Explore the vast range of titles available.

Background Step-count monitors (pedometers, body-worn trackers and smartphone applications) can increase walking, helping to tackle physical inactivity. We aimed to assess the effect of step-count monitors on physical activity (PA) in randomised controlled trials (RCTs) amongst community-dwelling adults; including longer-term effects, differences between step-count monitors, and between intervention components. Methods Systematic literature searches in seven databases identified RCTs in healthy adults, or those at risk of disease, published between January 2000–April 2020. Two reviewers independently selected studies, extracted data and assessed risk of bias. Outcome was mean differences (MD) with 95% confidence intervals (CI) in steps at follow-up between treatment and control groups. Our preferred outcome measure was from studies with follow-up steps adjusted for baseline steps (change studies); but we also included studies reporting follow-up differences only (end-point studies). Multivariate-meta-analysis used random-effect estimates at different time-points for change studies only. Meta-regression compared effects of different step-count monitors and intervention components amongst all studies at ≤4 months. Results Of 12,491 records identified, 70 RCTs (at generally low risk of bias) were included, with 57 trials (16,355 participants) included in meta-analyses: 32 provided change from baseline data; 25 provided end-point only. Multivariate meta-analysis of the 32 change studies demonstrated step-counts favoured intervention groups: MD of 1126 steps/day 95%CI [787, 1466] at ≤4 months, 1050 steps/day [602, 1498] at 6 months, 464 steps/day [301, 626] at 1 year, 121 steps/day [− 64, 306] at 2 years and 434 steps/day [191, 676] at 3–4 years. Meta-regression of the 57 trials at ≤4 months demonstrated in mutually-adjusted analyses that: end-point were similar to change studies (+ 257 steps/day [− 417, 931]); body-worn trackers/smartphone applications were less effective than pedometers (− 834 steps/day [− 1542, − 126]); and interventions providing additional counselling/incentives were not better than those without (− 812 steps/day [− 1503, − 122]). Conclusions Step-count monitoring leads to short and long-term step-count increases, with no evidence that either body-worn trackers/smartphone applications, or additional counselling/incentives offer further benefit over simpler pedometer-based interventions. Simple step-count monitoring interventions should be prioritised to address the public health physical inactivity challenge. Systematic review registration PROSPERO number CRD42017075810 .

In the UK, large-scale electronic primary care datasets can provide up-to-date, accurate epidemiological information on rarer diseases, where specialist diagnoses from hospital discharges and clinic letters are generally well recorded and electronically searchable. Current estimates of the number of people living with neuromuscular disease (NMD) have largely been based on secondary care data sources and lacked direct denominators. To estimate trends in the recording of neuromuscular disease in UK primary care between 2000-2019. The Clinical Practice Research Datalink (CPRD) database was searched electronically to estimate incidence and prevalence rates (per 100,000) for a range of NMDs in each year. To compare trends over time, rates were age standardised to the most recent CPRD population (2019). Approximately 13 million patients were actively registered in each year. By 2019, 28,230 active patients had ever received a NMD diagnosis (223.6), which was higher among males (239.0) than females (208.3). The most common classifications were Guillain-Barre syndrome (40.1), myasthenia gravis (33.7), muscular dystrophy (29.5), Charcot-Marie-Tooth (29.5) and inflammatory myopathies (25.0). Since 2000, overall prevalence grew by 63%, with the largest increases seen at older ages (≥65-years). However, overall incidence remained constant, though myasthenia gravis incidence has risen steadily since 2008, while new cases of muscular dystrophy fell over the same period. Lifetime recording of many NMDs on primary care records exceed current estimates of people living with these conditions; these are important data for health service and care planning. Temporal trends suggest this number is steadily increasing, and while this may partially be due to better recording, it cannot be simply explained by new cases, as incidence remained constant. The increase in prevalence among older ages suggests increases in life expectancy among those living with NMDs may have occurred.

