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.

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.

Pancreatic Stone Protein (PSP) as a predictive biomarker of multiple organ failure and clinical outcome

Background: COVID-19 syndrome is associated with high morbidity and mortality in haemodialyzed patients. Pancreatic Stone Protein (PSP) is an early biomarker of sepsis and a prognostic biomarker of disease severity in critically-ill patients and can be rapidly measured at the patient's bedside with a point-of-care-test from a small drop of whole blood. The aim of our pilot was to investigate PSP in patients requiring haemodialysis with SARS-CoV-2 infection, at different severities of COVID-19 disease. Method(s): Between February and July 2021, 23 patients (6 severe COVID-19 with Acute Kidney Injury, 6 moderate COVID-19 haemodialyzed, 2 haemodialyzed without COVID-19 and 3 healthy controls) were recruited at the University Hospital of Foggia for PSP evaluation. Biomarker's measurements were performed within 48 hours after admission or upon arrival for haemodialysis (pre-treatment). PSP was measured at the patient's bedside with "abioSCOPE", a point-of-care test capable of evaluating PSP levels in five minutes from a small drop (50mul) of whole blood or serum. Result(s): The preliminary results of this pilot study showed a trend for PSP to increase along with the severity of disease. In fact, serum PSP levels were significantly higher in Intensive Care Unit subjects than in COVID-19 negative haemodialysis subjects and controls (ANOVA p=0.032). Furthermore, PSP levels were significantly higher in subjects who died (p<0.017). Whether this increase is due to the kidney injury or COVID-19 disease remains unknown, and more research is needed to understand the relationship. Conclusion(s): Several clinical studies published in literature have shown the predictive value of PSP in the early identification of sepsis and severity of the clinical outcome. In our experience we have seen a trend for PSP to increase with disease severity also in COVID-19 patients. These results are preliminary, but PSP was significantly higher in patients who died, in accordance with the literature. This experience also has demonstrated the feasibility of a point of care system to be easily implemented in the unit and adopted by personnel and its design enables fast results and immediate decisions to be taken, especially in urgent situations.

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.

Frail Scale as Predictor of 30-Day Postoperative Outcomes in Geriatric Surgical Patients at a Tertiary Hospital in the Philippines from June 2020 to June 2021

Introduction: The geriatric population is a growing subset of surgical patients. Specialized surgical risk management is important since physiologic changes are only loosely associated with age. Searching for better risk assessment tools, we come across the 5-point FRAIL scale, a validated measure of weakness and physiologic malfunction resulting to vulnerability to stressors like surgery. Method(s): Our objective was to assess the effectiveness of FRAIL scale in predicting 30-day complications in geriatric surgical patients. We conducted this research at a tertiary hospital in the Philippines from June 2020 to June 2021. Patients were classified preoperatively as frail or robust, and they were monitored 30 days post-surgery for adverse outcomes. Result(s): Out of 100 patients, fifty-seven were frail. Postoperatively, 20% had complications, while 18% expired, with 76% of all adverse outcomes belonging to frail group. FRAIL scale had a significantly better predictive value as compared with Charlson comorbidity index and ACS surgical risk calculator in cases of mortality, but there was no significant difference in predicting morbidity for the three assessment tools. The increase in adverse outcomes compared with previous years was attributed to (1) the proportion of colorectal procedures, and (2) patients were probably in a more advanced stage of illness due to the delays in treatment caused by the COVID-19 pandemic. Conclusion(s): In conclusion, FRAIL scale is an easy-to-use and effective risk assessment tool for geriatric surgical patients. Since most frail patients admit of weakness, resistance training and aerobic exercises may be an appropriate strategy to improve surgical outcomes.

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.

The Use of Acute-Phase Proteins Apache Ii and Sofa to Predict the Mortality of Covid-19 Patients

Objective: Acute-phase proteins are a family of proteins synthesized by the liver. With this study, we aimed to investigate the effects of COVID-19 infection on acute phase reactants (AFR) and determine the usability of AFRs as prognostic factors in COVID-19 disease. Material(s) and Method(s): Serum samples taken for routine analysis of the patients admitted to the Emergency Department and diagnosed with COVID-19, were used. AFR levels of 30 patients who resulted in mortality and 30 recovered patients were evaluated. C-reactive protein (CRP), ferritin (FER), ceruloplasmin (Cp), albumin (Alb), prealbumin (Prealb), transferrin (Trf), lactate, Acute Physiology and Chronic Health Evaluation (APACHE), and Sequential Organ Failure Assessment (SOFA) assessment was performed. Result(s): The hazard ratio and 95% confidence interval for FER, CRP, lactate, Alb, Cp, Prealb, Trf, Age, SOFA, and APACHE were 1.001 (1.000-1.001), 1.005 (1.001- 1.008), 1.141 (1.016-1.243), 1.016 (0.740-1.399), 1.016 (0.740-1.399), 1.056 (1.017-1.100), 0.978 (0.917-1.035), 1.000 (0.995-1.006), 1.032 (1.004- 1.064), 1.104 (0.971-1.247), and 1.012 (0.974-1.051), respectively, in univariable model. Only CRP, lactate, and FER found significant in multivariable model. In addition, patients in the nonsurvivors group had significantly higher FER, CRP, lactate, APACHE, age, and SOFA. Nonsurvivors also had lower Alb, Prealb, and serum Trf level compared to survivors. Conclusion(s): CRP, lactate, and FER, which we have shown to be significantly higher in severe COVID-19 patients, will be valuable parameters that will contribute to clinical improvement if they are used in the follow-up of patients due to their easy measurement and predictive values.Copyright © 2023, Nobelmedicus. All rights reserved.

