Literature DB >> 22454258

Predicting the discharge status after liver transplantation at a single center: a new approach for a new era.

Dympna M Kelly1, Renee Bennett, Nancy Brown, Judy McCoy, Derek Boerner, Changhong Yu, Bijan Eghtesad, Wael Barsoum, John J Fung, Michael W Kattan.   

Abstract

The aim of this study was to develop a tool for preoperatively predicting the need of a patient to attend an extended care facility after orthotopic liver transplantation (OLT). A multidisciplinary group, which included 2 transplant surgeons, 2 transplant nurses, 1 nurse manager, 2 physical therapists, 1 case manager, 1 home health care professional, 1 rehabilitation physician, and 1 statistician, met to identify preoperative factors relevant to discharge planning. The parameters that were examined as potential predictors of the discharge status were as follows: age, sex, language, Karnofsky score, OLT alone (versus a combined procedure), creatinine, bilirubin, international normalized ratio (INR), albumin, body mass index (BMI), Child-Turcotte-Pugh score, chemical Model for End-Stage Liver Disease score, renal dialysis, location before transplantation, comorbidities (encephalopathy, ascites, hydrothorax, and hepatopulmonary syndrome), diabetes mellitus (DM), cardiac ejection fraction and right ventricular systolic pressure, sex and availability of the primary caregiver, donor risk index, and donor characteristics. Between January 2004 and April 2010, 730 of 777 patients (94%) underwent only liver transplantation, and 47 patients (6%) underwent combined procedures. Five hundred nineteen patients (67%) were discharged home, 215 (28%) were discharged to a facility, and 43 (6%) died early after OLT. A multivariate logistic regression analysis identified the following parameters as significantly influencing the discharge status: a low Karnofsky score, an older age, female sex, an INR of 2.0, a creatinine level of 2.0 mg/dL, DM, a high bilirubin level, a low albumin level, a low or high BMI, and renal dialysis before OLT. The nomogram was prospectively validated with a population of 126 OLT recipients with a concordance index of 0.813. In conclusion, a new approach to improving the efficiency of hospital care is essential. We believe that this tool will aid in reducing lengths of stay and improving the experience of patients by facilitating early discharge planning.
Copyright © 2012 American Association for the Study of Liver Diseases.

Entities:  

Mesh:

Year:  2012        PMID: 22454258     DOI: 10.1002/lt.23434

Source DB:  PubMed          Journal:  Liver Transpl        ISSN: 1527-6465            Impact factor:   5.799


  7 in total

1.  Development of a machine learning algorithm predicting discharge placement after surgery for spondylolisthesis.

Authors:  Paul T Ogink; Aditya V Karhade; Quirina C B S Thio; Stuart H Hershman; Thomas D Cha; Christopher M Bono; Joseph H Schwab
Journal:  Eur Spine J       Date:  2019-03-27       Impact factor: 3.134

Review 2.  [Deceased donor liver transplantation].

Authors:  D Seehofer; W Schöning; P Neuhaus
Journal:  Chirurg       Date:  2013-05       Impact factor: 0.955

3.  Prediction of early discharge after gynaecological oncology surgery within ERAS.

Authors:  Eric Lambaudie; Jérome Mathis; Christophe Zemmour; Camille Jauffret-Fara; Elie Toni Mikhael; Camille Pouliquen; Renaud Sabatier; Clément Brun; Marion Faucher; Djamel Mokart; Gilles Houvenaeghel
Journal:  Surg Endosc       Date:  2019-07-15       Impact factor: 4.584

4.  The multinomial logistic regression model for predicting the discharge status after liver transplantation: estimation and diagnostics analysis.

Authors:  E M Hashimoto; E M M Ortega; G M Cordeiro; A K Suzuki; M W Kattan
Journal:  J Appl Stat       Date:  2019-12-24       Impact factor: 1.416

5.  Risk-scoring model for prediction of non-home discharge in epithelial ovarian cancer patients.

Authors:  Mariam M AlHilli; Christine W Tran; Carrie L Langstraat; Janice R Martin; Amy L Weaver; Michaela E McGree; Andrea Mariani; William A Cliby; Jamie N Bakkum-Gamez
Journal:  J Am Coll Surg       Date:  2013-06-29       Impact factor: 6.113

6.  Impact of recipient functional status on 1-year liver transplant outcomes.

Authors:  Natasha H Dolgin; Babak Movahedi; Frederick A Anderson; Isabel Ma Brüggenwirth; Paulo N Martins; Adel Bozorgzadeh
Journal:  World J Transplant       Date:  2019-11-20

7.  Resources Utilization After Liver Transplantation in Patients With and Without Hepatopulmonary Syndrome: Cleveland Clinic Experience.

Authors:  Jacek B Cywinski; Natalya Makarova; Andrea Arney; Qiang Liu; Masato Fujiki; K V Narayanan Menon; Cristiano Quintini
Journal:  Transplant Direct       Date:  2020-03-27
  7 in total

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