Results
Patients Registered via Flash mob
A total of 241 FPs (including FP trainees) from all provinces in the country registered 258 patients, 113 (43.8%) online and 145 (56.2%) on paper. Of these patients, 203 (78.7%) were included by an FP (median work experience 8 years [interquartile range, 15.3 years]) and 55 (21.3%) by an FP trainee. A total of 182 (70.5%) patients were registered during office hours. Figure 2 summarizes patient inclusion and follow-up. A final diagnosis was obtained for 243 (94.2%) patients, and an MHS could be determined for 186 (72.1%) patients.
Figure 2.
Patient inclusion and follow-up.
Final Diagnosis and Univariate Analyses of Possible ACS Predictors (n = 243)
Of the 243 patients with a final diagnosis, 45 (18.5%) received a diagnosis of ACS, of whom 34 (75.6%) had a myocardial infarction, 10 (22.2%) unstable angina, and 1 (2.2%) ACS confirmed but not otherwise speci fied. Stable angina was diagnosed for 11 (4.5%) patients, another cardiac diagnosis for 40 (16.5%) patients, and a noncardiac diagnosis for 153 (63.0%) patients.
Table 2 summarizes patient characteristics and investigated predictors. Three possible predictors—sex, sex-adjusted age, and ischemic changes on ECG—were significantly associated with ACS in the univariate analysis.
FP Assessment of ACS Probability (n = 243)
Table 3 shows the test characteristics of the FP assessment. According to the FP assessment, 88 of 243 (36.2%) patients were at low risk of ACS (≤5) and 155 (63.8%) at high risk (>5). A total of 6 (2.5%) patients would have been falsely classified as not having ACS when using the FP assessment. The AUC for the FP assessment was 0.72 (95% CI, 0.63–0.81).
Marburg Heart Score (n = 186)
Table 3 shows the test characteristics of the MHS using cut-off values of ≤2 and ≤1. Of the 186 patients for whom an MHS could be calculated, 75 (40.3%) were at low risk of ACS (0-2) and 111 (59.7%) at intermediate-high risk (3-5). The ACS incidence in the MHS group was 19.4%. Nine (4.8%) patients would have been falsely classified as not having ACS when using the MHS with a cut-off value of ≤2. When using the MHS with a cut-off value of ≤1, 2 (1.1%) patients would have been missed, and 24 (12.9%) patients would have been classified as true negative. The AUC for the MHS was 0.64 (95% CI, 0.54–0.74), and that for FP assessment in the group for which an MHS could be determined was 0.71 (95% CI, 0.61–0.80) (Figure 3).
Figure 3.
ROC curves for FP assessment of ACS probability and the Marburg Heart Score in patients referred for suspected ACS (n = 186).
ACS = acute coronary syndrome; AUC = area under the curve; FP = family physician; ROC = receiver operating characteristic.
Sensitivity Analyses MHS (n = 215)
The sensitivity analysis showed a slightly greater sensitivity (76.9%), specificity (44.9%), and NPV (89.8%) of the MHS for ACS using a cut-off of ≤2. The PPV was 23.6%. The sensitivity analysis of the MHS using a cut-off of ≤1 showed a sensitivity of 94.9%, specificity of 17.0%, PPV of 20.2%, and NPV of 93.8% for ACS.
Alternative Scenario Analysis
In a strategy wherein both the MHS and FP assessments were negative, no patient would have been missed, whereas 35 of 186 (18.8%) patients would have been classified as true negative (Table 3).
Ann Fam Med. 2019;17(4):296-303. © 2019 Annals of Family Medicine, Inc.
Comments