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Improving prescribing antibiotics appropriately for respiratory infections in primary care is an antimicrobial stewardship priority. There is limited evidence to support interventions to reduce prescribing antibiotics in out-of-hours (OOH) primary care. Herein, we report a service innovation where point-of-care C-Reactive Protein (CRP) machines were introduced to three out-of-hours primary care clinical bases in England from August 2018–December 2019, which were compared with four control bases that did not have point-of-care CRP testing. We undertook a mixed-method evaluation, including a comparative interrupted time series analysis to compare monthly antibiotic prescription rates between bases with CRP machines and those without, an analysis of the number of and reasons for the tests performed, and qualitative interviews with clinicians. Antibiotic prescription rates declined during follow-up, but with no clear difference between the two groups of out-of-hours practices. A single base contributed 217 of the 248 CRP tests performed. Clinicians reported that the tests supported decision making and communication about not prescribing antibiotics, where having ‘objective’ numbers were helpful in navigating non-prescribing decisions and highlighted the challenges of training a fluctuant staff group and practical concerns about using the CRP machine. Service improvements to reduce prescribing antibiotics in out-of-hours primary care need to be developed with an understanding of the needs and context of this service.

Background Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e‐liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update conducted as part of a living systematic review. Objectives To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long‐term smoking abstinence. Search methods We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 May 2021, and reference‐checked and contacted study authors. We screened abstracts from the Society for Research on Nicotine and Tobacco (SRNT) 2021 Annual Meeting. Selection criteria We included randomized controlled trials (RCTs) and randomized cross‐over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both. Data collection and analysis We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow‐up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants or both. We used a fixed‐effect Mantel‐Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta‐analyses. Main results We included 61 completed studies, representing 16,759 participants, of which 34 were RCTs. Five of the 61 included studies were new to this review update. Of the included studies, we rated seven (all contributing to our main comparisons) at low risk of bias overall, 42 at high risk overall (including all non‐randomized studies), and the remainder at unclear risk. There was moderate‐certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.53, 95% confidence interval (CI) 1.21 to 1.93; I2 = 0%; 4 studies, 1924 participants). In absolute terms, this might translate to an additional three quitters per 100 (95% CI 1 to 6). There was low‐certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.44, 95% CI 0.94 to 2.19: I2 = 0; 3 studies, 1183 participants). There was moderate‐certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non‐nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate‐certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 0.95, 95% CI 0.52 to 1.72; I2 = 0; 6 studies, 1033 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.61, 95% CI 1.44 to 4.74; I2 = 0%; 6 studies, 2886 participants). In absolute terms this represents an additional six quitters per 100 (95% CI 2 to 15). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that non‐serious AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants), and again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.51, 95% CI 0.70 to 3.24; I2 = 0%; 7 studies, 1303 participants). Data from non‐randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit. Authors' conclusions There is moderate‐certainty evidence that ECs with nicotine increase quit rates compared to NRT and compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non‐nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect evidence of harm from nicotine EC, but longest follow‐up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up‐to‐date information to decision‐makers, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Worldwide, around 800 000 people die each year from suicide,1 which is the leading cause of death in the UK in young adults.2 Prediction modelling studies have attempted to incorporate demographic, clinical and other factors to identify high-risk individuals so that appropriate interventions can be offered.3 4 This approach has a large literature but has not always been judged successful. In one review, all 35 suicide risk prediction studies assessed were classified as having high risk of bias or insufficient diagnostic accuracy, based on targets of 80% sensitivity and 50% specificity.5 Others have written of a performance ‘glass ceiling’ in suicide prediction, and even that ‘risk categorization of individual patients has no role to play in preventing the suicide of psychiatric inpatients’.6 In spite of the mortality data quoted previously, in most populations, risk of death from suicide is low, usually below 1%. This has led to claims about performance of prediction models that appear counterintuitive, such as ‘suicide prediction models produce accurate overall classification models, but their accuracy of predicting a future event is near 0’, while noting that even in high-risk populations, the positive predictive value (PPV) of many prediction rules may be less than 1%.3 We describe two principal reasons why the nature of developing clinical prediction rules in low prevalence scenarios will almost invariably result in concerns about performance, on standards by which this is usually judged. Although we focus primarily on suicide prediction, these points apply more generally to other low prevalence clinical areas, some examples of which are also discussed. ### The effect of low prevalence on sample size Low prevalence can have a prohibitive impact on sample size requirements because of the need to observe enough outcome events for model development, as also noted in diagnostic evaluation studies.7 For example, consider a single risk factor that …

An appreciation of experimental design is an important aspect of introductory statistics teaching in a wide range of applied disciplines, including medical statistics. Understanding the impact of design decisions on the choice of analysis method and subsequent interpretation of results can help to embed the importance of statistical thinking in the experimental process. I discuss an interactive exercise, based on R.A. Fisher's celebrated “Lady Tasting Tea” experiment, that is intended to raise awareness of design issues as part of an undergraduate statistics module. The exercise used a discovery approach, with students encouraged to identify design issues and agree on solutions themselves via small group discussion, with only low-level prompting from the instructor. The value of this teaching style and possible extensions of the tea-tasting experiment to other related topics suitable for more widespread use are also discussed.

Objectives: This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To conduct component network meta‐analyses (cNMAs) to investigate the comparative effectiveness, safety and tolerability of different smoking cessation pharmacotherapies and electronic cigarettes (EC), singly and combined, when helping people to stop smoking tobacco. To investigate: how the different characteristics of smoking cessation pharmacotherapies and EC interventions (e.g. intervention subtype, dose, length of intervention, whether the intervention is used prequit as well as from quit date or from quit date only) influence efficacy, safety and tolerability; whether identifiable participant characteristics and behavioural support suggest different optimal intervention strategies.

This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To assess the evidence on the relationship between the use and availability of e‐cigarettes and subsequent cigarette smoking in young people (aged 29 years or less), and whether the relationship differs by socioeconomic status, gender, or other demographic characteristics.

Jason Oke and Tom Fanshawe expose four simple biases that can change our understanding of cancer survival rates and skew comparisons made between countries

ObjectivesTo inform point-of-care test (POCT) development, we quantified the primary care demand for laboratory microbiology tests by describing their frequencies overall, frequencies of positives, most common organisms identified, temporal trends in testing and patterns of cotesting on the same and subsequent dates.DesignRetrospective cohort study.SettingPrimary care practices in Oxfordshire.Participants393 905 patients (65% female; 49% aged 18–49).Primary and secondary outcome measuresThe frequencies of all microbiology tests requested between 2008 and 2018 were quantified. Patterns of cotesting were investigated with heat maps. All analyses were done overall, by sex and age categories.Results1 596 752 microbiology tests were requested. Urine culture±microscopy was the most common of all tests (n=673 612, 42%), was mainly requested without other tests and was the most common test requested in follow-up within 7 and 14 days. Of all urine cultures, 180 047 (27%) were positive and 172 651 (26%) showed mixed growth, and Escherichia coli was the most prevalent organism (132 277, 73% of positive urine cultures). Antenatal urine cultures and blood tests in pregnancy (hepatitis B, HIV and syphilis) formed a common test combination, consistent with their use in antenatal screening.ConclusionsThe greatest burden of microbiology testing in primary care is attributable to urine culture ± microscopy; genital and routine antenatal urine and blood testing are also significant contributors. Further research should focus on the feasibility and impact of POCTs for these specimen types.

