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. Author manuscript; available in PMC: 2016 Jan 15.
Published in final edited form as: AIDS. 2015 Dec;29(0 3):S221–S230. doi: 10.1097/QAD.0000000000000924

Table 3.

Modelling of characteristics associated with acute HIV infection (AHI) in the pooled dataset.

Predictor Unadjusted
POR (95% CI)
Domain-specific
model adjusted
POR (95% CI)a
Combined model
adjusted POR
(95% CI)b
Final model
adjusted POR
(95% CI)c
Beta
coefficientd
Scoree
Socio-demographic
  Age (18–29 years) 2.2 (1.5–3.2) 2.1 (1.4–3.0) 2.1 (1.4–3.0) 0.7 1
  Site
  Kilifi, Kenya Ref Ref Ref
  Mombasa, Kenya 0.8 (0.5–1.4) 1.7 (0.3–8.9) 1.7 (0.3–8.9)
  Lilongwe, Malawi 5.8 (2.9–11.6) 2.0 (0.8–4.7) 2.0 (0.8–4.7)
  Durban, South Africa 0.8 (0.4–1.7) 2.9 (0.5–16.5) 2.9 (0.5–16.5)
  Sex 1.7 (1.1–2.6) 1.1 (0.2–5.4) 1.1 (0.2–5.4)
Symptoms at evaluation visit

  Fever 5.7 (4.0–8.1) 1.9 (1.1–3.2) 2.2(1.4–3.5) 2.2(1.4–3.5) 0.8 1
  Diarrhoea 4.7 (2.9–7.8) 1.4 (0.8–2.4) 1.8 (1.1–2.9)e 1.8 (1.1–2.9) 0.6 1
  Fatigue 7.5 (5.2–10.8) 2.7 (1.6–4.8) 2.6 (1.6–4.2) 2.6 (1.6–4.2) 0.9 1
  Head ache 3.9 (2.8–5.6) 1.2 (0.7–2.1)
  Body pains 6.8 (4.7–9.7) 1.8 (1.1–2.9) 2.3 (1.5–3.4) 2.3 (1.5–3.4) 0.8 1
  Rash 3.7 (1.8–7.6) 1.5 (0.6–3.3)
  Sore throat 5.0 (3.2–7.9) 1.5 (0.9–2.6) 1.7 (1.0–2.8) 1.7 (1.0–2.8) 0.5 1

Signs at evaluation visit

  Rash 3.7 (1.8–7.6) 0.7 (0.6–3.3)
  Any palpable lymph nodes 6.8 (3.7–12.7) 1.1 (0.6–2.1)
  Genital ulcer 20.0 (12.9–31.1) 19.8 (12.5–31.3) 14.9 (8.6–26.0) 14.9 (8.6–26.0) 2.7 3

CI, confidence intervals; POR, prevalence odds ratio.

a

Factors associated with AHI at P ≤ 0.15 were included in two separate multivariable models for two domains: ‘symptoms’ and ‘signs’ findings. Each model is presented in this column, with a box indicating the results for each model.

b

Factors associated with AHI at P ≤ 0.15 in the initial domain-specific models were included in a combined model.

c

All variables in the final model, with the exception of sex or site, were associated with acute HIV infection at P ≤ 0.05.

d

Natural log of the adjusted prevalence odds ratio of the final model.

e

Predictor score is equal to its beta coefficient (natural log of the adjusted prevalence odds ratio) from the final generalized estimating equation model, rounded to the nearest integer.