The Characteristics and Laboratory Findings of SARS-CoV-2 Infected Patients during the First Three COVID-19 Waves in Portugal-A Retrospective Single-Center Study

Biomarkers for SARS-CoV-2 infection. A narrative review

COVID-19 is an infectious disease caused by SARS-CoV-2 with devastating effects on health-care systems. The magnitude of the problem has moved physicians and investigators to identify strategies to detect patients at a high risk of severe disease. The aim of this study was to identify the most relevant biomarkers in the published literature and their correlation with clinical outcomes. To this end, we performed a revision of studies that investigated laboratory abnormalities in patients with COVID-19, comparing non-severe and severe patients. Blood biomarkers were classified into five main categories: hematological, coagulation related to the liver or kidney, and inflammatory. From our analysis, the most relevant biomarkers associated with severe infection for each category were increased levels of leukocytes, neutrophils, and neutrophil-to-lymphocyte ratio; decreased platelet count; and high levels of aspartate transaminase, alanine transaminase, creatine kinase, troponin, creatinine, and blood urea nitrogen, C-reactive protein, ferritin, and IL-6. Moreover, lactate dehydrogenase and D-dimer levels were independent risk factors for death.

Quantitative Analysis of the Minimum Clinically Important Difference in the Brief Pain Inventory After Total Knee Arthroplasty

Purpose

Research on the Minimum Clinically Important Difference (MCID) of the Brief Pain Inventory (BPI) following Total Knee Arthroplasty (TKA) is limited. This study addresses this gap by determining the MCID of the BPI for patients undergoing primary TKA.

Patients and Methods

This study was designed to quantitatively determine the MCID of the BPI for patients undergoing primary TKA. A prospective cohort of 288 patients was evaluated, with the BPI administered both preoperatively and at a one-year follow-up. The MCID was calculated using two primary approaches: the anchor-based method, considered the gold standard, and the distribution-based method. Additionally, this study explored various calculation approaches within the distribution-based framework, benchmarking them against the anchor-based method. The distribution-based methods included calculations based on Standard Deviation (SD), Effect Size (ES), Standardized Response Mean (SRM), and Standard Error of Measurement (SEM). All statistical calculations were performed using established formulas.

Results

The anchor-based method determined the MCID for BPI pain severity to be 3.9 points, the pain interference dimension to be 5.8 points, and the total score to be 9.7 points. Comparisons with the gold standard highlighted the 0.65ES, 1.96SEM, and 0.5SRM methods as the most suitable approaches for distribution-based MCID estimation.

Conclusion

The MCID for BPI in TKA patients was established using both anchor-based and distribution-based methods. When anchor-based determination is impractical, the distribution-based methods-0.65ES, 1.96SEM, and 0.5SRM-are recommended for MCID calculation.

13-year-old-male with a left open humerus fracture with concomitant intramuscular mid-substance biceps rupture: A case report

A 13-year-old male presented with an open left humeral shaft fracture with intramuscular distal biceps rupture after being struck by a car. He underwent washout, humerus fixation, and open biceps repair. Immediate postoperative course was complicated by deep infection and failure of biceps repair. He subsequently required two additional surgeries. One year later, he exhibited full, painless elbow range of motion and biceps strength. This case is the first to report an open humeral shaft fracture with concomitant intramuscular, mid-substance biceps rupture in a pediatric patient. This was successfully treated with a full functional recovery.

A COVID-19 specific multiparametric and ECG-based score for the prediction of in-hospital mortality: ELCOVID score

We aimed to develop and validate a COVID-19 specific scoring system, also including some ECG features, to predict all-cause in-hospital mortality at admission. Patients were retrieved from the ELCOVID study (ClinicalTrials.gov identifier: NCT04367129), a prospective, multicenter Italian study enrolling COVID-19 patients between May to September 2020. For the model validation, we randomly selected two-thirds of participants to create a derivation dataset and we used the remaining one-third of participants as the validation set. Over the study period, 1014 hospitalized COVID-19 patients (mean age 74 years, 61% males) met the inclusion criteria and were included in this analysis. During a median follow-up of 12 (IQR 7-22) days, 359 (35%) patients died. Age (HR 2.25 [95%CI 1.72-2.94], p < 0.001), delirium (HR 2.03 [2.14-3.61], p = 0.012), platelets (HR 0.91 [0.83-0.98], p = 0.018), D-dimer level (HR 1.18 [1.01-1.31], p = 0.002), signs of right ventricular strain (RVS) (HR 1.47 [1.02-2.13], p = 0.039) and ECG signs of previous myocardial necrosis (HR 2.28 [1.23-4.21], p = 0.009) were independently associated to in-hospital all-cause mortality. The derived risk-scoring system, namely EL COVID score, showed a moderate discriminatory capacity and good calibration. A cut-off score of ≥ 4 had a sensitivity of 78.4% and 65.2% specificity in predicting all-cause in-hospital mortality. ELCOVID score represents a valid, reliable, sensitive, and inexpensive scoring system that can be used for the prognostication of COVID-19 patients at admission and may allow the earlier identification of patients having a higher mortality risk who may be benefit from more aggressive treatments and closer monitoring.

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.

Clinical Application of Serum Interleukin-6 Combined with Inflammatory Cytokines in the Dynamic Monitoring of Patients with Acute Cholecystitis

Objective

To investigate the dynamic fluctuations of serum interleukin-6 (IL-6), procalcitonin (PCT), and neutrophil counts in individuals diagnosed with acute cholecystitis. Additionally, the research seeks to investigate the potential clinical significance of these biomarkers in the early stages of acute cholecystitis.

Methods

This retrospective cohort study included one hundred patients with acute cholecystitis (60 with mild acute cholecystitis and 40 with severe cholecystitis) admitted to our hospital between January 2022 and December 2022 were included. The levels of various cytokines, PCT and neutrophils in serum on days 1, 3, 5, and 7 were dynamically detected. The difference in each indicator between the two groups was analysed, and the diagnostic value of each indicator for acute cholecystitis was evaluated using a receiver operating characteristic (ROC) curve.

Results

IL-6 and PCT levels and neutrophil counts were significantly higher in patients with moderate and severe cholecystitis than those in those with mild cholecystitis (P <0.01). The AUC values for the three indicators were all greater than 60%, and the AUC value for the joint diagnosis of the three indicators reached 90%.

Conclusion

Serum interleukin-6 combined with PCT and neutrophil count is helpful to determine the degree of disease development in patients with acute cholecystitis. The advantage of dynamic monitoring of the three indicators is that the detection is simple and worthy of clinical promotion.