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.

Polypharmacy and specific comorbidities in university primary care settings.

AIMS Polypharmacy is associated with adverse events and multimorbidity, but data are limited on its association with specific comorbidities in primary care settings. We measured the prevalence of polypharmacy and inappropriate prescribing, and assessed the association of polypharmacy with specific comorbidities. METHODS We did a cross-sectional analysis of 1002 patients aged 50-80years followed in Swiss university primary care settings. We defined polypharmacy as ≥5 long-term prescribed drugs and multimorbidity as ≥2 comorbidities. We used logistic mixed-effects regression to assess the association of polypharmacy with the number of comorbidities, multimorbidity, specific sets of comorbidities, potentially inappropriate prescribing (PIP) and potential prescribing omission (PPO). We used multilevel mixed-effects Poisson regression to assess the association of the number of drugs with the same parameters. RESULTS Patients (mean age 63.5years, 67.5% ≥2 comorbidities, 37.0% ≥5 drugs) had a mean of 3.9 (range 0-17) drugs. Age, BMI, multimorbidity, hypertension, diabetes mellitus, chronic kidney disease, and cardiovascular diseases were independently associated with polypharmacy. The association was particularly strong for hypertension (OR 8.49, 95%CI 5.25-13.73), multimorbidity (OR 6.14, 95%CI 4.16-9.08), and oldest age (75-80years: OR 4.73, 95%CI 2.46-9.10 vs.50-54years). The prevalence of PPO was 32.2% and PIP was more frequent among participants with polypharmacy (9.3% vs. 3.2%, p<0.006). CONCLUSIONS Polypharmacy is common in university primary care settings, is strongly associated with hypertension, diabetes mellitus, chronic kidney disease and cardiovascular diseases, and increases potentially inappropriate prescribing. Multimorbid patients should be included in further trials for developing adapted guidelines and avoiding inappropriate prescribing.

The essential role of radiotherapy in the treatment of Merkel cell carcinoma: a study from the Rare Cancer Network

To evaluate the role of postoperative radiotherapy (RT) in Merkel cell carcinoma (MCC).