This Article contains errors in Reference 25, which is incorrectly given as: 'O'Sullivan, J. W. et al. Overtesting and undertesting in primary care: a systematic review and meta-analysis BMJ Open 2018;8:e018557. https://doi.org/10.1136/bmjopen-2017-0185578557.' The correct reference is listed below as ref. 1.
\n \n\n \n \nThe authors regret the omission of the following In the Acknowledgements: \u201cLucy Mackillop was supported by the NIHR Oxford Biomedical Research Centre.\u201d In the Affiliations: \u201cNIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust.\u201d The authors would like to apologise for any inconvenience caused.
\n \n\n \n \nObjective: To investigate feasibility and acceptability of self-testing for proteinuria during pregnancy. Study design: Mixed methods approach which included: an accuracy study where pregnant women (n = 100) and healthcare professionals (n = 96) tested seven synthetic protein samples and completed a questionnaire, a feasibility study where pregnant women who were self-monitoring their blood pressure were asked to self-test for proteinuria (n = 30), and an online questionnaire about women's experiences of self-testing (n = 200). Main outcome measures: Sensitivity and specificity of testing and questionnaire results. Results: There were no significant differences in the accuracy of synthetic sample testing by pregnant women (sensitivity 0.81 (95% confidence intervals (CI) 0.78\u20130.85), specificity 0.93 (95% CI 0.91\u20130.95)) and healthcare professionals: (sensitivity 0.83 (95% CI 0.79\u20130.86), specificity 0.92 (95% CI 0.90\u20130.94)). Automated readers had significantly better sensitivity (0.94 (0.91\u20130.97) (p \u2264.001 in each case), but worse specificity 0.78 (0.69\u20130.85). Similar results were gained using self-tested urine samples compared to staff-testing using a reference standard of laboratory urine protein-creatinine ratio (uPCR). Women who completed the online survey with experience of self-testing (n = 39, 20%) generally found it easy, and with support from healthcare professionals felt it improved involvement in their care and reduced anxiety. Conclusions: Self-testing for proteinuria by pregnant women had similar accuracy to healthcare professional testing and was acceptable to both groups. Self-testing of urine combined with self-monitoring of blood pressure could provide a useful adjunct to clinic-based surveillance for the detection of pre-eclampsia. Such novel strategies warrant further research.
\n \n\n \n \nObjectives To characterise serum creatinine and urinary protein testing in UK general practices from 2005 to 2013 and to examine how the frequency of testing varies across demographic factors, with the presence of chronic conditions and with the prescribing of drugs for which kidney function monitoring is recommended. Design Retrospective open cohort study. Setting Routinely collected data from 630 UK general practices contributing to the Clinical Practice Research Datalink. Participants 4 573 275 patients aged over 18 years registered at up-to-standard practices between 1 April 2005 and 31 March 2013. At study entry, no patients were kidney transplant donors or recipients, pregnant or on dialysis. Primary outcome measures The rate of serum creatinine and urinary protein testing per year and the percentage of patients with isolated and repeated testing per year. Results The rate of serum creatinine testing increased linearly across all age groups. The rate of proteinuria testing increased sharply in the 2009-2010 financial year but only for patients aged 60 years or over. For patients with established chronic kidney disease (CKD), creatinine testing increased rapidly in 2006-2007 and 2007-2008, and proteinuria testing in 2009-2010, reflecting the introduction of Quality and Outcomes Framework indicators. In adjusted analyses, CKD Read codes were associated with up to a twofold increase in the rate of serum creatinine testing, while other chronic conditions and potentially nephrotoxic drugs were associated with up to a sixfold increase. Regional variation in serum creatinine testing reflected country boundaries. Conclusions Over a nine-year period, there have been increases in the numbers of patients having kidney function tests annually and in the frequency of testing. Changes in the recommended management of CKD in primary care were the primary determinant, and increases persist even after controlling for demographic and patient-level factors. Future studies should address whether increased testing has led to better outcomes.
\n \n\n \n \nBackground: Airborne transmission is the spread of an infectious agent caused by the dissemination of droplet nuclei (aerosols) that remain infectious when suspended in the air. We carried out a systematic review to identify, appraise and summarise the evidence from studies of the role of airborne transmission of SARS-CoV-2. Methods: We searched LitCovid, MedRxiv, Google Scholar and the WHO Covid-19 database from 1 February 2020 to 30 May 2022 and included studies on airborne transmission. Data were dual extracted, and we assessed quality using a modified QUADAS 2 risk of bias tool. Results: We included 128 primary studies and 29 reviews on airborne SARS-CoV-2. Of the 128 primary studies, 105 (82%) reported data on RT-PCR from air samples, 28 (22%) report cycle threshold values and 36 (28%) copies per sample volume. All primary studies were observational. The research often lacked standard methods, standard sampling sizes and reporting items. We found 69 descriptions of different air samplers deployed. Of the 80 in-hospital studies that reported binary RT-PCR tests, 362/3079 air samples from 75 studies conducted in hospital ward environments were positive (median 8%, IQR=0 to 23%); 23 studies reported 74/703 RT-PCR positive air samples in the ICU setting (median 17%, IQR=0% to 38%) Thirty-eight studies reported potential air transmission in the outdoors or in the community. Twenty-six studies attempted viral culture, none of which definitively demonstrated that replication-competent SARS-CoV-2 could be recovered in the air. Conclusion: SARS-CoV-2 RNA is detectable intermittently in the air in various settings. Standardized guidelines for conducting and reporting research on airborne transmission are needed. The lack of recoverable viral culture of SARS-CoV-2 from air samples prevents firm conclusions about the definitive role of airborne transmission in SARS-CoV-2.
