Section: high-dimensional statistics at Bernoulli-IMS One World Symposium 2020, August 24th to August 28th 2020, https://www.worldsymposium2020.org/
Two small-data n << p case studies: hydroxycholoroquine, Marseilles and Meijel. A March 2020 preprint by the famous Marseilles group of Didier Raoult caused international interest and controversy. It promoted a treatment for early Covid-19 infection centred on the anti-malarial drug hydroxychloroquine (HCQ). The study was an observational study with a treatment group and a control group of altogether 42 patients. An early HCQ adopter was the Dutch GP (and alternative medicine practitioner) Rob Elens, whose practice is in a village right in the middle of the initial Dutch Corona hotspot. He collected a very similar dataset, and in his case the treatment was almost randomised: at a certain point the Netherlands health inspectorate forbade the use of HCQ, so the treatment given to his patients was entirely determined by outside events: first the publication of Gautret et al., and then the Dutch government ukase. In my talk I will present some analyses by logistic regression, both frequentist and Bayesian, including a solution to the n << p problem, of the two data sets. How strong was this evidence was in support of HCQ?
Dr. Swamy Venuturupalli talks about the latest developments in lupus at the 2015 Latest on Lupus Patient Conference held by Lupus LA on Saturday October 17th at UCLA Medical Center.
Section: high-dimensional statistics at Bernoulli-IMS One World Symposium 2020, August 24th to August 28th 2020, https://www.worldsymposium2020.org/
Two small-data n << p case studies: hydroxycholoroquine, Marseilles and Meijel. A March 2020 preprint by the famous Marseilles group of Didier Raoult caused international interest and controversy. It promoted a treatment for early Covid-19 infection centred on the anti-malarial drug hydroxychloroquine (HCQ). The study was an observational study with a treatment group and a control group of altogether 42 patients. An early HCQ adopter was the Dutch GP (and alternative medicine practitioner) Rob Elens, whose practice is in a village right in the middle of the initial Dutch Corona hotspot. He collected a very similar dataset, and in his case the treatment was almost randomised: at a certain point the Netherlands health inspectorate forbade the use of HCQ, so the treatment given to his patients was entirely determined by outside events: first the publication of Gautret et al., and then the Dutch government ukase. In my talk I will present some analyses by logistic regression, both frequentist and Bayesian, including a solution to the n << p problem, of the two data sets. How strong was this evidence was in support of HCQ?
An overview over the use of AI for medical research and health care and the ethical and sustainability issues that arise in this context. Based on a lecture at the EUGLOH summer school "Artificial Intelligence" on 2022-07-07.
Watch the video of the presentation on Youtube: https://www.youtube.com/watch?v=WRegqg5yvRs
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Presentation on study to assess longitudinal changes in cognitive function among individuals with pediatric MS evaluated within the US Network of Pediatric MS Centers.
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Adoption of electronic health records to document extensive clinical information brings with it the opportunity to utilise that information to support clinical research, and ultimately to support clinical decision making. In this talk, I discuss both these opportunities and the challenges that we face when working with real-world clinical data, and introduce some of the strategies that we are adopting to make this data more usable, and to extract more value from it. I specifically discuss the use of natural language processing to transform clinical documentation into structured data for this purpose.
Journal Club - Discussion of Heriot et al. Criteria for identifying patients ...Salpy Kelian
Discussing, using many Bobs, how a monte carlo simulation works for a Journal Club paper regarding the modality used for detection of infectious endocarditis.
Katherine Promer Flores, MD (she/her)
Staff Physician
Division of Infectious Diseases and Global Public Health
Department of Medicine
University of California San Diego
Daniel Lee, MD
Clinical Professor of Medicine
Division of Infectious Diseases & Global Public Health
Department of Medicine
University of California, San Diego
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Section: high-dimensional statistics at Bernoulli-IMS One World Symposium 2020, August 24th to August 28th 2020, https://www.worldsymposium2020.org/
Two small-data n << p case studies: hydroxycholoroquine, Marseilles and Meijel. A March 2020 preprint by the famous Marseilles group of Didier Raoult caused international interest and controversy. It promoted a treatment for early Covid-19 infection centred on the anti-malarial drug hydroxychloroquine (HCQ). The study was an observational study with a treatment group and a control group of altogether 42 patients. An early HCQ adopter was the Dutch GP (and alternative medicine practitioner) Rob Elens, whose practice is in a village right in the middle of the initial Dutch Corona hotspot. He collected a very similar dataset, and in his case the treatment was almost randomised: at a certain point the Netherlands health inspectorate forbade the use of HCQ, so the treatment given to his patients was entirely determined by outside events: first the publication of Gautret et al., and then the Dutch government ukase. In my talk I will present some analyses by logistic regression, both frequentist and Bayesian, including a solution to the n << p problem, of the two data sets. How strong was this evidence was in support of HCQ?
