Literature DB >> 34351940

A new haematocytometric index: Predicting severity and mortality risk value in COVID-19 patients.

Meltem Kilercik1,2, Özlem Demirelce1, Muhittin Abdulkadir Serdar1,2, Parvana Mikailova1, Mustafa Serteser1,2.   

Abstract

INTRODUCTION: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection.
METHODS: Clinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software.
RESULTS: 97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0-30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886-0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group.
CONCLUSION: NLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.

Entities:  

Year:  2021        PMID: 34351940     DOI: 10.1371/journal.pone.0254073

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  8 in total

Review 1.  Prognostic value of albumin-to-globulin ratio in COVID-19 patients: A systematic review and meta-analysis.

Authors:  Juan R Ulloque-Badaracco; Melany D Mosquera-Rojas; Enrique A Hernandez-Bustamante; Esteban A Alarcón-Braga; Percy Herrera-Añazco; Vicente A Benites-Zapata
Journal:  Heliyon       Date:  2022-05-18

2.  Sex-adjusted approach to baseline variables demonstrated some improved predictive capabilities for disease severity and survival in patients with Coronavirus Disease 19.

Authors:  Munkh-Undrakh Batmunkh; Oyungerel Ravjir; Enkhsaikhan Lkhagvasuren; Naranzul Dambaa; Tsolmon Boldoo; Sarangua Ganbold; Khorolgarav Ganbaatar; Chinbayar Tserendorj; Khongorzul Togoo; Ariunzaya Bat-Erdene; Zolmunkh Narmandakh; Chimidtseren Soodoi; Otgonbayar Damdinbazar; Bilegtsaikhan Tsolmon; Batbaatar Gunchin; Tsogtsaikhan Sandag
Journal:  Inform Med Unlocked       Date:  2022-06-10

3.  Novel prognostic determinants of COVID-19-related mortality: A pilot study on severely-ill patients in Russia.

Authors:  Kseniya Rubina; Anna Shmakova; Aslan Shabanov; Yulii Andreev; Natalia Borovkova; Vladimir Kulabukhov; Anatoliy Evseev; Konstantin Popugaev; Sergey Petrikov; Ekaterina Semina
Journal:  PLoS One       Date:  2022-02-25       Impact factor: 3.240

4.  Clinical characteristics of the severe acute respiratory syndrome coronavirus 2 omicron variant compared with the delta variant: a retrospective case-control study of 318 outpatients from a single sight institute in Japan.

Authors:  Keiko Suzuki; Takaya Ichikawa; Satoshi Suzuki; Yoko Tanino; Yasutaka Kakinoki
Journal:  PeerJ       Date:  2022-08-02       Impact factor: 3.061

5.  Interaction Effect Between Hemoglobin and Hypoxemia on COVID-19 Mortality: an observational study from Bogotá, Colombia.

Authors:  Andrés Felipe Patiño-Aldana; Ángela María Ruíz Sternberg; Ángela María Pinzón Rondón; Nicolás Molano-Gonzalez; David Rene Rodriguez Lima
Journal:  Int J Gen Med       Date:  2022-09-02

6.  Hybrid Bayesian Network-Based Modeling: COVID-19-Pneumonia Case.

Authors:  Ilia Vladislavovich Derevitskii; Nikita Dmitrievich Mramorov; Simon Dmitrievich Usoltsev; Sergey V Kovalchuk
Journal:  J Pers Med       Date:  2022-08-17

Review 7.  C-Reactive Protein-to-Albumin Ratio and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis.

Authors:  Hernán J Zavalaga-Zegarra; Juan J Palomino-Gutierrez; Juan R Ulloque-Badaracco; Melany D Mosquera-Rojas; Enrique A Hernandez-Bustamante; Esteban A Alarcon-Braga; Vicente A Benites-Zapata; Percy Herrera-Añazco; Adrian V Hernandez
Journal:  Trop Med Infect Dis       Date:  2022-08-16

8.  Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients.

Authors:  Sara Saadatmand; Khodakaram Salimifard; Reza Mohammadi; Alex Kuiper; Maryam Marzban; Akram Farhadi
Journal:  Ann Oper Res       Date:  2022-09-29       Impact factor: 4.820

  8 in total

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