Step count is associated with adverse health outcomes in HIV patients better

than traditional HIV variables

Malagoli A, Caselgrandi A, Pacchioni M, Orsini M, Carli F, Menozzi M, Zona S, Santoro A, Theou O,

Wallace L, Mussini C, Martinez E, Block M,

Guaraldi G

Background: the end of the (HIV) disease era

“...The time has come to abandon disease as the primary focus of medical care. [...] The changed spectrum of health conditions, the complex interplay of biological and non-biological factors, the aging population, and the inter-individual variability in health priorities render medical care that is centered primarily on the diagnosis and treatment of individual diseases at best out-of-date and at worst harmful...”

Tinetti ME, Fried T. . Am J Med 2004;116:179–85.

Guaraldi G, Rockwood K. CID 2017;65(3):507-509;

HIV disease is not an exception but rather a paradigm if this new

healthcare era. The traditional pattern of stand-alone disease

medicine, has become out-of-date. It is time to reshape our obsolete

health care systems, still based on the anachronistic criterion of

“age” to define a person as “old”.

Background: Internet of Medical Things (IoMT) is the future of healthcare

IoMT Framework

• Big data management

• Real time collection variables

• Integration of physiological parameters and patient related outcomes (ePRO)

IoMT for better elder care

1. Vitals-Tracking

Wearables

2. Medication Adherence

Tools

3. Virtual Home Assistants

4. Portable Diagnostics

Devices

5. Personal Emergency

Response Systems

6. Disability Assistance

Tools

7. Smart Implants

8. Smart Senior Homes

9. Family Caregiver

Remote Monitoring

Tools

10.…

My Smart Age with HIV: an innovative mobile and Internet of Medical things IoMT framework for patient’s empowerment

Modena

Sydney

Barcelona

Hong Kong

Demographic

Anthropometric

HIV history (Successful HIV)

Comorbidity, MM (>3 CoM)

Frailty (37 item-FI)

Disability (IADL)

Physical function (hand grip, SPPB)

Cognitive function (Cogstate, CESD)

Quality of life (QoL - EQ-5D5L)

My Smart Age with HIV: an innovative mobile and Internet of Medical things IoMT framework for patient’s empowerment

Steps

Calories

Sleep

ePRO

SHARE questionnaire: Working, Interpersonal Relationship and conflicts

Life satisfaction, leisure activities social & spiritual support ….

• MYSAWH App ollects about

2.000 ePRO answers per week

with 17 answers per patient

per week

• Patients respond promptly to

the questionnaire:

→ 95\% of patients

answered within 24 hours;

→ 85\% of patients

answered within 12 hours;

→ 56\% of patients

answered within 3 hours.

MYSmartAWHiv: building up a HEALTH INDEX to improve Awareness in PLWHIV aged >50 years

My Smart Age with HIV: an innovative mobile and Internet of Medical thingsIoMT framework for patient’s empowerment

My Smart Age with HIV: Smartphone self-assessment of

frailty and information - communication technology

(ICT) to promote healthy ageing in HIV.

T 0 T 18mts

HEALTH INDEX: Measure of

Wellness

Health Index integrate PRO

and physiological parameters

1. Avoiding disease and disability Multimorbidity, Frailty, Disability

2. Having high cognitive/mental/physical function

Cognitive impairment, Depression

3. Actively engaging in life Working/ interpersonal relationship

4. Psychologically well adapted in later life

Life satisfaction, leisure activities, social & spiritual support

T 9mtsSuccessful

Aging

FRAILTY INDEX : Measure of

disease vulnerability

Frailty Index integrate physical

function and biological

parameters

Several studies found the discrepancybetween the successful ageing definition asoperationalized by researchers and according to perception of older people.

Objectve

to describe physical activity in people with HIV who used MYSAWH-app and to examine whether step count predicted adverse health outcomes.

Material and methods

Consecutive HIV patients aged>50 years were enrolled

from October 2016 to June 2017

Step count was evaluated in the first 60 days after study

entry.

Daily steps were collected by Garmin Vivofit2 wearable

device, a waterproof fitness tracker worn on the wrist 24

hours/day.

Definitions:

Walkers: +1 SD Not-walkers: -1 SD

of the median daily step of

the cohort in the past 60

days

Exclusion criteria: internet illiteracy

During the enrollment period, from October 2016 to June 2017,

175 patients were offered to participate in MySAwH protocol.

114 (70.6%) patients were enrolled. 5 patients refused due to unwillingness or fear of HIV status disclosure to family

members.

50(29.4%) patients were excluded being internet illiterate.

Social-demographic and clinical characteristics of the latter group

were compared to patients actively enrolled in the study

Multivariate analysis for

internet illiteracy

Almost 30%, of HIV patients >50 years are internet illiterate.

