Machine learning models reveal neurocognitive impairment type and prevalence are associated with distinct variables in HIV/AIDS

Tu, Wei; Chen, Patricia; Koenig, Noshin; Gomez, Daniela; Fujiwara, Esther; Gill, M John; Kong, Linglong; Power, Christopher

doi:10.1007/s13365-019-00791-6

Cited by 17 publications

(23 citation statements)

References 29 publications

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“…Four studies examined the impact of HAND on health-related QoL (HRQoL) [27,30,38,45], two studies assessed psychological state in those with HAND [50,51], one study examined the impact of positive health behaviours on HAND [42], one study examined associations between different PROMs and HAND [43], and one study explored how HAND impacted well-being [24,31,40,43,47], two studies recruited from community settings [42,49], and two studies recruited from a neurology clinic [27,30]. Fourteen studies employed quantitative methodologies: seven studies were case-control studies [35,38,40,42,43,47,51] and seven has a cross-sectional design [27, 30-32, 45, 50]. One qualitative study was included, which employed interpretative qualitative methods [49].…”

Section: Resultsmentioning

confidence: 99%

“…Living-Modified (8-items) [31] Physical functioning [31,35,38,40,43,47] Level of independence Health status (Functional ability across 8 common daily, 'complex' tasks (Telephone use, Shopping, Food preparation, Housekeeping, Laundry, Transportation, Medication management and Financial management) ALF Questionnaire (9-items) [32] Physical functioning [32] Mental functioning Social functioning PHQ-9 (9-item) [44] Mental health [43,45,51] Beck Depression Inventory BDI-II (21-Item) [53] Mental health [32,40,50] Profile of Mood States POMS (65-items) [37] Mental wellbeing [35] https://doi.org/10.1371/journal.pone.0251944.t003…”

Section: Lawson and Brody Instrumental Activities Of Dailymentioning

confidence: 99%

“…It covers eight domains, and allows the administer to calculate a PHS, MHS, and overall QoL score. Two studies; [45,51] used the EVGGFP [46], a single-item measure of HRQoL, which asks patients to rate their HRQoL today, and yields moderate validity for assessing HRQoL in PLWH [46]. A number of studies, in addition to the broader QoL instruments aforementioned [30,43,47], used PROMs to examine manifest functioning.…”

Section: Plos Onementioning

confidence: 99%

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Quality of life in people living with HIV-associated neurocognitive disorder: A scoping review study

et al. 2021

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Quality of life (QoL) is recognized as an essential end point in the disease management of chronic conditions such as HIV with calls to include good QoL as a ‘fourth 90’ in the 90-90-90 testing and treatment targets introduced by World Health Organization in 2016. Cognitive impairments impact a broad spectrum of experiences and are a common issue effecting people living with HIV (PLWH). Despite this, few studies have examined QoL in PLWH who also have a cognitive disorder. This study aimed to synthesize and describe what is known about QoL in those living with HIV-associated neurocognitive disorders (HAND). A scoping review of peer-reviewed literature was conducted to identify how QoL has been investigated and measured in PLWH with HAND, and how PLWH with HAND report and describe their QoL. We searched PsychInfo, Medline, Scopus, and Web of Science along with hand-searching reference lists from relevant studies found. Included studies were those published in English after 1st January 2003 which included PLWH with cognitive impairment not due to other pre-existing conditions. Fifteen articles met criteria for inclusion. Two studies measured QoL as a primary aim, with others including QoL assessment as part of a broader battery of outcomes. The MOS-HIV and SF-36 were the most commonly used measures of overall QoL, with findings generally suggestive of poorer overall QoL in PLWH with HAND, compared to PLWH without cognitive impairment. Studies which examined dimensions of QoL focused exclusively on functionality, level of independence, and psychological QoL domains. There is a considerable dearth of research examining QoL in PLWH with HAND. The initiatives which advocate for healthy aging and improved QoL in PLWH must be extended to include and understand the experiences those also living with cognitive impairment. Research is needed to understand the broad experiential impacts of living with these two complex, chronic conditions, to ensure interventions are meaningful to patients and potential benefits are not missed.

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Section: Resultsmentioning

confidence: 99%

Section: Lawson and Brody Instrumental Activities Of Dailymentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

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Quality of life in people living with HIV-associated neurocognitive disorder: A scoping review study

et al. 2021

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“…ML could both define normative HRV values for single or complex metrics and even create models able to predict how the newborn's condition will evolve based on big-data analysis (Fairchild and Aschner, 2012;Kumar et al, 2020). Indeed, in several research fields including neonatology, neurology, and cardiology, advanced ML is being successfully used to detect specific pathophysiological characteristics (Fraser, 2017;Pinaya et al, 2019;Tu et al, 2020;Turova et al, 2020;Vassar et al, 2020).…”

Section: The Current State Of Hrv Assessment and Limitationsmentioning

confidence: 99%

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Chiera¹,

Cerritelli²,

Casini³

et al. 2020

Front. Neurosci.

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Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often timeconsuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a noninvasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby's overall wellbeing and neurological development to detect stress-/painrelated behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby's stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant's HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant's clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients' health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.

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“…This database has a large number of participants with multimodal imaging data acquired using homogeneous hardware and software (Elliott et al, 2018). With the large number of participants in the UKB database, we have the opportunity to use the same database to discover and validate the findings independently, instead of adopting the ensemble methods to stabilize and validate the findings using the discovery set alone (Asahchop et al, 2018; Tu et al, 2020). Several GWAS of brain imaging based phenotypes have been reported (Elliott et al, 2018; Zhao et al, 2019) to take advantage of this large and rich database, but, a study of brain connectivity has not been conducted to the best of our knowledge.…”

Section: Introductionmentioning

confidence: 99%

Super‐variants identification for brain connectivity

Wang

et al. 2020

Human Brain Mapping

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Identifying genetic biomarkers for brain connectivity helps us understand genetic effects on brain function. The unique and important challenge in detecting associations between brain connectivity and genetic variants is that the phenotype is a matrix rather than a scalar. We study a new concept of super‐variant for genetic association detection. Similar to but different from the classic concept of gene, a super‐variant is a combination of alleles in multiple loci but contributing loci can be anywhere in the genome. We hypothesize that the super‐variants are easier to detect and more reliable to reproduce in their associations with brain connectivity. By applying a novel ranking and aggregation method to the UK Biobank databases, we discovered and verified several replicable super‐variants. Specifically, we investigate a discovery set with 16,421 subjects and a verification set with 2,882 subjects, where they are formed according to release date, and the verification set is used to validate the genetic associations from the discovery phase. We identified 12 replicable super‐variants on Chromosomes 1, 3, 7, 8, 9, 10, 12, 15, 16, 18, and 19. These verified super‐variants contain single nucleotide polymorphisms that locate in 14 genes which have been reported to have association with brain structure and function, and/or neurodevelopmental and neurodegenerative disorders in the literature. We also identified novel loci in genes RSPO2 and TMEM74 which may be upregulated in brain issues. These findings demonstrate the validity of the super‐variants and its capability of unifying existing results as well as discovering novel and replicable results.

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Machine learning models reveal neurocognitive impairment type and prevalence are associated with distinct variables in HIV/AIDS

Cited by 17 publications

References 29 publications

Quality of life in people living with HIV-associated neurocognitive disorder: A scoping review study

Quality of life in people living with HIV-associated neurocognitive disorder: A scoping review study

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Super‐variants identification for brain connectivity

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