Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis.
Katharine E StottJason T MohabirKatharine BowersJennifer L TenorDena L ToffalettiJennifer UnsworthAna Jimenez-ValverdeAjisa AhmaduMelanie MoyoEbbie GondweWezi Chimang'angaMadalitso ChaswekaDavid S LawrenceJoseph N JarvisTom HarrisonWilliam W HopeDavid G LallooHenry C MwandumbaJohn R PerfectChristina A Cuomonull nullPublished in: mBio (2024)
HIV-associated cryptococcal meningitis is associated with a high burden of mortality. Research into the different strain types causing this disease has yielded inconsistent findings in terms of which strains are associated with worse clinical outcomes. Our study suggests that the exposure of patients to potent anti-cryptococcal drugs has a more significant impact on clinical outcomes than the strain type of the infecting organism. Future research should focus on optimizing drug exposure, particularly in the context of novel anticryptococcal drugs coming into clinical use.
Keyphrases
- antiretroviral therapy
- hiv positive
- hiv infected
- hiv testing
- human immunodeficiency virus
- end stage renal disease
- hepatitis c virus
- hiv aids
- ejection fraction
- men who have sex with men
- newly diagnosed
- chronic kidney disease
- escherichia coli
- risk factors
- electronic health record
- prognostic factors
- type diabetes
- peritoneal dialysis
- current status
- cardiovascular disease
- drug induced
- dna methylation
- copy number
- south africa
- patient reported outcomes
- deep learning
- anti inflammatory