Diagnosing acute coronary syndrome in primary care: comparison of the physicians' risk estimation and a clinical decision rule

Ruling out acute coronary syndrome in primary care with a clinical decision rule and a capillary, high-sensitive troponin I point of care test: study protocol of a diagnostic RCT in the Netherlands (POB HELP)

INTRODUCTION

Chest pain is a common reason for consultation in primary care. To rule out acute coronary syndrome (ACS), general practitioners (GP) refer 40%-70% of patients with chest pain to the emergency department (ED). Only 10%-20% of those referred, are diagnosed with ACS. A clinical decision rule, including a high-sensitive cardiac troponin-I point-of-care test (hs-cTnI-POCT), may safely rule out ACS in primary care. Being able to safely rule out ACS at the GP level reduces referrals and thereby alleviates the burden on the ED. Moreover, prompt feedback to the patients may reduce anxiety and stress.

METHODS AND ANALYSIS

The POB HELP study is a clustered randomised controlled diagnostic trial investigating the (cost-)effectiveness and diagnostic accuracy of a primary care decision rule for acute chest pain, consisting of the Marburg Heart Score combined with a hs-cTnI-POCT (limit of detection 1.6 ng/L, 99th percentile 23 ng/L, cut-off value between negative and positive used in this study 3.8 ng/L). General practices are 2:1 randomised to the intervention group (clinical decision rule) or control group (regular care). In total 1500 patients with acute chest pain are planned to be included by GPs in three regions in The Netherlands. Primary endpoints are the number of hospital referrals and the diagnostic accuracy of the decision rule 24 hours, 6 weeks and 6 months after inclusion.

ETHICS AND DISSEMINATION

The medical ethics committee Leiden-Den Haag-Delft (the Netherlands) has approved this trial. Written informed consent will be obtained from all participating patients. The results of this trial will be disseminated in one main paper and additional papers on secondary endpoints and subgroup analyses.

TRIAL REGISTRATION NUMBERS

NL9525 and NCT05827237.

Platelet MicroRNA-484 as a Novel Diagnostic Biomarker for Acute Coronary Syndrome

OBJECTIVE

Platelet microRNAs (miRs) have been indicated as a diagnostic biomarker in various diseases, including acute coronary syndrome (ACS). This study aimed to investigate the expression of miR-223-5p, miR-126-5p, miR-484, and miR-130a-3p in individuals with coronary artery disease (CAD).

METHODS

Forty subjects with CAD and 13 healthy individuals were under study. The expression of miR-223-5p, miR-126-5p, miR-484, and miR-130a-3p was measured in platelets by quantitative reverse transcription-polymerase chain reaction. The relationship between miRNA expression and various parameters of the subjects was analyzed using analysis of variance and Spearman and t-tests.

RESULTS

The miR-484 expression was significantly upregulated in the ACS subjects (P = .0097). Moreover, miR-484 had diagnostic value for screening subjects with unstable angina vs controls (area under the curve [AUC] = 0.978, 95% confidence interval [CI] 0.92-1, P = .0006) and NSTEMI patients versus controls (AUC = 0.910, 95% CI 0.74-1, P = .005).

CONCLUSION

The results of this study indicate that the upregulated expression of miR-484 in ACS patients might be used as a diagnostic biomarker in ACS.

Development and validation of a prediction rule for patients suspected of acute coronary syndrome in primary care: a cross-sectional study

OBJECTIVE

To develop and validate a symptom-based prediction rule for early recognition of acute coronary syndrome (ACS) in patients with acute chest discomfort who call out-of-hours services for primary care (OHS-PC).

DESIGN

Cross-sectional study. A diagnostic prediction rule was developed with multivariable regression analyses. All models were validated with internal-external cross validation within seven OHS-PC locations. Both age and sex were analysed as statistical interaction terms, applying for age non-linear effects.

SETTING

Seven OHS-PC in the Netherlands.

PARTICIPANTS

2192 patients who called OHS-PC for acute chest discomfort (pain, pressure, tightness or discomfort) between 2014 and 2017. Backed up recordings of telephone triage conversations were analysed.

PRIMARY AND SECONDARY OUTCOMES MEASURES

Diagnosis of ACS retrieved from the patient's medical records in general practice, including hospital specialists discharge letters. Performance of the prediction rules was calculated with the c-statistic and the final model was chosen based on net benefit analyses.

