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.
Humans ; Male ; Female ; Emergency Service, Hospital ; Middle Aged ; Electrocardiography ; Machine Learning ; Singapore ; Chest Pain/blood* ; Troponin I/blood* ; Myocardial Infarction/blood* ; Risk Assessment/methods* ; Aged ; Algorithms ; Acute Coronary Syndrome/blood* ; Adult ; Sensitivity and Specificity

Adrenal Glands ; Humans ; Hyperaldosteronism ; Retrospective Studies ; Singapore

Although cardiovascular disease (CVD) is a major health challenge in Malaysia, many Malaysians are unaware of their CVD risk. The measurement of biomarkers in the general population may help to identify at-risk individuals before the onset of symptomatic CVD. The aim of this community health screening project was to determine the distribution of high-sensitivity troponin I (hsTnI) and other biomarkers of CVD risk in the general population of Johor, Malaysia. A sampling of self-declared healthy volunteers was conducted during the 2016 Kembara Mahkota community event in Johor. Levels of hsTnI, B-type natriuretic peptide (BNP) and homocysteine (HCY) were analyzed using the ARCHITECT immunoassay and clinical chemistry platforms utilizing fresh venous blood samples. Based on previous data, biomarker levels indicative of high risk were >10 and >12 ng/mL for hsTnI in women and men, respectively, BNP >50 pg/mL in the overall population, and HCY >13.6 µmol/L in women and >16.2 µmol/L in men. A total of 2744 volunteers participated in biomarker testing. Biomarker measurements showed that up to 10% of participants had moderate or high CVD risk based on hsTnI, approximately 2% were above the BNP threshold and >50% of subjects were above the HCY threshold. General population biomarker testing shows distribution of biomarker levels that may be indicative of CVD risk or the presence of disease and suggests that biomarker-guided risk strategies should be more widely implemented to determine the impact they would have on early detection and prevention of disease.

Thyroid disorders are common, affecting more than 10% of people in the US, and laboratory tests are integral in the management of these conditions. The repertoire of thyroid tests includes blood tests for thyroid-stimulating hormone (TSH), free thyroxine, free triiodothyronine, thyroglobulin (Tg), thyroglobulin antibodies (Tg-Ab), thyroid peroxidase antibodies (TPO-Ab), TSH receptor antibodies (TRAb), and calcitonin. TSH and free thyroid hormone tests are frequently used to assess the functional status of the thyroid. TPO-Ab and TRAb tests are used to diagnose Hashimoto's thyroiditis and Graves' disease, respectively. Tg and calcitonin are important tumor markers used in the management of differentiated thyroid carcinoma and medullary thyroid carcinoma (MTC), respectively. Procalcitonin may replace calcitonin as a biomarker for MTC. Apart from understanding normal thyroid physiology, it is important to be familiar with the possible pitfalls and caveats in the use of these tests so that they can be interpreted properly and accurately. When results are discordant, clinicians and laboratorians should be mindful of possible assay interferences and/or the effects of concurrent medications. In addition, thyroid function may appear abnormal in the absence of actual thyroid dysfunction during pregnancy and in critical illness. Hence, it is important to consider the clinical context when interpreting results. This review aims to describe the above-mentioned blood tests used in the diagnosis and management of thyroid disorders, as well as the pitfalls in their interpretation. With due knowledge and care, clinicians and laboratorians will be able to fully appreciate the clinical utility of these important laboratory tests.
Antibodies ; Biomarkers, Tumor ; Calcitonin ; Critical Illness ; Diagnosis ; Graves Disease ; Hematologic Tests ; Iodide Peroxidase ; Physiology ; Pregnancy ; Receptors, Thyrotropin ; Thyroglobulin ; Thyroid Function Tests ; Thyroid Gland* ; Thyroid Neoplasms ; Thyroiditis ; Thyrotropin ; Thyroxine ; Triiodothyronine

OBJECTIVE: The purpose of this study was to develop a risk prediction score for distinguishing benign ovarian mass from malignant tumors using CA-125, human epididymis protein 4 (HE4), ultrasound findings, and menopausal status. The risk prediction score was compared to the risk of malignancy index and risk of ovarian malignancy algorithm (ROMA). METHODS: This was a prospective, multicenter (n=6) study with patients from six Asian countries. Patients had a pelvic mass upon imaging and were scheduled to undergo surgery. Serum CA-125 and HE4 were measured on preoperative samples, and ultrasound findings were recorded. Regression analysis was performed and a risk prediction model was developed based on the significant factors. A bootstrap technique was applied to assess the validity of the HE4 model. RESULTS: A total of 414 women with a pelvic mass were enrolled in the study, of which 328 had documented ultrasound findings. The risk prediction model that contained HE4, menopausal status, and ultrasound findings exhibited the best performance compared to models with CA-125 alone, or a combination of CA-125 and HE4. This model classified 77.2% of women with ovarian cancer as medium or high risk, and 86% of women with benign disease as very-low, low, or medium-low risk. This model exhibited better sensitivity than ROMA, but ROMA exhibited better specificity. Both models performed better than CA-125 alone. CONCLUSION: Combining ultrasound with HE4 can improve the sensitivity for detecting ovarian cancer compared to other algorithms.
Adult ; *Algorithms ; Biomarkers, Tumor/*blood ; CA-125 Antigen/blood ; Decision Support Techniques ; Diagnosis, Differential ; Female ; Humans ; Menopause ; Middle Aged ; Ovarian Neoplasms/*diagnosis/ultrasonography ; Predictive Value of Tests ; Prospective Studies ; Proteins/*analysis ; ROC Curve ; Risk Assessment/methods ; Sensitivity and Specificity