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Table 5 Predictive factors of mortality (Cox regression analysis)

From: Clinical characteristics and outcome of HIV infected patients with chronic kidney disease in Sub Saharan Africa: an example from Cameroon

Variable

Basic models

Final models

HRa (95% CIb)

p

HRa (95% CIb)

p

Age (per years increase)

0.99 (0.96–1.02)

0.452

1.00 (0.97–1.02)

0.742

Gender (female vs male)

1.02 (0.55–1.89)

0.963

1.15 (0.61–2.16)

0.663

Unemployed

1.37 (0.68–2.73)

0.380

  

Hypertension

1.58 (0.84–2.96)

0.156

  

Diabetes

0.56 (0.23–1.40)

0.216

  

Hepatitis B

0.61 (0.08–4.53)

0.632

  

Hepatitis C

1.43 (0.58–3.55)

0.442

  

On cARTc

0.45 (0.23–0.89)

0.021

0.45 (0.23–0.89)

0.021

CD4 count (cells/mm3)

1.00 (0.99–1.00)

0.823

  

Stage of CKD at arrival

 G3

1 (reference)

   

 G4

0.45 (0.10–2.03)

0.299

  

 G5

1.16 (0.42–3.17)

0.780

  

Hemoglobin level (per g/dl)

0.91 (0.79–1.05)

0.201

  

Calcium level (per 10 mg/l)

0.81 (0.59–1.10)

0.178

  

Creatinine level (per 10 mg/l)

1.01 (0.97–1.05)

0.606

  
  1. Basic models are adjusted for age and sex; final models are adjusted for age, sex and all predictors with a p value < 0.1 in the basic models (use of cART)
  2. Values in italics are significant (p value< 0.05)
  3. aHR Hazard ratio, bCI Confidence interval, ccART Combined anti-retroviral treatment
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