Predictors of internet illiteracy were socio-demographic variables,

but not HIV variables. Poor education, increasing age, single status

are significant predictor of internet illiteracy

Results: Demographic, anthropometric and HIV variables

totalNot-Walkers<6600 steps

Walkers6600-14000

Super-Walkers>14000 steps p

steps.devst.1sd 11416(14.04%)

78(68.42%)

20(17.54%)

Male gender90 (78.95%)

14 (87.5%)

59 (75.64%)

17 (85%) 0.43

Age56.66 (5.58)

60.79 (8.14)

56.08 (5.02)

55.63 (3.75) 0.09

Waist crf (cm)92.07 (10.29)

91.75 (14.83)

92.43 (9.76)

90.9 (9.51) 0.83

BMI24.39 (22.37-27.03)

24.5 (21.87-26.87)

24.45 (22.36-26.86)

24.13 (22.77-27.18) 0.92

ASMI6.78 (1.45)

6.71 (1.01)

6.73 (1.36)

7.01 (2) 0.29

Hand grip (Kg)38.92 (28.17-45.7)

32.77 (21.42-45.77)

39.03 (29.5-45.65)

42.55 (36.24-44.91) 0.10

CD4 nadir 180 (81-300)

150 (50.5-226.5)

195 (97-303)

169 (83-356) 0.34

CD4 current690.5 (521.75-878.75)

538 (386.5-759.5)

716.5 (556.5-865.25)

711 (535.5-960.5) 0.10

CD4/CD8 ratio

0.91

(0.47)

0.73

(0.33)

0.93

(0.46)

1

(0.56) 0.09

HIV VL <40 c/mL 112 (98.25%) 15 (93.75%) 78 (100%) 19 (95%) 0.10

Results: comorbidity paramethers

Are these association expression of reverse causation?

totalNot-Walkers<6600 steps

Walkers6600-14000

Super-Walkers>14000 steps p

N° 114 16(14.04%) 78(68.42%) 20(17.54%)

Hypertension 59 (51.75%) 11 (68.75%) 43 (55.13%) 5 (25%) 0.01

T2DM 21 (18.42%) 5 (31.25%) 14 (17.95%) 2 (10%) 0.25

CVD 9 (7.89%) 3 (18.75%) 4 (5.13%) 2 (10%) 0.17

Osteoporosis 32 (28.07%) 10 (62.5%) 17 (21.79%) 5 (25%) <0.01

Cancers 1 (0.88%) 1 (6.25%) 0 (0%) 0 (0%) 0.04

Liver cirrhosis 11 (9.65%) 2 (12.5%) 6 (7.69%) 3 (15%) 0.56

COPD 7 (6.14%) 3 (18.75%) 3 (3.85%) 1 (5%) 0.07

Multimorbidity 19 (16.67%) 9 (56.25%) 10 (12.82%) 0 (0%) <0.01

Frailty

phenotype 5 (4.39%) 1 (6.25%) 1 (1.28%) 3 (15%) <0.01

Frailty index 0.28 (0.1) 0.38 (0.12) 0.27 (0.09) 0.25 (0.11) <0.01

waek handgrip 34 (29.82%) 9 (56.25%) 22 (28.21%) 3 (15%) 0.02

CESD score 13 (7-20) 15 (11.75-26.25) 13.5 (7-19.75) 9 (4-18.5) 0.12

GDS impairment

(Cogstate) 23 (20.18%) 6 (37.5%) 11 (14.1%) 6 (30%) 0.05

IADL 1 (1-1) 1 (0.94-1) 1 (1-1) 1 (1-1) <0.01

Results: Logistic regression analyses for prediction of MM

Results: Logistic regression analyses for prediction of Frailty

phenotype

Results: relatioship between frailty index and daily steps

Fit Pre-Frail Frail Most Frail

Results: Logistic regression analyses for prediction of Frailty by

mean of Frailty Index pre-specified cut-off

Results: Logistic regression analyses for prediction of disability

Take home message

1. Physical activity wearable device are easy to use tools capable to record health predictors in real life setting.

2. Steps but not traditional HIV variables were associated with health outcomes

3. This study suggests the need to include physical function measure variables in the monitoring of HIV patients

4. Patient and healthcare team are partner of the multidimensional assessment which define new health outcomes

A real anecdote from the clinical trial… Hei Doctor.

I hate your study!

Any time I make sex with my

partner he checks how many

calories he has spent!

Feasibility and Long Term Assessment of Physical and Behavioral

Functioning Among Older Adults with HIV

The objective of this study was to describe feasibility and long term assessment

of physical and daily functioning through mobile devices in HIV patients aged≥50 years.

This interim analysis assessed physical and behavioral functioning data of 106

HIV-infected patients enrolled in the first 6 month of MySAwH study.

Linear mixed effect model showed a significant improvement of Physical function

variables (table) but no significant change in behavioral function data.

DiscussionLong term assessment of physical and behavioral functioning via smartphones is a

feasible and acceptable data collection method.

Fitness tracker use can empower older HIV patients in promoting healthy physical

activity.

Malagoli A. To be presented at Comorbidity Meeting, Milan 2017