Objective To systematically review studies quantifying the associations of long term (clinic), mid-term (home), and short term (ambulatory) variability in blood pressure, independent of mean blood pressure, with cardiovascular disease events and mortality. Data sources Medline, Embase, Cinahl, and Web of Science, searched to 15 February 2016 for full text articles in English. Eligibility criteria for study selection Prospective cohort studies or clinical trials in adults, except those in patients receiving haemodialysis, where the condition may directly impact blood pressure variability. Standardised hazard ratios were extracted and, if there was little risk of confounding, combined using random effects meta-analysis in main analyses. Outcomes included all cause and cardiovascular disease mortality and cardiovascular disease events. Measures of variability included standard deviation, coefficient of variation, variation independent of mean, and average real variability, but not night dipping or day-night variation. Results 41 papers representing 19 observational cohort studies and 17 clinical trial cohorts, comprising 46 separate analyses were identified. Long term variability in blood pressure was studied in 24 papers, mid-term in four, and short-term in 15 (two studied both long term and short term variability). Results from 23 analyses were excluded from main analyses owing to high risks of confounding. Increased long term variability in systolic blood pressure was associated with risk of all cause mortality (hazard ratio 1.15, 95% confidence interval 1.09 to 1.22), cardiovascular disease mortality (1.18, 1.09 to 1.28), cardiovascular disease events (1.18, 1.07 to 1.30), coronary heart disease (1.10, 1.04 to 1.16), and stroke (1.15, 1.04 to 1.27). Increased mid-term and short term variability in daytime systolic blood pressure were also associated with all cause mortality (1.15, 1.06 to 1.26 and 1.10, 1.04 to 1.16, respectively). Conclusions Long term variability in blood pressure is associated with cardiovascular and mortality outcomes, over and above the effect of mean blood pressure. Associations are similar in magnitude to those of cholesterol measures with cardiovascular disease. Limited data for mid-term and short term variability showed similar associations. Future work should focus on the clinical implications of assessment of variability in blood pressure and avoid the common confounding pitfalls observed to date. Systematic review registration PROSPERO CRD42014015695.

Objectives: To report reliable estimates of short term and long term survival rates for people with a diagnosis of heart failure and to assess trends over time by year of diagnosis, hospital admission, and socioeconomic group. Design: Population based cohort study. Setting: Primary care, United Kingdom. Participants: Primary care data for 55 959 patients aged 45 and over with a new diagnosis of heart failure and 278 679 age and sex matched controls in the Clinical Practice Research Datalink from 1 January 2000 to 31 December 2017 and linked to inpatient Hospital Episode Statistics and Office for National Statistics mortality data. Main outcome measures: Survival rates at one, five, and 10 years and cause of death for people with and without heart failure; and temporal trends in survival by year of diagnosis, hospital admission, and socioeconomic group. Results: Overall, one, five, and 10 year survival rates increased by 6.6% (from 74.2% in 2000 to 80.8% in 2016), 7.2% (from 41.0% in 2000 to 48.2% in 2012), and 6.4% (from 19.8% in 2000 to 26.2% in 2007), respectively. There were 30 906 deaths in the heart failure group over the study period. Heart failure was listed on the death certificate in 13 093 (42.4%) of these patients, and in 2237 (7.2%) it was the primary cause of death. Improvement in survival was greater for patients not requiring admission to hospital around the time of diagnosis (median difference 2.4 years; 5.3 v 2.9 years, P<0.001). There was a deprivation gap in median survival of 0.5 years between people who were least deprived and those who were most deprived (4.6 v 4.1 years, P<0.001). Conclusions: Survival after a diagnosis of heart failure has shown only modest improvement in the 21st century and lags behind other serious conditions, such as cancer. New strategies to achieve timely diagnosis and treatment initiation in primary care for all socioeconomic groups should be a priority for future research and policy.

Objective: To assess the associations between statins and adverse events in primary prevention of cardiovascular disease and to examine how the associations vary by type and dosage of statins. Design: Systematic review and meta-analysis. Data sources: Studies were identified from previous systematic reviews and searched in Medline, Embase, and the Cochrane Central Register of Controlled Trials, up to August 2020. Review methods: Randomised controlled trials in adults without a history of cardiovascular disease that compared statins with non-statin controls or compared different types or dosages of statins were included. Main outcome measures: Primary outcomes were common adverse events: self-reported muscle symptoms, clinically confirmed muscle disorders, liver dysfunction, renal insufficiency, diabetes, and eye conditions. Secondary outcomes included myocardial infarction, stroke, and death from cardiovascular disease as measures of efficacy. Data synthesis: A pairwise meta-analysis was conducted to calculate odds ratios and 95% confidence intervals for each outcome between statins and non-statin controls, and the absolute risk difference in the number of events per 10 000 patients treated for a year was estimated. A network meta-analysis was performed to compare the adverse effects of different types of statins. An E _max model based meta-analysis was used to examine the dose-response relationships of the adverse effects of each statin. Results: 62 trials were included, with 120 456 participants followed up for an average of 3.9 years. Statins were associated with an increased risk of self-reported muscle symptoms (21 trials, odds ratio 1.06 (95% confidence interval 1.01 to 1.13); absolute risk difference 15 (95% confidence interval 1 to 29)), liver dysfunction (21 trials, odds ratio 1.33 (1.12 to 1.58); absolute risk difference 8 (3 to 14)), renal insufficiency (eight trials, odds ratio 1.14 (1.01 to 1.28); absolute risk difference 12 (1 to 24)), and eye conditions (six trials, odds ratio 1.23 (1.04 to 1.47); absolute risk difference 14 (2 to 29)) but were not associated with clinically confirmed muscle disorders or diabetes. The increased risks did not outweigh the reduction in the risk of major cardiovascular events. Atorvastatin, lovastatin, and rosuvastatin were individually associated with some adverse events, but few significant differences were found between types of statins. An E _max dose-response relationship was identified for the effect of atorvastatin on liver dysfunction, but the dose-response relationships for the other statins and adverse effects were inconclusive. Conclusions: For primary prevention of cardiovascular disease, the risk of adverse events attributable to statins was low and did not outweigh their efficacy in preventing cardiovascular disease, suggesting that the benefit-to-harm balance of statins is generally favourable. Evidence to support tailoring the type or dosage of statins to account for safety concerns before starting treatment was limited. Systematic review registration: PROSPERO CRD42020169955.

