Adjuvant pomegranate juice intake improves the inflammatory status of hospitalized COVID-19 patients: A randomized and placebo-controlled trial.

BACKGROUND: This study aimed to evaluate the effect of pomegranate juice intake on the inflammatory status and complete blood count in hospitalized Covid-19 patients. METHODS: This randomized, double-blinded placebo-controlled trial included 48 patients with two parallel arms. In addition to the standard care provided at the hospital, the patients consumed 500 mL of whole pomegranate juice (PJ) daily or a placebo for 14 days. Inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6), erythrocyte sedimentation rate (ESR)) and complete blood count were determined at baseline and after the 14 days of intervention. RESULTS: At the end of the intervention, a significant decreased was observed in primary outcomes [mean difference (95 %CI)] including IL-6 [5.24(0.87-9.61)], CRP [23.19(11.93-34.44)] and ESR [10.52(1.54-19.50)] in the PJ group vs. before the intervention. In addition, significant changes were also observed in the some of the secondary outcomes, including neutrophils, lymphocytes, platelets, platelets-to-lymphocyte(PLR) and neutrophils-to-lymphocyte (NLR) ratios (p < 0.05) in the PJ group compared to before the intervention. At the end of the intervention period, the mean change of IL-6 [- 7.09(-12.21 to - 1.96)], white blood cells [- 3.09(- 6.14 to - 0.05)], neutrophils [- 9.12(-18.08 to -0.15)], lymphocyte [7.05(0.17-13.92)], platelets [- 94.54(- 139.33 to - 49.75)], PLR [- 15.99(- 29.31 to - 2.67)], blood oxygen saturation [1.75(0.13-3.37)] and MCV [0.31(- 0.25 to 0.88)] levels were significantly different between groups while no difference was observed between the two groups in other blood indices. CONCLUSION: Our results suggest that pomegranate juice intake might slightly improve the inflammatory status and CBC outcomes of COVID-19 patients and it may be beneficial.

Establishment of reference intervals for complete blood count in times of COVID-19 and vaccination.

Introduction: COVID-19 and vaccination may affect some parameters of the complete blood count (CBC). The aim of this study was to determine reference intervals (RI) of CBC in healthy population with different COVID-19 and vaccination backgrounds and compare them with those established previously. Materials and methods: A cross-sectional study was conducted in donors who attended the Traumatology Hospital "Dr. Victorio de la Fuente Narváez" (HTVFN) from June to September 2021. Reference intervals were established using the non-parametric method on Sysmex XN-1000. For differences between groups with different COVID-19 and vaccination backgrounds, non-parametric tests were used. Results: The RI were established in 156 men and 128 women. Haemoglobin (Hb), haematocrit (Hct), red blood cells (RBC), platelets (Plt), mean platelets volume (MPV), monocytes and relative neutrophils were higher in men than women (P < 0.001). The percentiles of Hb, Hct, RBC, MPV and relative monocytes showed higher values; Plt, white blood cells (WBC), lymphocytes, monocytes, neutrophils, eosinophils and absolute basophils, the 2.5th was higher and the 97.5th was lower; for lymphocytes and relative neutrophils, both percentiles had a trend toward lower values, compared to previous RI. Differences between groups with different COVID-19 and vaccination backgrounds, in lymphocytes (P = 0.038), neutrophils (P = 0.017) and eosinophils (P = 0.018) in men; Hct (P = 0.014), RDW (P = 0.023) in women and MPV (P = 0.001) in both, were not considered pathological. Conclusions: The RI for the CBC were established in a Mestizo-Mexican population with different COVID-19 and vaccination backgrounds, so should be updated and validated in different hospitals close to the HTVFN that use the same analyser.