RESULTS

Among the 2192 patients who called the OHS-PC with acute chest discomfort, 8.3% females and 15.3% males had an ACS. The final diagnostic model included seven predictors (sex, age, acute onset of chest pain lasting less than 12 hours, a pressing/heavy character of the pain, radiation of the pain, sweating and calling at night). It had an adjusted c-statistic of 0.77 (95% CI 0.74 to 0.79) with good calibration.

CONCLUSION

The final prediction model for ACS has good discrimination and calibration and shows promise for replacing the existing telephone triage rules for patients with acute chest discomfort in general practice and OHS-PC.

TRIAL REGISTRATION NUMBER

NTR7331.

Prehospital diagnostic algorithm for acute coronary syndrome using machine learning: a prospective observational study

Rapid and precise prehospital recognition of acute coronary syndrome (ACS) is key to improving clinical outcomes. The aim of this study was to investigate a predictive power for predicting ACS using the machine learning-based prehospital algorithm. We conducted a multicenter observational prospective study that included 10 participating facilities in an urban area of Japan. The data from consecutive adult patients, identified by emergency medical service personnel with suspected ACS, were analyzed. In this study, we used nested cross-validation to evaluate the predictive performance of the model. The primary outcomes were binary classification models for ACS prediction based on the nine machine learning algorithms. The voting classifier model for ACS using 43 features had the highest area under the receiver operating curve (AUC) (0.861 [95% CI 0.775–0.832]) in the test score. After validating the accuracy of the model using the external cohort, we repeated the analysis with a limited number of selected features. The performance of the algorithms using 17 features remained high AUC (voting classifier, 0.864 [95% CI 0.830–0.898], support vector machine (radial basis function), 0.864 [95% CI 0.829–0.887]) in the test score. We found that the machine learning-based prehospital algorithms showed a high predictive power for predicting ACS.

Performance of risk scores for coronary artery disease: a retrospective cohort study of patients with chest pain in urgent primary care

OBJECTIVE

To evaluate the diagnostic performance of the Marburg Heart Score (MHS), INTERCHEST, Gencer rule, Bruins Slot rule and compare these with unaided clinical judgement in patients with chest pain in urgent primary care.

DESIGN

Retrospective, cohort study.

SETTING

Regional primary care facility responsible for out-of-hours primary care for a quarter-million people in the Netherlands.

PARTICIPANTS

Consecutive patients aged ≥18 years who were evaluated for chest pain.

MAIN OUTCOME MEASURES

Discriminatory ability (C-statistic), sensitivity, specificity, positive and negative predictive values (PPV/NPV). The reference standard involved a composite endpoint of the occurrence of death, acute coronary syndrome or coronary revascularisation (=major adverse cardiac events; MACE) up to 6 weeks after initial contact.

RESULTS

A total of 664 patients were included, of whom 4.8% (n=32) had a MACE event. C-statistics for MHS, INTERCHEST, Gencer and Bruins Slot rule were: 0.77 (95% CI 0.69 to 0.84), 0.85 (95% CI 0.78 to 0.92), 0.72 (95% CI 0.63 to 0.81) and 0.72 (95% CI 0.63 to 0.81), respectively. Optimal diagnostic accuracy was found for MHS ≥2 (sensitivity=81.3%, specificity=67.1%, PPV=11.1%, NPV=98.6%), INTERCHEST ≥2 (sensitivity=87.5%, specificity=78.8%, PPV=17.3%, NPV=99.1%), Gencer ≥2 (sensitivity=84.4%, specificity=37.8%, PPV=6.4%, NPV=98.0%) and Bruins Slot≥2 (sensitivity=90.6%, specificity=40.8%, PPV=7.2%, NPV=98.9%). Physicians referred 157 patients (23.6%) and missed 6 out of 32 MACEs (sensitivity=81.3%, specificity=79.3%, PPV=16.6%, NPV=98.8%). Using INTERCHEST with a referral threshold of ≥2 points, 4 MACEs would have been missed and 162 patients (24.4%) referred. The other risk scores resulted in far higher referral rates.

CONCLUSION

While available risk scores have reasonable to good discriminatory properties, they do not outperform unaided clinical judgment for evaluating chest pain in urgent primary care. Only the INTERCHEST score may slightly improve risk stratification.

