Establishment of a novel scoring model for mortality risk prediction in HIV-infected patients with cryptococcal meningitis

Molecular Diagnostics of Cryptococcus spp. and Immunomics of Cryptococcosis-Associated Immune Reconstitution Inflammatory Syndrome

Cryptococcal infection poses a significant global public health challenge, particularly in regions near the equator. In this review, we offer a succinct exploration of the Cryptococcus spp. genome and various molecular typing methods to assess the burden and genetic diversity of cryptococcal pathogens in the environment and clinical isolates. We delve into a detailed discussion on the molecular pathogenesis and diagnosis of immune reconstitution inflammatory syndrome (IRIS) associated with cryptococcosis, with a specific emphasis on cryptococcal meningitis IRIS (CM-IRIS). Our examination includes the recent literature on CM-IRIS, covering host cellulomics, proteomics, transcriptomics, and genomics.

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis

BACKGROUND

Early prediction of mortality in individuals with HIV (PWH) has perpetually posed a formidable challenge. With the widespread integration of machine learning into clinical practice, some researchers endeavor to formulate models predicting the mortality risk for PWH. Nevertheless, the diverse timeframes of mortality among PWH and the potential multitude of modeling variables have cast doubt on the efficacy of the current predictive model for HIV-related deaths. To address this, we undertook a systematic review and meta-analysis, aiming to comprehensively assess the utilization of machine learning in the early prediction of HIV-related deaths and furnish evidence-based support for the advancement of artificial intelligence in this domain.

METHODS

We systematically combed through the PubMed, Cochrane, Embase, and Web of Science databases on November 25, 2023. To evaluate the bias risk in the original studies included, we employed the Predictive Model Bias Risk Assessment Tool (PROBAST). During the meta-analysis, we conducted subgroup analysis based on survival and non-survival models. Additionally, we utilized meta-regression to explore the influence of death time on the predictive value of the model for HIV-related deaths.

RESULTS

After our comprehensive review, we analyzed a total of 24 pieces of literature, encompassing data from 401,389 individuals diagnosed with HIV. Within this dataset, 23 articles specifically delved into deaths during long-term follow-ups outside hospital settings. The machine learning models applied for predicting these deaths comprised survival models (COX regression) and other non-survival models. The outcomes of the meta-analysis unveiled that within the training set, the c-index for predicting deaths among people with HIV (PWH) using predictive models stands at 0.83 (95% CI: 0.75-0.91). In the validation set, the c-index is slightly lower at 0.81 (95% CI: 0.78-0.85). Notably, the meta-regression analysis demonstrated that neither follow-up time nor the occurrence of death events significantly impacted the performance of the machine learning models.

CONCLUSIONS

The study suggests that machine learning is a viable approach for developing non-time-based predictions regarding HIV deaths. Nevertheless, the limited inclusion of original studies necessitates additional multicenter studies for thorough validation.

The effect of machine learning algorithms in the prediction, and diagnosis of meningitis: A systematic review

Background and Aims

This systematic review aimed to evaluating the effectiveness of machine learning (ML) algorithms for the prediction and diagnosis of meningitis.

Methods

On November 12, 2022, a systematic review was carried out using a keyword search in the reliable scientific databases PubMed, EMBASE, Scopus, and Web of Science. The recommendations of Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) were adhered to. Studies conducted in English that employed ML to predict and identify meningitis were deemed to match the inclusion criteria. The eligibility requirements were used to independently review the titles and abstracts. The whole text was then obtained and independently reviewed in accordance with the eligibility requirements.

Results

After all the research matched the inclusion criteria, a total of 16 studies were added to the systematic review. Studies on the application of ML algorithms in the three categories of disease diagnosis ability (8.16) and disease prediction ability (8.16) (including cases related to identifying patients (50%), risk of death in patients (25%), the consequences of the disease in childhood (12.5%), and its etiology [12.5%]) were placed. Among the ML algorithms used in this study, logistic regression (LR) (4.16, 25%) and multiple logistic regression (MLR) (4.16, 25%) were the most used. All the included studies indicated improvements in the processes of diagnosis, prediction, and disease outbreak with the help of ML algorithms.

