Dataset Information

Trend of recognizing depression symptoms and antidepressants use in newly diagnosed Parkinson's disease: Population-based study.

ABSTRACT:

Objectives

Although depression symptoms are common among patients with Parkinson's disease (PD), the medical literature still reports underrecognition of depression in patients with PD. Our main objective is to examine the trend of depression recognition during the first year of PD diagnosis using large population data.

Methods

We conducted a population-based study of residents in Wales, using the Secure Anonymized Information Linkage (SAIL) Databank. We included newly diagnosed patients with PD aged 40 years or older with a first PD diagnosis between 2000 and 2015. Depression and antidepressants related data were extracted from SAIL. A series of multilevel logistic regressions were run to determine the factors affecting depression recognition. The results were presented using odds ratios (ORs) with 95% confidence intervals (CI).

Results

The study included 6596 patients with PD. About 38% of patients had a recorded code of antidepressants, depression diagnosis, or both within the first year of PD diagnosis. There was a significant association of depression diagnosis, antidepressant use, or both with the year of PD diagnosis (OR 0.972, 95% CI 0.962-0.983). We also found that patients who used monoamine oxidase inhibitors (MAO-B inhibitors) were associated with a lower depression diagnosis, use antidepressants, or both, compared to those who did not use MAO-B inhibitors (OR 0.769, 95% CI 0.627-0.943).

Conclusion

There is a slight decrease in depression recognition in PD patients between 2000 and 2015, which could be due to an increase in depression recognition during the prodromal phase of PD.

SUBMITTER: Orayj K

PROVIDER: S-EPMC8413829 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveThe objective of this study was to develop valid prognostic models to predict mortality, dependency, and "death or dependency" for use in newly diagnosed Parkinson's disease (PD).MethodsThe models were developed in the Parkinsonism Incidence in North-East Scotland study (UK, 198 patients) and validated in the ParkWest study (Norway, 192 patients), cohorts that attempted to identify and follow-up all new PD cases in the study area. Dependency was defined using the Schwab & England scale. We selected variables measured at time of diagnosis to include in the models. Internal validation and external validation were performed by calculating C-statistics (discrimination) and plotting observed versus predicted risk in quantiles of predicted risk (calibration).ResultsOlder age, male sex, increased severity of axial features, and Charlson comorbidity index were independent prognostic factors in the mortality model. Increasing age, higher smoking history, increased severity of axial features, and lower MMSE score were independent predictors in the models of dependency and "death or dependency." Each model had very good internal calibration and very good or good discrimination (internal and external C-statistics for the models were 0.73-0.75 and 0.68-0.78, respectively). Although each model clearly separated patients into groups according to risk, they tended to overestimate risk in ParkWest. The models were recalibrated to the baseline risk in the ParkWest study and then calibrated well in this cohort.ConclusionsWe have developed prognostic models for predicting medium-term risk of important clinical outcomes in newly diagnosed PD. These models have validity for use for stratification of randomization, confounder adjustment, and case-mix correction, but they are inadequate for individualized prognostication. © 2017. The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.