Association of Cerebrospinal Fluid Biomarkers with Submental and Cerebral Hemorrhage: A Case-Control Study.

Objective: This retrospective case-control study aimed to investigate the relationship between cerebrospinal fluid (CSF) biomarkers and subarachnoid hemorrhage (SAH) and cerebral hemorrhage (CH) and to determine whether these biomarkers can predict the risk of hemorrhage. Methods: Patients diagnosed with SAH and CH at Chongqing University Central Hospital between January 2020 and April 2022 were included in this study. CSF-adenosine deaminase (ADA), CSF-lactate (Lac), and CSF-lactate dehydrogenase (LDH) were measured, and their associations with hemorrhage risk were analyzed using multivariable logistic regression models. The predictive value of these biomarkers was evaluated using receiver operating characteristic (ROC) analysis. Results: A total of 114 SAH patients, 105 CH patients, and 53 healthy controls were included in this study. The multivariable analysis revealed that hypertension, CSF-ADA, and CSF-Lac were independent risk factors for SAH, while hypertension and CSF-LDH were independent risk factors for CH. The ROC analysis demonstrated that the combination of CSF-ADA and CSF-Lac had the highest predictive value for SAH (area under the curve = 0.938), while CSF-LDH had the highest predictive value for CH (area under the curve = 0.946). Conclusion: CSF biomarkers, specifically CSF-ADA, CSF-Lac, and CSF-LDH, are valuable predictors of SAH and CH. These biomarkers may assist in diagnosing and managing hemorrhagic stroke in clinical settings.

Application of the Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for establishing reference intervals from laboratory databases.

BACKGROUND: Reference intervals (RIs) are vital for interpreting laboratory biomarkers and enabling clinical decision-making. Among various RI-estimation methods, we explored the application value of Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for estimating the RI of urea, creatinine, and uric acid (UA). METHOD: This cross-sectional study collected patient data recorded between January 2020 and April 2022 at the Chongqing University Central Hospital Laboratory Information System. The RIs of urea, creatinine, and UA levels were established using the Hoffmann, Bhattacharya, nonparametric, and Q-Q plot methods, and RI differences with different computational methods were verified using the reference change value (RCV%) of biological variability. RESULTS: We included 16,474 and 123,570 patients in the physical examination and clinical groups, respectively. In the clinical group, differences in the RI upper limit of analytes with the four methods (excluding the Q-Q plot method) were within the permissible RCV% range; only the nonparametric test produced an RI of urea with the lower limit within the permissible RCV% range. In the physical examination group, the relative RI differences among the four methods (excluding the lower limit of RI obtained using the Q-Q plot) were all within the acceptable RCV% range; the relative deviation of the RI of UA with the four methods was within the acceptable RCV% range (excluding the lower RI limit obtained using the Q-Q plot and nonparametric test). CONCLUSION: The Hoffmann and Bhattacharya methods may provide reliable RIs for indirect estimations of urea, creatinine, and UA based on laboratory datasets.

Infection Prevalence and Antibiotic Resistance Levels in Ureaplasma urealyticum and Mycoplasma hominis in Gynecological Outpatients of a Tertiary Hospital in China from 2015 to 2018.

The aim of this study was to estimate the Ureaplasma urealyticum and Mycoplasma hominis infection prevalence and antibiotic resistance levels in gynecological outpatients. Clinical characteristics and laboratory data of gynecological outpatients of the Fourth People's Hospital of Chongqing from 2015 to 2018 were retrospectively analyzed. Antibiotic resistance levels in U. urealyticum and M. hominis were defined by a commercial Mycoplasma kit for antibiotic susceptibility testing. Univariate analysis and multivariate logistic regression analysis were performed to evaluate risk factors associated with Mycoplasma isolation. Comparisons of yearly distributions and resistance rates were assessed by chi-square tests. Fifty-six percent of gynecological outpatients were positive for U. urealyticum, and 11.02% were positive for M. hominis. In the univariate analysis, women aged 30-39 years or with a history of pregnancy or gynecological diseases had an increased risk for Mycoplasma isolation, while women who were postmenopausal or had an education level of undergraduate degree or above had a decreased risk of Mycoplasma isolation. In the multivariate logistic regression model, an independent risk factor for Mycoplasma isolation was a history of gynecological diseases, while a bachelor's degree, master's degree, or above were protective factors against Mycoplasma isolation. There were distinctly gradual increases in the positivity rates of U. urealyticum and M. hominis from 2015 to 2018 and an overall increasing trend of resistance to ten antibiotics among U. urealyticum and M. hominis. The top three antibiotics associated with resistance were ofloxacin, sparfloxacin, and levofloxacin. Doxycycline, josamycin, and minocycline were preferred because they had the lowest levels of resistance. Increases in the prevalence of infection and antibiotic resistance in U. urealyticum and M. hominis were observed from 2015 to 2018, clearly confirming the necessity to monitor the standardized administration of antibiotics.