Performance of a simplified HEART score and HEART-GP score for evaluating chest pain in urgent primary care

Background

Chest pain is a common symptom in urgent primary care. The distinction between urgent and non-urgent causes can be challenging. A modified version of the HEART score, in which troponin is omitted (‘simplified HEART’) or replaced by the so-called ‘sense of alarm’ (HEART-GP), may aid in risk stratification.

Method

This study involved a retrospective, observational cohort of consecutive patients evaluated for chest pain at a large-scale, out-of-hours, regional primary care facility in the Netherlands, with 6‑week follow-up for major adverse cardiac events (MACEs). The outcome of interest is diagnostic accuracy, including positive predictive value (PPV) and negative predictive value (NPV).

Results

We included 664 patients; MACEs occurred in 4.8% (n = 32). For  simplified HEART and HEART-GP, we found C‑statistics of 0.86 (95% confidence interval (CI) 0.80–0.91) and 0.90 (95% CI 0.85–0.95), respectively. Optimal diagnostic accuracy was found for a simplified HEART score ≥2 (PPV 9%, NPV 99.7%), HEART-GP score ≥3 (PPV 11%, NPV 99.7%) and HEART-GP score ≥4 (PPV 16%, NPV 99.4%). Physicians referred 157 patients (23.6%) and missed 6 MACEs. A simplified HEART score ≥2 would have picked up 5 cases, at the expense of 332 referrals (50.0%, p < 0.001). A HEART-GP score of ≥3 and ≥4 would have detected 5 and 3 MACEs and led to 293 (44.1%, p < 0.001) and 186 (28.0%, p = 0.18) referrals, respectively.

Conclusion

HEART-score modifications including the physicians’ ‘sense of alarm’ may be used as a risk stratification tool for chest pain in primary care in the absence of routine access to troponin assays. Further validation is warranted.

Supplementary Information

The online version of this article (10.1007/s12471-020-01529-4) contains supplementary material, which is available to authorized users.

Accuracy of telephone triage in primary care patients with chest discomfort: a cross-sectional study

OBJECTIVE

To assess the accuracy of semi-automatic assisted telephone triage in patients with acute chest discomfort against the diagnosis of acute coronary syndrome (ACS) or other life-threatening events (LTEs).

METHODS

A cross-sectional study was performed of telephone conversations with 2023 patients with acute chest discomfort (pain, pressure, tightness or discomfort) who called out-of-hours services for primary care (OHS-PC) between 2014 and 2016. Sensitivity, specificity, positive and negative predicted values were calculated for a high urgency (patient seen within one hour) against the diagnoses of ACS and other LTEs. Diagnoses were retrieved from the patients' medical records in general practice, including hospital specialists' discharge letters.

RESULTS

Of 2023 patients who called because of chest discomfort, 227 (11.2%) had an ACS (men 14.9%, women 8.2%) and 58 (2.9%) had another LTE (men 3.6%, women 2.3%). The sensitivity and specificity of a high Netherlands Triage System (NTS) urgency allocation against ACS/other LTEs were 0.73 (95% CI 0.68 to 0.78) and 0.43 (95% CI 0.40 to 0.45), respectively. In 13.2% of the calls the triage nurse overruled the NTS urgency, mostly by upscaling (11.0%). The sensitivity and specificity of the final urgency allocation were 0.86 (95% CI 0.81 to 0.90) and 0.34 (95% CI 0.32 to 0.37). The positive and negative predictive values of the final urgency were 0.18 (95% CI 0.17 to 0.19) and 0.94 (95% CI 0.92 to 0.95), respectively.

CONCLUSIONS

The semi-automatic triage NTS tool underestimated the urgency in 27% of patients with ACS/other LTEs. Overruling by triage nurses improved safety, but still 14% of men and women with ACS/other LTEs received too low urgency, while efficiency remained poor.

TRIAL REGISTRATION NUMBER

NTR7331.

Systematic Review of Clinical Decision Support Systems for Prehospital Acute Coronary Syndrome Identification

OBJECTIVES

Timely prehospital diagnosis and treatment of acute coronary syndrome (ACS) are required to achieve optimal outcomes. Clinical decision support systems (CDSS) are platforms designed to integrate multiple data and can aid with management decisions in the prehospital environment. The review aim was to describe the accuracy of CDSS and individual components in the prehospital ACS management.

