Natural history of growth hormone deficiency in a pediatric cohort.

BACKGROUND/AIMS Controversies still exist regarding the evaluation of growth hormone deficiency (GHD) in childhood at the end of growth. The aim of this study was to describe the natural history of GHD in a pediatric cohort. METHODS This is a retrospective study of a cohort of pediatric patients with GHD. Cases of acquired GHD were excluded. Univariate logistic regression was used to identify predictors of GHD persisting into adulthood. RESULTS Among 63 identified patients, 47 (75%) had partial GHD at diagnosis, while 16 (25%) had complete GHD, including 5 with multiple pituitary hormone deficiencies. At final height, 50 patients underwent repeat stimulation testing; 28 (56%) recovered and 22 (44%) remained growth hormone (GH) deficient. Predictors of persisting GHD were: complete GHD at diagnosis (OR 10.1, 95% CI 2.4-42.1), pituitary stalk defect or ectopic pituitary gland on magnetic resonance imaging (OR 6.5, 95% CI 1.1-37.1), greater height gain during GH treatment (OR 1.8, 95% CI 1.0-3.3), and IGF-1 level <-2 standard deviation scores (SDS) following treatment cessation (OR 19.3, 95% CI 3.6-103.1). In the multivariate analysis, only IGF-1 level <-2 SDS (OR 13.3, 95% CI 2.3-77.3) and complete GHD (OR 6.3, 95% CI 1.2-32.8) were associated with the outcome. CONCLUSION At final height, 56% of adolescents with GHD had recovered. Complete GHD at diagnosis, low IGF-1 levels following retesting, and pituitary malformation were strong predictors of persistence of GHD.

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.

A 18-years long (1993-2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 altitude)

A quality-controlled snow and meteorological dataset spanning the period 1 August 1993-31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist of measurements of air temperature, relative humidity, windspeed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow- and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gap-free record. Data relevant to snowpack properties are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information is provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free ''settling'' disks. This dataset has been partially used in the past to assist in developing snowpack models and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (doi:10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.

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.