Metodo LAMP como alternativa diagnostica para la deteccion del virus SARS-CoV-2

Summary Introduction: The SARS-CoV-2 coronavirus, that causes the COVID-19 disease, has become a global public health problem that requires the implementation of rapid and sensitive diagnostic tests. Aim(s): To evaluate and compare the sensitivity of LAMP assay to a standard method and use RT-LAMP for the diagnosis of SARS-CoV-2 in clinical samples from Colombian patients. Method(s): A descriptive and cross-sectional study was conducted. A total of 25 nasopharyngeal swab samples including negative and positive samples for SARS-CoV-2 were analyzed, through the RT-LAMP method compared to the RT-qPCR assay. Result(s): LAMP method detected ~18 copies of the N gene, in 30 min, evidenced a detection limit similar to the standard method, in a shorter time and a concordance in RT-LAMP of 100% with the results. Conclusion(s): RT-LAMP is a sensitive, specific, and rapid method that can be used as a diagnostic aid of COVID-19 disease.Copyright © 2021. All Rights Reserved.

Identification Symptoms and Underlying Diseases Related to COVID-19 And Prediction of Death Status Using Artificial Neural Network and Logistic Regression: A Data Mining Approach.

Background and Objectives: Due to the high prevalence of COVID-19 disease and its high mortality rate, it is necessary to identify the symptoms, demographic information and underlying diseases that effectively predict COVID-19 death. Therefore, in this study, we aimed to predict the mortality behavior due to COVID-19 in Khorasan Razavi province. Method(s): This study collected data from 51, 460 patients admitted to the hospitals of Khorasan Razavi province from 25 March 2017 to 12 September 2014. Logistic regression and Neural network methods, including machine learning methods, were used to identify survivors and non-survivors caused by COVID-19. Result(s): Decreased consciousness, cough, PO2 level less than 93%, age, cancer, chronic kidney diseases, fever, headache, smoking status, and chronic blood diseases are the most important predictors of death. The accuracy of the artificial neural network model was 89.90% in the test phase. Also, the sensitivity, specificity and area under the rock curve in this model are equal to 76.14%, 91.99% and 77.65%, respectively. Conclusion(s): Our findings highlight the importance of some demographic information, underlying diseases, and clinical signs in predicting survivors and non-survivors of COVID-19. Also, the neural network model provided high accuracy in prediction. However, medical research in this field will lead to complementary results by using other methods of machine learning and their high power.Copyright © 2022 The Authors.

Advantages of Total Bilirubin for Predicting Malignant Obstructive Jaundice, A Combination of the Pandemic Era and Limited Resources Settings

BACKGROUND: Hepatopancreatobiliary (HPB) cancer incidence and mortality are increasing worldwide. An initial diagnostic predictor is needed for recommending further diagnostic modalities, referral, and curative or palliative decisions. There were no studies conducted in area with limited accessibility setting of the COVID-19 pandemic, coupled with limited human resources and facilities. AIM: We aimed to investigate the advantages of total bilirubin for predicting malignant obstructive jaundice, a combination of the pandemic era and limited resources settings. METHOD(S): Data from all cholestasis jaundice patients at M. Djamil Hospital in Pandemic COVID-19 period from July 2020 to May 2022 were retrospectively collected. The data included demographics, bilirubin fraction results, and final diagnosis. Bivariate analysis for obtain demographic risk factor, and Receiver Operating Characteristics (ROC) analysis for getting bilirubin value. RESULT(S): Of a total 132 patients included, 35.6% were malignant obstructive jaundice, and Pancreatic adeno ca was the most malignant etiology (34.4%). Bivariate analysis showed a significant correlation between age and malignant etiology (p = 0,024). Direct and total Bilirubin reach the same level of Area Under Curve (AUC). Total bilirubin at the cutoff point level of 10.7 mg/dl had the most optimal results on all elements of ROC output, AUC 0.88, sensitivity 76.6%, specificity 90.1%, +LR 8.14, and-LR 0.26. CONCLUSION(S): The bilirubin fraction is a good initial indicator for differentiating benign and malignant etiology (AUC 0.8-0.9) in pandemic era and resource-limited areas to improve diagnostic effectiveness and reduce referral duration.Copyright © 2023 Avit Suchitra, M. Iqbal Rivai, Juni Mitra, Irwan Abdul Rachman, Rini Suswita, Rizqy Tansa.