METHODS

This systematic review examined the current literature regarding the accuracy of CDSS for ACS in the prehospital setting, the influence of computer-aided decision-making and of 4 components: electrocardiogram, biomarkers, patient history, and examination findings. The impact of these components on sensitivity, specificity, and positive and negative predictive values was assessed.

RESULTS

A total of 11,439 articles were identified from a search of databases, of which 199 were screened against the eligibility criteria. Eight studies were found to meet the eligibility and quality criteria. There was marked heterogeneity between studies which precluded formal meta-analysis. However, individual components analysis found that patient history led to significant improvement in the sensitivity and negative predictive values. CDSS which incorporated all 4 components tended to show higher sensitivities and negative predictive values. CDSS incorporating computer-aided electrocardiogram diagnosis showed higher specificities and positive predictive values.

CONCLUSIONS

Although heterogeneity precluded meta-analysis, this review emphasizes the potential of ACS CDSS in prehospital environments that incorporate patient history in addition to integration of multiple components. The higher sensitivity of certain components, along with higher specificity of computer-aided decision-making, highlights the opportunity for developing an integrated algorithm with computer-aided decision support.

Predictive Value of Hematologic Indices in the Diagnosis of Acute Coronary Syndrome

BACKGROUND

Distinguishing between Acute Coronary Syndrom (ACS) and SCAD (Stable Coronary Artery Disease) requires advanced laboratory instrument and electrocardiogram. However, their availabilities in primary care settings in developing countries are limited. Hematologic changes usually occur in the ACS patient and might be valuable to distinguish ACS from SCAD.

AIM

This study compares the hematologic indices between ACS and SCAD patients and analyses its predictive value for ACS.

MATERIAL AND METHODS

A total of 191 patients (79 ACS and 112 SCAD) were enrolled in this study based on the inclusion criteria. Patient's characteristic, hematologic indices on admission, and the final diagnosis were obtained from medical records. Statistical analyses were done using SPSS 23.0.

RESULTS

In this research MCHC value (33.40 vs. 32.80 g/dL; p < 0.05); WBC (11.16 vs. 7.40 x109/L; p < 0.001); NLR (6.29 vs. 2.18; p < 0.001); and PLR (173.88 vs 122.46; p < 0.001) were significantly higher in ACS compared to SCAD patients. While MPV (6.40 vs. 10.00 fL; p < 0.001) was significantly lower in ACS patients. ROC curve analysis showed MPV had the highest AUC (95%) for ACS diagnosis with an optimum cut-off point at ≤ 8.35 fL (sensitivity 93.6% and specificity 97.3%).

CONCLUSION

There was a significant difference between hematologic indices between ACS and SCAD patients. MPV is the best indices to distinguish ACS.

A Nationwide Flash-Mob Study for Suspected Acute Coronary Syndrome

PURPOSE

Our primary objective was to evaluate the Marburg Heart Score (MHS), a clinical decision rule, or to develop an adapted clinical decision rule for family physicians (FPs) to safely rule out acute coronary syndrome (ACS) in patients referred to secondary care for suspected ACS. The secondary objective was to evaluate the feasibility of using the flash-mob method, an innovative study design, for large-scale research in family medicine.

METHODS

In this 2-week, nationwide, prospective, observational, flash-mob study, FPs collected data on possible ACS predictors and assessed ACS probability (on a scale of 1-10) in patients referred to secondary care for suspected ACS.

RESULTS

We collected data for 258 patients in 2 weeks by mobilizing approximately 1 in 5 FPs throughout the country via ambassadors. A final diagnosis was obtained for 243 patients (94.2%), of whom 45 (18.5%) received a diagnosis of ACS. Sex, sex-adjusted age, and ischemic changes on electrocardiography were significantly associated with ACS. The sensitivity of the MHS (cut-off ≤2) was 75.0%, specificity was 44.0%, positive predictive value was 24.3%, and negative predictive value was 88.0%. For the FP assessment (cut-off ≤5), these test characteristics were 86.7%, 41.4%, 25.2%, and 93.2%, respectively.

CONCLUSIONS

For patients referred to emergency care, ACS could not be safely ruled out using the MHS or FP clinical assessment. The flash-mob study design may be a feasible alternative research method to investigate relatively simple, clinically relevant research questions in family medicine on a large scale and over a relatively short time frame.