To investigate the importance of the CBC, derived parameters, and morphology of peripheral blood cells in COVID-19 patients

Aim: To investigate the importance of the CBC, derived parameters, and morphology of peripheral blood cells in Covid-19 patients. Material and methods: According to their symptoms, patients were classified as asymptomatic, mild, or moderate-severe. This research included all paediatric and adult patients who had two CBC samples available (one at admission and another during discharge) throughout their hospital stay. Those who were already undergoing therapy for their cancer, haematological illness, liver disease, or chronic lung disease were not allowed to participate. Results: Patients' ages varied from 8 to 71. The patients' average age was 36.15+or-14.58 years. Sixty percent of research participants were male, making up a sex ratio of 1.5:1. (M: F). The average white blood cell count was 6.87+or-3.51 x109/L, the average red blood cell count was 4.61+or-0.88 x106/microL, and the average haemoglobin level was 12.80+or-2.15 g/dl upon admission. The average absolute neutrophil count was 3.81+or-3.46x109/L, the average absolute lymphocyte count was 2.31+or-1.40x109/L, the average absolute monocyte count was 0.38+or-0.31x109/L, and the average absolute eosinophil count was 0.15+or-0.18x109/L. Overall, the average number of platelets per microliter of blood was 149.21+or- 80.25. Neutrophil to lymphocyte ratio (NLR) at admission was 3.806;platelet to lymphocyte ratio (PLR) was 116.32+or-13.1;lymphocyte to monocyte ratio (LMR) was 8.91+or-5.25, and derivative neutrophil to lymphocyte ratio (d-NLR) was 2.61+or-1.36. Twenty (40%) of the patients were asymptomatic at admission, while 44% had mild symptoms, and 16% required oxygen and ventilator support due to moderate to severe symptoms. The RT-PCR test was positive for all of the patients examined. There was a noteworthy shift in both the mean WBC and mean platelet counts after the follow-up evaluation. No correlation was seen between clinical state on admission and any of the other CBC measures (p>0.05) Conclusion: The significance of CBC values and morphological inspection of the peripheral blood smear at baseline and subsequent assessment is highlighted in the research.

Evaluation of Hematological Changes During COVID-19: A Systematic Review

Objectives: COVID-19 pandemic has affected more than 6 million people globally. Most of the affected patients presents with fever, cough, nausea, vomiting, fatigue and dyspnea. Molecular testing by PCR is gold standard test to diagnose COVID-19 infection but if unavailable, hematological profile of COVID-19 patients is a good prognostic marker for COVID-19 disease. The aim of our review is to summarize the recently available literature regarding hematological alterations in COVID-19 patients along with their trend in the disease course and their prognostic implications in terms of severe disease. Design(s): Systematic review. Method(s): Literature published between 2020 to 2022 on Google Scholar was included in our review by following PRISMA guidelines. Articles were shortlisted on the basis of inclusion and exclusion criteria. Result(s): Total 139 articles were initially identified. After removal of duplicates and screening on basis of present exclusion and inclusion criteria 17 articles were found. Out of these 17 articles, there were 10 retrospective studies, 3 prospective studies, 2 case control studies and 2 cross sectional studies. Conclusion(s): Hematological markers predicts the outcome of COVID in patients irrespective of their age, gender and co-morbidities. There is a positive relationship between disease severity and blood count of neutrophils, leukocytes, NLR, MDW, thrombocytopenia, lymphocytopenia, IL-6 and CRP. Copyright © 2022, Bahrain Medical Bulletin. All rights reserved.

Medical students' understanding and interpreting abilities for Complete Blood Counts (CBC) in clinical practice

