ArticleInternational journal of laboratory hematology2021
Correlation of hematological parameters and cycle threshold in ambulatory patients with SARS-CoV-2 infection.
Article in International journal of laboratory hematology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Dynamic alterations in white blood cell counts and SARS-CoV-2 shedding in saliva: an infection predictor parameter.Frontiers in medicine · 2023Article
- Comparative Analysis of Age, Sex, and Viral Load in Outpatients during the Four Waves of SARS-CoV-2 in A Mexican Medium-Sized City.International journal of environmental research and public health · 2022Article
- The machine learning model based on trajectory analysis of ribonucleic acid test results predicts the necessity of quarantine in recurrently positive patients with SARS-CoV-2 infection.Frontiers in public health · 2022Observational
- Correlation of hematological parameters and cycle threshold in ambulatory patients with SARS-CoV-2 infection.International journal of laboratory hematology · 2021Article
- Hematologic analysis of hospitalized patients and outpatients infected with SARS-CoV-2 and possible use as a prognostic biomarker.Experimental hematologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
introductionFormer studies have shown that hematologic parameters are affected by the SARS-CoV-2 infection which has caused a global health problem. Therefore, this research aims to identify the most frequent symptoms and comorbidities in SARS-CoV-2 infected outpatients; besides, to analyze hematological parameters and their correlation with cycle threshold (Ct) values.
methodsWe analyzed a total of sixty outpatients with SARS-CoV-2 infection. They were divided according to sex. Afterward, a questionnaire was carried out to find out their symptoms and comorbidities. Additionally, blood biometry data were correlated with the Ct value, respectively.
resultsSixty patients were analyzed; the mean age was 43 years. All patients were from Nayarit, Mexico. The frequency index showed that the main symptoms were headache and anosmia, and the comorbidities were obesity and smoking. The analysis of blood biometry showed a clear increase in red blood cells (RBC) related parameters in women. In both sexes an increase in the number of white blood cells (WBC) was observed. Also, all the hematological alterations correlated with the grade of infection.
conclusionHeadache and anosmia are the most common symptoms according to the frequency index, the main comorbidities were obesity and smoking. Also, there is a Ct value correlation with hematological parameters (WBC, mean corpuscular volume, mean corpuscular hemoglobin, hemoglobin); they can be used as a prognostic marker of infection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.