Dr. Swamy Venuturupalli talks about the latest developments in lupus at the 2015 Latest on Lupus Patient Conference held by Lupus LA on Saturday October 17th at UCLA Medical Center.
Section: high-dimensional statistics at Bernoulli-IMS One World Symposium 2020, August 24th to August 28th 2020, https://www.worldsymposium2020.org/
Two small-data n << p case studies: hydroxycholoroquine, Marseilles and Meijel. A March 2020 preprint by the famous Marseilles group of Didier Raoult caused international interest and controversy. It promoted a treatment for early Covid-19 infection centred on the anti-malarial drug hydroxychloroquine (HCQ). The study was an observational study with a treatment group and a control group of altogether 42 patients. An early HCQ adopter was the Dutch GP (and alternative medicine practitioner) Rob Elens, whose practice is in a village right in the middle of the initial Dutch Corona hotspot. He collected a very similar dataset, and in his case the treatment was almost randomised: at a certain point the Netherlands health inspectorate forbade the use of HCQ, so the treatment given to his patients was entirely determined by outside events: first the publication of Gautret et al., and then the Dutch government ukase. In my talk I will present some analyses by logistic regression, both frequentist and Bayesian, including a solution to the n << p problem, of the two data sets. How strong was this evidence was in support of HCQ?
An overview over the use of AI for medical research and health care and the ethical and sustainability issues that arise in this context. Based on a lecture at the EUGLOH summer school "Artificial Intelligence" on 2022-07-07.
Watch the video of the presentation on Youtube: https://www.youtube.com/watch?v=WRegqg5yvRs
El Dr Welte té nombroses publicacions en àrees diverses relacionades amb el malalt crític. Particularment interessants són els seus estudis en relació al trasplantament pulmonar, així com els seus estudis sobre pneumònia i sèpsia. Així mateix, participa activament en la xarxa alemanya Capnetz, emprada per a l'elaboració d'estudis multicèntrics relacionats amb la pneumònia adquirida a la comunitat.
Presentation on study to assess longitudinal changes in cognitive function among individuals with pediatric MS evaluated within the US Network of Pediatric MS Centers.
Using real-world evidence to investigate clinical research questionsKarin Verspoor
Adoption of electronic health records to document extensive clinical information brings with it the opportunity to utilise that information to support clinical research, and ultimately to support clinical decision making. In this talk, I discuss both these opportunities and the challenges that we face when working with real-world clinical data, and introduce some of the strategies that we are adopting to make this data more usable, and to extract more value from it. I specifically discuss the use of natural language processing to transform clinical documentation into structured data for this purpose.
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Katherine Promer Flores, MD (she/her)
Staff Physician
Division of Infectious Diseases and Global Public Health
Department of Medicine
University of California San Diego
Daniel Lee, MD
Clinical Professor of Medicine
Division of Infectious Diseases & Global Public Health
Department of Medicine
University of California, San Diego
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University of Mississippi Medical Center
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Department of Medicine
University of California San Diego
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Division of Infectious Diseases & Global Public Health
Department of Medicine
University of California, San Diego
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Division of Infectious Diseases & Global Public Health
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University of California, San Diego
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Division of Infectious Diseases & Global Public Health
Department of Medicine
University of California, San Diego
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Division of Infectious Diseases & Global Public Health
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Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
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Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
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These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
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Hemodialysis: Chapter 3, Dialysis Water Unit - Dr.Gawad
Toxoplasmosis, Malaria, and HIV: Impact of Latent Co-infection on HIV Disease
1. AIDS CLINICAL ROUNDS
The UC San Diego AntiViral Research Center sponsors weekly
presentations by infectious disease clinicians, physicians and
researchers. The goal of these presentations is to provide the most
current research, clinical practices and trends in HIV, HBV, HCV, TB
and other infectious diseases of global significance.
The slides from the AIDS Clinical Rounds presentation that you are
about to view are intended for the educational purposes of our
audience. They may not be used for other purposes without the
presenter’s express permission.
