Diagnostic value of platelet indices in COVID 19 infection: a case-control study from a single tertiary care center

Assessment of the hematological profiles among COVID-19 patients during the first and second waves in Ethiopia: A multicenter retrospective cohort study

Background

The coronavirus disease 2019 is highly infectious and patients with coronavirus diseases demonstrated a series of clinical symptoms caused by severe acute respiratory syndrome coronavirus-2. Without a break of the wave's hematological profile of the patients is still ambiguous and differs from wave to wave.

Objective

This study aimed to assess the hematological profile among coronavirus disease 2019 patients during the first and the second waves in Ethiopia.

Methods

A multi-centered facility-based retrospective cohort study design was conducted at six coronavirus disease 2019 treatment centers. A total of 538 study participants were enrolled in the selected coronavirus disease 2019 treatment centers during the first and second waves of the pandemic. The demographic characteristics, underlying diseases, symptoms, and hematological parameters of patients were recorded. Data were entered into Epi-Data Manager 4.6 and analyzed using STATA 14.2. An independent sample t-test was used to assess the mean differences in hematological parameters across waves. Associations between categorical variables across waves were also determined using Chi-square and Fisher exact tests.

Results

Among the total study participants, 240 (44.6%) and 298 (55.4%) patients were taken from wave-1 and wave-2, respectively. The average age of the study participants was 56.44 ± 16.25 years. The most frequent comorbidities in this study were hypertension, diabetes mellitus, ischemic heart disease, and asthma. The most presenting symptoms of COVID-19 infection across the two waves were presented. In the first wave, dry cough 166 (69.2%), fatigue 153 (63.75%), shortness of breath 148 (61.67%), and fever accounted 116 (48.33%), while during the second wave, dry cough 242 (81.2%), fatigue 244 (81.88%) shortness of breath 204 (68.47%) and fever account 180 (60.40%). White blood cells (WBC), neutrophils, and lymphocytes had shown increment during the first wave. Platelet count and platelet distribution width (p < 0.001) had significant mean differences across the two waves, while the other had no significant mean difference.

Conclusion

In the present study, dry cough, fatigue, shortness of breath, and fever were found to be the most presenting symptoms of COVID-19 infection across the two waves. Only the platelet count and platelet distribution width had significant mean differences across the two waves, while the other had no significant mean difference across waves.

Platelet distribution width (PDW) as a significant correlate of COVID-19 infection severity and mortality

SARS-CoV-2 infection may cause a wide spectrum of symptoms, from asymptomatic, to mild respiratory symptoms and life-threatening sepsis. Among the clinical laboratory biomarkers analyzed during COVID-19 pandemic, platelet indices have raised great interest, due to the critical involvement of platelets in COVID-19-related thromboinflammation. Through an electronic literature search on MEDLINE, CINAHL, PubMed, EMBASE, Web of Science, and preprint servers we performed and updated a systematic review aimed at providing a detailed analysis of studies addressing the potential clinical utility of platelet distribution width, platelet distribution width (PDW), in laboratory medicine, exploring the possible association between increased PDW levels, disease severity, and mortality in COVID-19. Our systematic review revealed a wide heterogeneity of COVID-19 cohorts examined and a lack of homogenous expression of platelet indices. We found that 75 % of studies reported significantly elevated PDW values in COVID-19 infected cohorts compared to healthy/non-COVID-19 controls, and 40 % of studies reported that patients with severe COVID-19 showed increased PDW values than those with less-than-severe illness. Interestingly, 71.4 % of studies demonstrated significant increased PDW values in non survivors vs. survivors. Overall, these results suggest that platelets are critically involved as major players in the process of immunothrombosis in COVID-19, and platelet reactivity and morphofunctional alterations are mirrored by PDW, as indicator of platelet heterogeneity. Our results confirm that the use of PDW as prognostic biomarkers of COVID-19 sepsis still remains debated due to the limited number of studies to draw a conclusion, but new opportunities to investigate the crucial role of platelets in thrombo-inflammation are warranted.

Nomogram to predict the incidence of delirium in elderly patients with non-severe SARS-CoV-2 infection

Objective

To construct and validate nomogram models that predict the incidence of delirium in elderly patients with non-severe SARS-CoV-2 infection.

Methods

Elderly patients (≥65y) tested positive for SARS-CoV-2 infection at the hospital were included. We used the 3-min diagnostic Confusion Assessment Method for delirium diagnosis. Least absolute shrinkage and selection operator (LASSO) logistical regression analysis was performed to explore potential independent influencing factors of delirium. A predict model visualized by nomogram was constructed based on the confirmed variables. The predictive accuracy and clinical value of the model were evaluated using receiver operating characteristic (ROC) curves.

Results

The data of 311 elderly patients were analyzed, of whom 73 (23.47%) patients were diagnosed with delirium. Three independent influencing factors of delirium were confirmed: age (OR1.16,1.11-1.22), Glomerular filtration rate (OR 0.98,0.97-0.99), platelet-large cell ratio (1.06,1.02-1.10). These parameters were used to create a nomogram to predict the development of delirium, which showed good predictive accuracy confirmed by the ROC curves (AUC 0.82,0.76-0.88).

