METHODS: Two independent reviewers conducted a comprehensive search using Ovid MEDLINE published from years 1993 to 2016 and SCOPUS published from year 1985 to 2017 to screen for relevant studies. The main inclusion criteria included adult subjects, patients with suspected or confirmed signs of infection and relevant outcomes which looked into the role of sPLA2-IIA in detecting the presence of sepsis and bacterial infection in the subjects.
RESULTS AND DISCUSSION: Four studies met the inclusion criteria. SPLA2-IIA was found to be effective in detecting the presence of sepsis and bacterial infection in adults. The levels of serum sPLA2-IIA also correlated well with the presence of sepsis and bacterial infection.
CONCLUSION: This systematic review highlights the role of sPLA2-IIA as a reliable tool to diagnose sepsis and bacterial infection in adult patients. Nonetheless, further studies should be done in the future to provide more compelling evidence on its application in the clinical setting.
MATERIALS AND METHODS: A total of 312 patients classified to PCOS (n = 164) and non PCOS (n = 148) cohorts were selected from the Laboratory Information System (LIS) based on serum total testosterone (TT) and sex hormone binding globulin (SHBG) from the period of 1st April 2015 to 31st March 2016. PCOS was diagnosed based on Rotterdam criteria. Clinical hyperandrogenism and ultrasound polycystic ovarian morphology were obtained from the clinical records. The other relevant biochemical results such as serum luteinizing hormone (LH), follicle stimulating hormone (FSH) and albumin were also obtained from LIS. Free androgen index (FAI), calculated free testosterone (cFT) and calculated bioavailable testosterone (cBT) were calculated for these patients. Receiver Operating Characteristic (ROC) curve analysis were performed for serum TT, SHBG, FAI, cFT, cBT and LH: FSH ratio to determine the best marker to diagnose PCOS.
RESULTS: All the androgen parameters (except SHBG) were significantly higher in PCOS patients than in control (p<0.0001). The highest area under curve (AUC) curve was found for cBT followed by cFT and FAI. TT and LH: FSH ratio recorded a lower AUC and the lowest AUC was seen for SHBG. cBT at a cut off value of 0.86 nmol/L had the highest specificity, 83% and positive likelihood ratio (LR) at 3.79. This is followed by FAI at a cut off value of 7.1% with specificity at 82% and cFT at a cut off value of 0.8 pmol/L with specificity at 80%. All three calculated androgen indices (FAI, cFT and cBT) showed good correlation with each other. Furthermore, cFT, FAI and calculated BT were shown to be more specific with higher positive likelihood ratio than measured androgen markers.
CONCLUSIONS: Based on our study, the calculated testosterone indices such as FAI, cBT and cFT are useful markers to distinguish PCOS from non-PCOS. Owing to ease of calculation, FAI can be incorporated in LIS and can be reported with TT and SHBG. This will be helpful for clinician to diagnose hyperandrogenism in PCOS.
METHODS: The study samples comprised 140 subjects aged 18 to 50 years old, natural and unnatural causes of sudden death brought to the Department of Forensic Medicine, Hospital Sungai Buloh (HSgB) and Hospital Sultanah Aminah Johor Bahru (HSAJB) for a period of 12 months. The subjects were categorised into 5 groups: cardiovascular disease (CVD), sudden unexplained death (SUD), thoracic trauma (TT), non-thoracic trauma (NTT) and other diseases (OD).
RESULTS: Median troponin concentration in cases of CVD, SUD, TT, NTT, and OD were 0.51 μg/L, 0.17 μg/L, 0.62 μg/L, 0.90 μg/L and 0.51 μg/L respectively. We found no significant difference of troponin T level in different causes of death (p ≥ 0.05). NTT has the highest median troponin concentration with 0.90 μg/L, SUD possessed the lowest median concentration with 0.17 μg/L.
CONCLUSION: Troponin T is neither specific nor useful as cardiac biomarker for post mortem sample. Therefore, it may not be a useful diagnostic tool at autopsy.
METHODS: In this paper, we highlight a review of the studies that have used biomarkers to understand the association between air particles exposure and the development of respiratory problems resulting from the damage in the respiratory system. Data from previous epidemiological studies relevant to the application of biomarkers in respiratory system damage reported from exposure to air particles are also summarized.
RESULTS: Based on these analyses, the findings agree with the hypothesis that biomarkers are relevant in linking harmful air particles concentrations to increased respiratory health effects. Biomarkers are used in epidemiological studies to provide an understanding of the mechanisms that follow airborne particles exposure in the airway. However, application of biomarkers in epidemiological studies of health effects caused by air particles in both environmental and occupational health is inchoate.
CONCLUSION: Biomarkers unravel the complexity of the connection between exposure to air particles and respiratory health.