Background There has been a rapid growth in the publication of new prediction models relevant to child and adolescent mental health. However, before their implementation into clinical services, it is necessary to appraise the quality of their methods and reporting. We conducted a systematic review of new prediction models in child and adolescent mental health, and examined their development and validation. Method We searched five databases for studies developing or validating multivariable prediction models for individuals aged 18 years old or younger from 1 January 2018 to 18 February 2021. Quality of reporting was assessed using the Transparent Reporting of a multivariable prediction models for Individual Prognosis Or Diagnosis checklist, and quality of methodology using items based on expert guidance and the PROBAST tool. Results We identified 100 eligible studies: 41 developing a new prediction model, 48 validating an existing model and 11 that included both development and validation. Most publications (k = 75) reported a model discrimination measure, while 26 investigations reported calibration. Of 52 new prediction models, six (12%) were for suicidal outcomes, 18 (35%) for future diagnosis, five (10%) for child maltreatment. Other outcomes included violence, crime, and functional outcomes. Eleven new models (21%) were developed for use in high-risk populations. Of development studies, around a third were sufficiently statistically powered (k = 16%, 31%), while this was lower for validation investigations (k = 12, 25%). In terms of performance, the discrimination (as measured by the C-statistic) for new models ranged from 0.57 for a tool predicting ADHD diagnosis in an external validation sample to 0.99 for a machine learning model predicting foster care permanency. Conclusions Although some tools have recently been developed for child and adolescent mental health for prognosis and child maltreatment, none can be currently recommended for clinical practice due to a combination of methodological limitations and poor model performance. New work needs to use ensure sufficient sample sizes, representative samples, and testing of model calibration.

Background Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials). Objectives To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers. Search methods We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020. Selection criteria We included randomized controlled trials (RCTs) and cluster‐RCTs (cRCTs) carried out in primary care, including non‐pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician‐delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow‐up or longer. Data collection and analysis We followed standard Cochrane methods. Our primary outcome ‐ smoking abstinence ‐ was measured using the most rigorous intention‐to‐treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow‐up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta‐analyses using Mantel‐Haenszel random‐effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs). Main results We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate‐certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost‐free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate‐certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow‐up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost‐free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty‐four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta‐analyses in most cases. Meta‐analyses provided some evidence that adjunctive counseling combined with either cost‐free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision‐making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation. Authors' conclusions There is moderate‐certainty evidence that providing adjunctive counseling by an allied health professional, cost‐free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster‐randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta‐analysis to investigate this further.

Background Violence perpetrated by psychiatric inpatients is associated with modifiable factors. Current structured approaches to assess inpatient violence risk lack predictive validity and linkage to interventions. Methods Adult psychiatric inpatients on forensic and general wards in three psychiatric hospitals were recruited and followed up prospectively for 6 months. Information on modifiable (dynamic) risk factors were collected every 1–4 weeks, and baseline background factors. Data were transferred to a web-based monitoring system (FOxWeb) to calculate a total dynamic risk score. Outcomes were extracted from an incident-reporting system recording aggression and interpersonal violence. The association between total dynamic score and violent incidents was assessed by multilevel logistic regression and compared with dynamic score excluded. Results We recruited 89 patients and conducted 624 separate assessments (median 5/patient). Mean age was 39 (s.d. 12.5) years with 20% (n = 18) female. Common diagnoses were schizophrenia-spectrum disorders (70%, n = 62) and personality disorders (20%, n = 18). There were 93 violent incidents. Factors contributing to violence risk were a total dynamic score of ⩾1 (OR 3.39, 95% CI 1.25–9.20), 10-year increase in age (OR 0.67, 0.47–0.96), and female sex (OR 2.78, 1.04–7.40). Non-significant associations with schizophrenia-spectrum disorder were found (OR 0.50, 0.20–1.21). In a fixed-effect model using all covariates, AUC was 0.77 (0.72–0.82) and 0.75 (0.70–0.80) when the dynamic score was excluded. Conclusions In predicting violence risk in individuals with psychiatric disorders, modifiable factors added little incremental value beyond static ones in a psychiatric inpatient setting. Future work should make a clear distinction between risk factors that assist in prediction and those linked to needs.

Background During the COVID-19 pandemic in 2020, the UK government began a mass SARS-CoV-2 testing programme. This study aimed to determine the feasibility and acceptability of organised regular self-testing for SARS-CoV-2. Methods This was a mixed methods observational cohort study in asymptomatic students and staff at University of Oxford, who performed SARS-CoV-2 antigen lateral flow self-testing. Data on uptake and adherence, acceptability, and test interpretation were collected via a smartphone app, an online survey, and qualitative interviews. Findings Across three main sites, 551 participants (25% of those invited) performed 2728 tests during a follow-up of 5.6 weeks. 447 participants (81%) completed at least two, and 340 (62%) completed at least four tests. The survey, completed by 214 participants (39%), found that 98% of people were confident to self-test and believed self-testing to be beneficial. Acceptability of self-testing was high, with 91% of ratings being acceptable or very acceptable. 2711 (99.4%) test results were negative, nine were positive and eight were inconclusive. Results from eighteen qualitative interviews with students and staff revealed that participants valued regular testing, but there were concerns about test accuracy that impacted uptake and adherence. Interpretation This is the first study to assess feasibility and acceptability of regular SARS-CoV-2 self-testing. It provides evidence to inform recruitment, adherence to, and acceptability of regular SARS-CoV-2 self-testing programmes for asymptomatic individuals using lateral flow tests. We found that self-testing is acceptable and people were able to interpret results accurately. Funding This work was funded by Oxford University Medical Science Divisions, Lay Summary During the 2020 COVID-19 pandemic the UK government asked people to begin self-testing using rapid lateral flow tests. This study asked students and staff without COVID-19 symptoms at University of Oxford to do weekly self-testing using these tests and asked what they thought of the testing using a phone app, a survey and interviews. There were 551 people in the study, who did 2728 tests during the study. Most people (81%) did at least two tests. In the survey, almost everyone (98%) said they were confident to self-test and believed self-testing was beneficial. Most people (91%) said they found it acceptable or very acceptable to self-test. We found that self-testing is acceptable to people and they were able to interpret results correctly.

Aims To investigate the comparative and combined effectiveness of four types of components of behavioural interventions for cigarette smoking cessation: behavioural (e.g. counselling), motivational (e.g. focus on reasons to quit), delivery mode (e.g. phone), and provider (e.g. nurse). Design Systematic review and component network meta-analysis of randomized controlled trials identified from Cochrane reviews. Interventions included behavioural interventions for smoking cessation (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials), compared with another behavioural intervention or no support. Building on a 2021 review (CD013229), we conducted three analyses, investigating: comparative effectiveness of the components, whether models that allowed interactions between components gave different results to models assuming additivity, and predicted effect estimates for combined effects of components that had showed promise but where there were few trials. Setting Community and healthcare settings Participants Adults who smoke tobacco Measurements Smoking cessation at ≥6 months, preferring sustained, biochemically validated outcomes where available. Findings 312 trials (250,563 participants) were included. 50 were at high risk of bias using Cochrane risk of bias tool, V1 (ROB1); excluding these studies did not change findings. Head-to-head comparisons of components suggested that support via text-message (SMS) compared with telephone (odds ratio (OR) 1.48, 95% credibility interval (CrI) 1.13 to 1.94) or print materials (OR 1.44, 95% CrI 1.14 to 1.83) was more effective, individual delivery was less effective than delivery as part of a group (OR 0.78, 95% CrI 0.64 to 0.95). There was no conclusive evidence of synergistic or antagonistic interactions when combining components that were commonly used together. Adding multiple components that are commonly used in behavioural counselling suggested clinically relevant and statistically conclusive evidence of benefit. Components with the largest effects that could be combined, but rarely have been, were estimated to increase the odds of quitting between two and threefold. For example, financial incentives delivered via SMS, with tailoring a focus on how to quit, had an estimated OR of 2.94 (95% CrI 1.91 to 4.52). Conclusions Among the components of behavioural support for smoking cessation, behavioural counselling and guaranteed financial incentives are associated with the greatest success. Incorporating additional components associated with effectiveness may further increase benefit, with delivery via text-message showing particular promise.