2. Toxoplasmosis, malaria, and HIV:
Impact of latent co-infection on HIV
disease
Ajay R. Bharti, MD
Assistant Professor
Division of Infectious Diseases
1
3. Toxoplasmosis
• Toxoplasma gondii
• Acute infection
– Flu-like symptoms that resolve in a few weeks
– CMI controls but does not eradicate the parasite
– May cause congenital infection
• Latent infection
– Life long
– Dormant in tissue
• Brain: neurons and astrocytes
• Muscle: skeletal, heart, and smooth muscle
– Reactivation disease after loss of CMI
– Encephalitis and chorioretinitis
2
14. • St. Paul hospital, Addis Ababa
• Tested 330 samples (165 HIV+, 165 HIV-)
• Overall seroprevalence 90%
• High but similar in both groups
– HIV+ (93.3%) vs. HIV- (86.7%)
13
24. • First study to investigate the effect of LT in
humans
• Significant delay in reaction time in those with
LT
• Positive correlation between length of
infection and mean reaction time
23
26. • Prospective study of 3,890 male subjects
• LT increased the chance of traffic accidents
– (OR 2.43, CI95: 1.11–5.35, P = 0.027)
• RhD positivity reduced the risk of traffic
accidents in LT+ subjects
– (OR 0.35, CI95: 0.136–0.902, P= 0.028)
• RhD+ people are protected against LT-induced
impaired reaction time
25
27. • 758 women in 16th
week of gestation
• LT+ women had a
lower body weight
(p = 0.02)
• Cumulative effect
26
28. Other Effects of LTI
• Alzheimer’s disease
• Parkinson’s disease
• Schizophrenia
• OCD
• Increases probability of birth of male offspring
• Effect on personality
– High intelligence, guilt proneness, radicalism, and
high ergic tension
27
32. • Cysts widely distributed in brain
• Cerebral cortex had higher cyst density than
subcortical region
• Cerebellum consistently had low cysts
• Myelinated fiber tracts devoid of cysts
• No tropism towards dopaminergic or
hypothalamic systems
31
33. • Men with LT had decreased leukocyte, NK-cell
and monocyte counts
• Women had increased counts
• B-cell counts were reduced in both men and
women
• The difference between LT+ and LT- subjects
declined with decline in Toxo IgG titers
32
35. Background
• Prevalence of LT is similar or higher in HIV+
compared with HIV- individuals
• ARVs do not affect LT
• HIV-associated neurocognitive disorders
persist despite adequate ART
– Co-infections like LT may contribute to NCI
• Impact of LT on neurocognitive impairment in
HIV+ individuals has not been studied
34
36. Objectives
• To determine the prevalence of LT in our HIV+
cohort
• To evaluate its impact on neurocognitive
functioning
35
37. Methods
• Randomly selected 120 HIV+ participants from an NIH-
funded cohort project
• Toxoplasma IgG was measured in serum by commercial
immunoassay
• HNRC neurocognitive test battery was used
– Tests 7 ability areas
• Performance was summarized as the validated global
deficit score (GDS)
– GDS ≥ 0.5 defined neurocognitive impairment
• Data were analyzed by routine statistical methods,
including Pearson’s correlations and linear regression
36
38. Neuropsychological Test Battery
Verbal Fluency Executive Functioning
Sound Category Test
Animals WCST-64
Action Color Trails II
Attn/Working Memory Learning/Memory
PASAT-50 Verbal (Hopkins Verbal Learning
WMS-III Spatial Span Test - Revised)
Processing Speed Visual (Brief Visuospatial
Memory Test - Revised)
WAIS-III Digit Symbol
WAIS-III Symbol Search
Motor
Trails A Grooved Pegboard
Color Trails 1
37
39. Results
• LT was detected in 12 (10%) participants
• LT+ subjects were similar to LT- subjects
except that they were significantly older
• LT+ subjects were more likely to have
neurocognitive impairment (although not
statistically significant)
– This difference was greater among subjects who
were older than the median age of 44 years (60%
vs. 33%, p = 0.11)
38
41. Results
• LT was detected in 12 (10%) participants
• LT+ subjects were similar to LT- subjects except that they
were significantly older
• LT+ subjects were more likely to have neurocognitive
impairment (although not statistically significant)
– This difference was greater among subjects who were older
than the median age of 44 years (60% vs. 33%, p = 0.11)
• Among LT+ subjects, higher IgG titers titers were
associated with
– higher CD4+ T-cell counts (r=0.74, p=0.05, Fig. 1)
– worse GDS (r=0.31, p=0.33, Fig. 2)
– On excluding the 2 outliers, worse GDS (r=0.88, p=0.0007, Fig. 2)
