IMPACT OF LEAN AND BONE MASS ON

GLOMERULAR FILTRATION RATE ESTIMATION IN PEOPLE LIVING WITH HIV/AIDS

Corinne Isnard Bagnis

and Laurence Pieroni, Rachida Inaoui, Philippe Maksud,

Stéphanie Lallauret, Marc-Antoine Valantin, Roland Tubiana, Christine Katlama, Gilbert Deray, Marie Courbebaisse, JérômeTourret and Sophie Tezenas du Montcel

Corinne.bagnis@aphp.fr Pitié Salpetrière Hospital, Paris, France

BACKGROUND AND AIM OF THE STUDY

5 to 8% patients living with HIV/AIDS (PLWHA) exhibit Chronic

kidney disease (stage 3 : GFR below 30/ml/min/1.73m 2)

The optimal way to estimate GFR in PLWHA patients is not

known although MDRD and CKD EPI formulae are validated in

general population

Moreover, the impact of muscle mass on creatinine blood

level and therefore on GFR estimation is unknown in these

patients

2

2

METHODS

• 44 HIV-1 patients were included in a transversal monocentric comparative

study evaluating the accuracy of the different diagnostic tests available

compared to the gold standard measurement of GFR

• Adult, male, caucasian patients with an estimated GFR between 60 and 30

ml/min/1.73 m2 were included. Serum creatinine and cystatin C were

measured

• GFR was estimated using Cockcroft, MDRD, aMDRD, CKD EPI, CKD EPIcyst,

CKD EPIcyst/creat formulae, and measured using isotopic Chrome51 EDTA

clearance

• Bone and muscle mass were measured by DEXA scan (dual Xray

absorbtiometry)

3

Table 1A: Demographic data and treatment details at inclusion

Mean

or frequency

SD or %

Age 62 (10)

Age >50 (n=44) 36 (82%)

Delay since HIV infection diagnosis (years) (n=43) 19 (7)

Diabetes mellitus 13 (30%)

Hypertension (n=36) 17 (47%)

HAART (Highly active antiretroviral therapy) 42 (95%)

Tenofovir 20 (45%)

Atazanavir 15 (34%)

CD4 count (cells/mm3) (n=38) 446 (191)

CD4 count (cells/mm3) < 350 (n=38) 13 (34%)

Viral load (n=40)

≤40

among which ≤20

36 (90%)

28 (70%)

72 1 (2.5%)

120 1 (2.5%)

160 1 (2.5%)

56 402 1 (2.5%)

VHB infection 10 (23%)

VHC infection 4 (9%)

VHC VHB co infection 1 (2%)

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Table 1B: Biological data (mGFR: measured glomerular filtration rate)

Normal values Mean or frequency

SD or % mGFR (ml/min/1.73m2) 63.4 (16.5)

Blood

Enzymatic plasma creatinine (µmol/L) According to age and sex 139.9 (51.5)

Urea (mmol/L) According to age and sex 8.8 (3.1)

Albumin (g/L) 37-48 44.4 (3.7)

CRP (mg/L) < 5 7.1 (8.1)

CRP>10 mg/L 6 (14%)

Cystatin C (mg/L) < 1.2 1.6 (0.5)

Urines

Creatinine (mmol/L) ND 9.0 (5.2)

Cystatine C (mg/L) ND 1.0 (4.7) Proteinuria (g/L) <0.10 0.5 (0.7)

WHICH FORMULAE PERFORMS BEST ?

• Mean measured isotopic GFR was 63.4±13.5 ml/min/1.73m2

• All formulae under-estimated GFR

• Best performance was provided by CKD EPI with

• the best accuracy 30%

• a good precision

• a low bias

• and highest correlation coefficient

• CKD EPI Cyst and CKD EPI Cyst/creat performed worse than the

CKD EPI and sMDRD formula

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BODY COMPOSITION (BMI = BODY MASS

INDEX, BMC = BONE MINERAL CONTENT) 7

8BODY COMPOSITION (BMI = BODY MASS INDEX, BMC = BONE MINERAL CONTENT)

Patients characteristics

and GFR estimation

according to lean mass

(All GFR expressed as

ml/min/1.73m²)

Median (IQR) or frequency (%) in each lean mass category: N (%)

<70% (n=10)

70-85% (n=28)

>85% (n=6)

p-value†

Lean Mass 57961 (52716-60841)

55052 (47658-58638)

51475 (44325-61990)

-

Serum Creatinine (enzymatic)

