Literature DB >> 34930711

Sickle cell anemia: hierarchical cluster analysis and clinical profile in a cohort in Brazil.

Valéria de Freitas Dutra1, Thais Priscila Biassi2, Maria Stella Figueiredo2.   

Abstract

INTRODUCTION: Sickle cell anemia is a monogenic disorder caused by a mutation in the β-hemoglobin gene, resulting in sickle hemoglobin that can polymerize. Presentation and clinical course have significant inter-individual variability and classifying these patients for severity is a challenge.
METHODS: We applied hierarchical clusters with 10 routine laboratory tests to understand if this grouping could be associated with clinical manifestations. We included 145 adult homozygous patients (SS) at an outpatient clinic in a retrospective study.
RESULTS: We found five clusters by counting those that had been differentiated by unconjugated bilirubin, reticulocytes, LDH, leukocytes, lymphocytes and monocytes. When comparing groups to clinical findings, the clusters were different only for liver abnormality. Cluster 3 had the lower median of reticulocytes, LDH, leukocytes, lymphocytes and monocytes and a higher percentage of patients under treatment. Clusters 4 and 5 had higher frequencies of liver impairment and higher medians of reticulocytes, LDH, leukocytes, lymphocytes and monocytes. Hemolysis and inflammation seemed to influence the grouping.
CONCLUSION: In our study, cluster analysis showed five groups that exhibited different degrees of inflammation and hemolysis. When comparing clinical data, the result was different only for the criteria of liver abnormality.
Copyright © 2021 Associação Brasileira de Hematologia, Hemoterapia e Terapia Celular. Published by Elsevier España, S.L.U. All rights reserved.

Entities:  

Keywords:  Hemoglobin S; Hierarchical clusters; Sickle cell anemia

Year:  2021        PMID: 34930711     DOI: 10.1016/j.htct.2021.08.015

Source DB:  PubMed          Journal:  Hematol Transfus Cell Ther        ISSN: 2531-1379


  2 in total

Review 1.  Clinical Applications of Artificial Intelligence-An Updated Overview.

Authors:  Ștefan Busnatu; Adelina-Gabriela Niculescu; Alexandra Bolocan; George E D Petrescu; Dan Nicolae Păduraru; Iulian Năstasă; Mircea Lupușoru; Marius Geantă; Octavian Andronic; Alexandru Mihai Grumezescu; Henrique Martins
Journal:  J Clin Med       Date:  2022-04-18       Impact factor: 4.964

2.  Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis.

Authors:  Víctor Micó; Rodrigo San-Cristobal; Roberto Martín; Miguel Ángel Martínez-González; Jordi Salas-Salvadó; Dolores Corella; Montserrat Fitó; Ángel M Alonso-Gómez; Julia Wärnberg; Jesús Vioque; Dora Romaguera; José López-Miranda; Ramon Estruch; Francisco J Tinahones; José Lapetra; J Luís Serra-Majem; Aurora Bueno-Cavanillas; Josep A Tur; Vicente Martín Sánchez; Xavier Pintó; Miguel Delgado-Rodríguez; Pilar Matía-Martín; Josep Vidal; Clotilde Vázquez; Ana García-Arellano; Salvador Pertusa-Martinez; Alice Chaplin; Antonio Garcia-Rios; Carlos Muñoz Bravo; Helmut Schröder; Nancy Babio; Jose V Sorli; Jose I Gonzalez; Diego Martinez-Urbistondo; Estefania Toledo; Vanessa Bullón; Miguel Ruiz-Canela; María Puy- Portillo; Manuel Macías-González; Nuria Perez-Diaz-Del-Campo; Jesús García-Gavilán; Lidia Daimiel; J Alfredo Martínez
Journal:  Front Endocrinol (Lausanne)       Date:  2022-09-06       Impact factor: 6.055

  2 in total

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