The prevalence of delirium in acute medical inpatients is high, with estimates ranging from 10% to 31%. [1] Short-and long-term complications of delirium include increased mortality and length of hospitalisation, post-discharge institutionalisation, and long-term functional and cognitive decline. [2] This is a considerable healthcare burden: in developed countries the cost of delirium is equal to that of falls and diabetes mellitus. [3] A number of risk factors for delirium have been identified, including predisposing factors such as dementia and advancing age and acute precipitating factors such as drugs, infections and metabolic abnormalities. [2] Protective factors include a higher level of education, a marker of cognitive reserve. [4] Unfortunately, the data on delirium outcomes and risk factors in general medical inpatients are derived almost exclusively from geriatric populations in developed countries, a very different population to acute medical admissions in developing country settings with a high HIV/tuberculosis (TB) burden. [5] Furthermore, the few studies from developing country settings such as sub-Saharan Africa (SSA) have either been conducted in medical patients aged >60 years or in specialised populations, such as psychiatric and intensive care settings. [6][7][8] In developed countries such as the USA, studies were done among HIV-infected populations before universal access to combination antiretroviral therapy (ART). [9][10][11][12][13][14] HIV targets the central nervous system (CNS) with resultant neurocognitive impairment (NCI), a well-described predisposing risk factor for delirium. Acute and opportunistic infections (OIs), also known risk factors for delirium, occur more commonly with advancing immunosuppression. It is therefore unsurprising that studies have shown high prevalence rates of delirium (3.7 -57%) in HIV-infected populations. [6,[11][12][13] Delirium in HIV is often concomitant with NCI, in 8 -22% of cases. [15] Combination ART both prevents and improves NCI and decreases the incidences of acute and OIs. Widespread access to ART may therefore mitigate delirium risk. It is unclear whether HIV infection remains an independent risk factor for delirium in acute medical admissions in endemic HIV settings with universal ART programmes. [9] Furthermore, in developing country settings such as South Africa (SA), with high This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

BackgroundTimely identification of people who are at risk of dying is an important first component of end-of-life care. Clinicians often fail to identify such patients, thus trigger tools have been developed to assist in this process. We aimed to evaluate the performance of a identification tool (based on the Gold Standards Framework Prognostic Indicator Guidance) to predict death at 12 months in a population of hospitalised patients in South Africa.MethodsPatients admitted to the acute medical services in two public hospitals in Cape Town, South Africa were enrolled in a prospective observational study. Demographic data were collected from patients and patient notes. Patients were assessed within two days of admission by two trained clinicians who were not the primary care givers, using the identification tool. Outcome mortality data were obtained from patient folders, the hospital electronic patient management system and the Western Cape Provincial death registry which links a unique patient identification number with national death certificate records and system wide electronic records.Results822 patients (median age of 52 years), admitted with a variety of medical conditions were assessed during their admission. 22% of the cohort were HIV-infected. 218 patients were identified using the screening tool as being in the last year of their lives. Mortality in this group was 56% at 12 months, compared with 7% for those not meeting any criteria. The specific indicator component of the tool performed best in predicting death in both HIV-infected and HIV-uninfected patients, with a sensitivity of 74% (68–81%), specificity of 85% (83–88%), a positive predictive value of 56% (49–63%) and a negative predictive value of 93% (91–95%). The hazard ratio of 12-month mortality for those identified vs not was 11.52 (7.87–16.9, p < 0.001).ConclusionsThe identification tool is suitable for use in hospitals in low-middle income country setting that have both a high communicable and non-communicable disease burden amongst young patients, the majority under age 60.