These recommendations were systematically developed on behalf of the Network for Early Onset Cystic Kidney Disease (NEOCYST) by an international group of experts in autosomal dominant polycystic kidney disease (ADPKD) from paediatric and adult nephrology, human genetics, paediatric radiology and ethics specialties together with patient representatives. They have been endorsed by the International Pediatric Nephrology Association (IPNA) and the European Society of Paediatric Nephrology (ESPN). For asymptomatic minors at risk of ADPKD, ongoing surveillance (repeated screening for treatable disease manifestations without diagnostic testing) or immediate diagnostic screening are equally valid clinical approaches. Ultrasonography is the current radiological method of choice for screening. Sonographic detection of one or more cysts in an at-risk child is highly suggestive of ADPKD, but a negative scan cannot rule out ADPKD in childhood. Genetic testing is recommended for infants with very-early-onset symptomatic disease and for children with a negative family history and progressive disease. Children with a positive family history and either confirmed or unknown disease status should be monitored for hypertension (preferably by ambulatory blood pressure monitoring) and albuminuria. Currently, vasopressin antagonists should not be offered routinely but off-label use can be considered in selected children. No consensus was reached on the use of statins, but mTOR inhibitors and somatostatin analogues are not recommended. Children with ADPKD should be strongly encouraged to achieve the low dietary salt intake that is recommended for all children.This Consensus Statement developed on behalf of the Network for Early Onset Cystic Kidney Disease provides guidance on counselling, diagnosing and monitoring children with autosomal dominant polycystic kidney disease based on current evidence and a multi-stakeholder discussion of ethical issues.

Medication use in pregnancy is common and increasing. Pregnant women are often excluded from drug trials, therefore the safety to mother and baby of many medications used in pregnancy is unknown. Routine health data have been used to look for evidence of harm and safety of specific medications, but not to systematically look across all prescribed medications in pregnancy. To systematically identify medications prescribed during pregnancy requiring further research into their potential harms to mother or baby. We will describe trends in primary care prescribing in pregnancy over time, and socio-demographic patterning of prescribing, using data from pregnancies in the Clinical Practice Research Datalink (CPRD). We will identify and categorise maternal, fetal, and infant adverse outcomes reported in the CPRD and linked hospital and mortality data. We will use Bayesian signal detection models to analyse all medication/outcome pairs to identify where an outcome occurs significantly more frequently in mothers prescribed a specific medication than in mothers not prescribed it. Potential confounders will not be accounted for at this stage. Published evidence on the identified medication/outcome pairs will be reviewed and incorporated with the results from trends and signal detection analyses. These data will be used by Patient Involvement and Study Advisory Board workshops to prioritise medications for further research, with medications more commonly prescribed for underserved groups being given precedence. For three prioritised signals, cohort analyses will compare the occurrence of adverse outcomes in those prescribed compared to those not prescribed the medication of interest, adjusting for maternal morbidity, co-medications, and other measured confounders. This project will provide a list of medications used in pregnancy that should be prioritised for further safety research. Results of three detailed retrospective cohort studies will contribute to informed decision making for patients and clinicians. Study grant number: NIHR207172; CPRD accepted protocol number: 24_004518.

Type 2 diabetes (T2D) is more common in certain ethnic groups. This systematic review compares mortality risk between people with T2D from different ethnic groups and includes recent larger studies. We searched nine databases using PRISMA guidelines (PROSPERO CRD42022372542). We included community-based prospective studies among adults with T2D from at least two different ethnicities. Two independent reviewers undertook screening, data extraction and quality assessment using the Newcastle-Ottawa Scale. The primary outcome compared all-cause mortality rates between ethnic groups (hazard ratio (HR) with 95% confidence intervals). From 30,825 searched records, we included 13 studies (7 meta-analysed), incorporating 573,173 T2D participants; 12 were good quality. Mortality risk was lower amongst people with T2D from South Asian [HR 0.68 (0.65-0.72)], Black [HR 0.82 (0.77-0.87)] and Chinese [HR 0.57 (0.46-0.70)] ethnicity compared to people of White ethnicity. Narrative synthesis corroborated these findings but demonstrated that people of indigenous Māori ethnicity had greater mortality risk compared to European ethnicity. People with T2D of South Asian, Black and Chinese ethnicity have lower all-cause mortality risk than White ethnicity, with Māori ethnicity having higher mortality risk. Factors explaining mortality differences require further study, including understanding complication risk by ethnicity, to improve diabetes outcomes.

The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period. To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19. Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into \"usual\" and \"excess\" components, assuming 2015-19 rates represented \"usual\" mortality. The association of each RF with the 2020 \"excess\" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR). RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64. Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data.

