Missing pelvic inflammatory disease? Substantial differences in the rate at which doctors diagnose PID.

OBJECTIVES: The clinical diagnosis of pelvic inflammatory disease (PID) is subjective. Our aim was to determine if the pattern of diagnosis of PID among experienced clinicians varied compared with the diagnosis of genital warts. METHODS: We conducted a retrospective study of 325 PID diagnoses made by experienced clinicians at Melbourne Sexual Health Centre, Australia (2002-2006), where doctors saw 21 785 unselected female patients in a walk-in service. We compared the proportion of female patients diagnosed as having PID and genital warts between doctors and then compared doctors above (high diagnosing) and below (low diagnosing) the mean rate of PID diagnosis. RESULTS: There were significant and clinically important differences in the proportion of women diagnosed with having PID (0-5.7%) across 23 doctors investigated. Estimated standard deviation in the frequency of PID diagnosis (logit scale) was 1.26 (95% CI 0.81 to 1.95)--approximately four times greater than for warts. Patients seen by high (n = 4673) and low (n = 16 787) diagnosing doctors had similar epidemiological risk profiles suggesting true distribution of PID cases across doctors was similar (p>0.13). Women diagnosed with having PID by high diagnosing doctors compared with low diagnosing doctors were younger (odds ratio 1.7; 95% CI 1.1 to 2.8, p = 0.013) but otherwise had similar epidemiological and clinical features. CONCLUSIONS: Differences in diagnostic rates for PID between doctors are substantial and may be because of PID cases being missed by some doctors.

Cohort analysis of two multidisciplined adherence intervention programmes for patients on antiretroviral therapy.

The aim was to analyse data from two randomized controlled trials (RCTs) to determine if an adherence intervention programme for antiretroviral therapy (ART) resulted in a reduction in viral load. A cohort analysis of pre- and post-intervention viral loads and CD4 counts using paired analysis was undertaken on participants who received the intervention programme. Analysis was also undertaken on a control group. The intervention participants had an increase in mean CD4 count (450-478, P = 0.26), and a decline in log viral load (2.48-2.36, P = 0.056). The control group had a decline in mean CD4 counts (596-570, P = 0.53), and an increase in log viral load (2.09-2.11, P = 0.78). The use of an adherence intervention programme is associated with a decrease in mean viral load, which is in contrast to the control group that demonstrated an increase in viral load over time.

Predictors for non-adherence to antiretroviral therapy.

OBJECTIVES: To determine the risk factors for non-adherence to antiretroviral therapy. METHODS: Two hundred clients attending the Melbourne Sexual Health Centre completed a questionnaire about lifestyle, self-efficacy, depression, drug or alcohol use, social supports, and attitudes to health care. Self-reported adherence (SRA) was measured by missed doses in the last 4, 7 and 28 days. Routinely collected viral load levels were reviewed. RESULTS: Two hundred (85%) out of 231 eligible clients participated in the study. Viral load was most strongly associated with SRA for the last 28 days (P < 0.001). Non-adherence was defined as <98.2% SRA. Non-adherence was most strongly associated with having regular daily routines [odds ratio and 95% confidence interval = 0.4 (0.2, 0.7)], having set times for getting up and going to bed [0.5 (0.3, 1.0)], using marijuana more than 4 times per week [0.4 (0.2, 1.0)] and lower self-efficacy which included; being sure that you will be able to take medications as directed [0.2 (0.1, 0.6)] and being sure that missing doses of HIV medication will result in drug resistance [0.4 (0.2, 0.7)]. When significant questions were combined into a composite score to screen for non-adherence, the sensitivity to predict non-adherence was as high as 71% with a specificity of 59%. CONCLUSIONS: This study showed that a 10-min questionnaire was associated with clients past non-adherence to antiretroviral therapy and may be useful for predicting future adherence.