Procalcitonin as a Prognostic Marker of Complicated Appendicitis

Introduction: Acute appendicitis is the most common cause of acute abdominal pain as well as one of the most frequently performed procedures in general surgery. Different prognostic laboratory markers have been studied to identify patients with complicated appendicitis and it is unknown whether the level of procalcitonin in adults could be used as a predictive marker. From a cut-off point, Does procalcitonin have predictive value for complicated appendicitis? Methods: Prospective, observational study. Patients from the Civil Hospital of Guadalajara with a diagnosis of Appendicitis, presurgical laboratory studies and Procalcitonin, and undergo appendectomy in this institution. A calculated sample was obtained based on the surgeries performed annually. Result(s): 80 appendicectomies were performed in the 12-month period (2021;COVID pandemic) obtaining: 37 patients with uncomplicated appendicitis (Phase I and II) 43 patients with complicated appendicitis (Phase III and IV) The procalcitonin levels of both groups were analyzed to demonstrate differences between them, Mann-Whitney U test gives us as a result a p value <0.05. For the cut-off point at the most suitable procalcitonin level for this sample we decided to use the Yauden index method in the analysis of the ROC curve: it is observed that the cut-off point with a sensitivity of 72.1% and a specificity of 81.1% for the sample is 0.305. Conclusion(s): Procalcitonin has been shown to be a useful marker for discriminating the severity of appendicitis and that the best cutoff point for this sample is 0.3 ng/dl.

Direct bilirubin and the neutrophil-to-monocyte ratio timely predict intensive care unit admission in patients with severe acute respiratory syndrome coronavirus-2 infection (COVID-19)

Objective: Intensive care units (ICUs) collapsed under the global wave of coronavirus disease 2019 (COVID-19). Thus, we designed a clinical decision-making model that can help predict at hospital admission what patients with COVID-19 are at higher risk of requiring critical care. Method(s): This was a cross-sectional study in 119 patients that met hospitalization criteria for COVID-19 including less than 30 breaths per minute, peripheral oxygen saturation < 93%, and/or >= 50% lung involvement on imaging. Depending on the need for critical care, patients were retrospectively assigned to ICU and non-ICU groups. Demographic, clinical, and laboratory parameters were collected at admission and analyzed by classification and regression tree (CRT). Result(s): Forty-five patients were admitted to ICU and 80% of them were men older than 57.13 +/- 12.80 years on average. The leading comorbidity in ICU patients was hypertension. The CRT revealed that direct bilirubin (DB) > 0.315 mg/dl together with the neutrophil-to-monocyte ratio (NMR) > 15.90 predicted up to correctly in 92% of the patients the requirement of intensive care management, with sensitivity of 93.2%. Preexisting comorbidities did not influence on the tree growing. Conclusion(s): At hospital admission, DB and NMR can help identify nine in 10 patients with COVID-19 at higher risk of ICU admission.Copyright © 2022 Sociedad Medica del Hospital General de Mexico.

Design of a cost-effective diagnosis tool for SARSCov-2 variant detection through a next generation sequencing (NGS) based strategy

Background/Objectives: Current pandemic situation, together with the continuous emergence of new SARS-CoV-2 variants reveal the need to develop a more versatile tool than PCR-based methods that allows both high throughput COVID-19 diagnostic and specific variant detection at reduced cost and fast turnaround times. Thus, with the aim of overcoming current test limitations and providing a strategy with these characteristics arises our novel next generation sequencing based approach. Method(s): The developed strategy works with RNA samples obtained from nasopharyngeal swabs. RNA samples are processed with our custom laboratory protocol and can be sequenced with any Illumina platform to generate results within a 24h timeframe. A tailored bioinformatic pipeline analyzes the data and generates a clinical-level report. Result(s): Clinical validation results have shown that the designed solution, sensitively and specifically identifies negative and positive samples that display a broad range in viral loads and readily identifies the following major SARS-CoV-2 variants of concern (VoC): Alpha, Beta, Gamma, Delta, Lambda and Omicron (BA.1 and BA.2). Conclusion(s): The versatility of our solution allows the capability of identifying the presence of other common respiratory viruses as well as identifying patients at risk through the identification of susceptibility human variants in the host. This, together with the possibility of easily adding new VoC as they emerge, will make VoC monitoring in entire populations feasible, providing a new perspective on the application of NGS methods in the field of clinical microbiology.

Evaluation of Lung Ultrasound in Assessment of Critically Ill patients in Respiratory Intensive Care Unit

