Clinical prediction models to support the diagnosis of asthma in primary care: a systematic review protocol

Substantial over-diagnosis and under-diagnosis of asthma in adults and children has recently been reported. As asthma is mostly diagnosed in non-specialist settings, a clinical prediction model (CPM) to aid the diagnosis of asthma in primary care may help improve diagnostic accuracy. We aim to systematically identify, describe, compare, and synthesise existing CPMs designed to support the diagnosis of asthma in children and adults presenting with symptoms suggestive of the disease, in primary care settings or equivalent populations. We will systematically search Medline, Embase and CINAHL from 1 January 1990 to present. Any CPM derived for use in a primary care population will be included. Equivalent populations in countries without a developed primary care service will also be included. The probability of asthma diagnosis will be the primary outcome. We will include CPMs designed for use in clinical practice to aid the diagnostic decision making of a healthcare professional during the assessment of an individual with symptoms suggestive of asthma. We will include derivation studies, and external model validation studies. Two reviewers will independently screen titles/abstracts and full texts for eligibility and extract data from included papers. The CHARMS checklist (or PROBAST if available) will be used to assess risk of bias within each study. Results will be summarised by narrative synthesis with meta-analyses completed if possible. This systematic review will provide comprehensive information about existing CPMs for the diagnosis of asthma in primary care and will inform the development of a future diagnostic model.<br/

Excluding venous thromboembolism using point of care D-dimer tests in outpatients: a diagnostic meta-analysis

Objective To review the evidence on the diagnostic accuracy of the currently available point of care D-dimer tests for excluding venous thromboembolism

Sex- and age specific association of new-onset atrial fibrillation with in-hospital mortality in hospitalised COVID-19 patients

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a systemic disease with cardiovascular involvement, including cardiac arrhythmias. Notably, new-onset atrial fibrillation (AF) and atrial flutter (AFL) during hospitalisation in COVID-19 patients has been associated with increased mortality. However, how this risk is impacted by age and sex is still poorly understood. METHODS: For this multicentre cohort study, we extracted demographics, medical history, occurrence of electrical disorders and in-hospital mortality from the large international patient registry CAPACITY-COVID. For each electrical disorder, prevalence during hospitalisation was calculated. Subsequently, we analysed the incremental prognostic effect of developing AF/AFL on in-hospital mortality, using multivariable logistic regression analyses, stratified for sex and age. RESULTS: In total, 5782 patients (64% male; median age 67) were included. Of all patients 11.0% (95% CI 10.2–11.8) experienced AF and 1.6% (95% CI 1.3–1.9) experienced AFL during hospitalisation. Ventricular arrhythmias were rare (<0.8% (95% CI 0.6–1.0)) and a conduction disorder was observed in 6.3% (95% CI 5.7–7.0). An event of AF/AFL appeared to occur more often in patients with pre-existing heart failure. After multivariable adjustment for age and sex, new-onset AF/AFL was significantly associated with a poorer prognosis, exemplified by a two- to three-fold increased risk of in-hospital mortality in males aged 60–72 years, whereas this effect was largely attenuated in older male patients and not observed in female patients. CONCLUSION: In this large COVID-19 cohort, new-onset AF/AFL was associated with increased in-hospital mortality, yet this increased risk was restricted to males aged 60–72 years

Search Filters for Finding Prognostic and Diagnostic Prediction Studies in Medline to Enhance Systematic Reviews

Background: The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter. Methodology/Principal Findings: Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next -using word frequency methods - we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85. Conclusions/Significance: Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studie

Excluding pulmonary embolism in primary care using the Wells-rule in combination with a point-of care D-dimer test: a scenario analysis

ABSTRACT: BACKGROUND: In secondary care the Wells clinical decision rule (CDR) combined with a quantitative D-dimer test can exclude pulmonary embolism (PE) safely. The introduction of point-of-care (POC) D-dimer tests facilitates a similar diagnostic strategy in primary care. We estimated failure-rate and efficiency of a diagnostic strategy using the Wells-CDR combined with a POC-D-dimer test for excluding PE in primary care. We considered ruling out PE safe if the failure rate was <2% with a maximum upper confidence limit of 2.7%. METHODS: We performed a scenario-analysis on data of 2701 outpatients suspected of PE. We used test characteristics of two qualitative POC-D-dimer tests, as derived from a meta-analysis and combined these with the Wells-CDR-score. RESULTS: In scenario 1 (SimpliRed-D-dimer sensitivity 85%, specificity 74%) PE was excluded safely in 23.8% of patients but only by lowering the cut-off value of the Wells rule to <2. (failure rate: 1.4%, 95% CI 0.6-2.6%) In scenario 2 (Simplify-D-dimer sensitivity 87%, specificity 62%) PE was excluded safely in 12.4% of patients provided that the Wells-cut-off value was set at 0. (failure rate: 0.9%, 95% CI 0.2-2.6%) CONCLUSION: Theoretically a diagnostic strategy using the Wells-CDR combined with a qualitative POC-D-dimer test can be used safely to exclude PE in primary care albeit with only moderate efficienc