Psychological models of bipolar disorder (BD), such as the self‐regulation model (SRM; Leventhal, Nerenz, & Steele, 1984), highlight the crucial role of beliefs about mood in relapse vulnerability. To date, no studies have directly compared these beliefs between people with and without BD. Based on the SRM, the current research examined beliefs about mood in people with and without BD and explored the impact of current affect on these beliefs. Fifty euthymic people with a diagnosis of BD and 50 controls were recruited through an online screening study, clinical services, and support organizations. Experience sampling methodology (ESM) was used to assess beliefs (according to the Brief Illness Perceptions Questionnaire; Broadbent, Petrie, Main, & Weinman, 2006) across a typical week of everyday life. Data were analysed using multilevel modelling. Forty‐two people with a diagnosis of BD and 50 controls were included in the analyses. Results indicated that the BD group reported less control over mood, a shorter duration of mood, and less understanding of mood and were more likely to report the cause of depressive symptoms as something internal, compared with controls. When controlling for current affect, the BD group also reported more positive consequences, made more internal attributions for hypomanic symptoms, and reported less concern about mood, compared with controls. Findings suggest important differences in beliefs about mood between people with and without BD that are not the result of current affect. These beliefs may be particularly important in understanding underlying vulnerability to future relapse into depression and/or mania.

Aims C-reactive protein (CRP) and neutrophil count (NC) are important diagnostic indicators of inflammation. Point-of-care (POC) technologies for these markers are available but rarely used in community settings in the UK. To inform the potential for POC tests, it is necessary to understand the demand for testing. We aimed to describe the frequency of CRP and NC test requests from primary care to central laboratory services, describe variability between practices and assess the relationship between the tests.MethodsWe described the number of patients with either or both laboratory tests, and the volume of testing per individual and per practice, in a retrospective cohort of all adults in general practices in Oxfordshire, 2014–2016.Results372 017 CRP and 776 581 NC tests in 160 883 and 275 093 patients, respectively, were requested from 69 practices. CRP was tested mainly in combination with NC, while the latter was more often tested alone. The median (IQR) of CRP and NC tests/person tested was 1 (1–2) and 2 (1–3), respectively. The median (IQR) tests/practice/week was 36 (22–52) and 72 (50–108), and per 1000 persons registered/practice/week was 4 (3–5) and 8 (7–9), respectively. The median (IQR) CRP and NC concentrations were 2.7 (0.9–7.9) mg/dL and 4.1 (3.1–5.5)×109/L, respectively.ConclusionsThe high demand for CRP and NC testing in the community, and the range of results falling within the reportable range for current POC technologies highlight the opportunity for laboratory testing to be supplemented by POC testing in general practice.

Smoking is a leading cause of disease and death worldwide. In people who smoke, quitting smoking can reverse much of the damage. Many people use behavioural interventions to help them quit smoking; these interventions can vary substantially in their content and effectiveness.To summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts and to conduct a network meta-analysis to determine how modes of delivery; person delivering the intervention; and the nature, focus, and intensity of behavioural interventions for smoking cessation influence the likelihood of achieving abstinence six months after attempting to stop smoking; and whether the effects of behavioural interventions depend upon other characteristics, including population, setting, and the provision of pharmacotherapy. To summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary.This work comprises two main elements. 1. We conducted a Cochrane Overview of reviews following standard Cochrane methods. We identified Cochrane Reviews of behavioural interventions (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials) for smoking cessation by searching the Cochrane Library in July 2020. We evaluated the methodological quality of reviews using AMSTAR 2 and synthesised data from the reviews narratively. 2. We used the included reviews to identify randomised controlled trials of behavioural interventions for smoking cessation compared with other behavioural interventions or no intervention for smoking cessation. To be included, studies had to include adult smokers and measure smoking abstinence at six months or longer. Screening, data extraction, and risk of bias assessment followed standard Cochrane methods. We synthesised data using Bayesian component network meta-analysis (CNMA), examining the effects of 38 different components compared to minimal intervention. Components included behavioural and motivational elements, intervention providers, delivery modes, nature, focus, and intensity of the behavioural intervention. We used component network meta-regression (CNMR) to evaluate the influence of population characteristics, provision of pharmacotherapy, and intervention intensity on the component effects. We evaluated certainty of the evidence using GRADE domains. We assumed an additive effect for individual components.We included 33 Cochrane Reviews, from which 312 randomised controlled trials, representing 250,563 participants and 845 distinct study arms, met the criteria for inclusion in our component network meta-analysis. This represented 437 different combinations of components. Of the 33 reviews, confidence in review findings was high in four reviews and moderate in nine reviews, as measured by the AMSTAR 2 critical appraisal tool. The remaining 20 reviews were low or critically low due to one or more critical weaknesses, most commonly inadequate investigation or discussion (or both) of the impact of publication bias. Of note, the critical weaknesses identified did not affect the searching, screening, or data extraction elements of the review process, which have direct bearing on our CNMA. Of the included studies, 125/312 were at low risk of bias overall, 50 were at high risk of bias, and the remainder were at unclear risk. Analyses from the contributing reviews and from our CNMA showed behavioural interventions for smoking cessation can increase quit rates, but effectiveness varies on characteristics of the support provided. There was high-certainty evidence of benefit for the provision of counselling (odds ratio (OR) 1.44, 95% credibility interval (CrI) 1.22 to 1.70, 194 studies, n = 72,273) and guaranteed financial incentives (OR 1.46, 95% CrI 1.15 to 1.85, 19 studies, n = 8877). Evidence of benefit remained when removing studies at high risk of bias. These findings were consistent with pair-wise meta-analyses from contributing reviews. There was moderate-certainty evidence of benefit for interventions delivered via text message (downgraded due to unexplained statistical heterogeneity in pair-wise comparison), and for the following components where point estimates suggested benefit but CrIs incorporated no clinically significant difference: individual tailoring; intervention content including motivational components; intervention content focused on how to quit. The remaining intervention components had low-to very low-certainty evidence, with the main issues being imprecision and risk of bias. There was no evidence to suggest an increase in harms in groups receiving behavioural support for smoking cessation. Intervention effects were not changed by adjusting for population characteristics, but data were limited. Increasing intensity of behavioural support, as measured through the number of contacts, duration of each contact, and programme length, had point estimates associated with modestly increased chances of quitting, but CrIs included no difference. The effect of behavioural support for smoking cessation appeared slightly less pronounced when people were already receiving smoking cessation pharmacotherapies.Behavioural support for smoking cessation can increase quit rates at six months or longer, with no evidence that support increases harms. This is the case whether or not smoking cessation pharmacotherapy is also provided, but the effect is slightly more pronounced in the absence of pharmacotherapy. Evidence of benefit is strongest for the provision of any form of counselling, and guaranteed financial incentives. Evidence suggested possible benefit but the need of further studies to evaluate: individual tailoring; delivery via text message, email, and audio recording; delivery by lay health advisor; and intervention content with motivational components and a focus on how to quit. We identified 23 economic evaluations; evidence did not consistently suggest one type of behavioural intervention for smoking cessation was more cost-effective than another. Future reviews should fully consider publication bias. Tools to investigate publication bias and to evaluate certainty in CNMA are needed.El tabaquismo es una causa principal de enfermedad y muerte en todo el mundo. En las personas que fuman, dejar de fumar puede revertir gran parte del daño. Muchas personas utilizan intervenciones conductuales para ayudarles a dejar de fumar y estas intervenciones pueden variar considerablemente en contenido y efectividad.Resumir la evidencia de las revisiones Cochrane que evaluaron el efecto de las intervenciones conductuales diseñadas para apoyar los intentos de abandono del hábito de fumar y realizar un metanálisis en red para determinar cómo las modalidades de prestación; la persona que administra la intervención; y la naturaleza, el enfoque y la intensidad de las intervenciones conductuales para el abandono del hábito de fumar influyen en la probabilidad de lograr la abstinencia seis meses después de intentar dejar de fumar; y si los efectos de las intervenciones conductuales dependen de otras características, como la población, el contexto y la administración de farmacoterapia. Resumir la disponibilidad y los hallazgos principales de las evaluaciones económicas de intervenciones conductuales para dejar de fumar, en términos de costes y coste‐efectividad, mediante un breve comentario económico. MÉTODOS: Este artículo comprende dos elementos principales. 1. Se realizó una revisión global Cochrane de revisiones según los métodos estándar de Cochrane. Mediante una búsqueda en la Biblioteca Cochrane en julio de 2020 se identificaron las revisiones Cochrane de intervenciones conductuales (incluidas todas las intervenciones no farmacológicas, p.ej., orientación, ejercicio, hipnoterapia, materiales de autoayuda) para el abandono del hábito de fumar. La calidad metodológica de las revisiones se evaluó mediante AMSTAR 2 y los datos de las revisiones se resumieron de manera narrativa. 2. Las revisiones incluidas se utilizaron para identificar los ensayos controlados aleatorizados de intervenciones conductuales para el abandono del hábito de fumar en comparación con otras intervenciones conductuales o ninguna intervención para el abandono del hábito de fumar. Para ser incluidos, los estudios debían incluir a fumadores adultos y medir la abstinencia de fumar a los seis meses o más. La selección, la extracción de los datos y la evaluación del riesgo de sesgo siguieron los métodos Cochrane estándar. Los datos se resumieron mediante un metanálisis en red de componentes (MARC) bayesiano, y se examinaron los efectos de 38 componentes diferentes en comparación con una intervención mínima. Los componentes incluyeron elementos conductuales y motivacionales, proveedores de la intervención, modos de administración, naturaleza, enfoque e intensidad de la intervención conductual. Se utilizó la metarregresión en red de componentes (MRRC) para evaluar la influencia de las características de la población, la administración de farmacoterapia y la intensidad de la intervención sobre los efectos de los componentes. La certeza de la evidencia se evaluó mediante los dominios de GRADE. Se presupuso un efecto aditivo para los componentes individuales.Se incluyeron 33 revisiones Cochrane, de las cuales 312 ensayos controlados aleatorizados, que representaban a 250 563 participantes y 845 grupos de estudio distintos, cumplieron los criterios para su inclusión en el metanálisis en red de componentes. Esto representó 437 combinaciones diferentes de componentes. De las 33 revisiones, la confianza en los hallazgos de la revisión fue alta en cuatro y moderada en nueve, medida con la herramienta de lectura crítica AMSTAR 2. Las 20 revisiones restantes tuvieron una confianza baja o críticamente baja debido a una o más deficiencias graves, las más habituales fueron una investigación o discusión (o ambas) insuficiente acerca del impacto del sesgo de publicación. Cabe señalar que las debilidades críticas identificadas no afectaron los elementos de la búsqueda, la selección o la extracción de los datos del proceso de revisión, que mantienen una relación directa en este MARC. Entre los estudios incluidos, 125/312 tuvieron un riesgo general de sesgo bajo, 50 un riesgo de sesgo alto y el resto un riesgo de sesgo poco claro. Los análisis de las revisiones contribuyentes y de este MARC mostraron que las intervenciones conductuales para dejar de fumar pueden aumentar las tasas de abandono del hábito, pero la efectividad varía según las características del apoyo proporcionado. Hubo evidencia de certeza alta de un efecto beneficioso de la prestación de orientación (odds ratio [OR] 1,44; intervalo de credibilidad [ICr] del 95%: 1,22 a 1,70, 194 estudios, n = 72 273) y de los incentivos económicos garantizados (OR 1,46; ICr del 95% 1,15 a 1,85, 19 estudios, n = 8877). La evidencia de un efecto beneficioso se mantuvo cuando se eliminaron los estudios con alto riesgo de sesgo. Estos hallazgos fueron concordantes con los metanálisis pareados de las revisiones contribuyentes. Hubo evidencia de certeza moderada de un efecto beneficioso de las intervenciones administradas a través de mensajes de texto (la certeza se disminuyó debido a una heterogeneidad estadística inexplicada en la comparación pareada), y de los siguientes componentes en los que las estimaciones puntuales indicaron un efecto beneficioso pero los ICr no incorporaron una diferencia clínicamente significativa: personalización; contenido de la intervención con componentes motivacionales; contenido de la intervención centrado en cómo dejar de fumar. Los otros componentes de la intervención tuvieron evidencia de certeza muy baja a baja, y sus problemas principales fueron la imprecisión y el riesgo de sesgo. No hubo evidencia que indicara un aumento de los efectos perjudiciales en los grupos que recibieron apoyo conductual para dejar de fumar. Los efectos de la intervención no cambiaron al ajustar las características de la población, pero los datos fueron limitados. El aumento de la intensidad del apoyo conductual, medido a través del número de contactos, la duración de cada contacto y la duración del programa, tuvo estimaciones puntuales asociadas con un modesto aumento de las posibilidades de dejar de fumar, pero los ICr no incluyeron una diferencia. El efecto del apoyo conductual para dejar de fumar pareció ser ligeramente menos pronunciado cuando las personas ya recibían farmacoterapias para dejar de fumar.El apoyo conductual para dejar de fumar puede aumentar las tasas de abandono a los seis meses o más, sin evidencia de que este apoyo aumente los efectos perjudiciales. Esto es así tanto si se proporciona una farmacoterapia para dejar de fumar como si no, pero el efecto es ligeramente más pronunciado sin farmacoterapia. La evidencia de un efecto beneficioso es más sólida para la prestación de cualquier tipo de orientación y de incentivos económicos garantizados. La evidencia indicó un posible efecto beneficioso, pero la necesidad de realizar más estudios para evaluar: la personalización; la administración mediante mensajes de texto, correos electrónicos y grabaciones de audio; la administración por parte de un asesor de salud no profesional; y el contenido de la intervención con componentes motivacionales y centrada en cómo dejar de fumar. Se identificaron 23 evaluaciones económicas; la evidencia no indicó de manera homogénea que un tipo de intervención conductual para el abandono del hábito de fumar fuera más coste‐efectiva que otra. Las revisiones futuras deberían examinar a fondo el sesgo de publicación. Se necesitan herramientas para investigar el sesgo de publicación y evaluar la certeza en MARC.