Reaching a proper diagnosis for critically ill patients is like collecting pieces of puzzle and bed side lung ultrasound (LUS) becomes a crucial piece complementary to clinical and laboratory pieces. It is a bed side, real time tool for diagnosis of patients in ICU who are critical to be transferred to radiology unit especially in Covid-19 pandemic with risk of infection transmission. The aim was to evaluate the accuracy of lung ultrasound in assessment of critically ill patients admitted to Respiratory Intensive Care Unit (RICU), moreover to assess its diagnostic performance in different pulmonary diseases as compared to the gold standard approach accordingly. This observational prospective (cross sectional) study with a total 183 patients who met the inclusion criteria,were selected from patients admitted at the RICU;Chest Department, Zagazig University Hospitals, during the period from September 2019 to September 2021. LUS examination was performed to diagnose the different pulmonary diseases causing RF. All cases were examined by LUS on admission. From a total 183 patients, 111 patients 60.7% were males and 72 patients 39.3% were females, with a mean age of 56+/-12.77 years, 130 patients were breathing spontaneously received conservative management with O2 therapy, 32 patients needed NIV while 21 patients needed IMV with ETT. Exacerbated COPD was the most common disease finally diagnosed followed by bacterial pneumonia, exacerbated ILD, post Covid-19 fibrosis and pulmonary embolism in32, 29,27, 19 and 11 patients respectively with corresponding diagnostic accuracy of LUS 97.3%, AUC=0.943, 93.9% (AUC=0.922), 96.7%(AUC=0.920), 97.8%, AUC=0.895, and 97.8% respectively, while Covid-19 pneumonia was the final diagnosis in 8 patients with LUS diagnostic accuracy of 97.8% (AUC=0.869) with no statistical significant difference p-value=0.818 with bacterial pneumonia in distribution of US profiles. A profile was the commonest detected US profile among the studied patients followed by B profile, C profile, A/B profile and A' profile in 37.2%, 24.6%, 15.8% 4.9%, and 3.8% of cases respectively. Bed side LUS has a reliable, valuable diagnostic performance when integrated with clinical and laboratory data for the diagnosis of most pulmonary diseases in RICU.Copyright © 2023, Colegio de Farmaceuticos de la Provincia de Buenos Aires. All rights reserved.

Deep learning-based COVID-19 triage tool: An observational study on an X-ray dataset

Background: Easy availability, low cost, and low radiation exposure make chest radiography an ideal modality for coronavirus disease 2019 (COVID-19) detection. Objective(s): In this study, we propose the use of an artificial intelligence (AI) algorithm to automatically detect abnormalities associated with COVID-19 on chest radiographs. We aimed to evaluate the performance of the algorithm against the interpretation of radiologists to assess its utility as a COVID-19 triage tool. Material(s) and Method(s): The study was conducted in collaboration with Kaushalya Medical Trust Foundation Hospital, Thane, Maharashtra, between July and August 2020. We used a collection of public and private datasets to train our AI models. Specificity and sensitivity measures were used to assess the performance of the AI algorithm by comparing AI and radiology predictions using the result of the reverse transcriptase-polymerase chain reaction as reference. We also compared the existing open-source AI algorithms with our method using our private dataset to ascertain the reliability of our algorithm. Result(s): We evaluated 611 scans for semantic and non-semantic features. Our algorithm showed a sensitivity of 77.7% and a specificity of 75.4%. Our AI algorithm performed better than the radiologists who showed a sensitivity of 75.9% and specificity of 75.4%. The open-source model on the same dataset showed a large disparity in performance measures with a specificity of 46.5% and sensitivity of 91.8%, thus confirming the reliability of our approach. Conclusion(s): Our AI algorithm can aid radiologists in confirming the findings of COVID-19 pneumonia on chest radiography and identifying additional abnormalities and can be used as an assistive and complementary first-line COVID-19 triage tool.Copyright © Cancer Research, Statistics, and Treatment.

The Predictive Value of Cystatin C for AKI in Patients with COVID-19.

Objective. To evaluate a potential of cystatin C blood concentration to predict acute kidney injury (AKI) in patients with severe and extremely severe pneumonia associated with a COVID-19. Materials and methods. An observational prospective study of 117 patients with severe and extremely severe pneumonia associated with a COVID-19 in an ICU setting was conducted in 2020-2022 (site: multifunctional Medical Center, 1586 Military Clinical Hospital of the Ministry of Defense of Russia, Moscow Region, Russia). Routine laboratory tests and instrumental examinations were performed according to generally accepted protocols. Cystatin C concentrations in blood (s-CysC) and urine (u-CysC) were measured by immunoturbidimetric method. Results. AKI was diagnosed in 21 (17.9%) patients, kidney dysfunction without AKI was found in 22 (18.8%) patients with severe and extremely severe pneumonia associated with COVID-19. s-CysC and u-CysC levels in the group of patients with AKI were statistically significantly higher compared to the levels in the group of patients without AKI. The levels of s-CysC obtained within Day 1 - T (-1), and Day 2 - T (-2) prior to AKI onset turned out to be the independent factors for AKI development in patients with severe and extremely severe pneumonia associated with COVID-19: OR 5.37, Wald chi-square 5.534 (CI: 1.324;21.788);P=0.019 and OR 3.225, Wald chi-square 4.121 (CI: 1.041;9.989);P=0.042, respectively. s-CysC T (-2) value is informative, and s- CysC T (-1) is a highly informative predictor of AKI development in severe and extremely severe pneumonia associated with COVID-19: ROC AUC 0.853 (95% CI, 0.74-0.966), P_0.001) with 90% sensitivity and 73% specificity at a cut-off of 1.67 mg/L, and ROC AUC 0.905 (95% CI, 0.837-0.973), P_0.001) with 90% sensitivity and 73% specificity at a cut-off of 1.69 mg/l, respectively. Serum CysC levels started increasing 3 days prior to AKI onset, outpacing the increase of SCr levels. The u-CysC levels were not predictive of AKI development. Impaired renal function probability was increasing with patients' age (P_0.0001). Conclusions. Serum CysC seems to be a statistically significant predictor of AKI. s-CysC levels started increasing 3 days prior to AKI onset, surpassing the increase of SCr levels in patients with severe and extremely severe pneumonia associated with COVID-19. Urine CysC did not achieve statistical significance as a predictor for AKI, although u-CysC concentrations were significantly higher on days 3, 2, 1 prior to AKI onset and on the day of AKI onset in the group of patients with AKI.Copyright © 2023, V.A. Negovsky Research Institute of General Reanimatology. All rights reserved.

