans, giraffes and hyenas were also identified. Feeding on multiple hosts was common in flies sampled from the Shimba Hills but most flies from Nguruman had fed on single host species. Based on Multiple Correspondence Analysis (MCA), host-feeding patterns showed a correlation with site of sample collection and Sodalis status, while trypanosome status was correlated with sex and age of the flies, suggesting that recent host-feeding patterns from blood meal analysis cannot predict trypanosome status. In conclusion, the complexity of interactions found suggests that strategies of tsetse fly control should be specific to particular epidemic areas. Future studies should include laboratory experiments that use local colonies of tsetse flies, local strains of trypanosomes and local S. glossinidius under controlled environmental conditions to tease out the factors that affect vector competence and the relative influence of external environmental factors on the dynamics of these interactions.
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Cardiovascular disease is one of the leading causes of death around the world. Resting heart rate has been shown to be a strong and independent risk marker for adverse cardiovascular events and mortality, and yet its role as a predictor of risk is somewhat overlooked in clinical practice. With the aim of highlighting its prognostic value, the role of resting heart rate as a risk marker for death and other adverse outcomes was further examined in a number of different patient populations. A systematic review of studies that previously assessed the prognostic value of resting heart rate for mortality and other adverse cardiovascular outcomes was presented. New analyses of nine clinical trials were carried out. Both the original and extended Cox model that allows for analysis of time-dependent covariates were used to evaluate and compare the predictive value of baseline and time-updated heart rate measurements for adverse outcomes in the CAPRICORN, EUROPA, PROSPER, PERFORM, BEAUTIFUL and SHIFT populations. Pooled individual patient meta-analyses of the CAPRICORN, EPHESUS, OPTIMAAL and VALIANT trials, and the BEAUTIFUL and SHIFT trials, were also performed. The discrimination and calibration of the models applied were evaluated using Harrell’s C-statistic and likelihood ratio tests, respectively. Finally, following on from the systematic review, meta-analyses of the relation between baseline and time-updated heart rate, and the risk of death from any cause and from cardiovascular causes, were conducted. Both elevated baseline and time-updated resting heart rates were found to be associated with an increase in the risk of mortality and other adverse cardiovascular events in all of the populations analysed. In some cases, elevated time-updated heart rate was associated with risk of events where baseline heart rate was not. Time-updated heart rate also contributed additional information about the risk of certain events despite knowledge of baseline heart rate or previous heart rate measurements. The addition of resting heart rate to the models where resting heart rate was found to be associated with risk of outcome improved both discrimination and calibration, and in general, the models including time-updated heart rate along with baseline or the previous heart rate measurement had the highest and similar C-statistics, and thus the greatest discriminative ability. The meta-analyses demonstrated that a 5bpm higher baseline heart rate was associated with a 7.9% and an 8.0% increase in the risk of all-cause and cardiovascular death, respectively (both p less than 0.001). Additionally, a 5bpm higher time-updated heart rate (adjusted for baseline heart rate in eight of the ten studies included in the analyses) was associated with a 12.8% (p less than 0.001) and a 10.9% (p less than 0.001) increase in the risk of all-cause and cardiovascular death, respectively. These findings may motivate health care professionals to routinely assess resting heart rate in order to identify individuals at a higher risk of adverse events. The fact that the addition of time-updated resting heart rate improved the discrimination and calibration of models for certain outcomes, even if only modestly, strengthens the case that it be added to traditional risk models. The findings, however, are of particular importance, and have greater implications for the clinical management of patients with pre-existing disease. An elevated, or increasing heart rate over time could be used as a tool, potentially alongside other established risk scores, to help doctors identify patient deterioration or those at higher risk, who might benefit from more intensive monitoring or treatment re-evaluation. Further exploration of the role of continuous recording of resting heart rate, say, when patients are at home, would be informative. In addition, investigation into the cost-effectiveness and optimal frequency of resting heart rate measurement is required. One of the most vital areas for future research is the definition of an objective cut-off value for the definition of a high resting heart rate.