Background:Reactive arthritis, irritable bowel syndrome (IBS), Guillain-Barré syndrome, ulcerative colitis, and Crohn's disease may be sequelae ofCampylobacteror non-typhoidalSalmonella(NTS) infections. Proton pump inhibitors (PPI) and antibiotics may increase the risk of gastrointestinal infections (GII); however, their impact on sequelae onset is unclear. We investigated the incidence of sequelae, their association with antibiotics and PPI prescription, and assessed the economic impact on the NHS. Methods:Data from the Clinical Practice Research Datalink for patients consulting their GP forCampylobacteror NTS infection, during 2000-2015, were linked to hospital, mortality, and Index of Multiple Deprivation data. We estimated the incidence of sequelae and deaths in the 12 months following GII. We conducted logistic regression modelling for the adjusted association with prescriptions. We compared differences in resource use and costs pre- and post-infection amongst patients with and without sequelae. Findings:Of 20,471 patients with GII (Campylobacter17,838), less than 2% (347) developed sequelae, with IBS (268) most common. AmongCampylobacterpatients, those with prescriptions for PPI within 12 months before and cephalosporins within 7-days before/after infection had elevated risk of IBS (adjusted odds ratio [aOR] 2.1, 1.5-2.9) and (aOR 3.6, 1.1-11.7) respectively.Campylobactersequelae lead to ∼ £1.3 million, (£750,000, £1.7 million) in additional annual NHS expenditure. Interpretation:Sequelae ofCampylobacterand NTS infections are rare but associated with increased NHS costs. Prior prescription of PPI may be a modifiable risk factor. Incidence of sequelae, healthcare resource use and costs are essential parameters for future burden of disease studies.

Background: During the COVID-19 pandemic in 2020, the UK government began a mass SARS-CoV-2 testing programme. This study aimed to determine the feasibility and acceptability of organised regular self-testing for SARS-CoV-2. Methods: This was a mixed methods observational cohort study in asymptomatic students and staff at University of Oxford, who performed SARS-CoV-2 antigen lateral flow self-testing. Data on uptake and adherence, acceptability, and test interpretation were collected via a smartphone app, an online survey, and qualitative interviews. Findings: Across three main sites, 551 participants (25% of those invited) performed 2728 tests during a follow-up of 5.6 weeks. 447 participants (81%) completed at least two, and 340 (62%) completed at least four tests. The survey, completed by 214 participants (39%), found that 98% of people were confident to self-test and believed self-testing to be beneficial. Acceptability of self-testing was high, with 91% of ratings being acceptable or very acceptable. 2711 (99.4%) test results were negative, nine were positive and eight were inconclusive. Results from eighteen qualitative interviews with staff and students revealed that participants valued regular testing, but there were concerns about test accuracy that impacted uptake and adherence. Interpretation: This is the first study to assess feasibility and acceptability of regular SARS-CoV-2 self-testing. It provides evidence to inform recruitment, adherence to, and acceptability of regular SARS-CoV-2 self-testing programmes for asymptomatic individuals using lateral flow tests. We found that self-testing is acceptable and people were able to interpret results accurately. Funding: This work was funded by Oxford University Medical Science Divisions Declaration of Interests: LT works part-time for Sensyne Health as R&D Director and holds share options in the company. He also reports a research grant and personal fees from the company. Ethics Approval Statement: FACTS is a mixed methods cohort study conducted at the University of Oxford. It was approved by the University of Oxford Research Ethics Committee in October 2020 (CUREC ethics reference R72896/RE001).