Comparison of Diagnostic Accuracy of CRP Versus Ferritin in COVID Patients as a Marker of Severity of Disease Taking who Severity Classification as Gold Standard

Objective: To determine the diagnostic accuracy of elevated C reactive protein (CRP) and ferritin in predicting severe Covid-19 infection using the World Health Organization's (WHO) Covid-19 severity classification as gold standard. Study Design: Descriptive study. Place and Duration of Study: This study was conducted at the Pak Emirates Military Hospital, Rawalpindi, from January 1st 2021 till April 30th 2021. Ethical review committee's (ERC) approval was taken and good clinical practice guidelines were followed. Material(s) and Method(s): Baseline blood samples were sent to the hospital laboratory for the measurement of C reactive protein and ferritin levels. PCR was taken as gold standard for the diagnosis of Corona virus disease. Patients were classified into severe and non-severe categories using WHO classification of severity. Sensitivity, specificity, diagnostic accuracy, negative predictive value and positive predictive value were calculated for elevated CRP and ferritin. Result(s): There were 65 (57.5%) patients who had severe Covid-19 disease and 48 (42.5%) patients who had non-severe Covid-19 disease. Among the patients with severe Covid-19, 57 (87.7%) had elevated CRP levels, and 50 (76.9%) patients had elevated ferritin levels. Testing ferritin levels, against the severity of Covid-19 patients, there was a sensitivity of 76.9%, specificity of 79.2%, positive predictive value (PPV) of 83.3%, negative predictive value (NPV) of 71.7% and diagnostic accuracy of 77.8%. Testing CRP levels, there was a sensitivity of 87.7%, specificity of 85.4%, PPV of 89.1%, NPV of 83.6% and diagnostic accuracy of 86.7%. Conclusion(s): The results from our study show that CRP has a slightly improved diagnostic accuracy as compared to ferritin. However, both these markers have value in the prediction of severity of Covid-19 infection.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

The Analysis of Dynamic Processes of Virus Transmission: How Could Diagnostic Tests and Vaccinations Can Stop COVID-19 Pandemic?

Objectives: COVID-19 reached its fourth year of pandemic since 2020. The repeated waves of infections have been driven by multiple factors such as pathological traits of variants, diagnostic accuracy, and vaccination conditions. This study revisits and analyzes the dynamic processes of viral transmission to generate new scientific knowledge. Method(s): A cascade model of viral transmission from one case to another was developed, and theoretically analyzed how the number of infected cases at time t, D+[t], can be changed at time t+1, D+[t+1], considering six parameters: 1) k:level of transmission, 2) Rt: effective reproduction number, 3) rho: capture rate of infected cases, 4) theta: immunity protection rate in individuals, 5) epsilon: evasion rate from vaccines, and 6) Sn: test sensitivity. Result(s): The formula which associates D+[t] with D+[t+1] was given as follows: D+[t+1] = K.D+[t], where K = {(1-Sn) + (1-rho) / rho}{1-Rtk (1-theta(1-epsilon))k} / {1-Rt (1-theta(1-epsilon))}. Also, assuming K be smaller than 1, the lower limit of test sensitivity to stop the viral transmission was formulated: Sn > {Rt (1-theta(1-epsilon))-Rtk(1-theta(1-epsilon))k} / {(1-Rtk(1-theta(1-epsilon))k)rho}. In example computations, the formula indicated that a one-off PCR test with the sensitivity of 85% would not be sufficient to contain highly contagious infections such as the Omicron variants, and that it would be practically impossible to control the situation with the immune-evasive sub-variants in circulation. Conclusion(s): The theory developed in this study broadens the science on evidence-based public health and will be useful for outcomes studies and informed decisions on public policy for pandemic control.Copyright © 2023

Clinical significance of serum interleukin 6 in elderly patients infected with severe acute respiratory syndrome coronavirus 2 omicron variant and its correlation with underlying diseases.