Conclusion

We construct a credible nomogram to predict the development of delirium in elderly patients with Non-severe SARS-CoV-2 infection. Our finding may be useful to physicians in early prevention and treatment of delirium.

The Role of Platelet Parameters in Predicting the Disease Severity of COVID-19 Patients: A Hospital-Based Study

Background and objective Globally, a large number of people have been impacted by the extremely contagious coronavirus disease 2019 (COVID-19) infection, and several pieces of literature were published on hematological parameter changes in this infection, particularly focusing on leucocytes. In this study, we have analyzed the platelet parameters and platelet-leucocyte ratios in COVID-19 patients and correlated them with the disease severity. Methods The COVID-19 patients who were hospitalized during the second peak of the pandemic were assessed. The platelet count and indices, platelet to lymphocyte ratio (PLR), neutrophil to platelet ratio (NPR), and clinical severity of each patient were analyzed. The significance of parameters and clinical severity was evaluated using analysis of variance (ANOVA) and the Kruskal Wallis test. A bivariate analysis was performed to assess the strength of the association. Receiver operating characteristic (ROC) curves were plotted to detect the predictive value of parameters for disease severity. Results The data of 132 COVID-19 patients has been evaluated. The average mean age was 45.60 ± 15.76 years with slight female predominance. Thrombocytopenia was found in 33% of cases with the majority of them being mild. Age, platelet distribution width (PDW), and PLR and NPR parameters were significantly (p-value <0.05) associated with disease severity. ROC curves showed age, PDW, PLR, NPR, absolute neutrophil count (ANC), and absolute lymphocyte count (ALC) had significant prediction values for clinical severity. Conclusions Platelet parameters may not accurately reflect the severity of the disease, but when combined with leucocyte parameters and their ratios (PLR and NPR), they offer important information about disease severity.

Prognostic Potential of Thrombocyte Indices, Acute Phase Proteins, Electrolytes and Acid-Base Markers in Canine Parvovirus Infected Dogs With Systemic Inflammatory Response Syndrome

Dogs with canine parvovirus enteritis (CPVE) that develop systemic inflammatory response syndrome (SIRS) frequently have a poor prognosis. The aim of the study was to assess the prognostic potential of thrombocyte indices, acute phase proteins, electrolytes, and acid-base markers in CPVE puppies with SIRS (CPVE-SIRS+) at admission. A case-controlled, prospective, and observational study was performed on 36 CPVE puppies. Mean concentrations of C-reactive protein (CRP), albumin, thrombocyte count, mean platelet volume (MPV), platelet distribution width (PDW), sodium (Na+), potassium (K+), chloride (Cl-) and ionized calcium (iCa) were measured and strong ion difference 3 (SID3), ATOT-albumin and ATOT-total protein were determined in CPVE-SIRS+ survivors and nonsurvivors. A prognostic cut-off value for predicting the disease outcome was determined by receiver operating characteristic (ROC) curve analysis. The mean values of MPV, PDW and CRP were significantly higher and the mean values of albumin, Cl- and ATOT-albumin were significantly lower in CPVE-SIRS+ nonsurvivor than CPVE-SIRS+ survivor puppies on the day of admission, but the thrombocyte count, Na+, K+, iCa, SID3 and ATOT- total protein values did not differ significantly. The positive predictive values (PPVs) for survival using cut-off value of MPV (≤15.08 fL), PDW (≤14.85%), CRP (≤180.7 mg/L), albumin (≥1.795 g/dL), Cl- (≥96.00 mmol/L), and ATOT-albumin (≥7.539) were determined as 100%, 100%, 100%, 80%, 100%, and 80%, respectively with better area under ROC curve and sensitivity. Based on sensitivity, specificity, and PPVs from ROC analysis, it is concluded that the determination of Cl- concentration and MPV at admission followed by CRP will serve as the most appropriate biomarkers in predicting the disease outcome of CPVE puppies that develop SIRS.

Platelet-to-lymphocyte ratio and mean platelet volume-to-platelet count ratio for predicting mortality in critical COVID-19 patients

Introduction: Defining the markers that can be used in clinical practice for predicting the mortality of critical patients will be cautionary for taking necessary measures in high-risk cases. Although there are a large number of studies conducted during the pandemic, no mortality marker to predict the prognosis of intensive care unit (ICU) patients with COVID-19 has yet been defined. Platelet indices can be easily evaluated with a complete blood count (CBC) analysis, one of the most accessible tests worldwide. This study aimed to evaluate the role of platelet indices such as mean platelet volume (MPV), platelet distribution width (PDW), plateletcrit (PCT), platelet-to-lymphocyte ratio (PLR), and MPV-to-platelet count ratio (MPV/PLT) in predicting the mortality of ICU patients with COVID-19. Material and Method: This single-center, retrospective, cross-sectional study included 201 critical COVID-19 patients over 18 years of age who were hospitalized in ICU between August 2020 and February 2021. Patients were divided into two groups as survivors and non-survivors. The relationship of MPV, PDW, PCT, PLR, and MPV/PLT parameters evaluated at ICU admission with mortality was investigated. Results: There was no significant difference between the survivor and non-survivor groups in terms of platelet count, MPV, PCT, and PDW. The comparison of the platelet ratios revealed higher PLR and MPV/PLT ratio in the non-survivor group than in the survivor group (p