Background Physical health outcomes in severe mental illness are worse than in the general population. Routine physical health check completion in this group is poor. Aims To quantitatively and qualitatively evaluate the impact of point of care (POC) blood testing on physical health check completion in community mental health services. Method In a prospective cohort design, we equipped an early intervention service (EIS) and a community mental health team (CMHT) with a POC blood testing device for 6 months. We compared rates of blood test and full physical health check completion in the intervention teams with a matched EIS and CMHT, historically and during the intervention. We explored attitudes to POC testing using thematic analysis of semi-structured interviews with patients and clinicians. Results Although the CMHT scarcely used the POC device and saw no change in outcomes, direct comparison of testing rates in the intervention period showed increased physical health check completion in the EIS with the device (rate ratio RR = 5.18; 95% CI 2.54–12.44; P < 0.001) compared with usual care. The rate was consistent with the EIS's increasing rate of testing over time (RR = 0.45; 95% 0.09–2.08; P = 0.32). Similar trends were seen in blood test completion. POC testing was acceptable to patients but clinicians reported usability, provision and impact on the therapeutic relationship as barriers to uptake. Conclusions POC testing was beneficial and acceptable to patients and may increase physical health check uptake. Further research, accounting for clinician barriers, is needed to evaluate its clinical and cost-effectiveness.

Background The aim of RApid community Point-of-care Testing fOR COVID-19 (RAPTOR-C19) is to assess the diagnostic accuracy of multiple current and emerging point-of-care tests (POCTs) for active and past SARS-CoV2 infection in the community setting. RAPTOR-C19 will provide the community testbed to the COVID-19 National DiagnOstic Research and Evaluation Platform (CONDOR). Methods RAPTOR-C19 incorporates a series of prospective observational parallel diagnostic accuracy studies of SARS-CoV2 POCTs against laboratory and composite reference standards in patients with suspected current or past SARS-CoV2 infection attending community settings. Adults and children with suspected current SARS-CoV2 infection who are having an oropharyngeal/nasopharyngeal (OP/NP) swab for laboratory SARS-CoV2 reverse transcriptase Digital/Real-Time Polymerase Chain Reaction (d/rRT-PCR) as part of clinical care or community-based testing will be invited to participate. Adults (≥ 16 years) with suspected past symptomatic infection will also be recruited. Asymptomatic individuals will not be eligible. At the baseline visit, all participants will be asked to submit samples for at least one candidate point-of-care test (POCT) being evaluated (index test/s) as well as an OP/NP swab for laboratory SARS-CoV2 RT-PCR performed by Public Health England (PHE) (reference standard for current infection). Adults will also be asked for a blood sample for laboratory SARS-CoV-2 antibody testing by PHE (reference standard for past infection), where feasible adults will be invited to attend a second visit at 28 days for repeat antibody testing. Additional study data (e.g. demographics, symptoms, observations, household contacts) will be captured electronically. Sensitivity, specificity, positive, and negative predictive values for each POCT will be calculated with exact 95% confidence intervals when compared to the reference standard. POCTs will also be compared to composite reference standards constructed using paired antibody test results, patient reported outcomes, linked electronic health records for outcomes related to COVID-19 such as hospitalisation or death, and other test results. Discussion High-performing POCTs for community use could be transformational. Real-time results could lead to personal and public health impacts such as reducing onward household transmission of SARS-CoV2 infection, improving surveillance of health and social care staff, contributing to accurate prevalence estimates, and understanding of SARS-CoV2 transmission dynamics in the population. In contrast, poorly performing POCTs could have negative effects, so it is necessary to undertake community-based diagnostic accuracy evaluations before rolling these out. Trial registration ISRCTN, ISRCTN14226970

Alternative methods for dealing with within trial clustering have been proposed for conducting individual participant data (IPD) ‘one-stage’ meta-analysis. Does it matter which one is used? Will it affect the estimates and their precision? Tom Fanshawe and Rafael Perera Meta-analysis of studies using IPD is increasingly common and is likely to grow in popularity as a result of increased data sharing with repositories for collaborative data sharing become more established. IPD meta-analysis allows systematic reviews to pool data, beyond what is possible based only on the summary statistics, for example, intervention effects, reported in published papers and also provides the opportunity of fitting appropriate statistical methods to obtain summary estimates. Two-stage and one-stage meta-analyses are the commonly used statistical approaches in IPD. In the ‘two-stage’ meta-analysis, the …

Many diagnostic tests report only positive or negative diagnoses, as if these results were definitive. Should more tests allow a ‘neutral zone’, corresponding to an uncertain diagnosis? Diagnostic tests often use single continuous biomarker measurements to return a positive or a negative result. However, in clinical practice, a diagnosis might often be reached based on multiple signs, symptoms and test results rather than using only a single measurement. These multiple individual characteristics are sometimes incorporated into a statistical model that aims to estimate the probability of disease, which helps in making a diagnosis. Guidelines have been published for optimal development, validation and report of such tools.1 2 The receiver operating characteristic (ROC) curve remains a popular technique for showing diagnostic performance in terms of sensitivity and specificity, that is, how accurately the test can correctly classify people with and without disease. Traditionally, statistical methods that follow this approach assume that individuals can be classified into just two categories: either a positive or a negative diagnosis. The recent paper by Jeske et al 3 considers methods for identifying what has been termed a ‘neutral …

Last year we launched the EBM Methods Verdicts as part of an attempt to keep on top of developments in statistics that will impact on the way we do research.1 2 We focused on statistical methods and in particular on the output from five different journals: Journal of Clinical Epidemiology , Statistics in Medicine , Statistical Methods in Medical Research , BMC Medical Research Methodology and Biostatistics . The idea is simple: identify papers that we believe are likely to change the way we analyse or report evidence syntheses, randomised trials or studies related to diagnosis, prognosis or monitoring. Our editorial team typically focuses on one of these per month and aims to write a short commentary with a ‘verdict’ explaining how this will change how we do things. We are also interested in people submitting proposals for similar short pieces. Bayesian neural networks were the rage in the early 90s. Work in this area seemed to go quiet for most of the 00s but has exploded back into our consciousness in the last few years. This is clear by the number of papers published on the topic (figure 1) with nearly half of the total appearing in the last 2 …

© 2020 Fanshawe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction Point of care blood testing to aid diagnosis is becoming increasingly common in acute ambulatory settings and enables timely investigation of a range of diagnostic markers. However, this testing allows scope for errors in the pre-analytical phase, which depends on the operator handling and transferring specimens correctly. The extent and nature of these pre-analytical errors in clinical settings has not been widely reported. Methods We carried out a convergent parallel mixed-methods service evaluation to investigate pre-analytical errors leading to a machine error reports in a large acute hospital trust in the UK. The quantitative component comprised a retrospective analysis of all recorded error codes from Abbott Point of Care i-STAT 1, i-STAT Alinity and Abbott Rapid Diagnostics Afinion devices to summarise the error frequencies and reasons for error, focusing on those attributable to the operator. The qualitative component included a prospective ethnographic study and a secondary analysis of an existing ethnographic dataset, based in hospital-based ambulatory care and community ambulatory care respectively. Results The i-STAT had the highest usage (113,266 tests, January 2016-December 2018). As a percentage of all tests attempted, its device-recorded overall error rate was 6.8% (95% confidence interval 6.6% to 6.9%), and in the period when reliable data could be obtained, the operator-attributable error rate was 2.3% (2.2% to 2.4%). Staff identified that the most difficult step was the filling of cartridges, but that this could be improved through practice, with a perception that cartridge wastage through errors was rare. Conclusions In the observed settings, the rate of errors attributable to operators of the primary point of care device was less than 1 in 40. In some cases, errors may lead to a small increase in resource use or time required so adequate staff training is necessary to prevent adverse impact on patient care.