Objective To investigate the clinical significance of serum interleukin 6 (IL-6) in elderly patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant and its correlation with underlying diseases. Methods A total of 22 elderly patients (80 years old) infected with omicron variant, who were admitted to Department of Infectious Diseases, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. to Jun. 2022 and tested positive for SARS-CoV-2 RNA, were included. The level of serum IL-6 was measured by flow cytometry, and the level of serum C reactive protein (CRP) was measured by immunonephelometry. Patients were divided into pneumonia group (16 cases) and non-pneumonia group (6 cases) according to the imaging examination results, and were divided into severe group (severe and critical type, 5 cases) and non-severe group (mild and normal type, 17 cases) according to the condition. Binary logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the correlation between serum IL-6 and CRP levels and the severity of the disease and whether it would progress to pneumonia. Meanwhile, the relationships between underlying diseases and serum IL-6 level were explored. Results Among the 22 patients, 6 were mild, 11 were normal, 3 were severe, and 2 were critical. The baseline serum IL-6 level in the pneumonia group was significantly higher than that in the non-pneumonia group (20.16+/-12.36pg/mL vs 5.42+/-1.57 pg/mL, P=0.009), and there was no significant difference in baseline serum CRP level between the 2 groups (P0.05). There were no significant differences in baseline serum IL-6 or CRP levels between the severe group and the non-severe group (both P0.05). Logistic regression analysis showed that the baseline serum IL-6 and CRP might be related to pneumonia after infection with omicron variant (odds ratio OR=2.407, 95% confidence interval CI0.915-6.328;OR=1.030, 95% CI 0.952-1.114). ROC curve analysis showed that the area under curve values of serum IL-6 and CRP in predicting the progression to pneumonia were 0.969 (95% CI 0.900-1.000) and 0.656 (95% CI 0.380-0.932), respectively, with statistical significance (Z=2.154, P=0.030). There were no significant differences in the baseline serum IL-6 level or proportions of severe patients or pneumonia patients among patients with or without hypertension, diabetes mellitus, coronary heart disease, chronic kidney disease or chronic obstructive pulmonary disease (all P0.05). The baseline serum IL-6 levels of the omicron variant infected elderly patients with 1, 2, and 3 or more underlying diseases were 12.50 (9.15, 21.75), 23.55 (9.63, 50.10), and 10.90 (5.20, 18.88) pg/mL, respectively, with no statistical significance (P0.05). Conclusion For omicron variant infected patients, serum IL-6 level is significantly increased in patients with pneumonia manifestations and is correlated with disease progression. Serum IL-6 level is of great guiding significance to judge disease progression and evaluate efficacy and prognosis of elderly coronavirus disease 2019 patients.Copyright © 2022, Second Military Medical University Press. All rights reserved.

Was the diagnosis of gestational diabetes from 34 weeks gestation of pregnancy more prevalent during Covid-19 due to the change in how gestational diabetes was diagnosed?

Aim: During Covid we noticed that more women were being diagnosed with Gestational Diabetes (GDM) from 34 weeks gestation than prior to Covid. It was suspected that this was due to how GDM was diagnosed, from Oral Glucose Tolerance Test (OGTT) prior to Covid to HbA1c with Fasting or Random Blood Glucose (RBG) during Covid. Method(s): An audit of our GDM database was performed, looking at rates of late GDM diagnosis from 2018-present. Result(s): Prior to Covid the late diagnosis rate was 14-15%. In 2020 and 2021 this increased to 27.7%. This year diagnosis is only by OGTT, and the rate has dropped to 21%. There was also a significant rise in the number of women who were being diagnosed from 34 weeks gestation whom had previously been tested for GDM earlier in their pregnancy. In 2018 and 2019 52-56% of these women had previously been tested. In 2020 this increased up to 84% and fell to 74% in 2021. This year the rate has fallen to 67%. In 2018 and 2019 all women had been diagnosed using OGTT's. In 2020 61% of women had previously been tested for GDM by HbA1c and RBG, with this increasing to 84% in 2021. This year only 10% had previously been tested using HbA1 and RBG. Conclusion(s): The sharp increase in late diagnosis of GDM during the Covid seems to be related to the change in diagnostic testing and shows that OGTT is the more accurate way to diagnose GDM and not HbA1c with RBG.