Conclusion

The results of the study showed that in all included studies, ML algorithms were an effective approach to facilitate diagnosis, predict consequences for risk classification, and improve resource utilization by predicting the volume of patients or services as well as discovering risk factors. The role of ML algorithms in improving disease diagnosis was more significant than disease prediction and prevalence. Meanwhile, the use of combined methods can optimize differential diagnoses and facilitate the decision-making process for healthcare providers.

Divergent neuroimmune signatures in the cerebrospinal fluid predict differential gender-specific survival among patients with HIV-associated cryptococcal meningitis

Introduction

Survival among people with HIV-associated cryptococcal meningitis (CM) remains low, particularly among women, despite the currently optimal use of antifungal drugs. Cryptococcus dissemination into the central nervous system [brain, spinal cord, and cerebrospinal fluid (CSF)] elicits the local production of cytokines, chemokines, and other biomarkers. However, no consistent diagnostic or prognostic neuroimmune signature is reported to underpin the risk of death or to identify mechanisms to improve treatment and survival. We hypothesized that distinct neuroimmune signatures in the CSF would distinguish survivors from people who died on antifungal treatment and who may benefit from tailored therapy.

Methods

We considered baseline clinical features, CSF cryptococcal fungal burden, and CSF neuroimmune signatures with survival at 18 weeks among 419 consenting adults by "gender" (168 women and 251 men by biological sex defined at birth).

Results

Survival at 18 weeks was significantly lower among women than among men {47% vs. 59%, respectively; hazard ratio (HR) = 1.4 [95% confidence interval (CI), 1.0 to 1.9; p = 0.023]}. Unsupervised principal component analysis (PCA) demonstrated divergent neuroimmune signatures by gender, survival, and intragender-specific survival. Overall, women had lower levels of programmed death ligand 1, Interleukin (IL) (IL-11RA/IL-1F30, and IL-15 (IL-15) than men (all p < 0.028). Female survivors compared with those who died expressed significant elevations in levels of CCL11 and CXCL10 chemokines (both p = 0.001), as well as increased T helper 1, regulatory, and T helper 17 cytokines (all p < 0.041). In contrast, male survivors expressed lower levels of IL-15 and IL-8 compared with men who died (p < 0.044).

Conclusions

Survivors of both genders demonstrated a significant increase in the levels of immune regulatory IL-10. In conclusion, the lower survival among women with CM was accompanied by distinct differential gender-specific neuroimmune signatures. These female and male intragender-specific survival-associated neuroimmune signatures provide potential targets for interventions to advance therapy to improve the low survival among people with HIV-associated CM.

Disseminated Cryptococcosis Is a Common Finding among Human Immunodeficiency Virus-Infected Patients with Suspected Sepsis and Is Associated with Higher Mortality Rates

Cryptococcosis is the leading cause of death among people with HIV in Sub-Saharan Africa. The lack of optimum diagnoses and medications significantly impair the management of the disease. We investigated the burden of cryptococcosis and related mortality among people with HIV and suspected sepsis in Ethiopia. We conducted a prospective study at (1) Adama Hospital Medical College and (2) Asella Referral and Teaching Hospital from September 2019 to November 2020. We enrolled adult, HIV-infected patients presenting with suspected sepsis and assessed their 28-day survival rates. We performed blood cultures and cryptococcal antigen (CrAg) testing. In total, 82 participants were enrolled with a median age of 35 years, and 61% were female. Overall, eleven (13%) had positive CrAg tests, of which five grew Cryptococcus in blood cultures. Despite high-dose fluconazole (1200 mg/d) monotherapy being given to those with positive CrAg tests, the 28-day mortality was 64% (7/11), with mortality being significantly higher than among the CrAg-negative patients (9% (6/71); p < 0.001). Cryptococcosis was the leading cause of mortality among HIV-infected sepsis patients in this Ethiopian cohort. The CrAg screening of HIV-infected patients attending an emergency department can minimize the number of missed cryptococcosis cases irrespective of the CD4 T cell count and viral load. These findings warrant the need for a bundle approach for the diagnosis of HIV-infected persons presenting with sepsis in low- and middle-income countries.

Development and Validation of a Nomograph Model for Post-Operative Central Nervous System Infection after Craniocerebral Surgery

PURPOSE

A nomograph model of predicting the risk of post-operative central nervous system infection (PCNSI) after craniocerebral surgery was established and validated.