Introduction: The current study aimed to assess students' competency of the Faculty of Medicine, Makkah region Saudi Arabia in interpreting common laboratory investigations like Complete Blood Counts. Methods: The current cross-sectional, quantitative and exploratory study was carried out at the Faculty of Medicine, Rabigh, King Abdulaziz University (KAU), Jeddah, from April 1 to April 20, 2022. An online questionnaire was circulated via various social media like Facebook, Twitter, and WhatsApp. Results: A total of 1,010 respondents participated in the survey, representing an overall response rate of 70%. Among all the respondents, females were 677 (67%) while males were 333 (33%). There were 277 (27.4%), 479 (47.4%), and 254 (25.1%) students from the fourth, fifth, and sixth years, respectively. For most of the statements, more than 70% of students responded correctly, but particularly for three of the questions, students' correct responses were 561 (55.5%), 518 (51.3%), and 491 (48.6%), which were not up to the mark. A gender-wise comparison showed that the percentage of correct answers given by female students was significantly higher than that of male students for all statements (p < 0.001). For most of the indices, more than 70% of students responded correctly, while for four questions, students' correct responses were not up to the mark. Comparison between students' gender revealed that, apart from two, the percentage of female students who correctly interpreted the indices was significantly higher than that of male students (p 0.001). In the results of all participants' responses to the clinical scenario interpretation the female students performed significantly better in scenarios 1 and 2 (p 0.001). Conclusions: Overall, our study participants' comprehension of CBC values and interpretation of the case scenarios was adequate. On the other hand, female students demonstrated better conceptual understanding than male students. We recommend improving assessment systems to help students expand their interpretation skills.

Complete Blood Counts in COVID-19 patients at JIIU's Indian Institute of Medical Science and Research, Jalna, Maharashtra

Background: The new 2019 coronavirus disease (COVID-19), according to the World Health Organization (WHO), has been characterized as a pandemic. As more is being discovered about this virus, we aim to report findings of the complete blood count (CBC) of COVID-19 patients. Method(s): A total of 100 patients were admitted at the Noor Hospital of JIIU's IIMSR, Jalna. The CBCs of these patients, following a confirmed diagnosis of COVID-19, were analyzed and a significant P P<0.05 was found after a full statistical analysis. Result(s): CBC analysis revealed changes in the levels of red blood cells (RBCs), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), and C-reactive protein (CRP). Conclusion(s): Clinicians should expect similar findings when dealing with the new COVID-19. This would serve in providing physicians with important knowledge on the changes that can be expected from the CBC of COVID-19 patients. Copyright © 2022 Ubiquity Press. All rights reserved.

Complete blood count alterations of covid-19 patients in a tertiary care hospital in north India

In confirmed positive patients, the purpose of this study is to assess the relationship between Coronavirus Disease 19 (COVID-19) and the primary complete blood count (CBC) parameters. In a retrospective cross-sectional study, 192 files of patients with a confirmed diagnosis of COVID-19 who were being treated at Govt medical College &Hospital Rajouri in India were randomly chosen as a study group for haematological parameters, and an additional 192 files of patients without a confirmed diagnosis of COVID-19 whose medical histories did not include any conditions that might have an impact on their haematological profile were chosen as a control group. The control group's gender, age, and nationality were matched to those of the study group. In contrast to COVID-19 negative patients, anaemia and thrombocytopenia weresignificantly more common in COVID-19 positive patients.However, the prevalence of leukopenia did not differ statistically between the two groups, but the positive individuals were 3.4 times more likely to be anaemic and around 5.3 times more likely to be thrombocytopenic. The median values for mean cell volume (MCV), total white blood cell (WBC) count, lymphocyte count, and basophil count between the two groups, however, did not indicate any statistically significant differences. Further research is advised to corroborate these findings because severe positive individuals may have highly developed anaemia and thrombocytopenia. Copyright © 2022 Ubiquity Press. All rights reserved.

Haematology audit of 801 COVID-19 patients' basics and beyond- Prospective observational study.

Background and Objective: COVID-19 has become a major health concern since 2020. Its clinical presentation varies from asymptomatic cases to cases with respiratory failure needing ICU management. It has created a huge burden on limited health care resources. We need better understanding of the pathogenesis and interplay between virus and other factors which decide outcome. We seek biomarkers to predict severe illness to offer better triaging of patients to provide hospital-based care to the patients at risk of severe illness. Material and Methods: We took 801 consecutive RT-PCR-positive COVID cases coming to our center. Their hematological work-up, such as complete blood count, peripheral smear, reticulocyte count, and G6PD activity, was tested. The pattern of hematological abnormalities was assessed across disease severity groups to identify predictors of severe illness from basic investigation. Also, the interplay between iron deficiency and possible hemoglobinopathy trait and COVID was explored. Results Discussion and Conclusion: We found old age, male gender, diabetes, neutrophilia, lymphopenia, monocytopenia, and eosinopenia at presentation to be associated with moderate to severe illness and may help in triaging with other inflammatory and radiological parameters. We found thrombocytosis rather than thrombocytopenia as a predictor of severe illness. Our preliminary findings suggest the need to explore the protective role of hemoglobinopathy traits and iron deficiency against severe COVID illness.

