title: A Risk Index for Geriatric Acute Medical Admissions (RIGAMA).
abstract: OBJECTIVE
  to create and validate a Risk Index for Geriatric Acute Medical Admissions (RIGAMA) for those aged ≥ 65, based on accumulation of deficits.
  
  
  METHODS
  we retrospectively validated a 30-item RIGAMA against inpatient mortality, length of stay (LOS), discharge to long-term care (LTC) and 30-day readmission, adjusted for age.
  
  
  RESULTS
  ≥ 1 RIGAMA deficit was superior to age in predicting mortality and prolonged LOS, with a clear incremental effect. The latter was true for ≥3 deficits in predicting 30-day readmission. Three to 5 deficits predicted discharge to LTC better than age.
  
  
  CONCLUSIONS
  RIGAMA is easy to collect by the admitting junior doctor and may help trigger early senior support and inform the appropriate use of hospital resources by older patients.
authors.affiliation: Division of Internal Medicine, St James's Hospital, Dublin, Ireland.
authors.forename: R
authors.initials: R
authors.lastname: Romero-Ortuno
authors.forename: C
authors.initials: C
authors.lastname: O'Dwyer
authors.forename: D
authors.initials: D
authors.lastname: Byrne
authors.forename: D
authors.initials: D
authors.lastname: O'Riordan
authors.forename: B
authors.initials: B
authors.lastname: Silke
mesh_terms: D000208:Acute Disease; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D004632:Emergency Medical Services / Q000379:methods* / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006299:Health Services for the Aged / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007494:Ireland; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D010351:Patient Discharge / Q000706:statistics & numerical data; D010359:Patient Readmission / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012307:Risk Factors; D013222:State Medicine / Q000706:statistics & numerical data