Prediction of Hospital Discharge Outcome from Changes in Cerebrospinal Fluid/serum Albumin Quotient and Cerebrospinal Fluid Lactate Dehydrogenase in Patients with Cryptococcal meningitis

Huang, Yuguang; Zou, Jun; Zhang, Keming; Li, Hang; Hu, Dongying; Liao, Wanqing; Zhang, Lei; Pan, Weihua

doi:10.2217/fmb-2021-0272

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Besides the alteration in the CNS glucose metabolism, the lactate metabolism in the CNS must also be considered. Previous studies have demonstrated that abnormal lactate metabolism in patients with CM brain are closely related to poor prognosis and can also lead to serious consequences such as abnormal mental state, seizures, and significant increase in intracranial pressure [ 46 , 64 , 65 ]. In this study, higher levels of CSF-LDH were observed in the SDB group, which suggested that the abnormal lactate metabolism of the CNS may be related to the structural damage of the brain.…”

Section: Discussionmentioning

confidence: 99%

A Retrospective Analysis of Central and Peripheral Metabolic Characteristics in Patients with Cryptococcal Meningitis

Qin,

Nong,

Zhu

et al. 2024

Neurol Ther

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Introduction Most current treatment strategies and investigations on cryptococcal meningitis (CM) focus primarily on the central nervous system (CNS), often overlooking the complex interplay between the CNS and the peripheral system. This study aims to explore the characteristics of central and peripheral metabolism in patients with CM. Methods Patients diagnosed with CM as per the hospital records of the Fourth People’s Hospital of Nanning were retrospectively analyzed. Patients were divided into two groups, non-structural damage of the brain (NSDB) and structural damage of the brain (SDB), according to the presence of brain lesions as detected with imaging. Based on the presence of enlarged cerebral ventricles, the cases in the SDB group were classified into non-ventriculomegaly (NVM) and ventriculomegaly (VM). Various parameters of cerebrospinal fluid (CSF) and peripheral blood (PB) were analyzed. Results A significant correlation was detected between CSF and PB parameters. The levels of CSF-adenosine dehydrogenase (ADA), CSF-protein, CSF-glucose, and CSF-chloride ions were significantly correlated with the levels of PB-aminotransferase, PB-bilirubin, PB-creatinine (Cr), PB-urea nitrogen, PB-electrolyte, PB-protein, and PB-lipid. Compared with NSDB, the levels of CSF-glucose were significantly decreased in the SDB group, while the levels of CSF-lactate dehydrogenase (LDH) and CSF-protein were significantly increased in the SDB group. In the SDB group, the levels of PB-potassium, PB-hemoglobin(Hb), and PB-albumin were significantly decreased in the patients with VM, while the level of PB-urea nitrogen was significantly increased in these patients. Conclusion Metabolic and structural alterations in the brain may be associated with peripheral metabolic changes.

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Section: Discussionmentioning

confidence: 99%

A Retrospective Analysis of Central and Peripheral Metabolic Characteristics in Patients with Cryptococcal Meningitis

Qin,

Nong,

Zhu

et al. 2024

Neurol Ther

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Lactate dehydrogenase-1 may play a key role in the brain energy disturbance caused by cryptococcal meningitis

Zhu,

Long,

Wei

et al. 2024

Journal of Microbiology, Immunology and Infection

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Development and validation of a machine learning model to predict prognosis in HIV-negative cryptococcal meningitis patients: A multicentre retrospective study

Liu

et al. 2022

Preprint

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Background: An increasing number of HIV-negative cryptococcal meningitis (CM) patients have been reported with fatality approaching 30%.At present, HIV-negative CM patients are stratified according to clinical guidelines and clinical experience for individualized treatment, but the effect seems to be not ideal in clinical practice. Therefore, an accurate model that predict the prognosis for HIV-negative CM patients is needed to provide reference for precision treatment. Methods: This retrospective study involved 490 HIV-negative CM patients diagnosed between January 1, 1998, and March 31, 2022, by neurologists from 3 tertiary Chinese centres. Prognosis was evaluated at 10 weeks after the initiation of antifungal therapy. We used least absolute shrinkage and selection operator (LASSO) for feature filtering and developed a machine learning (ML) model to predict the prognosis in HIV-negative CM patients. Fifty-six patients from 2 other hospitals were analysed for external validation. An artificial intelligence (AI)-based detection model was also developed to automate the rapid counting of microscopic cryptococcal counts. Results:The final prediction model for HIV-negative CM patients comprised 8 variables: CSF cryptococcal count, CSF white blood cell (WBC), altered mental status, hearing impairment, CSF chloride levels, CSF opening pressure (OP), aspartate aminotransferase levels at admission and decreased rate of CSF cryptococcal count within 2 weeks after admission. The areas under the curve (AUCs) in the internal and external validation sets were 0.87 (95% CI 0.794-0.944) and 0.86 (95% CI 0.744-0.975), respectively. An AI model was trained to detect and count cryptococci, and the mean average precision (mAP) was 0.993. Additionally, an online and freely available platform for predicting prognosis and detecting and counting cryptococci in HIV-negative CM patients was established. Conclusions:A ML model for predicting prognosis in HIV-negative CM patients was built and validated, and the model might provide a reference for personalized treatment of HIV-negative CM patients. The change in the CSF cryptococcal count in the early phase of HIV-negative CM treatment can reflect the prognosis of the disease. In addition, utilizing AI to detect and count CSF cryptococci in HIV-negative CM patients can eliminate the interference of human factors in detecting cryptococci in CSF samples and reduce the workload of the examiner.

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Prediction of Hospital Discharge Outcome from Changes in Cerebrospinal Fluid/serum Albumin Quotient and Cerebrospinal Fluid Lactate Dehydrogenase in Patients with Cryptococcal meningitis

Cited by 3 publications

References 38 publications

A Retrospective Analysis of Central and Peripheral Metabolic Characteristics in Patients with Cryptococcal Meningitis

A Retrospective Analysis of Central and Peripheral Metabolic Characteristics in Patients with Cryptococcal Meningitis

Lactate dehydrogenase-1 may play a key role in the brain energy disturbance caused by cryptococcal meningitis

Development and validation of a machine learning model to predict prognosis in HIV-negative cryptococcal meningitis patients: A multicentre retrospective study

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