title: In-hospital risk prediction for post-stroke depression: development and validation of the Post-stroke Depression Prediction Scale.
abstract: OBJECTIVE
  The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early identification of stroke patients at increased risk for post-stroke depression.
  
  
  METHODS
  The study included 410 consecutive stroke patients who were able to communicate adequately. Predictors were collected within the first week after stroke. Between 6 to 8 weeks after stroke, major depressive disorder was diagnosed using the Composite International Diagnostic Interview. Multivariable logistic regression models were fitted. A bootstrap-backward selection process resulted in a reduced model. Performance of the model was expressed by discrimination, calibration, and accuracy.
  
  
  RESULTS
  The model included a medical history of depression or other psychiatric disorders, hypertension, angina pectoris, and the Barthel Index item dressing. The model had acceptable discrimination, based on an area under the receiver operating characteristic curve of 0.78 (0.72-0.85), and calibration (P value of the U-statistic, 0.96). Transforming the model to an easy-to-use risk-assessment table, the lowest risk category (sum score, <-10) showed a 2% risk of depression, which increased to 82% in the highest category (sum score, >21).
  
  
  CONCLUSIONS
  The clinical prediction model enables clinicians to estimate the degree of the depression risk for an individual patient within the first week after stroke.
authors.affiliation: Department of Rehabilitation, Nursing Science and Sports, University Medical Centre Utrecht, Utrecht, The Netherlands. J.M.deMan@umcutrecht.nl
authors.forename: Janneke M
authors.initials: JM
authors.lastname: de Man-van Ginkel
authors.forename: Thóra B
authors.initials: TB
authors.lastname: Hafsteinsdóttir
authors.forename: Eline
authors.initials: E
authors.lastname: Lindeman
authors.forename: Roelof G A
authors.initials: RG
authors.lastname: Ettema
authors.forename: Diederick E
authors.initials: DE
authors.lastname: Grobbee
authors.forename: Marieke J
authors.initials: MJ
authors.lastname: Schuurmans
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000209:etiology*; D005260:Female; D006801:Humans; D007297:Inpatients / Q000523:psychology / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011569:Psychiatric Status Rating Scales / Q000592:standards*; D012306:Risk; D020521:Stroke / Q000150:complications* / Q000175:diagnosis / Q000523:psychology*; D013997:Time Factors; D055815:Young Adult
keywords: depression; prediction; screening tool; stroke