Predictive value of different body segments to estimate height in a South African adult hospital population

Author(s):  
Hannah Williamson ◽  
Corinna Walsh ◽  
Mariette Nel ◽  
Louise van den Berg
2007 ◽  
Vol &NA; ◽  
pp. S49
Author(s):  
Irena Angelova-Fischer ◽  
Gencho Genchev ◽  
Mary Gantcheva ◽  
Nikolai Tsankov

1987 ◽  
Vol 7 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Ettore Beghi ◽  
Pasquale Simone ◽  
Francesco Apollo ◽  
Pietro Di Viesti ◽  
Maurizio Treviso ◽  
...  

2013 ◽  
Vol 23 (8) ◽  
pp. 415-427 ◽  
Author(s):  
Marelize Swart ◽  
Michelle Skelton ◽  
Yuan Ren ◽  
Peter Smith ◽  
Simbabrashe Takuva ◽  
...  

2019 ◽  
Author(s):  
Peter Raubenheimer ◽  
Cascia Day ◽  
Faried Abdullah ◽  
Katherine Manning ◽  
Clint Cupido ◽  
...  

Abstract Background: Timely 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.Aim: To evaluate the performance of a screening tool (based on the Gold Standards Framework Prognostic Indicator Guidance) to predict death at 12 months in a population of hospitalised patients in South AfricaDesign: Prospective cohort observational study using linkage analysis of hospitalised patients to death certification records.Setting/participants: Patients admitted to the acute medical services in two public hospitals in Cape Town, South AfricaResults: 822 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). Conclusions:The 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.


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