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Volumn 62, Issue 3, 2007, Pages 592-600

Predicting hospital mortality, length of stay, and transfer to long-term care for injured patients

Author keywords

Hospital; Injury; Length of stay; Long term care; Mortality

Indexed keywords

ADULT; AGED; ARTICLE; COMA; CONTROLLED STUDY; EMERGENCY HEALTH SERVICE; FEMALE; HOSPITAL DISCHARGE; HUMAN; HYPOTENSION; INJURY; LENGTH OF STAY; LONG TERM CARE; MAJOR CLINICAL STUDY; MALE; MEDICAL RECORD; MORTALITY; PENETRATING TRAUMA; PREDICTION; PRIORITY JOURNAL;

EID: 34147153204     PISSN: 00225282     EISSN: 15298809     Source Type: Journal    
DOI: 10.1097/01.ta.0000257239.15436.29     Document Type: Article
Times cited : (22)

References (19)
  • 2
    • 0030790380 scopus 로고    scopus 로고
    • Modeling injury outcomes using time-to-event methods
    • Clark DE, Ryan LM. Modeling injury outcomes using time-to-event methods. J Trauma. 1997;42:1129-1134.
    • (1997) J Trauma , vol.42 , pp. 1129-1134
    • Clark, D.E.1    Ryan, L.M.2
  • 3
    • 0036617741 scopus 로고    scopus 로고
    • Concurrent prediction of hospital mortality and length of stay from risk factors on admission
    • Clark DE, Ryan LM. Concurrent prediction of hospital mortality and length of stay from risk factors on admission. Health Serv Res. 2002;37:631-645.
    • (2002) Health Serv Res , vol.37 , pp. 631-645
    • Clark, D.E.1    Ryan, L.M.2
  • 6
    • 0001485919 scopus 로고
    • Piecewise exponential models for survival data with covariates
    • Friedman M. Piecewise exponential models for survival data with covariates. Ann Statistics. 1982;10:101-113.
    • (1982) Ann Statistics , vol.10 , pp. 101-113
    • Friedman, M.1
  • 7
    • 0034736555 scopus 로고    scopus 로고
    • A multi-state model for evolution of intensive care unit patients: Prediction of nosocomial infections and deaths
    • Escolano S, Golmard JL, Korinek AM, Mallet A. A multi-state model for evolution of intensive care unit patients: Prediction of nosocomial infections and deaths. Stat Med. 2000;19:3465-3482.
    • (2000) Stat Med , vol.19 , pp. 3465-3482
    • Escolano, S.1    Golmard, J.L.2    Korinek, A.M.3    Mallet, A.4
  • 9
    • 12944280269 scopus 로고    scopus 로고
    • Dynamic microsimulation to model multiple outcomes in cohorts of critically ill patients
    • Clermont G, Kaplan V, Moreno R, et al. Dynamic microsimulation to model multiple outcomes in cohorts of critically ill patients. Intensive Care Med. 2004;30:2237-2244.
    • (2004) Intensive Care Med , vol.30 , pp. 2237-2244
    • Clermont, G.1    Kaplan, V.2    Moreno, R.3
  • 12
    • 0031590065 scopus 로고    scopus 로고
    • Recommended framework for presenting injury mortality data
    • Recommended framework for presenting injury mortality data. MMWR Morb Mortal Wkly Rep. 1997;46:1-30.
    • (1997) MMWR Morb Mortal Wkly Rep , vol.46 , pp. 1-30
  • 13
    • 34147111580 scopus 로고    scopus 로고
    • American College of Surgeons. National Trauma Data Bank Report 2004 Dataset Version 4.0, Chicago: American College of Surgeons, 2004
    • American College of Surgeons. National Trauma Data Bank Report 2004 (Dataset Version 4.0). Chicago: American College of Surgeons, 2004.
  • 14
    • 0024357057 scopus 로고
    • Effect of pre-existing disease on length of hospital stay in trauma patients
    • MacKenzie EJ, Morris JA Jr., Edelstein SL. Effect of pre-existing disease on length of hospital stay in trauma patients. J Trauma. 1989;29:757-764.
    • (1989) J Trauma , vol.29 , pp. 757-764
    • MacKenzie, E.J.1    Morris Jr., J.A.2    Edelstein, S.L.3
  • 15
    • 0027546683 scopus 로고
    • Injury severity scoring: Perspectives in development and future directions
    • Osler T. Injury severity scoring: Perspectives in development and future directions. Am J Surg. 1993;165:43S-51S.
    • (1993) Am J Surg , vol.165
    • Osler, T.1
  • 16
    • 0030949283 scopus 로고    scopus 로고
    • Specifications for calculation of risk-adjusted odds of death using trauma registry data
    • Mullins RJ, Mann NC, Brand DM, Lenfesty BS. Specifications for calculation of risk-adjusted odds of death using trauma registry data. Am J Surg. 1997;173:422-425.
    • (1997) Am J Surg , vol.173 , pp. 422-425
    • Mullins, R.J.1    Mann, N.C.2    Brand, D.M.3    Lenfesty, B.S.4
  • 17
    • 34147138141 scopus 로고    scopus 로고
    • Subcommittee on Trauma Registry Programs, American College of Surgeons Committee on Trauma, Available at, Accessed January 8
    • Subcommittee on Trauma Registry Programs, American College of Surgeons Committee on Trauma. National Trauma Data Bank Reference Manual: Background, caveats, and resources. Available at www.facs.org/trauma/ntdb.html. Accessed January 8, 2007.
    • (2007) National Trauma Data Bank Reference Manual: Background, caveats, and resources
  • 18
    • 4043124651 scopus 로고    scopus 로고
    • Risk adjustment for injured patients using administrative data
    • Clark DE, Winchell RJ. Risk adjustment for injured patients using administrative data. J Trauma. 2004;57:130-140.
    • (2004) J Trauma , vol.57 , pp. 130-140
    • Clark, D.E.1    Winchell, R.J.2
  • 19
    • 0034949644 scopus 로고    scopus 로고
    • A multicenter evaluation of whether gender dimorphism affects survival after trauma
    • Wohltmann CD, Franklin GA, Boaz PW, et al. A multicenter evaluation of whether gender dimorphism affects survival after trauma. Am J Surg. 2001;181:297-300.
    • (2001) Am J Surg , vol.181 , pp. 297-300
    • Wohltmann, C.D.1    Franklin, G.A.2    Boaz, P.W.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.