Physical inactivity is an important cause of noncommunicable diseases. Interventions can increase short-term physical activity (PA), but health benefits require maintenance. Few interventions have evaluated PA objectively beyond 12 months. We followed up two pedometer interventions with positive 12-month effects to examine objective PA levels at 3-4 years. Long-term follow-up of two completed trials: Pedometer And Consultation Evaluation-UP (PACE-UP) 3-arm (postal, nurse support, control) at 3 years and Pedometer Accelerometer Consultation Evaluation-Lift (PACE-Lift) 2-arm (nurse support, control) at 4 years post-baseline. Randomly selected patients from 10 United Kingdom primary care practices were recruited (PACE-UP: 45-75 years, PACE-Lift: 60-75 years). Intervention arms received 12-week walking programmes (pedometer, handbooks, PA diaries) postally (PACE-UP) or with nurse support (PACE-UP, PACE-Lift). Main outcomes were changes in 7-day accelerometer average daily step counts and weekly time in moderate-to-vigorous PA (MVPA) in ≥10-minute bouts in intervention versus control groups, between baseline and 3 years (PACE-UP) and 4 years (PACE-Lift). PACE-UP 3-year follow-up was 67% (681/1,023) (mean age: 59, 64% female), and PACE-Lift 4-year follow-up was 76% (225/298) (mean age: 67, 53% female). PACE-UP 3-year intervention versus control comparisons were as follows: additional steps/day postal +627 (95% CI: 198-1,056), p = 0.004, nurse +670 (95% CI: 237-1,102), p = 0.002; total weekly MVPA in bouts (minutes/week) postal +28 (95% CI: 7-49), p = 0.009, nurse +24 (95% CI: 3-45), p = 0.03. PACE-Lift 4-year intervention versus control comparisons were: +407 (95% CI: -177-992), p = 0.17 steps/day, and +32 (95% CI: 5-60), p = 0.02 minutes/week MVPA in bouts. Neither trial showed sedentary or wear-time differences. Main study limitation was incomplete follow-up; however, results were robust to missing data sensitivity analyses. Intervention participants followed up from both trials demonstrated higher levels of objectively measured PA at 3-4 years than controls, similar to previously reported 12-month trial effects. Pedometer interventions, delivered by post or with nurse support, can help address the public health physical inactivity challenge. PACE-UP isrctn.com ISRCTN98538934; PACE-Lift isrctn.com ISRCTN42122561.

Brisk walking in older people can increase step-counts and moderate to vigorous intensity physical activity (MVPA) in ≥10-minute bouts, as advised in World Health Organization guidelines. Previous interventions have reported step-count increases, but not change in objectively measured MVPA in older people. We assessed whether a primary care nurse-delivered complex intervention increased objectively measured step-counts and MVPA. A total of 988 60-75 year olds, able to increase walking and randomly selected from three UK family practices, were invited to participate in a parallel two-arm cluster randomised trial; randomisation was by household. Two-hundred-ninety-eight people from 250 households were randomised between 2011 and 2012; 150 individuals to the intervention group, 148 to the usual care control group. Intervention participants received four primary care nurse physical activity (PA) consultations over 3 months, incorporating behaviour change techniques, pedometer step-count and accelerometer PA intensity feedback, and an individual PA diary and plan. Assessors were not blinded to group status, but statistical analyses were conducted blind. The primary outcome was change in accelerometry assessed average daily step-counts between baseline and 3 months, with change at 12 months a secondary outcome. Other secondary outcomes were change from baseline in time in MVPA weekly in ≥10-minute bouts, accelerometer counts, and counts/minute at 3 months and 12 months. Other outcomes were adverse events, anthropometric measures, mood, and pain. Qualitative evaluations of intervention participants and practice nurses assessed the intervention's acceptability. At 3 months, eight participants had withdrawn or were lost to follow-up, 280 (94%) individuals provided primary outcome data. At 3 months changes in both average daily step-counts and weekly MVPA in ≥10-minute bouts were significantly higher in the intervention than control group: by 1,037 (95% CI 513-1,560) steps/day and 63 (95% CI 40-87) minutes/week, respectively. At 12 months corresponding differences were 609 (95% CI 104-1,115) steps/day and 40 (95% CI 17-63) minutes/week. Counts and counts/minute showed similar effects to steps and MVPA. Adverse events, anthropometry, mood, and pain were similar in the two groups. Participants and practice nurses found the intervention acceptable and enjoyable. The PACE-Lift trial increased both step-counts and objectively measured MVPA in ≥10-minute bouts in 60-75 year olds at 3 and 12 months, with no effect on adverse events. To our knowledge, this is the first trial in this age group to demonstrate objective MVPA increases and highlights the value of individualised support incorporating objective PA assessment in a primary care setting. Controlled-Trials.com ISRCTN42122561.