AimsThe demand for test requests from general practice to laboratory services remains high. Tests performed at the point of care could reduce turnaround time and speed up clinical decision making. Replicating laboratory testing in the community would require panels of tests to be performed simultaneously, which is now approaching technological feasibility. We assessed frequencies and combinations of test requests from community settings to inform the potential future development of multiplex point-of-care panels.MethodsWe assessed all laboratory test requests made from general practice in Oxfordshire, UK, from January 2014 to March 2017. We summarised test request frequency overall and in combination, using heatmaps and hierarchical cluster analysis. Results are also presented by age/sex subgroups. We further assessed patterns of tests requested within 7 and 14 days after an initial test request.Results11 763 473 test requests were made for 413 073 individuals (28% age >65). Of more than 500 test types, 62 were requested at least 5000 times, most commonly renal function tests (approximately 296 000/year), full blood count (278 000/year) and liver function tests (237 000/year). Cluster analysis additionally identified a clear grouping of tests commonly used to investigate anaemia. Follow-up test frequency was much lower than the frequency of multiple tests ordered at initial presentation.ConclusionsThe current high volume of single and combination test requests highlights an opportunity for reliable multiplex point-of-care panels to cover a core set of frequently requested tests. The impact on test use of introducing such panels to general practice requires additional research.

IntroductionA significant percentage of patients admitted to hospital have undiagnosed hypertension. However, present hypertension guidelines in the UK, Europe and USA do not define a blood pressure threshold at which hospital inpatients should be considered at risk of hypertension, outside of the emergency setting. The objective of this study is to identify the optimal in-hospital mean blood pressure threshold, above which patients should receive postdischarge blood pressure assessment in the community.Methods and analysisScreening for Hypertension in the INpatient Environment is a prospective diagnostic accuracy study. Patients admitted to hospital whose mean average daytime blood pressure after 24 hours or longer meets the study eligibility threshold for mean daytime blood pressure (≥120/70 mm Hg) and who have no prior diagnosis of, or medication for hypertension will be eligible. At 8 weeks postdischarge, recruited participants will wear an ambulatory blood pressure monitor for 24 hours. Mean daytime ambulatory blood pressure will be calculated to assess for the presence or absence of hypertension. Diagnostic performance of in-hospital blood pressure will be assessed by constructing receiver operator characteristic curves from participants’ in-hospital mean systolic and mean diastolic blood pressure (index test) versus diagnosis of hypertension determined by mean daytime ambulatory blood pressure (reference test).Ethics and disseminationEthical approval has been provided by the National Health Service Health Research Authority South Central—Oxford B Research Ethics Committee (19/SC/0026). Findings will be disseminated through national and international conferences, peer-reviewed journals and social media.

Objective Low disease prevalence poses challenges for diagnostic accuracy studies because of the large sample sizes that are required to obtain sufficient precision. The aim is to collate and discuss designs of diagnostic accuracy studies suited for use in low-prevalence situations. Study Design and Setting We conducted a literature search including backward citation tracking and expert consultation. Two reviewers independently selected studies on designs for estimating diagnostic accuracy in a low-prevalence situation. During a 1-day expert meeting, all designs were discussed and recommendations were formulated. Results We identified six designs for diagnostic accuracy studies that are suitable in low-prevalence situations because they reduced the total sample size or the number of patients undergoing the index test or reference standard depending on which poses the highest burden. We described the advantages and limitations of these designs and evaluated efficiencies in sample sizes, risk of bias, and alignment with the clinical pathway for applicability in routine care. Conclusion Choosing a study design for diagnostic accuracy studies in low-prevalence situations should depend on whether the aim is to limit the number of patients undergoing the index test or reference standard, and the risk of bias associated with a particular design type.

Background Practitioners who enhance how they express empathy and create positive expectations of benefit could improve patient outcomes. However, the evidence in this area has not been recently synthesised. Objective To estimate the effects of empathy and expectations interventions for any clinical condition. Design Systematic review and meta-analysis of randomised trials. Data sources Six databases from inception to August 2017. Study selection Randomised trials of empathy or expectations interventions in any clinical setting with patients aged 12 years or older. Review methods Two reviewers independently screened citations, extracted data, assessed risk of bias and graded quality of evidence using GRADE. Random effects model was used for meta-analysis. Results We identified 28 eligible (n = 6017). In seven trials, empathic consultations improved pain, anxiety and satisfaction by a small amount (standardised mean difference −0.18 [95% confidence interval −0.32 to −0.03]). Twenty-two trials tested the effects of positive expectations. Eighteen of these (n = 2014) reported psychological outcomes (mostly pain) and showed a modest benefit (standardised mean difference −0.43 [95% confidence interval −0.65 to −0.21]); 11 (n = 1790) reported physical outcomes (including bronchial function/ length of hospital stay) and showed a small benefit (standardised mean difference −0.18 [95% confidence interval −0.32 to −0.05]). Within 11 trials (n = 2706) assessing harms, there was no evidence of adverse effects (odds ratio 1.04; 95% confidence interval 0.67 to 1.63). The risk of bias was low. The main limitations were difficulties in blinding and high heterogeneity for some comparisons. Conclusions Greater practitioner empathy or communication of positive messages can have small patient benefits for a range of clinical conditions, especially pain. Protocol registration Cochrane Database of Systematic Reviews (protocol) DOI: 10.1002/14651858.CD011934.pub2.

Copyright © 2017 John Wiley & Sons, Ltd. Introduction: Previous studies suggest that many systematic reviews contain meta-analyses that display temporal trends, such as the first study's result being more extreme than later studies' or a drift in the pooled estimate. We assessed the extent and characteristics of temporal trends using all Cochrane intervention reports published 2008-2012. Methods: We selected the largest meta-analysis within each report and analysed trends using methods including a Z-test (first versus subsequent estimates); generalised least squares; and cumulative sum charts. Predictors considered include meta-analysis size and review group. Results: Of 1288 meta-analyses containing at least 4 studies, the point estimate from the first study was more extreme and in the same direction as the pooled estimate in 738 (57%), with a statistically significant difference (first versus subsequent) in 165 (13%). Generalised least squares indicated trends in 717 (56%); 18% of fixed effects analyses had at least one violation of cumulative sum limits. For some methods, meta-analysis size was associated with temporal patterns and use of a random effects model, but there was no consistent association with review group. Conclusions: All results suggest that more meta-analyses demonstrate temporal patterns than would be expected by chance. Hence, assuming the standard meta-analysis model without temporal trend is sometimes inappropriate. Factors associated with trends are likely to be context specific.

Despite the significant global burden of gastroenteritis and resulting sequelae, there is limited evidence on risk factors for sequelae development. We updated and extended previous systematic reviews by assessing the role of antibiotics, proton pump inhibitors (PPI) and symptom severity in the development of sequelae following campylobacteriosis and salmonellosis. We searched four databases, including PubMed, from 1 January 2011 to 29 April 2016. Observational studies reporting sequelae of reactive arthritis (ReA), Reiter's syndrome (RS), irritable bowel syndrome (IBS) and Guillain-Barré syndrome (GBS) following gastroenteritis were included. The primary outcome was incidence of sequelae of interest amongst cases of campylobacteriosis and salmonellosis. A narrative synthesis was conducted where heterogeneity was high. Of the 55 articles included, incidence of ReA (n = 37), RS (n = 5), IBS (n = 12) and GBS (n = 9) were reported following campylobacteriosis and salmonellosis. A pooled summary for each sequela was not estimated due to high level of heterogeneity across studies (I2 > 90%). PPI usage and symptoms were sparsely reported. Three out of seven studies found a statistically significant association between antibiotics usage and development of ReA. Additional primary studies investigating risk modifying factors in sequelae of GI infections are required to enable targeted interventions., Highlights • There is no clear direction of the association between antibiotics and gastroenteritis triggered reactive arthritis. • Precision of genomic methods and increased use of record linkage techniques may provide clarity. Antibiotics are known to change the gut flora but little is known of their potential to cause complications in patients who have gastroenteritis. We conducted a systematic review of the existing evidence to assess the potential association of antibiotic usage in patients with gastroenteritis and the occurrence of complications such as reactive arthritis (ReA). The available evidence did not indicate a clear direction in the association of antibiotics and ReA. The lack of clarity in the association of antibiotics and ReA raises a call for further primary research on the role of medications in the development of complications of gastroenteritis.