Impact of dexamethasone and tocilizumab on hematological parameters in COVID-19 patients with chronic disease.

Background and aim: The most effective way to control severity and mortality rate of the novel coronavirus disease (COVID-19) is through sensitive diagnostic approaches and an appropriate treatment protocol. We aimed to identify the effect of adding corticosteroid and Tocilizumab to a standard treatment protocol in treating COVID-19 patients with chronic disease through hematological and lab biomarkers. Materials and methods: This study was performed retrospectively on 68 COVID-19 patients with chronic disease who were treated by different therapeutic protocols. The patients were categorized into four groups: control group represented the patients' lab results at admission before treatment protocols were applied; group 1 included patients treated with anticoagulants, Hydroxychloroquine, and antibiotics; group 2 comprised patients treated with Dexamethasone; and group 3 included patients treated with Dexamethasone and Tocilizumab. Results: The WBC and neutrophil counts were increased significantly in group 3 upon the treatment when they were compared with patients in group 1 (p = 0.004 and p = 0.001, respectively). The comparison of C-reactive Protein (CRP) level at admission was higher in group 3 than in group 1 with p = 0.030. After 10 days of treatment, CRP level was decreased in all groups, but in group 3 it was statistically significant (p = 0.002). Conclusion: The study paves the way into the effectiveness of combining Dexamethasone with Tocilizumab in treatment COVID-19 patients with chronic diseases.

Antecedentes y objetivo: La forma más eficaz de controlar la gravedad y la tasa de mortalidad de la enfermedad del nuevo coronavirus (COVID-19) es mediante enfoques de diagnóstico sensibles y un protocolo de tratamiento adecuado. Nuestro objetivo fue identificar el efecto de agregar corticosteroides y tocilizumab a un protocolo de tratamiento estándar en el tratamiento de pacientes con COVID-19 con enfermedad crónica a través de biomarcadores hematológicos y de laboratorio. Materiales y métodos: Este estudio se realizó de forma retrospectiva en 68 pacientes COVID-19 con enfermedad crónica que fueron tratados por diferentes protocolos terapéuticos. Los pacientes se clasificaron en cuatro grupos: el grupo de control representaba los resultados de laboratorio de los pacientes en el momento de la admisión antes de que se aplicaran los protocolos de tratamiento; el grupo 1 incluyó a pacientes tratados con anticoagulantes, hidroxicloroquina y antibióticos; el grupo 2 estaba compuesto por pacientes tratados con dexametasona; y el grupo 3 incluyó a pacientes tratados con dexametasona y tocilizumab. Resultados: Los recuentos de glóbulos blancos y neutrófilos aumentaron significativamente en el grupo 3 tras el tratamiento cuando se compararon con los pacientes del grupo 1 (p = 0,004 y p = 0,001, respectivamente). La comparación del nivel de proteína C reactiva (CRP) al ingreso fue mayor en el grupo 3 que en el grupo 1, con p = 0,030. Después de 10 días de tratamiento, el nivel de CRP disminuyó en todos los grupos, pero en el grupo 3 fue estadísticamente significativo (p = 0,002). Conclusión: El estudio allana el camino hacia la eficacia de la combinación de dexametasona con tocilizumab en el tratamiento de pacientes con COVID-19 con enfermedades crónicas.