The Compatibility of Chest CT Scan with RT-PCR in Suspected COVID-19 Patients

BACKGROUND: Thoracic computed tomography (CT) scan plays a role in detecting and assessing the progression of COVID-19. It can evaluate the response to the therapy given. In diagnosis, the CT scan of the chest may complement the limitations of reverse transcription polymerase chain reaction (RT-PCR). Several recent studies have discussed the importance of CT scans in COVID-19 patients with false-negative RT-PCR results. The sensitivity of chest CT scan in the diagnosis of COVID-19 is reportedly around 98%. AIM: This study aimed to determine the compatibility of CT scan of the thorax with RT-PCR in suspected COVID-19 patients. MATERIALS AND METHODS: This research was conducted in the Radiology Department of the Wahidin Sudirohusodo Hospital Makassar from April to December 2020 with 350 patients. The method used was a 2 x 2 table diagnostic test. RESULT(S): The study included 188 male patients (53.7%) and 162 female patients (46.2%). The most common age group was 46-65 years (35.4%). The most common types of lesions were ground-glass opacity (163 cases), consolidation (128 cases), and fibrosis (124 cases), mostly found in the inferior lobe with a predominantly peripheral or subpleural distribution. The sensitivity of the CT scan to the PCR examination was 86%, and the specificity was 91%. CONCLUSION(S): Thoracic CT scan was a good modality in establishing the diagnosis of COVID-19. CT scan of the chest with abnormalities could confirm the diagnosis in 88% of cases based on RT-PCR examination. It excluded the diagnosis in 91% based on the RT-PCR examination. The accuracy of the thoracic CT scan was 88% with RT-PCR as the reference value.Copyright © 2023 Sri Asriyani, Albert Alexander Alfonso, Mirna Muis, Andi Alfian Zainuddin, Irawaty Djaharuddin, Muhammad Ilyas.

Usefulness of C-reactive protein to determine the severity of SARS-CoV-2 infection in Peru.

Background: Recently, many biomarkers have been studied to determine severe cases of COVID-19. C-reactive protein (CRP) has shown high sensitivity in identifying patients with severe disease and utility comparable to computed tomography. Aim(s): To determine the usefulness of CRP to predict the severity of SARS-CoV-2 infection in patients hospitalized at the Naval Medical Center of Peru during the period January-September in the year 2021. Method(s): A quantita-tive, observational, analytical, retrospective, and diagnostic test type design was used. A sample size of 503 patients was calculated, which were divided into two groups according to their severity. Result(s): An optimal cut-off point of 10.92 mg/L for CRP levels was determined for the diagnosis of severe COVID-19. An area under the curve (AUC) of 0.762 was calculated and sensitivity, specificity, positive and negative predictive values and diagnostic accuracy values of 78.88%, 66.4%;41.42%;87.01%;and 67.27%;respectively. Fagan's normogram showed a post-test probability of 41%. In the adjusted model, CRP (aOR = 4.853;95% CI 2.987-7.886;p = 0.001), ferritin (aOR = 1.001;95% CI: 1.001-1.002;p = 0.001) and hypothyroidism (adjusted OR = 4899;95% CI: 1272-18872;p = 0.021) showed significance. Conclusion(s): The present study showed an association between CRP and the severity of SARS-CoV-2 infection in an adjusted model, showing its potential utility and contributing to determine the cut-off point of CRP in the Peruvian population and its international comparison.Copyright © 2023, Sociedad Chilena de Infectologia. All rights reserved.

Development and Evaluation of a Textanalytics Algorithm for Automated Application of the Bsr Covid-19 Shielding Criteria in Rheumatology Patients

Background/Aims In April 2020 the British Society for Rheumatology (BSR) issued a risk stratification guide to identify patients at the highest risk of COVID-19 requiring shielding. This guidance was based on patients' age, comorbidities, and immunosuppressive therapies - including biologics that are not captured in primary care records. This meant rheumatologists needed to manually review outpatient letters to score patients' risk. The process required considerable clinician time, with shielding decisions not always transparently communicated. Our aim was to develop an automated shielding algorithm by text-mining outpatient letter diagnoses and medications, reducing the need for future manual review. Methods Rheumatology outpatient letters from Salford Royal Hospital, a large UK tertiary hospital, were retrieved between 2013-2020. The two most recent letters for each patient were extracted, created before 01.04.2020 when BSR guidance was published. Free-text diagnoses were processed using Intelligent Medical Objects software1 (Concept Tagger), which utilised interface terminology for each condition mapped to a SNOMED-CT code. We developed the Medication Concept Recognition tool (MedCore Named Entity Recognition) to retrieve medications type, dose, duration and status (active/past) at the time of the letter. The medication status was established based on the heading where they appeared (e.g. past medications, current medications), but incorporated additional information such as medication stop dates. The age, diagnosis and medication variables were then combined to output the BSR shielding score. The algorithm's performance was calculated using clinical review as the gold standard. Results To allow for the comparison with manual decisions, we focused on all 895 patients who were reviewed clinically. 64 patients (7.1%) had not consented for their data to be used for research as part of the national opt-out scheme. After removing duplicates, 803 patients were used to run the algorithm. 11,558 free-text diagnoses were extracted and mapped to SNOMED CT, with 15,003 free-text medications (that included past, present and any planned treatment). The automated shielding algorithm demonstrated a sensitivity of 80.3% (95% CI: 74.7, 85.2%) and specificity of 92.2% (95% CI: 89.7, 94.2%). Positive likelihood ratio was 10.3 (95% CI: 7.7, 13.7), negative likelihood ratio was 0.21 (95% CI: 0.16, 0.28), F1 score was 0.81. False positive rate was 7.9%, whilst false negative rate was 19.7%. Further evaluation of false positives/negatives revealed clinician interpretation of BSR guidance and misclassification of medications status were important contributing factors. Conclusion An automated algorithm for risk stratification has several advantages including reducing clinician time for manual review to allow more time for direct care, improving efficiency and transparently communicating decisions based on individual risk. With further development, it has the potential to be adapted for future public health initiatives that requires prompt automated review of hospital outpatient letters.