METHODS

The clinical medical records of patients after cranial surgery in Renmin Hospital of Wuhan University from January 2020 to September 2022 were collected, of whom 998 patients admitted to Shouyi Hospital District were used as the training set and 866 patients admitted to Guanggu Hospital District were used as the validation set. Lasso regression was applied to screen the independent variables in the training set, and the model was externally validated in the validation set.

RESULTS

A total of 1864 patients after craniocerebral surgery were included in this study, of whom 219 (11.75%) had PCNSI. Multivariate logistic regression analysis showed that age > 70 years, a previous history of diabetes, emergency operation, an operation time ≥ 4 h, insertion of a lumbar cistern drainage tube ≥ 72 h, insertion of an intracranial drainage tube ≥ 72 h, intraoperative blood loss ≥ 400 mL, complicated with shock, postoperative albumin ≤ 30 g/L, and an ICU length of stay ≥ 3 days were independent risk factors for PCNSI. The area under the curve (AUC) of the training set was 0.816 (95% confidence interval (95%CI), 0.773-0.859, and the AUC of the validation set was 0.760 (95%CI, 0.715-0.805). The calibration curves of the training set and the validation set showed p-values of 0.439 and 0.561, respectively, with the Hosmer-Lemeshow test. The analysis of the clinical decision curve showed that the nomograph model had high clinical application value.

CONCLUSION

The nomograph model constructed in this study to predict the risk of PCNSI after craniocerebral surgery has a good predictive ability.

High socioeconomic status is associated with stroke severity among stroke patients in the National Brain Centre Hospital, Jakarta, Indonesia

Rapid economic growth has widened the gap between the rich and the poor, contributing to inequalities in socioeconomic status (SES) in Indonesia and possibly inequalities in health care. Here, we aimed to assess the potential association between SES and stroke severity in Indonesia, one of the largest low- and middle-income countries. Patients diagnosed with stroke at National Brain Centre (NBC) Hospital, Jakarta, Indonesia, in 2020 were included in the study. SES was measured based on marital status, occupation, education level, source of payment, and hospitalized class with smoking status and sex as confounder. Stroke severity was classified based on the National Institutes of Health Stroke Scale score into minor stroke (Adams et al., 1993, Amarenco et al., 2014, Andersen and Olsen, 2018, Austin and Steyerberg, 2017) and moderate to severe stroke (>4). A total of 2,443 patients with moderate to severe stroke (58%) were analyzed. Currently employed patients had a lower adjusted OR (aOR) of 0.65 (95% confidence interval [CI], 0.51-0.83) than unemployed patients. Patients with the highest education level, at least a diploma degree, had a lower aOR of 0.67 (95% CI, 0.49-0.92) than those with an elementary or no education. Our findings showed that patients with a higher SES had a lower risk of more severe stroke than those with a lower SES. Hence, we must focus on improving SES as part of stroke management.

Therapeutic Lumbar Punctures in Human Immunodeficiency Virus-Associated Cryptococcal Meningitis: Should Opening Pressure Direct Management?

Background

Increased intracranial pressure (ICP) frequently complicates cryptococcal meningitis. Therapeutic lumbar punctures (LPs) have acute survival benefits in the first week, and we sought to understand the longer-term survival impact of therapeutic LPs.

Methods

We prospectively enrolled human immunodeficiency virus (HIV)-seropositive adults with cryptococcal meningitis from 2013 to 2017 in Uganda. We assessed the association between clinical characteristics, CSF parameters, and 14- and 30-day mortality by baseline ICP. We also assessed 30-day mortality by number of follow-up therapeutic LPs performed within 7 days.

Results

Our analysis included 533 participants. Participants with baseline ICP >350 mm H₂O were more likely to have Glasgow Coma Scale (GCS) score <15 (P < .001), seizures (P < .01), and higher quantitative cryptococcal cultures (P < .001), whereas participants with ICP <200 mm H₂O were more likely to have baseline sterile CSF cultures (P < .001) and CSF white blood cell count ≥5 cells/µL (P = .02). Thirty-day mortality was higher in participants with baseline ICP >350 mm H₂O and ICP <200 mm H₂O as compared with baseline ICP 200-350 mm H₂O (hazard ratio, 1.55 [95% confidence interval, 1.10-2.19]; P = .02). Among survivors at least 7 days, the 30-day relative mortality was 50% higher among participants who did not receive any additional therapeutic LPs compared to those with ≥1 additional follow-up LP (33% vs 22%; P = .04), irrespective of baseline ICP.

