Effect of Storage Temperature and Time on Stability of Liver Enzymes in Blood Serum

Biospecimen Qualification in a Clinical Biobank of Urological Diseases

Development of novel biomarkers for diagnosis of disease and assessment of treatment efficacy utilizes a wide range of biospecimens for discovery research. The fitness of biospecimens for the purpose of biomarker development depends on the clinical characteristics of the donor and on a number of critical and potentially uncontrolled pre-analytical variables. Pre-analytical factors influence the reliability of the biomarkers to be analyzed and can seriously impact analytic outcomes. Sample quality stratification assays and tools can be utilized by biorepositories to minimize bias resulting from samples' inconsistent quality. In this study, we evaluated the quality of biobanked specimens by comparing analytical outcomes at 1, 5, and 10 years after collection. Our results demonstrate that currently available assays and tools can be used by biobank laboratories to support objective biospecimen qualification. We have established a workflow to monitor the quality of different types of biospecimens and, in this study, present the results of a qualification exercise applied to fluid samples and their derivatives in the context of urological diseases.

Comparative plasma biochemistry analyte data in nesting leatherback (Dermochelys coriacea), foraging green (Chelonia mydas) and foraging and nesting hawksbill (Eretmochelys imbricata) sea turtles in Grenada, West Indies

Blood biochemistry represents a minimally invasive tool for monitoring sea turtle health, assessing injured sea turtles and supporting conservation strategies. In Grenada, West Indies, plasma biochemical variables were examined in 33 nesting leatherback (Dermochelys coriacea), 49 foraging green (Chelonia mydas), 49 foraging hawksbill (Eretmochelys imbricata) and 12 nesting hawksbill sea turtles sampled between 2017 and 2022. Plasma biochemistry reference intervals are described herein except for nesting hawksbills, which are represented by descriptive statistics due to the low sample size. Select analyte concentrations were positively correlated with curved carapace length in leatherbacks (chloride), green turtles (total protein, albumin and globulin) and foraging hawksbills (total protein, albumin and phosphorus). Cholesterol (7.8 mmol/l ± 1.6 SD) and triglyceride (6.9 mmol/l ± 1.9 SD) concentrations were significantly higher in leatherbacks compared to foraging green turtles, foraging hawksbills and nesting hawksbills (P < 0.001 for all). Cholesterol was significantly higher in nesting hawksbills compared to foraging green turtles (P = 0.050) and foraging hawksbills (P = 0.050). Foraging hawksbills demonstrated significantly higher aspartate transaminase activities than leatherbacks (P = 0.002), green turtles (P = 0.009) and nesting hawksbills (P < 0.001). Biochemical results provide baseline population health data and support guidance for treatments during clinical sea turtle rehabilitation efforts. They also provide insight into species-specific physiologic differences and preludes further studies to better characterize the impacts of life-stage class on biochemistry reference intervals to better support wild sea turtle populations in Grenada.

Factors Predicting Outcome in Intensive Care Unit-Admitted COVID-19 Patients: Using Clinical, Laboratory, and Radiologic Characteristics

PURPOSE

To investigate the factors contributing to mortality in coronavirus disease 2019 (COVID-19) patients admitted in the intensive care unit (ICU) and design a model to predict the mortality rate.

METHOD

We retrospectively evaluated the medical records and CT images of the ICU-admitted COVID-19 patients who had an on-admission chest CT scan. We analyzed the patients' demographic, clinical, laboratory, and radiologic findings and compared them between survivors and nonsurvivors.

RESULTS

Among the 121 enrolled patients (mean age, 62.2 ± 14.0 years; male, 82 (67.8%)), 41 (33.9%) survived, and the rest succumbed to death. The most frequent radiologic findings were ground-glass opacity (GGO) (71.9%) with peripheral (38.8%) and bilateral (98.3%) involvement, with lower lobes (94.2%) predominancy. The most common additional findings were cardiomegaly (63.6%), parenchymal band (47.9%), and crazy-paving pattern (44.4%). Univariable analysis of radiologic findings showed that cardiomegaly (p : 0.04), pleural effusion (p : 0.02), and pericardial effusion (p : 0.03) were significantly more prevalent in nonsurvivors. However, the extension of pulmonary involvement was not significantly different between the two subgroups (11.4 ± 4.1 in survivors vs. 11.9 ± 5.1 in nonsurvivors, p : 0.59). Among nonradiologic factors, advanced age (p : 0.002), lower O2 saturation (p : 0.01), diastolic blood pressure (p : 0.02), and hypertension (p : 0.03) were more commonly found in nonsurvivors. There was no significant difference between survivors and nonsurvivors in terms of laboratory findings. Three following factors remained significant in the backward logistic regression model: O2 saturation (OR: 0.91 (95% CI: 0.84-0.97), p : 0.006), pericardial effusion (6.56 (0.17-59.3), p : 0.09), and hypertension (4.11 (1.39-12.2), p : 0.01). This model had 78.7% sensitivity, 61.1% specificity, 90.0% positive predictive value, and 75.5% accuracy in predicting in-ICU mortality.

CONCLUSION

A combination of underlying diseases, vital signs, and radiologic factors might have prognostic value for mortality rate prediction in ICU-admitted COVID-19 patients.