Background Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further. Objectives To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy). Search methods We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP in June 2018 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support. Selection criteria Randomised or quasi‐randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person‐to‐person contact (defined as face‐to‐face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all. We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer. Data collection and analysis For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow‐up. We used the most rigorous definition of abstinence for each trial, and biochemically‐validated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta‐analysis using a random‐effects model. Main results Eighty‐three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I² = 8%, 65 studies, n = 23,331) for abstinence at longest follow‐up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I² = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378). Authors' conclusions There is high‐certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support. More research is needed to assess the effectiveness of specific components that comprise behavioural support.

Background Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes to ease the transition from cigarette smoking to abstinence. It works by reducing the intensity of craving and withdrawal symptoms. Although there is clear evidence that NRT used after smoking cessation is effective, it is unclear whether higher doses, longer durations of treatment, or using NRT before cessation add to its effectiveness. Objectives To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long‐term smoking cessation, compared to one another. Search methods We searched the Cochrane Tobacco Addiction Group trials register, and trial registries for papers mentioning NRT in the title, abstract or keywords. Date of most recent search: April 2018. Selection criteria Randomized trials in people motivated to quit, comparing one type of NRT use with another. We excluded trials that did not assess cessation as an outcome, with follow‐up less than six months, and with additional intervention components not matched between arms. Trials comparing NRT to control, and trials comparing NRT to other pharmacotherapies, are covered elsewhere. Data collection and analysis We followed standard Cochrane methods. Smoking abstinence was measured after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs), and study withdrawals due to treatment. We calculated the risk ratio (RR) and the 95% confidence interval (CI) for each outcome for each study, where possible. We grouped eligible studies according to the type of comparison. We carried out meta‐analyses where appropriate, using a Mantel‐Haenszel fixed‐effect model. Main results We identified 63 trials with 41,509 participants. Most recruited adults either from the community or from healthcare clinics. People enrolled in the studies typically smoked at least 15 cigarettes a day. We judged 24 of the 63 studies to be at high risk of bias, but restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results, apart from in the case of the preloading comparison. There is high‐certainty evidence that combination NRT (fast‐acting form + patch) results in higher long‐term quit rates than single form (RR 1.25, 95% CI 1.15 to 1.36, 14 studies, 11,356 participants; I2 = 4%). Moderate‐certainty evidence, limited by imprecision, indicates that 42/44 mg are as effective as 21/22 mg (24‐hour) patches (RR 1.09, 95% CI 0.93 to 1.29, 5 studies, 1655 participants; I2 = 38%), and that 21 mg are more effective than 14 mg (24‐hour) patches (RR 1.48, 95% CI 1.06 to 2.08, 1 study, 537 participants). Moderate‐certainty evidence (again limited by imprecision) also suggests a benefit of 25 mg over 15 mg (16‐hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41, 3 studies, 3446 participants; I2 = 0%). Five studies comparing 4 mg gum to 2 mg gum found a benefit of the higher dose (RR 1.43, 95% CI 1.12 to 1.83, 5 studies, 856 participants; I2 = 63%); however, results of a subgroup analysis suggest that only smokers who are highly dependent may benefit. Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward; there was moderate‐certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44, 9 studies, 4395 participants; I2 = 0%). High‐certainty evidence from eight studies suggests that using either a form of fast‐acting NRT or a nicotine patch results in similar long‐term quit rates (RR 0.90, 95% CI 0.77 to 1.05, 8 studies, 3319 participants; I2 = 0%). We found no evidence of an effect of duration of nicotine patch use (low‐certainty evidence); 16‐hour versus 24‐hour daily patch use; duration of combination NRT use (low‐ and very low‐certainty evidence); tapering of patch dose versus abrupt patch cessation; fast‐acting NRT type (very low‐certainty evidence); duration of nicotine gum use; ad lib versus fixed dosing of fast‐acting NRT; free versus purchased NRT; length of provision of free NRT; ceasing versus continuing patch use on lapse; and participant‐ versus clinician‐selected NRT. However, in most cases these findings are based on very low‐ or low‐certainty evidence, and are the findings from single studies. AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low‐ or very low‐certainty evidence for all comparisons. Most comparisons found no evidence of an effect on cardiac AEs, SAEs or withdrawals. Rates of these were low overall. Significantly more withdrawals due to treatment were reported in participants using nasal spray in comparison to patch in one trial (RR 3.47, 95% CI 1.15 to 10.46, 922 participants; very low certainty) and in participants using 42/44 mg patches in comparison to 21/22 mg patches across two trials (RR 4.99, 95% CI 1.60 to 15.50, 2 studies, 544 participants; I2 = 0%; low certainty). Authors' conclusions There is high‐certainty evidence that using combination NRT versus single‐form NRT, and 4 mg versus 2 mg nicotine gum, can increase the chances of successfully stopping smoking. For patch dose comparisons, evidence was of moderate certainty, due to imprecision. Twenty‐one mg patches resulted in higher quit rates than 14 mg (24‐hour) patches, and using 25 mg patches resulted in higher quit rates than using 15 mg (16‐hour) patches, although in the latter case the CI included one. There was no clear evidence of superiority for 42/44 mg over 21/22 mg (24‐hour) patches. Using a fast‐acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate‐certainty evidence that using NRT prior to quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is of low and very low certainty. New studies should ensure that AEs, SAEs and withdrawals due to treatment are both measured and reported.

Background Competitions might encourage people to undertake and/or reinforce behaviour change, including smoking cessation. Competitions involve individuals or groups having the opportunity to win a prize following successful cessation, either through direct competition or by entry into a lottery or raffle. Objectives To determine whether competitions lead to higher long‐term smoking quit rates. We also aimed to examine the impact on the population, the costs, and the unintended consequences of smoking cessation competitions. Search methods This review has merged two previous Cochrane reviews. Here we include studies testing competitions from the reviews ‘Competitions and incentives for smoking cessation' and ‘Quit and Win interventions for smoking cessation'. We updated the evidence by searching the Cochrane Tobacco Addiction Group Specialized Register in June 2018. Selection criteria We considered randomized controlled trials (RCTs), allocating individuals, workplaces, groups within workplaces, or communities to experimental or control conditions. We also considered controlled studies with baseline and post‐intervention measures in which participants were assigned to interventions by the investigators. Participants were smokers, of any age and gender, in any setting. Eligible interventions were contests, competitions, lotteries, and raffles, to reward cessation and continuous abstinence in smoking cessation programmes. Data collection and analysis For this update, data from new studies were extracted independently by two review authors. The primary outcome measure was abstinence from smoking at least six months from the start of the intervention. We performed meta‐analyses to pool study effects where suitable data were available and where the effect of the competition component could be separated from that of other intervention components, and report other findings narratively. Main results Twenty studies met our inclusion criteria. Five investigated performance‐based reward, where groups of smokers competed against each other to win a prize (N = 915). The remaining 15 used performance‐based eligibility, where cessation resulted in entry into a prize draw (N = 10,580). Five of these used Quit and Win contests (N = 4282), of which three were population‐level interventions. Fourteen studies were RCTs, and the remainder quasi‐randomized or controlled trials. Six had suitable abstinence data for a meta‐analysis, which did not show evidence of effectiveness of performance‐based eligibility interventions (risk ratio (RR) 1.16, 95% confidence interval (CI) 0.77 to 1.74, N = 3201, I2 = 57%). No trials that used performance‐based rewards found a beneficial effect of the intervention on long‐term quit rates. The three population‐level Quit and Win studies found higher smoking cessation rates in the intervention group (4% to 16.9%) than the control group at long‐term follow‐up, but none were RCTs and all had important between‐group differences in baseline characteristics. These studies suggested that fewer than one in 500 smokers would quit because of the contest. Reported unintended consequences in all sets of studies generally related to discrepancies between self‐reported smoking status and biochemically‐verified smoking status. More serious adverse events were not attributed to the competition intervention. Using the GRADE system we rated the overall quality of the evidence for smoking cessation as ‘very low', because of the high and unclear risk of bias associated with the included studies, substantial clinical and methodological heterogeneity, and the limited population investigated. Authors' conclusions At present, it is impossible to draw any firm conclusions about the effectiveness, or a lack of it, of smoking cessation competitions. This is due to a lack of well‐designed comparative studies. Smoking cessation competitions have not been shown to enhance long‐term cessation rates. The limited evidence suggesting that population‐based Quit & Win contests at local and regional level might deliver quit rates above baseline community rates has not been tested adequately using rigorous study designs. It is also unclear whether the value or frequency of possible cash reward schedules influence the success of competitions. Future studies should be designed to compensate for the substantial biases in the current evidence base.