\n \n\n \n \nObjective: 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.
\n \n\n \n \nJason Oke and Tom Fanshawe expose four simple biases that can change our understanding of cancer survival rates and skew comparisons made between countries.
\n \n\n \n \nBackground:The aim was to examine the association between smoking cessation and prognosis in smoking-related cancer as it is unclear that cessation reduces mortality.Methods:In this retrospective cohort study from 1999 to 2013, we assessed the association between cessation during the first year after diagnosis and all-cause and cancer-specific mortality.Results:Of 2882 lung, 757 upper aero-digestive tract (UAT) and 1733 bladder cancer patients 27%, 29% and 21% of lung, UAT and bladder cancer patients quit smoking. In lung cancer patients that quit, all-cause mortality was significantly lower (HR: 0.82 (0.74-0.92), while cancer-specific mortality (HR: 0.89 (0.76-1.04) and death due to index cancer (HR: 0.90 (0.77-1.05) were non-significantly lower. In UAT cancer, all-cause mortality (HR: 0.81 (0.58-1.14), cancer-specific mortality (HR: 0.84 (0.48-1.45), and death due to index cancer (HR: 0.75 (0.42-1.34) were non-significantly lower. There was no evidence of an association between quitting and mortality in bladder cancer. The HRs were 1.02 (0.81-1.30) for all-cause, 1.23 (0.81-1.86) for cancer specific, and 1.25 (0.71-2.20) for death due to index cancer. These showed a non-significantly lower risk in sensitivity analyses.Conclusions:People with lung and possibly UAT cancer who quit smoking have a lower risk of mortality than people who continue smoking.
\n \n\n \n \nBackground Multiple myeloma is a haematological cancer characterised by numerous non-specific symptoms leading to diagnostic delay in a large proportion of patients. Aim To identify which blood tests are useful in suggesting or excluding a diagnosis of myeloma. Design and setting A matched case-control study set in UK primary care using routinely collected data from the Clinical Practice Research Datalink. Method Symptom prevalence and blood tests were analysed up to 5 years before diagnosis in 2703 cases and 12 157 matched controls. Likelihood ratios (LR) were used to classify tests or their combinations as useful rule-in tests (LR+ = \u22655), or rule-out tests (LR- = \u22640.2). Results Raised plasma viscosity (PV) had an LR+ = 2.0, 95% confidence interval [CI] = 1.7 to 2.3; erythrocyte sedimentation rate (ESR) 1.9, 95% CI = 1.7 to 2.0; and C-reactive protein (CRP) 1.2, 95% CI = 1.1 to 1.4. A normal haemoglobin had an LR- = 0.42, 95% CI = 0.39 to 0.45; calcium LR- = 0.81, 95% CI = 0.78 to 0.83; and creatinine LR- = 0.80, 95% CI = 0.77 to 0.83. The test combination with the lowest LR- was all normal haemoglobin with calcium and PV, which had an LR- = 0.06, 95% CI = 0.02 to 0.18, though the LR- for normal haemoglobin and PV together was 0.12 (95% CI = 0.07 to 0.23). Conclusion Plasma viscosity and ESR are better for both ruling in and ruling out the disease compared with C-reactive protein. A combination of a normal ESR or PV and normal haemoglobin is a simple rule-out approach for patients currently being tested in primary care.
\n \n\n \n \nObjectives To quantify the duration of each step of the diagnostic pathway for patients with multiple myeloma from symptom onset to confirmation of diagnosis. Design Systematic review and meta-analysis. Data sources and selection criteria The MEDLINE and Embase databases were searched up until January 2018 to identify articles that reported time intervals from onset of symptoms to diagnosis. Articles focusing on children or adolescents and on the asymptomatic form of the disease (monoclonal gammopathies and smouldering myeloma) were excluded. Data collection and data analysis Data were extracted independently by two reviewers. Weighted estimates of the median and IQR were calculated. Risk of bias was assessed using the Aarhus checklist. Main results Nine studies were included. The patient interval (first symptom to first presentation) had a median of 26.3 days (IQR: 1-98, n=465, two studies). Subsequently, the primary care interval (first presentation to first referral) was 21.6 days (IQR: 4.6-55.8, n=326, two studies), the diagnostic interval (first presentation to diagnosis) was 108.6 days (IQR: 33.3-241.7, n=5395, seven studies) and the time to diagnosis (first symptom to diagnosis) interval was 163 days (IQR: 84-306, n=341, one study). No studies reported data for the referral to diagnosis interval. Conclusion The review demonstrates that there is scope for significant reductions in the time to myeloma diagnosis. At present, many patients experience a diagnostic interval longer than 3 months until diagnosis is confirmed. Review registration Not available. Protocol available in the appendix.