Chest pain in general practice: a systematic review of prediction rules

OBJECTIVE

To identify and assess the performance of clinical decision rules (CDR) for chest pain in general practice.

DESIGN

Systematic review of diagnostic studies.

DATA SOURCES

Medline/Pubmed, Embase/Ovid, CINAHL/EBSCO and Google Scholar up to October 2018.

STUDY SELECTION

Studies that assessed CDRs for intermittent-type chest pain and for rule out of acute coronary syndrome (ACS) applicable in general practice, thus not relying on advanced laboratory, computer or diagnostic testing.

REVIEW METHODS

Reviewers identified studies, extracted data and assessed the quality of the evidence (using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2)), independently and in duplicate.

RESULTS

Eight studies comprising five CDRs met the inclusion criteria. Three CDRs are designed for rule out of coronary disease in intermittent-type chest pain (Gencer rule, Marburg Heart Score, INTERCHEST), and two for rule out of ACS (Grijseels rule, Bruins Slot rule). Studies that examined the Marburg Heart Score had the highest methodological quality with consistent sensitivity (86%-91%), specificity (61%-81%) and positive (23%-35%) and negative (97%-98%) predictive values (PPV and NPV). The diagnostic performance of Gencer (PPV: 20%-34%, NPV: 95%-99%) and INTERCHEST (PPV: 35%-43%, NPV: 96%-98%) appear comparable, but requires further validation. The Marburg Heart Score was more sensitive in detecting coronary disease than the clinical judgement of the general practitioner. The performance of CDRs that focused on rule out of ACS were: Grijseels rule (sensitivity: 91%, specificity: 37%, PPV: 57%, NPV: 82%) and Bruins Slot (sensitivity: 97%, specificity: 10%, PPV: 23%, NPV: 92%). Compared with clinical judgement, the Bruins Slot rule appeared to be safer than clinical judgement alone, but the study was limited in sample size.

CONCLUSIONS

In general practice, there is currently no clinical decision aid that can safely rule out ACS. For intermittent chest pain, several rules exist, of which the Marburg Heart Score has been most extensively tested and appears to outperform clinical judgement alone.

The conundrum of acute chest pain in general practice: a nationwide survey in The Netherlands

Background

GPs are frequently confronted with patients with acute onset chest pain. Although usually benign, approximately 5% is due to acute coronary syndrome (ACS). Unfortunately, ACS is not always recognised, leading to a missed diagnosis in 2–5% of presentations.

Aim

The authors set out to study the level of risk GPs are willing to accept with regards to missing an ACS diagnosis, and the receptiveness of implementing new clinical decision aids.

Design & setting

This study involved an online survey among GPs in the Netherlands.

Method

A concept survey was constructed, which was tested among a panel of 24 GPs. The survey was then modified to achieve content validity. This survey was electronically distributed among 1000 GPs.

Results

A total of 313 (31.3%) GPs completed the survey. Of those surveyed, the median age was 50 years (interquartile range 41–57), 53.0% were female, and 6.4% were specialist GPs ('kaderarts') in cardiology or acute care. GPs estimated the missed ACS rate to be <5.0% in clinical practice, most often estimating a chance of 1.0–2.5% (35.2%) or 0.5–1.0% (29.7%). For atypical case presentations, 70% of GPs would accept a 0.1–1.0% missed diagnosis rate, while keeping the referral threshold to a maximum of 50 unnecessary referrals for each ACS case (75% of responders). GPs would welcome additional decision aids, with 79.2% favouring a clinical decision aid, 77.1% favouring troponin point-of-care (POC) testing, and 85.5% favoring a combination of a clinical decision aid and a troponin POC test.

Conclusion

GPs perceive that they miss more ACS cases than they feel comfortable with, which is reflected in a defensive referral strategy. The vast majority of GPs would welcome the use of clinical decision aids and/or cardiac biomarker POC testing for ruling out ACS, if accompanied by more certainty than based on clinical judgment alone.

The cost-utility of point-of-care troponin testing to diagnose acute coronary syndrome in primary care

Background

The added value of using a point-of-care (POC) troponin test in primary care to rule out acute coronary syndrome (ACS) is debated because test sensitivity is inadequate early after symptom onset. This study investigates the potential cost-utility of diagnosing ACS by a general practitioner (GP) when a POC troponin test is available versus GP assessment only.

