메뉴 건너뛰기




Volumn 22, Issue 6, 2013, Pages 506-513

In-hospital mortality prediction in patients receiving mechanical ventilation in Taiwan

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL VENTILATION; COMORBIDITY; COMPARATIVE STUDY; FEMALE; HUMAN; LENGTH OF STAY; MALE; METHODOLOGY; MIDDLE AGED; MORTALITY; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; RISK ASSESSMENT; STATISTICAL MODEL; STATISTICS; TAIWAN; TIME; VALIDATION STUDY;

EID: 84888402979     PISSN: 10623264     EISSN: None     Source Type: Journal    
DOI: 10.4037/ajcc2013950     Document Type: Article
Times cited : (10)

References (25)
  • 1
    • 84863075913 scopus 로고    scopus 로고
    • A simplified score for transfer of patients requiring mechanical ventilation to a long-term care hospital
    • Chen HY, Vanness DJ, Golestanian E. A simplified score for transfer of patients requiring mechanical ventilation to a long-term care hospital. Am J Crit Care. 2011;20(6):e122-e130.
    • (2011) Am J Crit Care. , vol.20 , Issue.6
    • Chen, H.Y.1    Vanness, D.J.2    Golestanian, E.3
  • 2
    • 0037116657 scopus 로고    scopus 로고
    • Characteristics and outcomes in adult patients receiving mechanical ventilation
    • Esteban A, Anzueto A, Frutos F, et al. Characteristics and outcomes in adult patients receiving mechanical ventilation. JAMA. 2002;287:345-355.
    • (2002) JAMA. , vol.287 , pp. 345-355
    • Esteban, A.1    Anzueto, A.2    Frutos, F.3
  • 3
    • 77955300682 scopus 로고    scopus 로고
    • Early enteral nutrition and outcomes of critically ill patients treated with vasopressors and mechanical ventilation
    • Khalid I, Doshi P, DiGiovine B. Early enteral nutrition and outcomes of critically ill patients treated with vasopressors and mechanical ventilation. Am J Crit Care. 2010;19(3):261-268.
    • (2010) Am J Crit Care. , vol.19 , Issue.3 , pp. 261-268
    • Khalid, I.1    Doshi, P.2    DiGiovine, B.3
  • 4
    • 58149388697 scopus 로고    scopus 로고
    • Overview of artificial neural networks
    • Zou J, Han Y, So SS. Overview of artificial neural networks. Methods Mol Biol. 2008;458:15-23.
    • (2008) Methods Mol Biol. , vol.458 , pp. 15-23
    • Zou, J.1    Han, Y.2    So, S.S.3
  • 5
    • 77951005755 scopus 로고    scopus 로고
    • Data mining of patients on weaning trials from mechanical ventilation using cluster analysis and neural networks
    • Arizmendi C, Romero E, Alquezar R, et al. Data mining of patients on weaning trials from mechanical ventilation using cluster analysis and neural networks. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:4343-4346.
    • (2009) Conf Proc IEEE Eng Med Biol Soc. , vol.2009 , pp. 4343-4346
    • Arizmendi, C.1    Romero, E.2    Alquezar, R.3
  • 6
    • 33645818376 scopus 로고    scopus 로고
    • Power of breathing determined noninvasively with use of an artificial neural network in patients with respiratory failure
    • Banner MJ, Euliano NR, Brennan V, et al. Power of breathing determined noninvasively with use of an artificial neural network in patients with respiratory failure. Crit Care Med. 2006;34:1052-1059.
    • (2006) Crit Care Med. , vol.34 , pp. 1052-1059
    • Banner, M.J.1    Euliano, N.R.2    Brennan, V.3
  • 7
    • 84863991322 scopus 로고    scopus 로고
    • Nurses' detection of ineffective inspiratory efforts during mechanical ventilation
    • Chacón E, Estruga A, Murias G, et al. Nurses' detection of ineffective inspiratory efforts during mechanical ventilation. Am J Crit Care. 2012;21(4):e89-e93.
    • (2012) Am J Crit Care. , vol.21 , Issue.4
    • Chacón, E.1    Estruga, A.2    Murias, G.3
  • 10
    • 78751490491 scopus 로고    scopus 로고
    • International perspectives on the influence of structure and process of weaning from mechanical ventilation
    • Rose L, Blackwood B, Burns SM, Frazier SK, Egerod I. International perspectives on the influence of structure and process of weaning from mechanical ventilation. Am J Crit Care. 2011;20(1):e10-e18.
    • (2011) Am J Crit Care. , vol.20 , Issue.1
    • Rose, L.1    Blackwood, B.2    Burns, S.M.3    Frazier, S.K.4    Egerod, I.5
  • 12
    • 0027133523 scopus 로고
    • Risk adjustment in outcome assessment: the Charlson comorbidity index
    • D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med. 1993;32:382-387.
    • (1993) Methods Inf Med. , vol.32 , pp. 382-387
    • D'Hoore, W.1    Sicotte, C.2    Tilquin, C.3
  • 13
    • 84865131426 scopus 로고    scopus 로고
    • Predicting two-year quality of life after breast cancer surgery using artificial neural network and linear regression models
    • Shi HY, Tsai JT, Chen YM, Culbertson R, Chang HT, Hou MF. Predicting two-year quality of life after breast cancer surgery using artificial neural network and linear regression models. Breast Cancer Res Treat. 2012;135(1):221-229.
    • (2012) Breast Cancer Res Treat. , vol.135 , Issue.1 , pp. 221-229
    • Shi, H.Y.1    Tsai, J.T.2    Chen, Y.M.3    Culbertson, R.4    Chang, H.T.5    Hou, M.F.6
  • 14