Effect of complete blood count parameters on the clinical course of COVID-19 in pregnant women

Coronavirus Disease-19 (COVID-19) pandemic, affected pregnant women as well as many people. Aim of this study is to compare complete blood count (CBC) parameters of pregnant women infected with COVID-19 to that of healthy pregnant women and determine their prognostic features. 142 pregnant women infected with COVID-19 and 46 healthy pregnant women, included in this retrospective case-control study. Patients infected with COVID-19 were grouped as mild, moderate and severe, according to the findings of oxygen saturation and lung involvement. Age, gestational age, gravida, hospitalization length and CBC parameters of the participants were compared, according to the groups. CBC test revealed that uninfected pregnant women had statistically lower level of white blood cell count (WBC, p=0.001), platelet count (p=0,024), neutrophil count (p=0,001), lymphocytes (p=0,005), monocytes (p=0,001) and platelecrit (p=0.007) than from infected pregnant women. Evaluation of pregnant women with COVID-19 grouped into 3 categories as mild, moderate and severe showed that age, gravida and hospitalization length were comparable between groups, WBC (p=0.012) and neutrophile (p=0.001) counts of mild group were significantly lower than moderate group and there was no significant difference between moderate and severe groups regarding WBC and neutrophile counts (respectively p=0,281, p=0.542). CBC analysis is simple, applicable, widely used and cheap laboratory method. CBC parameters seem as a candidate for predicting COVID-19 clinical course. However, larger sample sized prospective studies supporting this idea are required. Copyright © 2022 Ondokuz Mayis Universitesi. All rights reserved.

Complete Blood Count for COVID- 19 Patients Based on Age and Gender

Coronavirus infection (COVID-19), is now a worldwide pandemic. The researchers are trying to find more about this virus in term of diagnosis and management. Many researchers reported that the routine complete blood count is one of the main analysis to be perform for the patients as part of the confirmation test for the disease. Our aim is to find more about complete blood count (CBC) of patients infected with COVID-19 and to see whether the results would show any significant differences regarding age and gender. A group of 110 patients with a confirmed COVID-19 admitted to the Salah El- Deen Hospital in Tikrit City, Iraq. The cases were collected and analyzed from January to Decemper 2020. CBC analysis showed a significant differences in the levels of red blood cells (RBCs), hemoglobin (HGB), hematocrit (HCT), and C-reactive protein (CRP) based on gender, but no significant changes regarding age groups. more studies should be done in the future in this department. © 2022 American Institute of Physics Inc.. All rights reserved.

Routine hematology parameters in COVID-19: A predictor of disease severity and mortality.

Background: Our understanding of the pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still evolving and is limited for prognostication. The study was performed to predict severity and mortality based on hematology parameters in coronavirus disease (COVID-19). Material and Methods: The study was a single-center retrospective analysis of 240 patients with COVID-19. The hematological parameters were compared between different grades of severity. The receiver operating characteristics (ROC) curve along with the Classification and Regression Trees (CART) methods were used for the analysis. Result: The total leukocyte count, absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), and neutrophil-monocyte ratio (NMR) were increasing along with an increase in severity; while the absolute lymphocyte count and lymphocyte-monocyte ratio (LMR) were decreasing (P < 0.001). For prediction of severity and mortality on admission, the NLR, NMR, and LMR were significant (P < 0.001). The NLR, NMR, and LMR had an area under the receiver operating characteristics curve (AUROC) of 0.86 (95% CI of 0.80-0.91), 0.822 (95% CI of 0.76-0.88), and 0.69 (95% CI of 0.60-0.79), respectively, for severity. While the NLR, NMR, and LMR had an AUROC value of 0.85 (95% CI of 0.79-0.92), 0.83 (95% CI of 0.77-0.89), and 0.67 (95% CI of 0.57-0.78), respectively, for mortality. Conclusion: With the increase in severity there was an increase in the total leukocyte count and absolute neutrophil count while the absolute lymphocyte count decreased. On admission, the cut-off value of NLR >5.2, NMR >12.1, while LMR <2.4 may predict severity and mortality in COVID-19.