Background Each year, infection with Plasmodium causes millions of clinical cases of malaria and hundreds of thousands of deaths. Resistance to different antimalarial medications continues to develop and spread, threatening effective prophylaxis and treatment. Surveillance of resistance is required to inform health policy and preserve effective antimalarial drugs; molecular methods can be used to surveil likely parasite resistances. However, there is no consensus on the most accurate molecular methods, and large variation exists in practice. The objective of this update to this systematic review is to improve and update identification of the sensitivity and specificity of each molecular method for detecting selected antimalarial drug resistance markers. Methods We will include diagnostic accuracy studies that compare at least two of any molecular methods to examine blood samples from patients diagnosed with, or suspected of having malaria, to detect at least one selected marker of antimalarial drug resistance. We will search PubMed, EMBASE, BIOSIS, and Web of Science from 2000 to present. Two reviewers will independently screen all results, extract data, consider applicability, and evaluate the methodological quality of included studies using QUADAS-2. We will carry out a meta-analysis and use statistical methods to compare results from homogenous studies. We will use narrative to synthesise and compare results of heterogeneous studies. Discussion This review will help to identify sub-optimal molecular methods for antimalarial marker detection which may be discontinued and identify more sensitive and specific methods which may be adopted. More sensitive and specific detection of drug resistance can be used to improve the breadth and accuracy of surveillance. This would enable the identification of previously undiscovered areas of antimalarial resistances and susceptibilities, improve the precision of estimates of the prevalence of resistances, and improve our ability to detect smaller changes in these patterns. Higher-quality evidence generated by more accurate and detailed surveillance can be used to inform guidelines on the use of antimalarial drugs, leading to better outcomes for more patients. Systematic review registration This systematic review protocol was registered with PROSPERO on 22 November 2017 (registration number CRD42017082101). Electronic supplementary material The online version of this article (10.1186/s13643-018-0891-6) contains supplementary material, which is available to authorized users.

Diagnostic tests play an important role in the clinical decision-making process by providing information that enables patients to be identified and stratified to the most appropriate treatment and management strategies. Decision analytic modelling facilitates the synthesis of evidence from multiple sources to evaluate the cost effectiveness of diagnostic tests. This study critically reviews the methods used to model the cost effectiveness of diagnostic tests in UK National Institute for Health Research (NIHR) Health Technology Assessment (HTA) reports. UK NIHR HTA reports published between 2009 and 2018 were screened to identify those reporting an economic evaluation of a diagnostic test using decision analytic modelling. Existing decision modelling checklists were identified in the literature and a modified checklist tailored to diagnostic economic evaluations was developed, piloted and used to assess the diagnostic models in HTA reports. Of 728 HTA reports published during the study period, 55 met the inclusion criteria. The majority of models performed well with a clearly defined decision problem and analytical perspective (89% of HTAs met the criterion). The model structure usually reflected the care pathway and progression of the health condition. However, there are areas requiring improvement. These are predominantly systematic identification of treatment effects (20% met), poor selection of comparators (50% met) and assumed independence of tests used in sequence (32% took correlation between sequential tests into consideration). The complexity and constraints of performing decision analysis of diagnostic tests on costs and health outcomes makes it particularly challenging and, as a result, quality issues remain. This review provides a comprehensive assessment of modelling in HTA reports, highlights problems and gives recommendations for future diagnostic modelling practice. Electronic supplementary material The online version of this article (10.1007/s41669-018-0109-9) contains supplementary material, which is available to authorized users.

© 2018 Nickless et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background A stepped wedge cluster randomised trial (SWCRT) is a multicentred study which allows an intervention to be rolled out at sites in a random order. Once the intervention is initiated at a site, all participants within that site remain exposed to the intervention for the remainder of the study. The time since the start of the study (“calendar time”) may affect outcome measures through underlying time trends or periodicity. The time since the intervention was introduced to a site (“exposure time”) may also affect outcomes cumulatively for successful interventions, possibly in addition to a step change when the intervention began. Methods Motivated by a SWCRT of self-monitoring for bipolar disorder, we conducted a simulation study to compare model formulations to analyse data from a SWCRT under 36 different scenarios in which time was related to the outcome (improvement in mood score). The aim was to find a model specification that would produce reliable estimates of intervention effects under different scenarios. Nine different formulations of a linear mixed effects model were fitted to these datasets. These models varied in the specification of calendar and exposure times. Results Modelling the effects of the intervention was best accomplished by including terms for both calendar time and exposure time. Treating time as categorical (a separate parameter for each measurement time-step) achieved the best coverage probabilities and low bias, but at a cost of wider confidence intervals compared to simpler models for those scenarios which were sufficiently modelled by fewer parameters. Treating time as continuous and including a quadratic time term performed similarly well, with slightly larger variations in coverage probability, but narrower confidence intervals and in some cases lower bias. The impact of misspecifying the covariance structure was comparatively small. Conclusions We recommend that unless there is a priori information to indicate the form of the relationship between time and outcomes, data from SWCRTs should be analysed with a linear mixed effects model that includes separate categorical terms for calendar time and exposure time. Prespecified sensitivity analyses should consider the different formulations of these time effects in the model, to assess their impact on estimates of intervention effects.

BackgroundSore throat is a common and self-limiting condition. There remains ambiguity in stratifying patients to immediate, delayed, or no antibiotic prescriptions. The National Institute for Health and Care Excellence (NICE) recommends two clinical prediction rules (CPRs), FeverPAIN and Centor, to guide decision making.AimTo describe the diagnostic accuracy of CPRs in identifying streptococcal throat infections.Design & settingAdults presenting to UK primary care with sore throat, who did not require immediate antibiotics.MethodAs part of the Treatment Options without Antibiotics for Sore Throat (TOAST) trial, 565 participants, aged ≥18 years, were recruited on day of presentation to general practice. Physicians could opt to give delayed prescriptions. CPR scores were not part of the trial protocol but were calculated post hoc from baseline assessments. Diagnostic accuracy was calculated by comparing scores with throat swab cultures.ResultsIt was found that 81/502 (16.1%) patients had group A, C, or G streptococcus cultured on throat swab. Overall diagnostic accuracy of both CPRs was poor: area under receiver operating characteristics (ROC) curve 0.62 for Centor; and 0.59 for FeverPAIN. Post-test probability of a positive or negative test was 27.3% (95% confidence interval [CI] = 6.0% to 61.0%) and 84.1% (95% CI = 80.6% to 87.2%) for FeverPAIN ≥4; versus 25.7% (95% CI = 16.2% to 37.2%) and 85.5% (95% CI = 81.8% to 88.7%) for Centor ≥3. Higher CPR scores were associated with increased delayed antibiotic prescriptions (χ2 = 8.42, P = 0.004 for FeverPAIN ≥4; χ2 = 32.0, PConclusionIn those who do not require immediate antibiotics in primary care, neither CPR provides a reliable way of diagnosing streptococcal throat infection. However, clinicians were more likely to give delayed prescriptions to those with higher scores.