– Higher memory deficit (p=0.01)
40
43. Results
• LT was detected in 12 (10%) participants
• LT+ subjects were similar to LT- subjects except that they
were significantly older
• LT+ subjects were more likely to have neurocognitive
impairment (although not statistically significant)
– This difference was greater among subjects who were older
than the median age of 44 years (60% vs. 33%, p = 0.11)
• Among LT+ subjects, higher IgG titers titers were
associated with
– higher CD4+ T-cell counts (r=0.74, p=0.05, Fig. 1)
– worse GDS (r=0.31, p=0.33, Fig. 2)
– On excluding the 2 outliers, worse GDS (r=0.88, p=0.0007, Fig. 2)
– Higher memory deficit (p=0.01)
42
45. Results
• LT was detected in 12 (10%) participants
• LT+ subjects were similar to LT- subjects except that they
were significantly older
• LT+ subjects were more likely to have neurocognitive
impairment (although not statistically significant)
– This difference was greater among subjects who were older
than the median age of 44 years (60% vs. 33%, p = 0.11)
• Among LT+ subjects, higher IgG titers titers were
associated with
– higher CD4+ T-cell counts (r=0.74, p=0.05, Fig. 1)
– worse GDS (r=0.31, p=0.33, Fig. 2)
– On excluding the 2 outliers, worse GDS (r=0.88, p=0.0007, Fig. 2)
– Higher memory deficit (p=0.01)
44
46. Conclusions
• Prevalence of LT in our HIV+ cohort was 10%
– Similar to the general population (10.8%)
– Not generalizable as our cohort consisted of drug
abusers
• LT+ older subjects trended towards worse
neurocognitive functioning and higher anti-Toxo
IgG titers were associated with worse functioning
• Studies with a larger number of LT+ individuals
are needed to validate this finding
45
47. Future Directions
• Identify a larger HIV and LT co-infected cohort
– Owen clinic and HNRC
• Investigate the impact on driving in more
detail
– Driving simulator studies
• Mechanistic studies
– Role of inflammation: plasma and CSF
– In vitro brain model
46
49. Malaria
• Mosquito-borne infectious disease
• Plasmodium spp.
– P. falciparum, P. vivax
– P. ovale, P. malariae
• 300-500 million episodes of acute illness
• > 1 million deaths/year worldwide
48
51. Malaria and HIV Interactions
• HIV+ patients are twice as likely to get malaria*
• ↑HIV RNA and ↓CD4 counts
• Malaria doubles HIV-1-RNA with 0.25 log ↑**
• HIV RNA ↑ (0.82 log ↑) greatest when
• Febrile patient
• Parasite density >2,000/µL
• CD4 >300/µL
• Mathematical model
• Village of ~200,000 had excess 8,500 HIV infections and
980,000 malaria episodes***
*Patnaik et al J Infect Dis 2005; **Kublin et al Lancet 2005; ***Kublin Science 2006
50
53. Asymptomatic Malaria
• Seen in areas of high transmission
• Also reported in low edemicity regions
• Clinical immunity that controls parasitemia but does
not completely eliminate it
• Described for both P. falciparum & P. vivax malaria
• Few studies on HIV and asymptomatic malaria co-
infections
• Since malaria prevalence is not homogenous, sites
need to be tested individually
52
55. Study Objective
• To retrospectively determine the prevalence
of malaria co-infection in a cohort of HIV-
infected individuals in southern India
54
56. Methods
• Individuals presenting to YRG CARE, Chennai,
India between Jan 1, 2008 and Dec 31, 2008
• Stored serum samples randomly selected from
HIV+ individuals
• Retrospectively diagnosed malaria by antibody
testing and PCR
55
58. Discussion
• Considerable burden of malaria co-infection
• Predominently due to P. vivax
• Rate of P. falciparum 6-fold higher than in the
general population
• Co-infected subjects not more likely to be
immunosupressed than HIV mono-infected
• Negative PCR
– Possibly due to parasitemia below detection limit
– Parasite DNA degradation unlikely
• Our strategy may be used for identifying co-
infections in areas with unstable malaria
transmission
57
59. Future Directions
• Alternate site with high malaria prevalence
– Nigeria
• Use of more suitable specimens
– Whole blood or Dried blood spots
58
61. Acknowledgements
• United States • India
– Scott Letendre – N. Kumarasamy
– Davey Smith – Jabin
– Tom Marcotte
– Ron Ellis • Nigeria
– Connie Benson – Kanayo Okwuasaba
– Chip Schooley – Ndidi Agala
– Igor Grant
– Allen McCutchan
• Funding
– Cris Achim – NIMH 1 K23 MH085512-01A2
– D. J. Perkins – CFAR International Pilot Project Grant
– Walter Royal
• Study participants
60