Background and Objectives: This study aims to identify reasons for unscheduled return visits (URVs), and risk factors for diagnostic errors leading to URVs, with comparisons to data from a similar study conducted in the same institution 9 years ago. Materials and Methods: This retrospective study included adult patients who attended the emergency department (ED) of a tertiary hospital in Singapore between January 2014 and June 2014, with re-attendance within 72 h for the same or similar complaint. The primary outcome was wrong or delayed diagnoses. Secondary outcomes include admission to the ED observation unit or ward on return visit. Findings were compared with the previous study performed in 2005 to identify trends. Results: Of 67,422 attendances, there were 1298 (1.93%) URVs from 1207 patients (median age 34, interquartile range 24 to 52 years; 59.7% male). The most common presenting complaint was abdominal pain (22.2%). One hundred ninety-one (15.8%) patients received an initial wrong or delayed diagnosis. Factors (adjusted odds ratio; 95% CI) associated with this were: presenting complaints of abdominal pain (2.99; 2.12–4.23), fever (1.60; 1.1–2.33), neurological deficit (4.26; 1.94–9.35), and discharge without follow-up (1.61; 1.1–2.26). Among re-attendances, 459 (38.0%) required admission. Factors (adjusted odds ratio; 95% CI) associated with admission were: male gender (1.88; 1.42 to 2.48); comorbidities of diabetes mellitus (2.07; 1.29–3.31), asthma (5.23; 1.59–17.26), and renal disease (7.48; 2.00–28.05); presenting complaints of abdominal pain (1.83; 1.32–2.55), fever (3.05; 2.10–4.44), and giddiness or vertigo (2.17; 1.26–3.73). There was a reduction in URV rate compared to the previous study in 2005 (1.93% versus 2.19%). Abdominal pain at the index visit remains a significant cause of URVs (22.2% versus 25.1%). Conclusions: Presenting complaints of neurological deficits, abdominal pain, fever, and discharge without follow-up were associated with wrong or delayed diagnoses among URVs.

High sensitive cardiac troponin assays can be used for prediction of major adverse cardiac events (MACE) in patients with chest pain. We included patients with symptoms suggestive of acute coronary syndrome in the emergency department observation unit. We compared the accuracy of conventional troponin T (cTnT) with high sensitive troponin T (hsTnT) at various ranges, as well as the utility of hsTnT and cTnT in prediction of 30-day and 1-year MACE. 1023 patients were included (68.1% male, median age 56 years). There were 2712 hsTnT and cTnT values compared. hsTnT had a higher AUC than cTnT for 30-day and 1-year MACE. The optimal cut-off of 0-hour hsTnT for 30-day (PPV 34%, NPV 96.6%) and 1-year MACE (PPV 40.2%, NPV 94.2%) was 16 ng/L. For 844 patients who had values for both 0 and 2 h hsTnT, we proposed a rule-out cut-off of 0 and 2 h hsTnT < 16 ng/L (NPV 97.0%, 95%CI 95.5–98.1%) and a rule-in cut-off of 0 and 2 h hsTnT ≥ 26 ng/L (PPV 58.8%, 95%CI 40.7%-75.4%) for 30-day MACE. Negative 0–2 h delta-hsTnT had poor predictive discriminant capabilities on 30-day (PPV 8.2%) and 1-year MACE (PPV 12.3%). The cut off values of hsTnT used in the 0 and 2-hour algorithm to rule-out (16 ng/L) and rule-in MACE (26 ng/L) are in the range that previous cTnT assays are unable to measure accurately. Risk scores can be used to further improve NPV of the rule-out group. A fall in hsTnT level acutely is not predictive of MACE.

Background and Objectives: We aimed to compare the time to diagnosis for acute coronary syndromes using high-sensitivity troponin I (hsTnI) and conventional troponin I (TnI) in patients presenting to the emergency department (ED) with chest pain. Materials and Methods: This was an observational prospective study involving patients presenting to the ED of Sant’Andrea Hospital University la Sapienza in Rome (Italy) with chest pain from January to December 2014. Serum troponin was drawn at presentation, and at 3, 6, 9, and/or 12 h if clinically indicated. Depending on date of recruitment, patients had either hsTnI (Abbott Laboratories) or TnI (Abbott Laboratories) performed. The primary endpoint was the time to diagnosis at index visit. Results: A total of 1059 patients were recruited, (673 [63.6%] male, median age 60 years [interquartile range 49–73 years]), out of whom 898 (84.8%) patients were evaluated with hsTnI and 161 (15.2%) with TnI. A total of 393 (37.1%) patients had the diagnosis of acute coronary syndrome in ED. The median time to diagnosis for those evaluated with TnI was 400 min, IQR 120–720 min, while the use of hsTnI led to a significantly shorter time to diagnosis (median 200 min, IQR 100–200 min, p < 0.001). Conclusions: This study confirms that in patients presenting to the emergency department with chest pain, the use of hsTnI is associated with a reduced time to ruling in/out ACS, and, consequently, hsTnI should be routinely used over TnI for more rapid identification of ACS with benefits for patients and related costs.

Introduction: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers age, sex and cardiac troponin I (TnI) results to risk-stratify patients for type 1 myocardial infarction. Method: Patients aged ≥25 years who presented to the emergency department (ED) of Singapore General Hospital with symptoms suggestive of acute coronary syndrome with no diagnostic 12-lead electrocardiogram (ECG) changes were included. Participants had serial ECGs and high-sensitivity troponin assays performed at 0, 2 and 7 hours. The primary outcome was the adjudicated diagnosis of type 1 myocardial infarction at 30 days. We compared the performance of MI3 in predicting the primary outcome with the European Society of Cardiology (ESC) 0/2-hour algorithm as well as the 99th percentile upper reference limit (URL) for TnI. Results: There were 1351 patients included (66.7% male, mean age 56 years), 902 (66.8%) of whom had only 0-hour troponin results and 449 (33.2%) with serial (both 0 and 2-hour) troponin results available. MI3 ruled out type 1 myocardial infarction with a higher sensitivity (98.9, 95% confidence interval [CI] 93.4–99.9%) and similar negative predictive value (NPV) 99.8% (95% CI 98.6–100%) as compared to the ESC strategy. The 99th percentile cut-off strategy had the lowest sensitivity, specificity, positive predictive value and NPV. Conclusion: The MI3 algorithm was accurate in risk stratifying ED patients for myocardial infarction. The 99th percentile URL cut-off was the least accurate in ruling in and out myocardial infarction compared to the other strategies.