Preoperative Stratification of Liver Transplant Recipients: Validation of the LTRS.


Journal

Transplantation
ISSN: 1534-6080
Titre abrégé: Transplantation
Pays: United States
ID NLM: 0132144

Informations de publication

Date de publication:
12 2020
Historique:
pubmed: 18 7 2020
medline: 9 2 2021
entrez: 18 7 2020
Statut: ppublish

Résumé

The liver transplant risk score (LTRS) was developed to stratify 90-day mortality of patients referred for liver transplantation (LT). We aimed to validate the LTRS using a new cohort of patients. The LTRS stratifies the risk of 90-day mortality of LT recipients based on their age, body mass index, diabetes, model for end-stage liver disease (MELD) score, and need for dialysis. We assessed the performance of the LTRS using a new cohort of patients transplanted in the United States between July 2013 and June 2017. Exclusion criteria were age <18 years, ABO incompatibility, redo or multivisceral transplants, partial grafts, malignancies other than hepatocellular carcinoma and fulminant hepatitis. We found a linear correlation between the number of points of the LTRS and 90-day mortality. Among 18 635 recipients, 90-day mortality was 2.7%, 3.8%, 5.2%, 4.8%, 6.7%, and 9.3% for recipients with 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). The LTRS also stratified 1-year mortality that was 5.5%, 7.7%, 9.9%, 9.3%, 10.8%, and 15.4% for 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). An inverse correlation was found between the LTRS and 4-year survival that was 82%, 79%, 78%, 82%, 78%, and 66% for patients with 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). The LTRS remained an independent predictor after accounting for recipient sex, ethnicity, cause of liver disease, donor age, cold ischemia time, and waiting time. The LTRS can stratify the short- and long-term outcomes of LT recipients at the time of their evaluations irrespective of their gender, ethnicity, and primary cause of liver disease.

Sections du résumé

BACKGROUND
The liver transplant risk score (LTRS) was developed to stratify 90-day mortality of patients referred for liver transplantation (LT). We aimed to validate the LTRS using a new cohort of patients.
METHODS
The LTRS stratifies the risk of 90-day mortality of LT recipients based on their age, body mass index, diabetes, model for end-stage liver disease (MELD) score, and need for dialysis. We assessed the performance of the LTRS using a new cohort of patients transplanted in the United States between July 2013 and June 2017. Exclusion criteria were age <18 years, ABO incompatibility, redo or multivisceral transplants, partial grafts, malignancies other than hepatocellular carcinoma and fulminant hepatitis.
RESULTS
We found a linear correlation between the number of points of the LTRS and 90-day mortality. Among 18 635 recipients, 90-day mortality was 2.7%, 3.8%, 5.2%, 4.8%, 6.7%, and 9.3% for recipients with 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). The LTRS also stratified 1-year mortality that was 5.5%, 7.7%, 9.9%, 9.3%, 10.8%, and 15.4% for 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). An inverse correlation was found between the LTRS and 4-year survival that was 82%, 79%, 78%, 82%, 78%, and 66% for patients with 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). The LTRS remained an independent predictor after accounting for recipient sex, ethnicity, cause of liver disease, donor age, cold ischemia time, and waiting time.
CONCLUSIONS
The LTRS can stratify the short- and long-term outcomes of LT recipients at the time of their evaluations irrespective of their gender, ethnicity, and primary cause of liver disease.

Identifiants

pubmed: 32675743
doi: 10.1097/TP.0000000000003353
pii: 00007890-202012000-00017
pmc: PMC8015433
mid: NIHMS1667751
doi:

Types de publication

Journal Article Observational Study Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

e332-e341

Subventions

Organisme : NCI NIH HHS
ID : T32 CA113263
Pays : United States

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Auteurs

Michele Molinari (M)

Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA.

Dana Jorgensen (D)

Division of Biostatistics, University of Pittsburgh Medical Center, Pittsburgh, PA.

Subhashini Ayloo (S)

Department of Surgery, Rutgers University, New Jersey Medical School, Newark, NJ.

Stalin Dharmayan (S)

Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA.

Christof Kaltenmeier (C)

Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA.

Rajil B Mehta (RB)

Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA.

Naudia Jonassaint (N)

Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA.

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Classifications MeSH