Relationship between the hematological indices and COVID-19

Background: Recently, the novel coronavirus disease-2019 (COVID-19) has a wide spread around the world. Clinically, it was responsible for respiratory illness ranged from mild to life-threatening infection. The study aimed to investigate the link of gender, age, ABO blood groups, and hematological indices with COVID-19 infection. Methods: One hindered COVID-19 cases, as confirmed using reverse transcription-polymerase chain reaction test, were checked for some sociodemographic features, blood group, and hematology parameters. A blood sample was collected from each person in an EDTA container and immediately tested for blood group using commercial antisera, in addition to complete blood count parameters using of a semiautomated hematology analyzer (Mindray BC-3200). Results: Of 100 COVID-19 patients, 52% were male and 48% were female. About 33% and 31% of the study participants were of age group 15-31 and 32-49 years, respectively. The majority (37%) of COVID-19 patients carried blood group O+ve, followed by A+ve (24%). A+ve blood group was significantly more reported in males (32.7%) than females (14.6%). Notably, 61% of participants showed low Hb level. Erythropenia was detected in 41% of the participants, while thrombocytopenia was observed only in 19% of the patients. Moreover, lymphocytopenia was detected in 82%, low packed cell volume in 66%, decreased mean corpuscular volume in 20%, and declined mean corpuscular hemoglobin concentration in 8% of the participants. In contrast, leukocytosis and neutrophilia were found in 69% and 73% of the participants, respectively. Conclusion: Taken together, the study findings highlighted the link of COVID-19 with age, gender, blood groups, and hematology parameters, which is important in diagnosis, prognosis, and management of illness. © 2022 Biomedical and Biotechnology Research Journal (BBRJ) ;Published by Wolters Kluwer - Medknow

Commercialized kits to assess T-cell responses against SARS-CoV-2 S peptides. A pilot study in health care workers.

Background: It is crucial to assess the levels of protection generated by natural infection or SARS-CoV-2 vaccines, mainly in individuals professionally exposed and in vulnerable groups. Measuring T-cell responses may complement antibody tests currently in use as correlates of protection. Our aim was to assess the feasibility of a validated assay of T-cell responses. Methods: Twenty health-care-workers (HCW) were included. Antibody test to SARS-CoV-2 N and S-proteins in parallel with a commercially available whole-blood-interferon-gamma-release-assay (IGRA) to S-peptides and two detection methods, CLIA and ELISA were determined. Results: IGRA test detected T-cell responses in naturally exposed and vaccinated HCW already after first vaccination dose. The correlation by the two detection methods was very high (R > 0.8) and sensitivity and specificity ranged between 100 and 86% and 100-73% respectively. Even though there was a very high concordance between specific antibody levels and the IGRA assay in the ability to detect immune response to SARS-CoV-2, there was a relatively low quantitative correlation. In the small group primed by natural infection, one vaccine dose was sufficient to reach immune response plateau. IGRA was positive in one, with Ig(S) antibody negative vaccinated immunosuppressed HCW illustrating another advantage of the IGRA-test. Conclusion: Whole-blood-IGRA-tests amenable to automation and constitutes a promising additional tool for measuring the state of the immune response to SARS-CoV-2; they are applicable to large number of samples and may become a valuable correlate of protection to COVID-19, particularly for vulnerable groups at risk of being re-exposed to infection, as are health-care-workers.

Introducción: Es fundamental evaluar los niveles de protección inmune en infectados o tras la vacunación frente a SARS-CoV-2. La cuantificación de la respuesta inmune celular T puede complementar la determinación de anticuerpos. Evaluamos la viabilidad de un ensayo comercial validado de respuesta celular T específica frente a SARS-CoV-2. Métodos: Se incluyeron veinte trabajadores sanitarios (TS). Medimos anticuerpos contra las proteínas N y S de SARS-CoV-2 y realizamos el ensayo de liberación de interferón-gamma (IFNγ) en sangre completa (IGRA) frente a péptidos de la proteína S. IFNγ se determinó mediante dos métodos de detección: CLIA y ELISA. Resultados: IGRA detectó respuesta celular T en TS tanto infectados como vacunados. La correlación de los dos métodos de detección de IFNγ fue muy alta (R >0,8) y la sensibilidad y la especificidad variaron entre 100 y 86% y 100-73% respectivamente. Hubo una concordancia muy alta entre los niveles de anticuerpos específicos y el ensayo IGRA aunque la correlación cuantitativa fue relativamente baja. En el grupo de infectados, una dosis de vacuna fue suficiente para alcanzar el «plateau¼ de respuesta inmune. IGRA fue claramente positivo en un profesional vacunado inmunosuprimido que presentaba anticuerpos contra la proteína S negativos. Conclusiones: IGRA frente a péptidos de la proteína-S es susceptible de automatización y constituye una herramienta prometedora para medir la respuesta inmune celular frente a SARS-CoV-2; es aplicable a un gran número de muestras y puede servir para valorar la protección, particularmente en los grupos vulnerables en riesgo de volver a exponerse a la infección, como los TS.

Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients.

To reduce the mortality of COVID-19 older patients, clear criteria to predict in-hospital mortality are urgently needed. Here, we aimed to evaluate the performance of selected routine laboratory biomarkers in improving the prediction of in-hospital mortality in 641 consecutive COVID-19 geriatric patients (mean age 86.6 ± 6.8) who were hospitalized at the INRCA hospital (Ancona, Italy). Thirty-four percent of the enrolled patients were deceased during the in-hospital stay. The percentage of severely frail patients, assessed with the Clinical Frailty Scale, was significantly increased in deceased patients compared to the survived ones. The age-adjusted Charlson comorbidity index (CCI) score was not significantly associated with an increased risk of death. Among the routine parameters, neutrophilia, eosinopenia, lymphopenia, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, procalcitonin, IL-6, and NT-proBNP showed the highest predictive values. The fully adjusted Cox regressions models confirmed that high neutrophil %, NLR, derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and low lymphocyte count, eosinophil %, and lymphocyte-to-monocyte ratio (LMR) were the best predictors of in-hospital mortality, independently from age, gender, and other potential confounders. Overall, our results strongly support the use of routine parameters, including complete blood count, in geriatric patients to predict COVID-19 in-hospital mortality, independent from baseline comorbidities and frailty.

A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patients.

In this article, we discuss the development of prognostic machine learning (ML) models for COVID-19 progression, by focusing on the task of predicting ICU admission within (any of) the next 5 days. On the basis of 6,625 complete blood count (CBC) tests from 1,004 patients, of which 18% were admitted to intensive care unit (ICU), we created four ML models, by adopting a robust development procedure which was designed to minimize risks of bias and over-fitting, according to reference guidelines. The best model, a support vector machine, had an AUC of .85, a Brier score of .14, and a standardized net benefit of .69: these scores indicate that the model performed well over a variety of prediction criteria. We also conducted an interpretability study to back up our findings, showing that the data on which the developed model is based is consistent with the current medical literature. This also demonstrates that CBC data and ML methods can be used to predict COVID-19 patients' ICU admission at a relatively low cost: in particular, since CBC data can be quickly obtained by means of routine blood exams, our models could be used in resource-constrained settings and provide health practitioners with rapid and reliable indications.

Complete blood cells count abnormalities in COVID-19 patients and their prognostic significance: Single center study in Makkah, Saudi Arabia.

