title: Shunts in normal-pressure hydrocephalus: do we place too many or too few?
abstract: OBJECTIVE
  The average 65-year-old patient with moderate dementia can look forward to only 1.4 quality-adjusted life years (QALYs), that is, longevity times quality of life. Some of these patients suffer from normal-pressure hydrocephalus (NPH) and respond dramatically to shunt insertion. Currently, however, NPH cannot be diagnosed with certainty. The authors constructed a Markov decision analysis model to predict the outcome in patients with NPH treated with and without shunts.
  
  
  METHODS
  Transition probabilities and health utilities were obtained from a review of the literature. A sensitivity analysis and Monte Carlo simulation were applied to test outcomes over a wide range of parameters. Using shunt response and complication rates from the literature, the average patient receiving a shunt would gain an additional 1.7 QALYs as a result of automatic shunt insertion. Even if 50% of patients receiving a shunt have complications, the shunt response rate would need to be less than 5% for empirical shunt insertion to do more harm than good. Authors of most studies have reported far better statistics.
  
  
  CONCLUSIONS
  In summary, many more patients with suspected NPH should be considered for shunt insertion.
authors.affiliation: Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA. sherman.stein@uphs.upenn.edu
authors.forename: Sherman C
authors.initials: SC
authors.lastname: Stein
authors.forename: Mark G
authors.initials: MG
authors.lastname: Burnett
authors.forename: Seema S
authors.initials: SS
authors.lastname: Sonnad
mesh_terms: D000368:Aged; D002557:Cerebrospinal Fluid Shunts / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D003663:Decision Trees; D003704:Dementia / Q000401:mortality / Q000601:surgery*; D006801:Humans; D006850:Hydrocephalus, Normal Pressure / Q000401:mortality / Q000601:surgery*; D008390:Markov Chains; D009010:Monte Carlo Method; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data; D011336:Probability; D019057:Quality-Adjusted Life Years; D016019:Survival Analysis