Methods

A patient-level simulation model was developed, representing a hypothetical cohort of the Dutch population (>35 years) consulting the GP with chest complaints. All health related consequences as well as cost consequences were included. Both symptom duration, selection of patients in whom the POC troponin test is performed, and test performance at different time points were incorporated. Health outcomes were expressed as Quality-Adjusted Life Years (QALYs). The main outcome parameters involve the effect of POC troponin testing on (in)correct hospital referrals, QALYs, and costs.

Results

The POC troponin strategy decreases the referral rate in non-ACS patients from 38.46% to 31.85%. Despite a small increase in non-referral among ACS patients from 0.22% to 0.27%, the overall health effect is negligible. Costs will decrease with €77.25/patient (95% CI €-126.81 to €-33.37).

Conclusions

The POC troponin strategy is likely cost-saving, by reducing hospital referrals. The small increase in missed ACS patients can be partly explained by conservative assumptions used in the analysis. Besides, current developments in POC troponin tests will likely further improve their diagnostic performance. Therefore, future prospective studies are warranted to investigate whether those developments make the POC troponin test to a safe and cost-effective diagnostic tool for diagnosing ACS in general practices.

Electronic supplementary material

The online version of this article (doi:10.1186/s12872-017-0647-6) contains supplementary material, which is available to authorized users.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.

Chest pain out-of-hours - an interview study of primary care physicians' diagnostic approach, tolerance of risk and attitudes to hospital admission

Background

Acute chest pain constitutes a considerable diagnostic challenge outside hospitals. This will often lead to uncertainty in choosing the right management, and the physicians’ approach may be influenced by their knowledge of diagnostic measures and their tolerance of risk. The aim of this study was to investigate primary care physicians’ diagnostic approach, tolerance of risk and attitudes to hospital admission in patients with acute chest pain out-of-hours in Norwegian primary care.

Methods

Data were registered prospectively from four Norwegian casualty clinics. Data from structured telephone interviews with 100 physicians shortly after a consultation with a patient presenting at the casualty clinic with “chest pain” were analysed. Tolerance of risk was measured by the Pearson Risk Scale and the Tolerance of Risk Scale, the latter developed for this study.

Results

“Patient history and symptoms” was considered the most important, and “negative ECG” and “effect of sublingual nitroglycerine” the least important aspects in the diagnostic approach. There were no significant differences in length of experience or gender when testing “risk avoiders” against the rest. Almost all physicians felt that their risk assessment out-of-hours was reasonably good, and felt reasonably safe, but only 50% agreed with the statement “I don’t worry about my decisions after I’ve made them”. Concerning chest pain patients only, 51% of the physicians were worried about complaints being made about them, 75% agreed that admitting someone to hospital put patients in danger of being “over-tested”, and 51% were more likely to admit the patient if the patient herself wanted to be admitted.

Conclusions

Physicians working out-of-hours showed considerable differences in their diagnostic approach, and not all physicians diagnose patients with chest pain according to current guidelines and evidence. Continuous medical education must focus on the diagnostic approach in patients with chest pain in primary care and empowerment of physicians through training and emphasis on risk assessment and “tolerance of risk”.

The value of signs, symptoms and plasma heart-type fatty acid-binding protein (H-FABP) in evaluating patients presenting with symptoms possibly matching acute coronary syndrome: background and methods of a diagnostic study in primary care

Background

Chest complaints presented to a general practitioner (GP) are frequently caused by diseases which have advantageous outcomes. However, in some cases, acute coronary syndrome (ACS) is present (1.5-22% of cases). The patient’s signs, symptoms and electrocardiography results are insufficient diagnostic tools to distinguish mild disease from ACS. Therefore, most patients presenting chest complaints are referred to secondary care facilities where ACS is then ruled out in a majority of patients (78%). Recently, a point of care test for heart-type fatty acid-binding protein (H-FABP) using a low cut-off value between positive and negative of 4 ng/ml has become available. We aim to study the role of this point of care device in triage of patients presenting chest complaints possibly due to ACS, in primary care. Our research protocol is presented in this article. Results are expected in 2015.

Methods/Design

Participating GPs will register signs and symptoms in all patients presenting chest complaints possibly due to ACS. Point of care H-FABP testing will also be performed. Our study will be a derivation study to identify signs and symptoms that, combined with point of care H-FABP testing, can be part of an algorithm to either confirm or rule out ACS. The diagnostic value for ACS of this algorithm in general practice will be determined.