Background Migrants to the UK face disproportionate risk of infections, non-communicable diseases, and under-immunisation compounded by healthcare access barriers. Current UK migrant screening strategies are unstandardised with poor implementation and low uptake. Health Catch-UP! is a collaboratively produced digital clinical decision support system that applies current guidelines (UKHSA and NICE) to provide primary care professionals with individualised multi-disease screening (7 infectious diseases/blood-borne viruses, 3 chronic parasitic infections, 3 non-communicable disease or risk factors) and catch-up vaccination prompts for migrant patients. Methods We carried out a mixed-methods process evaluation of Health Catch-UP! in two urban primary healthcare practices to integrate Health Catch-UP! into the electronic health record system of primary care, using the Medical Research Council framework for complex intervention evaluation. We collected quantitative data (demographics, patients screened, disease detection and catch-up vaccination rates) and qualitative participant interviews to explore acceptability and feasibility. Results Ninety-nine migrants were assessed by Health Catch-UP! across two sites (S1, S2). 96.0% ( n  = 97) had complete demographics coding with Asia 31.3% ( n  = 31) and Africa 25.2% ( n  = 25), the most common continents of birth (S1 n  = 92 [48.9% female ( n  = 44); mean age 60.6 years (SD 14.26)]; and S2 n  = 7 [85.7% male ( n  = 6); mean age 39.4 years (SD16.97)]. 61.6% ( n  = 61) of participants were eligible for screening for at least one condition and uptake of screening was high 86.9% ( n  = 53). Twelve new conditions were identified (12.1% of study population) including hepatitis C ( n  = 1), hypercholesteraemia ( n  = 6), pre-diabetes ( n  = 4), and diabetes ( n  = 1). Health Catch-UP! identified that 100% ( n  = 99) of patients had no immunisations recorded; however, subsequent catch-up vaccination uptake was poor (2.0%, n  = 1). Qualitative data supported acceptability and feasibility of Health Catch-UP! from staff and patient perspectives, and recommended Health Catch-UP! integration into routine care (e.g. NHS health checks) with an implementation package including staff and patient support materials, standardised care pathways (screening and catch-up vaccination, laboratory, and management), and financial incentivisation. Conclusions Clinical Decision Support Systems like Health Catch-UP! can improve disease detection and implementation of screening guidance for migrant patients but require robust testing, resourcing, and an effective implementation package to support both patients and staff.

Pedometers can increase walking and moderate-to-vigorous physical activity (MVPA) levels, but their effectiveness with or without support has not been rigorously evaluated. We assessed the effectiveness of a pedometer-based walking intervention in predominantly inactive adults, delivered by post or through primary care nurse-supported physical activity (PA) consultations. A parallel three-arm cluster randomised trial was randomised by household, with 12-mo follow-up, in seven London, United Kingdom, primary care practices. Eleven thousand fifteen randomly selected patients aged 45-75 y without PA contraindications were invited. Five hundred forty-eight self-reporting achieving PA guidelines were excluded. One thousand twenty-three people from 922 households were randomised between 2012-2013 to one of the following groups: usual care (n = 338); postal pedometer intervention (n = 339); and nurse-supported pedometer intervention (n = 346). Of these, 956 participants (93%) provided outcome data (usual care n = 323, postal n = 312, nurse-supported n = 321). Both intervention groups received pedometers, 12-wk walking programmes, and PA diaries. The nurse group was offered three PA consultations. Primary and main secondary outcomes were changes from baseline to 12 mo in average daily step-counts and time in MVPA (in ≥10-min bouts), respectively, measured objectively by accelerometry. Only statisticians were masked to group. Analysis was by intention-to-treat. Average baseline daily step-count was 7,479 (standard deviation [s.d.] 2,671), and average time in MVPA bouts was 94 (s.d. 102) min/wk. At 12 mo, mean steps/d, with s.d. in parentheses, were as follows: control 7,246 (2,671); postal 8,010 (2,922); and nurse support 8,131 (3,228). PA increased in both intervention groups compared with the control group; additional steps/d were 642 for postal (95% CI 329-955) and 677 for nurse support (95% CI 365-989); additional MVPA in bouts (min/wk) were 33 for postal (95% CI 17-49) and 35 for nurse support (95% CI 19-51). There were no significant differences between the two interventions at 12 mo. The 10% (1,023/10,467) recruitment rate was a study limitation. A primary care pedometer-based walking intervention in predominantly inactive 45- to 75-y-olds increased step-counts by about one-tenth and time in MVPA in bouts by about one-third. Nurse and postal delivery achieved similar 12-mo PA outcomes. A primary care pedometer intervention delivered by post or with minimal support could help address the public health physical inactivity challenge. isrctn.com ISRCTN98538934.