External validation of prognostic models predicting outcome after chronic subdural hematoma

Background: Several prognostic models for outcomes after chronic subdural hematoma (CSDH) treatment have been published in recent years. However, these models are not sufficiently validated for use in daily clinical practice. We aimed to assess the performance of existing prediction models for outcomes in patients diagnosed with CSDH. Methods: We systematically searched relevant literature databases up to February 2021 to identify prognostic models for outcome prediction in patients diagnosed with CSDH. For the external validation of prognostic models, we used a retrospective database, containing data of 2384 patients from three Dutch regions. Prognostic models were included if they predicted either mortality, hematoma recurrence, functional outcome, or quality of life. Models were excluded when predictors were absent in our database or available for < 150 patients in our database. We assessed calibration, and discrimination (quantified by the concordance index C) of the included prognostic models in our retrospective database. Results: We identified 1680 original publications of which 1656 were excluded based on title or abstract, mostly because they did not concern CSDH or did not define a prognostic model. Out of 18 identified models, three could be externally validated in our retrospective database: a model for 30-day mortality in 1656 patients, a model for 2 months, and another for 3-month hematoma recurrence both in 1733 patients. The models overestimated the proportion of patients with these outcomes by 11% (15% predicted vs. 4% observed), 1% (10% vs. 9%), and 2% (11% vs. 9%), respectively. Their discriminative ability was poor to modest (C of 0.70 [0.63–0.77]; 0.46 [0.35–0.56]; 0.59 [0.51–0.66], respectively). Conclusions: None of the examined models showed good predictive performance for outcomes after CSDH treatment in our dataset. This study confirms the difficulty in predicting outcomes after CSDH and emphasizes the heterogeneity of CSDH patients. The importance of developing high-quality models by using unified predictors and relevant outcome measures and appropriate modeling strategies is warranted

Modelling the impact of toxic and disturbance stress on white-tailed eagle (Haliaeetus albicilla) populations

Several studies have related breeding success and survival of sea eagles to toxic or non-toxic stress separately. In the present investigation, we analysed single and combined impacts of both toxic and disturbance stress on populations of white-tailed eagle (Haliaeetus albicilla), using an analytical single-species model. Chemical and eco(toxico)logical data reported from laboratory and field studies were used to parameterise and validate the model. The model was applied to assess the impact of ∑PCB, DDE and disturbance stress on the white-tailed eagle population in The Netherlands. Disturbance stress was incorporated through a 1.6% reduction in survival and a 10–50% reduction in reproduction. ∑PCB contamination from 1950 up to 1987 was found to be too high to allow the return of white-tailed eagle as a breeding species in that period. ∑PCB and population trends simulated for 2006–2050 suggest that future population growth is still reduced. Disturbance stress resulted in a reduced population development. The combination of both toxic and disturbance stress varied from a slower population development to a catastrophical reduction in population size, where the main cause was attributed to the reduction in reproduction of 50%. Application of the model was restricted by the current lack of quantitative dose–response relationships between non-toxic stress and survival and reproduction. Nevertheless, the model provides a first step towards integrating and quantifying the impacts of multiple stressors on white-tailed eagle populations