Conclusions

Management of increased ICP remains crucial in improving clinical outcomes in cryptococcal meningitis. Guidelines should consider an approach to therapeutic LPs that is not dictated by baseline ICP.

Therapeutic lumbar puncture and lumbar drainage: which is more effective for the management of intracranial hypertension in HIV patients with cryptococcal meningitis? Results of a prospective non-randomized interventional study in China

OBJECTIVE

This study aimed to evaluate the effectiveness of therapeutic lumbar drainage (LD) compared to therapeutic lumbar puncture (LP) for the management of intracranial hypertension (ICH) among HIV-positive patients with cryptococcal meningitis (CM).

METHODS

The study was a multicenter prospective non-randomized interventional clinical trial. One hundred and sixteen HIV-associated CM patients were identified who presented with ICH (≥250 mmH₂O). The LP group comprised 76 cases, while the LD group consisted of 40 cases. We compared mortality, intracranial pressure (ICP) normalization rate, and clinical symptom remission at 10 weeks, between the two groups.

RESULTS

The cumulative mortality at week 10 was 22.4% in the LP group and 20% in the LD group (p = .927), without any significant difference in mortality between the two groups. Improvement after treatment at 2-weeks, ICP normalization, and headache reversal event occurrence in the two groups showed no significant difference (p > .05). The incidence of CSF Cryptococcus clearance at two weeks in the LD group was significantly higher than in the LP group (p < .05). The frequency of invasive lumbar therapeutic procedures in the LP group during the first week was higher than that of the LD group (p < .05). Localized infection at the puncture site occurred more frequently in the LD group than in the LP group (p < .05).

CONCLUSION

For HIV-positive CM patients with an elevated ICP, LD and LP are comparably effective and safe options to normalize ICP. LP increases the frequency of invasive lumbar therapeutic procedures but does not incur more risk of infection events at the puncture site, while LD may accelerate CSF Cryptococcus clearance but may induce more frequent localized infection.

TRIAL REGISTRATION

This study was registered as one of 12 trials under a general project at the Chinese Clinical Trial Registry (ChiCTR1900021195).

Clinical Characteristics and Risk Factors for Mortality in Cryptococcal Meningitis: Evidence From a Cohort Study

Introduction

Despite advances in the diagnosis and management, cryptococcal meningitis (CM) is still associated with high mortality due to insufficient knowledge about clinical characteristics and risk factors for poor outcomes. The aim of the present study is to provide additional evidence for regarding clinical characteristics, diagnosis, and factors associated with increased risk of mortality in CM patients.

Methods

In this cohort study, we included eligible patients consecutively admitted to West China Hospital between January 2009 and December 2018. The clinical characteristics and diagnosis method of cerebrospinal fluid culture and India ink stain were analyzed. Independent risk factors were identified by a multivariable logistic regression.

Results

A total of 186 CM patients were included in the analysis. After a 1-year follow-up, 63 patients had died. Headache is the most common presenting symptom (97.3%), followed by vomiting (72%), fever (71.5%), altered consciousness (45.7%), abnormal vision (32.8%), and seizure (15.1%). Older age, altered consciousness or seizures, lower white blood cell count or total protein in cerebrospinal fluid (CSF), and unidentified CSF cryptococcal antigen (CrAg) are all factors associated with increasing risk of death (P < 0.05). We also found a dose-dependent trend between the number of symptoms and risk of death (trend p < 0.001). Multivariate logistic regression revealed that age (P = 0.004, OR = 1.042, 95% CI 1.013–1.071), seizure (P = 0.025, OR = 3.105, 95% CI 1.152–8.369), altered consciousness (P < 0.001, OR=6.858, 95% CI 3.063–15.38), and unidentified CSF CrAg are the independent prognostic factors. In addition, we observed that diagnosis of 28.5% and 22.5% CM could not be established by a single testing of CSF India ink stain or culture, respectively. Use of multiple testing methods or combination of the two assays increases the detection rate.

Conclusion

Our data show that older age, seizures, altered consciousness, and an inability to detect CSF CrAg are the independent risk factors of death within 1 year in CM patients. Moreover, we recommend use of multiple testing methods with CSF culture and India ink stain. Combined testing with both assays should be considered for initial CM diagnosis.