External validation and updating of prediction models of bleeding risk in patients with cancer receiving anticoagulants

OBJECTIVE: Patients with cancer are at increased bleeding risk, and anticoagulants increase this risk even more. Yet, validated bleeding risk models for prediction of bleeding risk in patients with cancer are lacking. The aim of this study is to predict bleeding risk in anticoagulated patients with cancer. METHODS: We performed a study using the routine healthcare database of the Julius General Practitioners' Network. Five bleeding risk models were selected for external validation. Patients with a new cancer episode during anticoagulant treatment or those initiating anticoagulation during active cancer were included. The outcome was the composite of major bleeding and clinically relevant non-major (CRNM) bleeding. Next, we internally validated an updated bleeding risk model accounting for the competing risk of death. RESULTS: The validation cohort consisted of 1304 patients with cancer, mean age 74.0±10.9 years, 52.2% males. In total 215 (16.5%) patients developed a first major or CRNM bleeding during a mean follow-up of 1.5 years (incidence rate; 11.0 per 100 person-years (95% CI 9.6 to 12.5)). The c-statistics of all selected bleeding risk models were low, around 0.56. Internal validation of an updated model accounting for death as competing risk showed a slightly improved c-statistic of 0.61 (95% CI 0.54 to 0.70). On updating, only age and a history of bleeding appeared to contribute to the prediction of bleeding risk. CONCLUSIONS: Existing bleeding risk models cannot accurately differentiate bleeding risk between patients. Future studies may use our updated model as a starting point for further development of bleeding risk models in patients with cancer

Atrial fibrillation: trends in prevalence and antithrombotic prescriptions in the community

Introduction: In the past decade, the atrial fibrillation (AF) landscape, including the treatment modalities, has drastically changed. This raises the question how AF prevalence and choices in antithrombotic therapy prescription have developed in the community over time. Methods: Routine care data from the Julius General Practitioners’ Network (JGPN) were used to calculate the yearly prevalence of AF and to quantify the percentage of all patients who were prescribed a platelet inhibitor, vitamin K antagonist (VKA), non-VKA oral anticoagulant (NOAC) or no antithrombotic medication. To explore whether certain patient characteristics are associated with selective prescription of oral anticoagulants (OAC), we applied logistic regression analyses. Results: From 2008 through 2017, the JGPN database included 7459 unique AF patients. During this period, the prevalence of AF increased from 0.4% to 1.4%. The percentage of patients prescribed a VKA declined from 47% to 41%, whereas the percentage of patients prescribed a NOAC rose from 0% to 20%. In patients with new-onset AF, older age, heart failure, diabetes mellitus, vascular disease and dementia were independently associated with a higher likelihood of VKA rather than NOAC prescription. In 2017, 25% of all patients with AF and a CHA2DS2-VASc score ≥ 2 were not prescribed OAC therapy (i.e. 8% with platelet inhibitor monotherapy and 17% without any antithrombotic therapy). Conclusion: Between 2008 and 2017, AF prevalence in the community more than tripled. Prescription patterns showed possible ‘channelling’ of VKAs over NOACs in frailer, elderly patients, whereas still about one in every four AF patients with a CHA2DS2-VASc score ≥ 2 was not prescribed any prophylactic OAC therapy

Safety of off-label dose reduction of non-vitamin K antagonist oral anticoagulants in patients with atrial fibrillation

Aim: To investigate the effects of off-label non-vitamin K oral anticoagulant (NOAC) dose reduction compared with on-label standard dosing in atrial fibrillation (AF) patients in routine care. Methods: Population-based cohort study using data from the United Kingdom Clinical Practice Research Datalink, comparing adults with non-valvular AF receiving an off-label reduced NOAC dose to patients receiving an on-label standard dose. Outcomes were ischaemic stroke, major/non-major bleeding and mortality. Inverse probability of treatment weighting and inverse probability of censoring weighting on the propensity score were applied to adjust for confounding and informative censoring. Results: Off-label dose reduction occurred in 2466 patients (8.0%), compared with 18 108 (58.5%) on-label standard-dose users. Median age was 80 years (interquartile range [IQR] 73.0-86.0) versus 72 years (IQR 66-78), respectively. Incidence rates were higher in the off-label dose reduction group compared to the on-label standard dose group, for ischaemic stroke (0.94 vs 0.70 per 100 person years), major bleeding (1.48 vs 0.83), non-major bleeding (6.78 vs 6.16) and mortality (10.12 vs 3.72). Adjusted analyses resulted in a hazard ratio of 0.95 (95% confidence interval [CI] 0.57-1.60) for ischaemic stroke, 0.88 (95% CI 0.57-1.35) for major bleeding, 0.81 (95% CI 0.67-0.98) for non-major bleeding and 1.34 (95% CI 1.12-1.61) for mortality. Conclusion: In this large population-based study, the hazards for ischaemic stroke and major bleeding were low, and similar in AF patients receiving an off-label reduced NOAC dose compared with on-label standard dose users, while non-major bleeding risk appeared to be lower and mortality risk higher. Caution towards prescribing an off-label reduced NOAC dose is therefore required