Challenges in the Diagnosis and Investigation of Giant Cell Arteritis during Covid- 19 Pandemic Restrictions: Does the Southend Pretest Probability Score Help to Guide Clinical Diagnosis?

Background/Aims During 2020-2021 many usual hospital services were affected as focus turned towards managing COVID-19. Elective outpatient surgery ceased and rheumatology staff were redeployed to covid wards. This reduced the availability of temporal artery biopsy (TAB) and temporal artery ultrasound (TAUS) to aid in diagnosing giant cell arteritis (GCA). The rheumatology team making diagnoses of GCA or not-GCA were doing so often based entirely on clinical and laboratory findings. We aimed to determine referral patterns and investigations for suspected GCA during the covid pandemic, compare diagnoses at 6 months after initial assessment and retrospectively apply the Southend Pretest Probability Score (PTPS) and correlate with the diagnosis of GCA or not-GCA. Methods We reviewed all electronic referrals for suspected GCA from July 2020 - June 2021. Clinical details and investigations reviewed. PTPS applied giving a result of low, intermediate or high probability of GCA. Results 84 referrals for suspected GCA over 12 months. 20 diagnosed GCA/ large vessel vasculitis (LVV), 64 not-GCA. Peak referral months Nov 2020 and April 2021 with 13 and 16 referrals. Lowest in October 2020 with 1 referral. 57 female, 27 male. Mean age 70.1 years. 19% male referrals diagnosed GCA, 26% female diagnosed GCA. All LVV and PMR diagnoses were female. 27 TAUS, 6 TAB, 7 PET, 13 CT, 3 MRI performed. 30 patients had no additional investigations. Of 20 GCA;14 had supporting investigations, 6 were clinical diagnoses. All GCA diagnoses were consistent at 6 months. One not-GCA case was subsequently diagnosed with LVV on CTPET. All other not-GCA diagnoses were consistent at 6 months. The PTPS was retrospectively applied based on available clinical information in all except 2 cases, and compared to GCA/not-GCA diagnosis and investigations undertaken. Conclusion Referral numbers for suspected GCA were higher than previous years however the number of actual GCA diagnoses was similar. With limitations on diagnostic investigations due to covid, diagnoses of GCA with and without additional tests were accurate at 6 months, and correlated with a high probability score. The PTPS is a therefore valuable clinical tool in the assessment of GCA. (Table Presented).

Production and characterisation of a SARSCoV-2 S-protein RBD homodimer with increased avidity for specific antibodies

Monitoring of the proportion of immune individuals and the effectiveness of vaccination in a population involves evaluation of several important parameters, including the level of virus-neutralising antibodies. In order to combat the COVID-19 pandemic, it is essential to develop approaches to detecting SARS-CoV-2 neutralising antibodies by safe, simple and rapid methods that do not require live viruses. To develop a test system for enzyme-linked immunosorbent assay (ELISA) that detects potential neutralising antibodies, it is necessary to obtain a highly purified recombinant receptor-binding domain (RBD) of the spike (S) protein with high avidity for specific antibodies. The aim of the study was to obtain and characterise a SARSCoV-2 S-protein RBD homodimer and a recombinant RBD-expressing cell line, as well as to create an ELISA system for detecting potential neutralising antibodies. Material(s) and Method(s): the genetic construct was designed in silico. To generate a stable producer cell line, the authors transfected CHO-S cells, subjected them to antibiotic pressure, and selected the optimal clone. To isolate monomeric and homodimeric RBD forms, the authors purified the recombinant RBD by chromatographic methods. Further, they analysed the activity of the RBD forms by Western blotting, bio-layer interferometry, and indirect ELISA. The analysis involved monoclonal antibodies GamXRH19, GamP2C5, and h6g3, as well as serum samples from volunteers vaccinated with Gam-COVID-Vac (Sputnik V) and unvaccinated ones. Result(s): the authors produced the CHO-S cell line for stable expression of the recombinant SARS-CoV-2 S-protein RBD. The study demonstrated the recombinant RBD's ability to homodimerise after fed-batch cultivation of the cell line for more than 7 days due to the presence of unpaired cysteines. The purified recombinant RBD yield from culture broth was 30-50 mg/L. Monomeric and homodimeric RBD forms were separated using gel-filtration chromatography and characterised by their ability to interact with specific monoclonal antibodies, as well as with serum samples from vaccinated volunteers. The homodimeric recombinant RBD showed increased avidity for both monoclonal and immune sera antibodies. Conclusion(s): the homodimeric recombinant RBD may be more preferable for the analysis of levels of antibodies to the receptor-binding domain of the SARS-CoV-2 S protein.Copyright © 2023 Authors. All rights reserved.