Discussion

A safe diagnostic elimination of ACS by application of the algorithm can be of significant clinical relevance. Improved triage and thus reduction of the number of patients with chest complaints without underlying ACS, that are referred to secondary care facilities, could lead to a substantial cost reduction.

Trial registration

ClinicalTrials.gov, NCT01826994, accepted April 8^th 2013.

Should general practitioners order troponin tests?

Cardiac troponin I and T are the preferred biomarkers for assessing myocardial injury, and the timing of troponin testing is fundamental to its clinical utility. There are arguments for and against the use of troponin testing in the community, and the stance that general practitioners should never order a troponin test can be considered an oversimplification. GPs have a generally sufficient understanding of the test for use in primary care, and have a better understanding of false-negative troponin test results than false-positive results. We suggest that hospitalisation, rather than troponin testing, should be the default option for patients with symptoms suggestive of acute coronary syndrome. A single troponin test is reasonable in primary care to exclude the possibility of acute myocardial infarction in asymptomatic low-risk patients whose symptoms resolved at least 12 hours prior. GPs should factor in the complex logistics of troponin testing in the community before ordering a troponin test: results need to be accurate and timely, and might be obtained at a time of day when it is difficult to contact the doctor or the patient.

Using qualitative research to inform development of a diagnostic algorithm for UTI in children

BACKGROUND

Diagnostic and prognostic algorithms can help reduce clinical uncertainty. The selection of candidate symptoms and signs to be measured in case report forms (CRFs) for potential inclusion in diagnostic algorithms needs to be comprehensive, clearly formulated and relevant for end users.

OBJECTIVE

To investigate whether qualitative methods could assist in designing CRFs in research developing diagnostic algorithms. Specifically, the study sought to establish whether qualitative methods could have assisted in designing the CRF for the Health Technology Association funded Diagnosis of Urinary Tract infection in Young children (DUTY) study, which will develop a diagnostic algorithm to improve recognition of urinary tract infection (UTI) in children aged <5 years presenting acutely unwell to primary care.

METHODS

Qualitative methods were applied using semi-structured interviews of 30 UK doctors and nurses working with young children in primary care and a Children's Emergency Department. We elicited features that clinicians believed useful in diagnosing UTI and compared these for presence or absence and terminology with the DUTY CRF.

RESULTS

Despite much agreement between clinicians' accounts and the DUTY CRFs, we identified a small number of potentially important symptoms and signs not included in the CRF and some included items that could have been reworded to improve understanding and final data analysis.

CONCLUSIONS

This study uniquely demonstrates the role of qualitative methods in the design and content of CRFs used for developing diagnostic (and prognostic) algorithms. Research groups developing such algorithms should consider using qualitative methods to inform the selection and wording of candidate symptoms and signs.

Point-of-Care Troponin T Testing in the Management of Patients with Chest Pain in the Swedish Primary Care

Objective. To investigate the diagnostic accuracy and clinical benefit of point-of-care Troponin T testing (POCT-TnT) in the management of patients with chest pain. Design. Observational, prospective, cross-sectional study with followup. Setting. Three primary health care (PHC) centres using POCT-TnT and four PHC centres not using POCT-TnT in the southeast of Sweden. Patients. All patients ≥35 years old, contacting one of the primary health care centres for chest pain, dyspnoea on exertion, unexplained weakness, and/or fatigue with no other probable cause than cardiac, were included. Symptoms should have commenced or worsened during the last seven days. Main Outcome Measures. Emergency referrals, patients with acute myocardial infarctions (AMI), or unstable angina (UA) within 30 days of study enrolment. Results. 25% of the patients from PHC centres with POCT-TnT and 43% from PHC centres without POCT-TnT were emergently referred by the GP (P = 0.011 ). Seven patients (5.5%) from PHC centres with POCT-TnT and six (8.8%) from PHC centres without POCT-TnT were diagnosed as AMI or UA (P = 0.369). Two patients with AMI or UA from PHC centres with POCT-TnT were judged as missed cases in primary health care. Conclusion. The use of POCT-TnT may reduce emergency referrals but probably at the cost of an increased risk to miss patients with AMI or UA.

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 studies.