Diagnostic performance of the GGT/HDL-C ratio for NAFLD in adults with obesity undergoing bariatric surgery.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) has become the most frequent liver disease, closely related with metabolic risk factors such as obesity, insulin resistance, dyslipidemia, diabetes mellitus, and metabolic syndrome. In this context, γ-Glutamyl transpeptidase (GGT) and high-density lipoprotein cholesterol (HDL-C) have shown correlations with steatosis severity and metabolic syndrome, respectively. This positions the GGT/HDL-C ratio as a potential diagnostic indicator for NAFLD. OBJECTIVE: To assess the diagnostic performance of the GGT/HDL-C ratio for NAFLD in adults with obesity undergoing bariatric surgery. METHODS: We conducted an analytical cross-sectional study, designed as a diagnostic test evaluation. A secondary database of 249 adults with obesity was analyzed. The optimal cut-off point was ascertained using three methodologies, and five adjustment models were constructed for the total population, further stratified by sex. RESULTS: The optimal cut-off point was 20.5 U/mmol and the AUC of the ratio was 0.81 (95% CI: 0.64-0.98), with sensitivity and specificity being 82.5% and 77.8%, respectively. In the overall group with an elevated GGT/HDL-C ratio, the prevalence of NAFLD increased by 14% (PR: 1.14; 95% CI: 1.04-1.33). Specifically, women displaying this altered ratio showed a 19% increased prevalence (PR: 1.19; 95% CI: 1.07-1.42) compared to those with normal values. CONCLUSIONS: The GGT/HDL-C ratio is a promising biomarker for the diagnosis of NAFLD in an adult population living with obesity.

Oropouche virus infection in patients with acute febrile syndrome: Is a predictive model based solely on signs and symptoms useful?

BACKGROUND: Oropouche fever is an infectious disease caused by the Oropouche virus (OROV). The diagnosis and prediction of the clinical picture continue to be a great challenge for clinicians who manage patients with acute febrile syndrome. Several symptoms have been associated with OROV virus infection in patients with febrile syndrome; however, to date, there is no clinical prediction rule, which is a fundamental tool to help the approach of this infectious disease. OBJECTIVE: To assess the performance of a prediction model based solely on signs and symptoms to diagnose Oropouche virus infection in patients with acute febrile syndrome. MATERIALS AND METHODS: Validation study, which included 923 patients with acute febrile syndrome registered in the Epidemiological Surveillance database of three arbovirus endemic areas in Peru. RESULTS: A total of 97 patients (19%) were positive for OROV infection in the development group and 23.6% in the validation group. The area under the curve was 0.65 and the sensitivity, specificity, PPV, NPV, LR + and LR- were 78.2%, 35.1%, 27.6%, 83.6%, 1.20 and 0.62, respectively. CONCLUSIONS: The development of a clinical prediction model for the diagnosis of Oropouche based solely on signs and symptoms does not work well. This may be due to the fact that the symptoms are nonspecific and related to other arbovirus infections, which confuse and make it difficult to predict the diagnosis, especially in endemic areas of co-infection of these diseases. For this reason, epidemiological surveillance of OROV in various settings using laboratory tests such as PCR is important.