    • 84869120235 scopus 로고    scopus 로고
    • Artificial neural network model for predicting 5-year mortality after surgery for hepatocellular carcinoma: a nationwide study
    • Shi HY, Lee KT, Wang JJ, Sun DP, Lee HH, Chiu CC. Artificial neural network model for predicting 5-year mortality after surgery for hepatocellular carcinoma: a nationwide study. J Gastrointest Surg. 2012;16(11):2126-2131.
    • (2012) J Gastrointest Surg. , vol.16 , Issue.11 , pp. 2126-2131
    • Shi, H.Y.1    Lee, K.T.2    Wang, J.J.3    Sun, D.P.4    Lee, H.H.5    Chiu, C.C.6
  • 15
    • 0003413187 scopus 로고    scopus 로고
    • Neural Networks: A Comprehensive Foundation
    • Englewood Cliffs, NJ: Prentice-Hall
    • Haykin S. Neural Networks: A Comprehensive Foundation. Englewood Cliffs, NJ: Prentice-Hall; 1999.
    • (1999)
    • Haykin, S.1
  • 16
    • 77953166434 scopus 로고    scopus 로고
    • Assessing risk prediction models in casecontrol studies using semiparametric and nonparametric methods
    • Huang Y, Pepe MS. Assessing risk prediction models in casecontrol studies using semiparametric and nonparametric methods. Stat Med. 2010;29:1391-1410.
    • (2010) Stat Med. , vol.29 , pp. 1391-1410
    • Huang, Y.1    Pepe, M.S.2
  • 17
    • 84863558651 scopus 로고    scopus 로고
    • Long-term home mechanical ventilation in the United States
    • King AC. Long-term home mechanical ventilation in the United States. Respir Care. 2012;57(6):921-930.
    • (2012) Respir Care. , vol.57 , Issue.6 , pp. 921-930
    • King, A.C.1
  • 18
    • 84862807681 scopus 로고    scopus 로고
    • The relationship between volume and outcome after bariatric surgery: a nationwide study in Taiwan
    • Chiu CC, Wang JJ, Tsai TC, Chu CC, Shi HY. The relationship between volume and outcome after bariatric surgery: a nationwide study in Taiwan. Obes Surg. 2012;22(7):1008-1015.
    • (2012) Obes Surg. , vol.22 , Issue.7 , pp. 1008-1015
    • Chiu, C.C.1    Wang, J.J.2    Tsai, T.C.3    Chu, C.C.4    Shi, H.Y.5
  • 19
    • 0030603526 scopus 로고    scopus 로고
    • Prediction of outcome in critically ill patients using artificial neural network synthesised by genetic algorithm
    • Dybowski R, Weller P, Chang R, et al. Prediction of outcome in critically ill patients using artificial neural network synthesised by genetic algorithm. Lancet. 1996;347:1146-1150.
    • (1996) Lancet. , vol.347 , pp. 1146-1150
    • Dybowski, R.1    Weller, P.2    Chang, R.3
  • 20
    • 15244347342 scopus 로고    scopus 로고
    • Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data
    • Eftekhar B, Mohammad K, Ardebili HE, et al. Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data. BMC Med Inform Decis Mak. 2005;5:3.
    • (2005) BMC Med Inform Decis Mak. , vol.5 , pp. 3
    • Eftekhar, B.1    Mohammad, K.2    Ardebili, H.E.3
  • 21
    • 84875784410 scopus 로고    scopus 로고
    • A comparison of intensive care unit mortality prediction models through the use of data mining techniques
    • Kim S, Kim W, Park RW. A comparison of intensive care unit mortality prediction models through the use of data mining techniques. Healthc Inform Res. 2011;17:232-243.
    • (2011) Healthc Inform Res. , vol.17 , pp. 232-243
    • Kim, S.1    Kim, W.2    Park, R.W.3
  • 22
    • 84862574405 scopus 로고    scopus 로고
    • Does patient volume affect clinical outcomes in adult intensive care units?
    • Kanhere MH, Kanhere HA, Cameron A, et al. Does patient volume affect clinical outcomes in adult intensive care units? Intensive Care Med. 2012;38:741-751.
    • (2012) Intensive Care Med , vol.38 , pp. 741-751
    • Kanhere, M.H.1    Kanhere, H.A.2    Cameron, A.3
  • 23
    • 84055173597 scopus 로고    scopus 로고
    • Impact of case volume on survival of septic shock in patients with malignancies
    • Zuber B, Tran TC, Aegerter P, et al. Impact of case volume on survival of septic shock in patients with malignancies. Crit Care Med. 2012;40:55-62.
    • (2012) Crit Care Med. , vol.40 , pp. 55-62
    • Zuber, B.1    Tran, T.C.2    Aegerter, P.3
  • 24
    • 79960737323 scopus 로고    scopus 로고
    • The role of standardized protocols in unplanned extubations in a medical intensive care unit
    • Jarachovic M, Mason M, Kerber K, McNett M. The role of standardized protocols in unplanned extubations in a medical intensive care unit. Am J Crit Care. 2011;20(4):304-311.
    • (2011) Am J Crit Care. , vol.20 , Issue.4 , pp. 304-311
    • Jarachovic, M.1    Mason, M.2    Kerber, K.3    McNett, M.4
  • 25
    • 82455206221 scopus 로고    scopus 로고
    • Long-term survival in patients with tracheostomy and prolonged mechanical ventilation in Olmsted County, Minnesota
    • Kojicic M, Li G, Ahmed A, et al. Long-term survival in patients with tracheostomy and prolonged mechanical ventilation in Olmsted County, Minnesota. Respir Care. 2011;56(11): 1765-1770.
    • (2011) Respir Care. , vol.56 , Issue.11 , pp. 1765-1770
    • Kojicic, M.1    Li, G.2    Ahmed, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.