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    Home > Active Ingredient News > Infection > JNNP: Predictor of inflammatory response syndrome after HIV-negative immunoactive cryptococcal meningitis infection

    JNNP: Predictor of inflammatory response syndrome after HIV-negative immunoactive cryptococcal meningitis infection

    • Last Update: 2020-12-22
    • Source: Internet
    • Author: User
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    As a deep fungal disease, cryptococcal disease mainly invades the central nervous system, accounting for about 80% of cryptococcal infection, with a serious prognosis and a high mortality rate.
    genus of cryptococcals consists of 17 species and 8 variants, classified in fungal taxonomics as semi-known submens, spores, cryptococcal yeast, cryptococcal yeast.
    pathogenic bacteria are mainly newborn crycobacteria, has been reported to cause human diseases, such as pale yellow crycoccus, pale white crycoccus and Loren crycoccus, but rare.
    three variants of the new crycobacteria, namely var neoformans, vartii and shanghaiensis.
    can be divided into A, B, C, D and AD types 5 by serological classification, in addition to a small number of uncertain types.
    about 10%-20% of HIV-CM patients develop abnormal cryptococcal immunodevelopment syndrome (IRIS) after highly active antiretroviral therapy (HAART) begins.
    , however, it is not clear what factors could have predicted the occurrence of CM-PIIRS.
    , this study aims to fill this research gap mainly to explore the HIV-negative immunoactive CM-PIIRS prediction indicators.
    2011 to December 2019, 113 patients were assessed and treated by CM at sun yat-sen University Third Affiliated Hospital in Guangzhou, China.
    Online analysis of demographic characteristics (age sex), clinical symptoms (headache, fever, visual and hearing impairment, mental state, nausea and vomiting) and treatment history, blood and cerebrospinal fluid (CSF) sample tests, improved Rankin scale (mRS) scores, and lumbar punctures.
    use random forests to select useful predictors and predict the development of PIIRS.
    first uses the selected variables to fit the random forest into the training set (75%, n=84) and then uses it to predict the PIIRS status of the test set (25%, n=29).
    a simple prediction rule by using all patients and the most useful predictors to fit the decision tree.
    further analysis of the time from the beginning of sterilization treatment to the emergence or follow-up of PIIRS, and the relationship between the reduction rate of cerebrospinal fluid fungal count and later PIIRS.
    compared baseline characteristics of 41 PIIRS patients and 72 patients without PIIRS.
    , fever, mental state changes, vomiting, epilepsy, co-disease, and initial MRS scores were not different.
    , however, the visual and auditory symptoms, VPS, higher CSF open pressure, and higher CSF fungal counts were higher in CM patients without PIIRS.
    the accuracy of the random forest was 0.749 (95% CI 0.571 to 0.893) and the area under the curve was 0.799 (95% CI was 0.631-0.939).
    based on cerebrospinal fluid fungal count and TC division is not significant.
    the low cerebrospinal fluid fungal count (≤338/mL) group occurred faster than the high cerebrospinal fluid fungal count (-gt;338/mL) group, with a difference of 28.6 days (95% CI 10.2-47.1, p=0.005).
    linear regression has an interaction coefficient of 0.002 (p-0.941) between PIIRS and the number of days after treatment, indicating that the reduction rate of cerebrospinal fluid fungal count after treatment was independent of the occurrence of PIIRS, and similar results can be found in cerebrospinal fluid glucose, protein and chloride.
    the decision tree identified CM patients with hearing loss and cerebrospinal fluid hypertension (230mmH2O) as high-risk patients with PIIRS.
    survival analysis of the number of days between the on-the-basis of sterilization therapy and the emergence of PIIRS showed that it was associated with hearing loss, cerebrospinal fluid pressure, and cerebrospinal fluid fungal counts.
    the first time that predictive indicators of PIIRS development were shown in patients with HIV-negative immunologic functioning CM.
    the current cerebrospinal fluid pressure above 230mmH2O is a strong predictor of PIIRS.
    patients with increased intracranial pressure may have a more severe inflammatory response.
    addition, this paper found that more patients with CM-PIIRS were found than those without CM-PIIRS (39.0 percent to 4.1 percent).
    hearing loss is also a powerful predictor of CM-PIIRS.
    addition to elevated intracranial pressure, cryptococcal infections themselves can cause hearing loss.
    mechanisms may play a role in hearing loss in CM patients.
    hearing impairment associated with the onset of CM may indicate a strong inflammatory response.
    36.3% of patients who were not infected with HIV-CM had PIIRS, and the median incidence was 50 days after the onset of antifellar therapy.
    is similar to HIV infection with CM on HAART, with an iris incidence rate of 31.7% and a median incidence of 60 days.
    5 cm-PIIRS patients had a higher EOS count than those without CM, and further survival analysis from the start of treatment to the number of days of PIIRS also revealed its relationship with cerebrospinal fluid fungal count.
    the high fungal count of PIIRS in the low cerebrospinal fluid fungal count (≤338/mL) group occurred early in the group PIIRS , with significant differences (28.6 days).
    results suggest that patients with low cerebrospinal fluid fungal counts have a lower risk of developing PIIRS, but IF PIIRS occurs in these patients, PIIRS occurs earlier.
    addition, multiple logistic regression and tree-based analysis showed that cerebrospinal fluid fungal counts could not be used as predictors of CM-PIIRS, which was inconsistent with CM-IRIS.
    addition, the rate of decrease in cerebrospinal fluid fungal counts was not found to be associated with PIIRS events.
    , baseline hearing loss and high cerebrospinal fluid pressure (230mmH2O) were potential risk factors for the assessment of PIIRS in HIV-negative immunoactive CM patients.
    Liu J, Luo C, Li M, et al Predictors of postinfectiousitisy response syndrome in HIV-negative immunocompetent cryptoccal meningitisJournal of Neurology, Neurosurgery Psython Published Online First: 04 December 2020. doi:10.1136/jnnp-2020-324921MedSci Original Source: MedSci Original Copyright Notice: All notes on this website "Source: Met Medical" or "Source: MedSci Original" text, images and audio-visual materials, copyrighted by Mace Medical, not authorized by any media Websites or individuals may not be reproduced, and the authorizing reprints must include "Source: Metz Medicine".
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