Survey of the capacity for essential surgery and anaesthesia services in Papua New Guinea.

OBJECTIVE: To assess capacity to provide essential surgical services including emergency, obstetric and anaesthesia care in Papua New Guinea (PNG) in order to support planning for relevant post-2015 sustainable development goals for PNG. DESIGN: Cross-sectional survey. SETTING: Hospitals and health facilities in PNG. PARTICIPANTS: 21 facilities including 3 national/provincial hospitals, 11 district/rural hospitals, and 7 health centres. OUTCOME MEASURES: The WHO Situational Analysis Tool to Assess Emergency and Essential Surgical Care (WHO-SAT) was used to measure each participating facility's capacity to deliver essential surgery and anaesthesia services, including 108 items related to relevant infrastructure, human resources, interventions and equipment. RESULTS: While major surgical procedures were provided at each hospital, fewer than 30% had uninterrupted access to oxygen, and 57% had uninterrupted access to resuscitation bag and mask. Most hospitals reported capacity to provide general anaesthesia, though few hospitals reported having at least one certified surgeon, obstetrician and anaesthesiologist. Access to anaesthetic machines, pulse oximetry and blood bank was severely limited. Many non-hospital health centres providing basic surgical procedures, but almost none had uninterrupted access to electricity, running water, oxygen and basic supplies for resuscitation, airway management and obstetric services. CONCLUSIONS: Capacity for essential surgery and anaesthesia services is severely limited in PNG due to shortfalls in physical infrastructure, human resources, and basic equipment and supplies. Achieving post-2015 sustainable development goals, including universal healthcare, will require significant investment in surgery and anaesthesia capacity in PNG.

Risk and prognostic significance of tuberculosis in patients from The TREAT Asia HIV Observational Database.

BACKGROUND: To assess the risk and the prognostic significance of tuberculosis (TB) diagnosis in patients from The TREAT Asia HIV Observational Database, a multi-centre prospective cohort of HIV-infected patients receiving HIV care in the Asia-Pacific region. METHODS: The risk of TB diagnosis after recruitment was assessed in patients with prospective follow-up. TB diagnosis was fitted as a time-dependent variable in assessing overall survival. RESULTS: At baseline, 22% of patients were diagnosed with TB. TB incidence was 1.98 per 100 person-years during follow up, with predictors including younger age, lower recent CD4 count, duration of antiretroviral treatment, and living in high TB burden countries. Among 3279 patients during 6968 person-years, 142 died (2.04 per 100 person-years). Compared to patients with CDC category A or B illness only, mortality was marginally higher in patients with single Non-TB AIDS defining illness (ADI), or TB only (adjusted HR 1.35, p = 0.173) and highest in patients with multiple non-TB AIDS or both TB and other ADI (adjusted HR 2.21, p < 0.001). CONCLUSION: The risk of TB diagnosis was associated with increasing immunodeficiency and partly reduced by antiretroviral treatment. The prognosis of developing TB appeared to be similar to that following a diagnosis of other non-TB ADI.

Short-term clinical disease progression in HIV-infected patients receiving combination antiretroviral therapy: results from the TREAT Asia HIV observational database.

OBJECTIVE: The aim of our study was to develop, on the basis of simple clinical data, predictive short-term risk equations for AIDS or death in Asian patients infected with human immunodeficiency virus (HIV) who were included in the TREAT Asia HIV Observational Database. METHODS: Inclusion criteria were highly active antiretroviral therapy initiation and completion of required laboratory tests. Predictors of short-term AIDS or death were assessed using Poisson regression. Three different models were developed: a clinical model, a CD4 cell count model, and a CD4 cell count and HIV RNA level model. We separated patients into low-risk, high-risk, and very high-risk groups according to the key risk factors identified. RESULTS: In the clinical model, patients with severe anemia or a body mass index (BMI; calculated as the weight in kilograms divided by the square of the height in meters)