124 (118-143) 127 (119-154) 121 (114-131) 0.7425

Age>50 years 9 (90%) 23 (82%) 4 (67%) 0.6271

Weight (kg) 86 (79-94) 70 (61-73) 59 (51-72) 0.0024

BMI (kg/m2) 30 (25-31) 23 (21-24) 21 (18-21) 0.0005

BMI > 25 kg/m2 6 (60%) 5 (18%) 0 0.0132

Low T-score (<-1) 1 (10%) 19 (68%) 5 (83%) 0.0017

Delay since HIV diagnosis

years

19 (16-20) 22 (16-24) 21 (18-23)

0.4588

CD4 < 350/mm3 3 (33%) 8 (35%) 2 (33%) 1

Tenofovir 2 (20%) 14 (50%) 4 (67%) 0.1637

Atazanavir 3 (30%) 11 (39%) 1 (17%) 0.6586

GFR measured 57 (53-72) 66 (53.5-70.5) 64.5 (50-74) 0.8653

Cockcroft Enzymatic 68 (53-75) 53 (40-58.5) 58 (34-59) 0.0488

Cockcroft Enzymatic/SC 81 (56-87) 54 (39.5-64) 55.2 (32-65) 0.0310

MDRD Enzymatic 51 (43- 54) 50.5 (39.5-54) 53.5 (48-59) 0.6856

CKD EPI 51.5 (44-57) 51.5 (40-56.5) 57 (49-65) 0.5805

CKD EPI-Cyst 46.5 (39-55) 50 (33.5-56) 51.5 (32-60) 0.9462

CKD EPI-creat-cyst 50 (42-54) 51.5 (33-58) 54 (40-64) 0.8605

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GFR ESTIMATION ACCORDING TO LEAN MASS

Patients with higher weights

and BMI had lower lean mass

values and lower T scores

GFR estimation according to bone mineralization (All GFR expressed as ml/min/1.73m²)

N (Median (IQR) or N(%) in each T-score category

< -1 (n=25)

³ -1 (n=19)

p-value †

Age>50 years 20 (80%) 16 (84%) 1

Weight (kg) 68 (57-72) 79 (70-90) 0.0012

BMI (kg/m2) 21 (21-23) 25 (22-30) 0.0010

BMI > 25 kg/m2 2 (8%) 9 (47%) 0.0045

Measured GFR 66 (53-71) 59 (53-72) 0.8682

Delay since HIV diagnosis (years) 20 (14-24) 20 (17-23) 0.9608

Cd4 count < 350/mm3 7 (33%) 6 (35%) 1

Tenofovir 11 (44%) 9 (47%) 1

Atazanavir 11 (44%) 4 (21%) 0.1985

Cockcroft Enzymatic 52 (35-59) 60 (51-73) 0.0380

Cockcroft Enzymatic/body

surface area 49 (37.5-61) 68 (50-84) 0.0310

MDRD Enzymatic 50 (47-54) 51 (41-55) 0.8309

CKD EPI 52 (48-60) 54 (44-57) 0.8775

CKD EPI-Cyst 48 (35-53) 51 (36-60) 0.3933

CKD EPI-Combined 49 (40-60) 52 (39-59) 0.6019

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Only weight and BMI

influenced T-scores

values

DISCUSSION

Our study is underpowered because of an inferior number

of included patients (n=44) than what was estimated

(n=60)

Our study does not allow to draw any conclusions for

women or patients from African descent because, due to

expected number of patients to include, we deliberately

chose to restrain our study to Caucasian men

Normal muscle mass in the HIV population is not known

We used dexa scan to measure lean mass but few studies

document the best method

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MAIN MESSAGES

• All formulae under-estimated GFR

• Best performance was provided by CKD EPI with the best accuracy 30%, a

good precision, a low bias and highest correlation coefficient

• Cockcroft formula estimated GFR was significantly correlated with lean mass

values and bone mineralization (T-scores)

• Cockcroft bias was significantly lower in patients with low bone mineralization than in

the other two groups, indicating less over estimation of GFR

• No significant difference was observed using other estimations based on lean

mass or T-score categorization

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• 16 out of 44 patients exhibited abnormal muscular mass (< 70%)

• had the lower values for T-score (often below -1)

• had higher BMI and measured weights

• Using total body BMD T score, 24 patients (56%) exhibited values below -

1 SD

• Low bone mass (estimated by T-scores below 1 SD) was significantly correlated

to increased lean mass

• No other factor than BMI impacted significantly on T-scores

• The different treatment received (vitamin D, calcium, bisphosphonates) had no

significant impact on bone mass

• In our study, tenofovir did not exhibit any significant effect on lean mass nor

bone mass but significantly influenced absolute bias (p<0.05)

MAIN MESSAGES13