Prognosis of Children with HIV-1 Infection Starting Antiretroviral Therapy in Southern Africa: A Collaborative Analysis of Treatment Programs

BACKGROUND: Prognostic models for children starting antiretroviral therapy (ART) in Africa are lacking. We developed models to estimate the probability of death during the first year receiving ART in Southern Africa. METHODS: We analyzed data from children ≤10 years old who started ART in Malawi, South Africa, Zambia or Zimbabwe from 2004-2010. Children lost to follow-up or transferred were excluded. The primary outcome was all-cause mortality in the first year of ART. We used Weibull survival models to construct two prognostic models: one with CD4%, age, WHO clinical stage, weight-for-age z-score (WAZ) and anemia and one without CD4%, because it is not routinely measured in many programs. We used multiple imputation to account for missing data. RESULTS: Among 12655 children, 877 (6.9%) died in the first year of ART. 1780 children were lost to follow-up/transferred and excluded from main analyses; 10875 children were included. With the CD4% model probability of death at 1 year ranged from 1.8% (95% CI: 1.5-2.3) in children 5-10 years with CD4% ≥10%, WHO stage I/II, WAZ ≥-2 and without severe anemia to 46.3% (95% CI: 38.2-55.2) in children <1 year with CD4% <5%, stage III/IV, WAZ< -3 and severe anemia. The corresponding range for the model without CD4% was 2.2% (95% CI: 1.8-2.7) to 33.4% (95% CI: 28.2-39.3). Agreement between predicted and observed mortality was good (C-statistics=0.753 and 0.745 for models with and without CD4% respectively). CONCLUSION: These models may be useful to counsel children/caregivers, for program planning and to assess program outcomes after allowing for differences in patient disease severity characteristics.

Multidisciplinary consensus on assessment of unruptured intracranial aneurysms: proposal of an international research group.

BACKGROUND AND PURPOSE To address the increasing need to counsel patients about treatment indications for unruptured intracranial aneurysms (UIA), we endeavored to develop a consensus on assessment of UIAs among a group of specialists from diverse fields involved in research and treatment of UIAs. METHODS After composition of the research group, a Delphi consensus was initiated to identify and rate all features, which may be relevant to assess UIAs and their treatment by using ranking scales and analysis of inter-rater agreement (IRA) for each factor. IRA was categorized as very high, high, moderate, or low. RESULTS Ultimately, 39 specialists from 4 specialties agreed (high or very high IRAs) on the following key factors for or against UIA treatment decisions: (1) patient age, life expectancy, and comorbid diseases; (2) previous subarachnoid hemorrhage from a different aneurysm, family history for UIA or subarachnoid hemorrhage, nicotine use; (3) UIA size, location, and lobulation; (4) UIA growth or de novo formation on serial imaging; (5) clinical symptoms (cranial nerve deficit, mass effect, and thromboembolic events from UIAs); and (6) risk factors for UIA treatment (patient age and life expectancy, UIA size, and estimated risk of treatment). However, IRAs for features rated with low relevance were also generally low, which underlined the existing controversy about the natural history of UIAs. CONCLUSIONS Our results highlight that neurovascular specialists currently consider many features as important when evaluating UIAs but also highlight that the appreciation of natural history of UIAs remains uncertain, even within a group of highly informed individuals.

The unruptured intracranial aneurysm treatment score: a multidisciplinary consensus.

OBJECTIVE We endeavored to develop an unruptured intracranial aneurysm (UIA) treatment score (UIATS) model that includes and quantifies key factors involved in clinical decision-making in the management of UIAs and to assess agreement for this model among specialists in UIA management and research. METHODS An international multidisciplinary (neurosurgery, neuroradiology, neurology, clinical epidemiology) group of 69 specialists was convened to develop and validate the UIATS model using a Delphi consensus. For internal (39 panel members involved in identification of relevant features) and external validation (30 independent external reviewers), 30 selected UIA cases were used to analyze agreement with UIATS management recommendations based on a 5-point Likert scale (5 indicating strong agreement). Interrater agreement (IRA) was assessed with standardized coefficients of dispersion (vr*) (vr* = 0 indicating excellent agreement and vr* = 1 indicating poor agreement). RESULTS The UIATS accounts for 29 key factors in UIA management. Agreement with UIATS (mean Likert scores) was 4.2 (95% confidence interval [CI] 4.1-4.3) per reviewer for both reviewer cohorts; agreement per case was 4.3 (95% CI 4.1-4.4) for panel members and 4.5 (95% CI 4.3-4.6) for external reviewers (p = 0.017). Mean Likert scores were 4.2 (95% CI 4.1-4.3) for interventional reviewers (n = 56) and 4.1 (95% CI 3.9-4.4) for noninterventional reviewers (n = 12) (p = 0.290). Overall IRA (vr*) for both cohorts was 0.026 (95% CI 0.019-0.033). CONCLUSIONS This novel UIA decision guidance study captures an excellent consensus among highly informed individuals on UIA management, irrespective of their underlying specialty. Clinicians can use the UIATS as a comprehensive mechanism for indicating how a large group of specialists might manage an individual patient with a UIA.