Impact of COVID-19 pandemic on the accuracy of telephone triage of callers with shortness of breath and/or chest discomfort in Dutch out-of-hours primary care: A retrospective observational study

Background: Anecdotal reports suggest that missed diagnosis in general practice during the first wave of the COVID-19 pandemic contributed to a drop in life-threatening events (LTEs) detected in hospitals. Objectives: To investigate the impact of the COVID-19 pandemic on the accuracy of urgency allocation by telephone triage of patients with shortness of breath and/or chest discomfort in out-of-hours primary care (OHS-PC). Accuracy is defined as the correct allocation of high urgency to patients with LTEs and low urgency to those without. Methods: Retrospective observational study with data from callers contacting OHS-PC for shortness of breath and/or chest discomfort, between 1 March and 1 June 2019 (pre-pandemic) and 1 March to 1 June 2020 (first wave COVID-19 pandemic). Sensitivity and specificity of telephone urgency allocation were compared during both periods with LTEs, including acute coronary syndrome, and pulmonary embolism, as the reference. Results: 3,064 adults (1,840 COVID-19 pandemic and 1,224 pre-pandemic, p < 0.001) were included in the study. The sensitivity of urgency allocation was similar during and before the COVID-19 pandemic (0.68, 95% CI 0.59 to 0.75 vs. 0.68, 95% CI 0.60 to 0.75, p = 0.944). Specificity was slightly higher during the COVID-19 pandemic (0.52, 95% CI 0.50 to 0.55 vs. 0.45, 95% CI 0.42 to 0.48, p < 0.001). Conclusion: Despite a surge in calls from adults with shortness of breath and/or chest discomfort during the COVID-19 pandemic, the accuracy of telephone triage for LTEs in OHS-PC remained similar to the pre-pandemic era. Improvement of telephone triage seems necessary in both periods

YEARS clinical decision rule for diagnosing pulmonary embolism: a prospective diagnostic cohort follow-up study in primary care

Objectives The Wells rule is often used in primary care to rule out pulmonary embolism (PE), but its efficiency is low as many referred patients do not have PE. In this study, we evaluated in primary care an alternative and potentially more efficient diagnostic strategy—the YEARS algorithm; a simplified three-item version of the Wells rule combined with a pretest probability adjusted D-dimer interpretation. Design In this comprehensive prospective diagnostic validation study, primary care patients suspected of PE were enrolled by their general practitioner. All three YEARS items were collected in addition to D-dimer results, and patients were followed for 3 months to establish the final diagnosis. Setting Primary care in the Netherlands. Participants 753 patients with suspected acute PE were included. Five patients (0.7%) were lost to followup. Main outcome measures Failure rate (number of PE cases among patients classified by the algorithm as ‘PE ruled-out’) and efficiency (fraction of patients classified as ‘PE probable/further imaging needed’). Results Prevalence of PE was 5.5% (41/748 patients). In total, 603 patients were classified as ‘PE ruled-out’ by the YEARS algorithm (532 with zero YEARS items and a D-dimer<1000 ng/mL and 71 with≥1 positive YEARS item and a D-dimer<500 ng/mL), resulting in an efficiency of 80.6% (603/748 patients, 95% CI 77.6% to 83.4%). Of these patients, three patients had a diagnosis of nonfatal PE during 3 months follow-up, all three with zero YEARS items and D-dimer between 500 and 1000 ng/ mL, resulting in an overall diagnostic failure rate of 0.50% (3/603 patients, 95% CI 0.13% to 1.57%). In the patients categorised as ‘imaging needed’ (n=145), a total of 38 (26.2%) were indeed diagnosed with PE. Conclusions Our study suggests that acute PE can be safely ruled out in 80% of patients by the YEARS algorithm in a primary care setting, while only 20% of patients required referral to hospital care for imaging tests. In those classified as ‘imaging needed’, PE was present in about one in every four patients, demonstrating a high detection proportion