Background: Excess weight and unexpected weight loss are associated with multiple disease states and increased morbidity and mortality, but weight measurement is not routine in many primary care settings. The aim of this study was to characterise who has had their weight recorded in UK primary care, how frequently, by whom and in relation to which clinical events, symptoms and diagnoses. Methods: A longitudinal analysis of UK primary care electronic health records (EHR) data from 2000 to 2017. Descriptive statistics were used to summarise weight recording in terms of patient sociodemographic characteristics, health professional encounters, clinical events, symptoms and diagnoses. Negative binomial regression was used to model the likelihood of having a weight record each year, and Cox regression to the likelihood of repeated weight recording. Results: A total of 14,049,871 weight records were identified in the EHR of 4,918,746 patients during the study period, representing 26,998,591 person-years of observation. Around a third of patients had a weight record each year. Forty-nine percent of weight records were repeated within a year with an average time to a repeat weight record of 1.92 years. Weight records were most often taken by nursing staff (38–42%) and GPs (37–39%) as part of a routine clinical care, such as chronic disease reviews (16%), medication reviews (6–8%) and health checks (6–7%), or were associated with consultations for contraception (5–8%), respiratory disease (5%) and obesity (1%). Patient characteristics independently associated with an increased likelihood of weight recording were as follows: female sex, younger and older adults, non-drinkers, ex-smokers, low or high BMI, being more deprived, diagnosed with a greater number of comorbidities and consulting more frequently. The effect of policy-level incentives to record weight did not appear to be sustained after they were removed. Conclusion: Weight recording is not a routine activity in UK primary care. It is recorded for around a third of patients each year and is repeated on average every 2 years for these patients. It is more common in females with higher BMI and in those with comorbidity. Incentive payments and their removal appear to be associated with increases and decreases in weight recording.

Hypertension has been identified as a risk factor for coronavirus disease 2019 (COVID-19) and associated adverse outcomes. This study examined the association between preinfection blood pressure (BP) control and COVID-19 outcomes using data from 460 general practices in England. Eligible patients were adults with hypertension who were tested or diagnosed with COVID-19. BP control was defined by the most recent BP reading within 24 months of the index date (January 1, 2020). BP was defined as controlled (<130/80 mm Hg), raised (130/80–139/89 mm Hg), stage 1 uncontrolled (140/90–159/99 mm Hg), or stage 2 uncontrolled (≥160/100 mm Hg). The primary outcome was death within 28 days of COVID-19 diagnosis. Secondary outcomes were COVID-19 diagnosis and COVID-19–related hospital admission. Multivariable logistic regression was used to examine the association between BP control and outcomes. Of the 45 418 patients (mean age, 67 years; 44.7% male) included, 11 950 (26.3%) had controlled BP. These patients were older, had more comorbidities, and had been diagnosed with hypertension for longer. A total of 4277 patients (9.4%) were diagnosed with COVID-19 and 877 died within 28 days. Individuals with stage 1 uncontrolled BP had lower odds of COVID-19 death (odds ratio, 0.76 [95% CI, 0.62–0.92]) compared with patients with well-controlled BP. There was no association between BP control and COVID-19 diagnosis or hospitalization. These findings suggest BP control may be associated with worse COVID-19 outcomes, possibly due to these patients having more advanced atherosclerosis and target organ damage. Such patients may need to consider adhering to stricter social distancing, to limit the impact of COVID-19 as future waves of the pandemic occur.

Background: Natriuretic peptide (NP) testing is recommended for patients presenting to primary care with symptoms of chronic heart failure (HF) to prioritise referral for diagnosis.Aim: To report NP test performance at European Society of Cardiology (ESC) and National Institute for Health and Care Excellence (NICE) guideline referral thresholds.Design and setting: Diagnostic accuracy study using linked primary and secondary care data (2004 to 2018).Method: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of NP testing for HF diagnosis was assessed.Results: In total, 229 580 patients had an NP test and 21 102 (9.2%) were diagnosed with HF within 6 months. The ESC NT-proBNP threshold ≥125 pg/mL had a sensitivity of 94.6% (95% confidence interval [CI] = 94.2 to 95.0) and specificity of 50.0% (95% CI = 49.7 to 50.3), compared with sensitivity of 81.7% (95% CI = 81.0 to 82.3) and specificity of 80.3% (95% CI = 80.0 to 80.5) for the NICE NT-proBNP ≥400 pg/mL threshold. PPVs for an NT-proBNP test were 16.4% (95% CI = 16.1 to 16.6) and 30.0% (95% CI = 29.6 to 30.5) for ESC and NICE thresholds, respectively. For both guidelines, nearly all patients with an NT-proBNP level below the threshold did not have HF (NPV: ESC 98.9%, 95% CI = 98.8 to 99.0 and NICE 97.7%, 95% CI = 97.6 to 97.8).Conclusion: At the higher NICE chronic HF guideline NP thresholds, one in five cases are initially missed in primary care but the lower ESC thresholds require more diagnostic assessments. NP is a reliable ‘rule-out’ test at both cut-points. The optimal NP threshold will depend on the priorities and capacity of the healthcare system.