\n \n\n \n \nPURPOSE Smoking cessation after a diagnosis of lung, bladder, and upper aerodigestive tract cancer appears to improve survival, and support to quit would improve cessation. The aims of this study were to assess how often general practitioners provide active smoking cessation support for these patients and whether physician behavior is influenced by incentive payments. METHODS Using electronic primary care records from the UK Clinical Practice Research Datalink, 12,393 patients with incident cases of cancer diagnosed between 1999 and 2013 were matched 1 to 1 to patients with incident cases of coronary heart disease (CHD) diagnosed during the same time. We assessed differences in the proportion for whom physicians updated smoking status, advised quitting, and prescribed cessation medications, as well as the proportion of patients who stopped smoking within a year of diagnosis. We further examined whether any differences arose because the physicians were offered incentives to address smoking in patients with CHD and not cancer. RESULTS At diagnosis, 32.0% of patients with cancer and 18.2% of patients with CHD smoked tobacco. Patients with cancer were less likely than patients with CHD to have their general practitioners update smoking status (OR = 0.18; 95% CI, 0.17-0.19), advise quitting (OR = 0.38; 95% CI, 0.36-0.40), or prescribe medication (OR = 0.67; 95% CI, 0.63-0.73), and they were less likely to have stopped smoking (OR = 0.76; 95% CI, 0.69-0.84). One year later 61.7% of patients with cancer and 55.4% with CHD who were smoking at diagnosis were still smoking. Introducing incentive payments was associated with more frequent interventions, but not for patients with CHD specifically. CONCLUSIONS General practitioners were less likely to support smoking cessation in patients with cancer than with CHD, and patients with cancer were less likely to stop smoking. This finding is not due to the difference in incentive payments.
\n \n\n \n \nObjectives: To determine how many kidney function tests are done, on whom, how frequently they are performed and how they have changed over time. Design: Retrospective study of all serum creatinine, urine albumin and urine creatinine tests. Setting: Primary and secondary care in Oxfordshire from 1993 to 2013. Participants: Unselected population of 1 220 447 people. Main outcome measures: The total number of creatinine and urinary protein tests ordered from primary and secondary care and the number of tests per year stratified by categories of estimated glomerular filtration rate (EGFR). The frequency of testing in patients having their kidney function monitored. Results: Creatinine requests from primary care increased steadily from 1997 and exceeded 220 000 requests in 2013. Tests corresponding to normal kidney function (EGFR 60/mL/min/1.73 m2) constituted 59% of all kidney function tests in 1993 and accounted for 83% of all tests in 2013. Test corresponding to chronic kidney disease (CKD) stages 3-5 declined after 2007. Reduced kidney function, albuminuria, male gender, diabetes and age were independently associated with more frequent monitoring. For a female patient between 61 and 80 years and with stage 3a CKD, the average number of serum creatinine tests (95% CI) was 3.23/ year (3.19 to 3.26) and for a similar woman with diabetes, the average number of tests was 5.50 (5.44 to 5.56) tests per year. Conclusions: There has been a large increase in the number of kidney function tests over the past two decades. However, we found little evidence that this increase is detecting more CKD. Tests are becoming more frequent in people with and without evidence of renal impairment. Future work using a richer data source could help unravel the underlying reasons for the increased testing and determine how much is necessary and useful.
\n \n\n \n \nAim To identify the key components of natriuretic peptide (NP)-guided treatment interventions which reduced hospitalisation in patients with heart failure (HF). Methods and results We extracted detailed information on the components of interventions from studies of NP-guided treatment of HF identified in a previous systematic review. We used meta-regression techniques to assess univariate associations between components and the strength of the reduction in HF hospitalisations and all-cause mortality. A Bayesian meta-analysis approach was used to re-estimate study-level effects in order to identify the study with the most effective NP-guided monitoring intervention. Finally, we examined the intervention options common to the studies in which the 95% credible interval excluded no effect. We identified eight components of NP-guided treatment from ten studies. Univariate comparisons produced mainly equivocal results, but single trial choice and common components analysis led to similar conclusions. Using a predefined treatment protocol, setting a stringent NP target (N-terminal pro-B-type natriuretic peptide of 1000 pg/mL or B-type natriuretic peptide 100 pg/mL) and including a relative targetwere potential key components to reducing HF hospitalisations using NP-guided therapy. Conclusion This analysis provides a description of the key components of NP-guided treatment which could help policy makers develop specific recommendations for HF management. Our research suggests that NP-guided interventions could be simplified, but more research in relevant health settings, such as primary care, is required.
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