OBJECTIVES: To evaluate the role of different peripheral blood count parameters as a cheap and rapid test in determination of coronavirus disease -19 (COVID-19) severity and patients' outcome. METHODS: The data of 462 confirmed COVID-19 patients who attended at the Security Force Hospital, Makkah, Saudi Arabia, from October 2020 to March 2021 was retrospectively reviewed and C. Patients with viral infection and respiratory diseases other than COVID-19 were excluded from the study. Complete blood count parameters were compared in accordance with the severity of the clinical presentation, age, and disease outcome. RESULTS: A total of 277 (60%) were male and 185 (40%) female. Clinically, 32 (6.9%) had severe illness and 430 (93.1%) showed moderate clinical disease. Organ failure occurred in 2.8% of the patients. There was significant leucocytosis, neutrophilia, lymphopenia, high neutrophil-lymphocyte (N/L) ratio, and anemia in patients with severe COVID-19 diseases as well as in non-survivors' cases (p<0.001). Similarly, the inflammatory markers (C-reactive protein [CRP] and serum ferritin) were significantly elevated in the above-mentioned 2 groups (p<0.001). Significant decrease of the platelets count was detectable in clinically severe cases and non-survivors (p<0.01). Older age (>60 years) was associated with high leucocyte, neutrophil count, lymphopenia, anemia, organ failure, and poor outcome. CONCLUSION: Leucocytosis, neutrophilia, lymphopenia, and high N/L ratio together with elevated serum level of ferritin and CRP are eminent features of COVID-19 severity. The inclusion of these parameters in the regimens for patients' categorization on admission will enable early effective intervention and proper decision making during clinical case management.

A transfer learning based deep learning model to diagnose covid-19 CT scan images.

To save the life of human beings during the pandemic conditions we need an effective automated method to deal with this situation. In pandemic conditions when the available resources becomes insufficient to handle the patient's load, then we needed some fast and reliable method which analyse the patient medical data with high efficiency and accuracy within time limitations. In this manuscript, an effective and efficient method is proposed for exact diagnosis of the patient whether it is coronavirus disease-2019 (covid-19) positive or negative with the help of deep learning. To find the correct diagnosis with high accuracy we use pre-processed segmented images for the analysis with deep learning. In the first step the X-ray image or computed tomography (CT) of a covid-19 infected person is analysed with various schemes of image segmentation like simple thresholding at 0.3, simple thresholding at 0.6, multiple thresholding (between 26-230) and Otsu's algorithm. On comparative analysis of all these methods, it is found that the Otsu's algorithm is a simple and optimum scheme to improve the segmented outcome of binary image for the diagnosis point of view. Otsu's segmentation scheme gives more precise values in comparison to other methods on the scale of various image quality parameters like accuracy, sensitivity, f-measure, precision, and specificity. For image classification here we use Resnet-50, MobileNet and VGG-16 models of deep learning which gives accuracy 70.24%, 72.95% and 83.18% respectively with non-segmented CT scan images and 75.08%, 80.12% and 99.28% respectively with Otsu's segmented CT scan images. On a comparative study we find that the VGG-16 models with CT scan image segmented with Otsu's segmentation gives very high accuracy of 99.28%. On the basis of the diagnosis of the patient firstly we go for an arterial blood gas (ABG) analysis and then on the behalf of this diagnosis and ABG report, the severity level of the patient can be decided and according to this severity level, proper treatment protocols can be followed immediately to save the patient's life. Compared with the existing works, our deep learning based novel method reduces the complexity, takes much less time and has a greater accuracy for exact diagnosis of coronavirus disease-2019 (covid-19).

How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory data.

The current gold standard for COVID-19 diagnosis, the rRT-PCR test, is hampered by long turnaround times, probable reagent shortages, high false-negative rates and high prices. As a result, machine learning (ML) methods have recently piqued interest, particularly when applied to digital imagery (X-rays and CT scans). In this review, the literature on ML-based diagnostic and prognostic studies grounded on hematochemical parameters has been considered. By doing so, a gap in the current literature was addressed concerning the application of machine learning to laboratory medicine. Sixty-eight articles have been included that were extracted from the Scopus and PubMed indexes. These studies were marked by a great deal of heterogeneity in terms of the examined laboratory test and clinical parameters, sample size, reference populations, ML algorithms, and validation approaches. The majority of research was found to be hampered by reporting and replicability issues: only four of the surveyed studies provided complete information on analytic procedures (units of measure, analyzing equipment), while 29 provided no information at all. Only 16 studies included independent external validation. In light of these findings, we discuss the importance of closer collaboration between data scientists and medical laboratory professionals in order to correctly characterise the relevant population, select the most appropriate statistical and analytical methods, ensure reproducibility, enable the proper interpretation of the results, and gain actual utility by using machine learning methods in clinical practice.