Hypermetabolic ipsilateral supraclavicular and axillary lymphadenopathy: Optimal time point for performing 18F-FDG PET/CT after COVID-19 vaccination

Ziel/Aim We aimed at evaluating the incidence of SARS-CoV2 vaccine-related axillary and supraclavicular hypermetabolic lymphadenopathy (HLA) and evaluate which timepoint produces the least number of false-positive findings in HLA. Methodik/Methods For this retrospective, multi-center imaging study patients with any form of SARS-CoV2 vaccination prior to 18F-FDG-PET/CT between January 2021 and December 2021 were included. Patients were divided into six groups according to the timepoint of vaccination prior to 18F-FDG-PET/CT imaging: Group 1 (0-6 Days), Group 2 (7-13 Days), Group 3 (14-20 Days), Group 4 (21-27 Days), Group 5 (28-34 Days) and Group 6 (35-80 Days). As reference SUVmax of mediastinal blood pool (MBP) and SUVmax contralateral reference lymph node (RL) were determined. For each group, the following parameters were assessed. A) absolute SUVmax of HLA B) incidence of HLA [defined as the ratio of SUVmaxHLA/ SUVmax Mediastinal Blood Pool (rHLA/MBP)] greater than 1,5 C) rHLA/MBP D) ratio SUVmax HLA vs. SUVmax contralateral reference lymph node (rHLA/RL). Ergebnisse/Results HLA showed the highest incidence in Group 1(day 0-6) 16/23 (70 %). Similarly, SUVmax HLA and rHLA/MBP were highest in this group, SUVmax 4.97 +/- 4.1 and 2.58 +/- 2.1 respectively. The incidence of HLA, SUVmax HLA, and rHLA/MBP were higher in Group 3 (14-20 days) than in Group 2 (7- 13days);57 % vs 44 %;5.05 +/- 4.33vs 3.9 +/- 2.81 (p = 0.723 and 2.32 +/- 1.8 vs 1.83 +/- 1.38(p = 0.788). All parameters for HLA dropped markedly after at least 21 days of vaccination. There were no significant differences in SUVmax HLA, rHLA/MBP and rHLA/RL in group 4 (21-27 days), group 5 (28-34 days) and group 6 (35-80 Days). [1] Schlussfolgerungen/Conclusions It is crucial for diagnostic physicians to assess the recent history of COVID-19 vaccination prior to FDG-PET/CT scan to reduce the risk of false-positive calls. If feasible, FDG PET should be postponed by at least 3 weeks after SARS-CoV2 vaccination especially if an accurate evaluation of axillary status is required.

Diagnostic Analysis of mZN Microscopy and PCR for Detection of Cryptosporidiosis in Goat Kids - A Molecular Epidemiological Study

The occurrence of Cryptosporidium species infection and its risk factors in neonatal goats is less explored. Also it is due to the fact that diseases like colibacillosis and neonatal viral enteritis complex caused by Group A rotaviruses and Bovine corona viruses can co-exist with Cryptosporidium and can lead to mixed infections and the latter is often overlooked. Therefore, in the current research we explored the cryptosporidial occurrence in neonatal goats of Mathura district of Uttar Pradesh, India. In this study, a total of 644 faecal samples were collected from neonatal goats at different villages and certain organized farms of Mathura district age-wise, season-wise and breed-wise, and were examined for Cryptosporidium based on modified Ziehl-Neelsen technique, conventional 18SSU rRNA nested PCR assay. The overall prevalence of Cryptosporidium infection in goats based on microscopy was 36.80% (237/644;p value <0.0001) and 18SSU rRNA nested PCR 52.95% (341/644;p value <0.0001) respectively. Cryptosporidium species typing was also done using 18SSU rRNA nested PCR-RFLP product using enzymes Mbo-II, Ssp-I and Vsp-I, which revealed species including C. parvum C. bovis, C. ryanae, C. hominis and C. andersoni. Also the infection was clinically associated based on age, gender and seasons to identify the causal relationships that precipitate the cryptosporidial infection in goat kids. Since mZN microscopy based screening requires expertise and may sometimes be confuse with other weak acid fast bodies and also due to low sensitivity, combination of diagnostic tests are used in this study to identify the best test combination that yields best statistical fit in terms of kappa-agreement and McNemar's test. Cryptosporidiosis is caused by an enteric protozoan parasite and the first report in sheep and goat was observed in early 1980s, with other important etiological agents for neonatal diarrhoea, mortality and morbidity in neonatal kids and lambs, responsible for economic losses.Copyright © 2023 Indian Veterinary Assocaition. All rights reserved.