Prognostic role of inflammatory indices in risk classification of patients with COVID-19

Objective: The Covid-19 pandemic has revealed the importance of an evidence-based efficient triage system in the early identification of high risk patients and the rational use of limited medical resources for reducing mortality. The aim of this study was to evaluate the role of various inflammatory indices that can be easily calculated using readily accessible, inexpensive routine test parameters in risk stratification and prediction of prognosis in patients with Covid-19. Material and Methods: The study was carried out retrospectively with the data of 8036 patients with Covid-19, who were grouped according to their prognosis in outpatient and inpatient follow-ups, and inpatients as survivors and death. Using the complete blood count and C-reactive protein baseline results of the patients at admission, neutrophillymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocytelymphocyte ratio (MLR), MVP-platelet ratio (MPR), platelet mass index (PMI), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), and multi-inflammatory indices (MII) were calculated. Results: Our results demonstrate that almost all of the inflammatory indices were significantly different in severe patients and in patients with high mortality risk, but not all of them had a predictive value. It has been seen that the most effective factors in determining the disease severity at the onset of Covid-19 are SIRI and age, and SII, MII-1 and MII-3 may also contribute to this prediction. Our results have also revealed that NLR is the most effective independent factor to predict mortality both at disease onset and for inpatients. Conclusion: Inflammatory indices, especially SIRI, NLR, SII, MII-1 and MII-3 can substantially contribute to clinical decisions in the early identification of high-risk patients and predicting mortality beginning from the onset of Covid-19.

Predictive value of C-reactive protein-to-albumin ratio for risk of 28-day mortality in patients with severe pneumonia

Objectives: To explore the predictive value of C-reactive protein (CRP)-to-albumin (ALB) ratio (CAR) for the risk of 28-day mortality in patients with severe pneumonia.Methods: A total of 152 patients with severe pneumonia treated from January 2020 to January 2022 were enrolled and assigned into survival group (n=107) and death group (n=45) according to their survival status after treatment for 28 d. Their clinical data were compared, and the influencing factors for 28-day mortality were explored by multiple logistic regression analysis. The receiver operating characteristic (ROC) curve was plotted to assess the value of CAR for predicting 28-day mortality risk. A risk prediction model was constructed, and its prediction efficiency was evaluated.Results: The death group had significantly older age, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Murray Lung Injury Score, Sequential Organ Failure Assessment score, white blood cell count, neutrophil count, red cell volume distribution width, neutrophil-to-lymphocyte ratio (NLR), fibrinogen, procalcitonin, blood lactic acid (Lac), CRP and CAR and significantly lower oxygenation index and ALB than those of the survival group (p<0.05). APACHE II score, NLR, Lac and CAR were independent risk factors for 28-day mortality (p<0.05). AUC of the established prediction model was 0.826, with sensitivity of 88.45 % and specificity of 87.32 %, indicating high discrimination. The nomogram model had clinical value when the risk threshold probability was 11-93 %.Conclusions: CAR is an independent risk factor that shows a high predictive value for the 28-day mortality risk in patients with severe pneumonia.

Production of Sars-Cov-2 Membrane Protein as Better Target Protein for Diagnostic Application

Intro: The COVID-19 pandemic is caused by the SARS-CoV-2 virus, an enveloped RNA of the coronavirus family. The advancement in molecular technology and biochemistry has accelerated the development of diagnostic reagents and assays. Much attention has been focused on the S protein, but the high mutation rate in this region could lead to false negative results. Thus, a better target protein for diagnostic application is needed for accurate detection. Method(s): Nucleotide sequences encoded for membrane (M) glycoprotein gene region of SARS-CoV-2 from Malaysian isolates were extracted from GISAID, aligned, and selected accordingly. The DNA plasmid was commercially synthesized with codon optimization for Escherichia coli (E. coli), and the presence of the M gene was confirmed by PCR. The plasmid was then transformed into E. coli. Later, the expression of M glycoprotein was induced, separated on an SDS-PAGE gel, and transferred onto a nitrocellulose membrane, followed by immunostaining. Finding(s): The analysis of the M glycoprotein against the Omicron strains demonstrated that the amino acid is conserved (99.5%). The M glycoprotein was successfully expressed and detected with antibodies from SARS-CoV-2 infected patients at ~26 kDa. The protein is currently upscale for the generation of monoclonal Ab (Mab). Discussion(s): The M protein of SARS-CoV-2 is more conserved among the virus and also has been reported to confer antigenic properties. Selection of M protein perhaps a better option compared to current detection assays that use spike (S) protein, which could lead to false negative results, as this gene region particularly the ribosome-binding domain (RBD) rapidly undergoes mutations. The utilization of M protein potentially improves negative predictive value (NPV) of the diagnostic test. Conclusion(s): Further development of diagnostic reagents is needed to improve the assay's specificity. The newly developed M protein and the MAb can be used to generate a more accurate viral detection assay.Copyright © 2023

Does the ICU Requirement Score allow the poisoned patient to be safely managed without admission to the intensive care unit? - a validation cohort study.

BACKGROUND: The Intensive care unit (ICU) Requirement Score (IRS) has been defined as identifying poisoned patients on hospital admission who do not require ICU referral, in an effort to reduce health expenses. However, this score has been poorly validated. We aimed to evaluate the IRS in a large cohort of poisoned patients. METHODS: We performed a single-center retrospective cohort study. IRS was calculated using clinical parameters obtained on admission including age, systolic blood pressure, heart rate, Glasgow coma score, intoxication type, co-morbidities (i.e., arrhythmia, cirrhosis, and respiratory insufficiency), and the combination of the intoxication with another reason for ICU admission. We evaluated the ability of IRS < 6 determined on admission to predict the lack of need for ICU treatment, defined as the need for mechanical ventilation, vasopressors, and/or renal replacement therapy in the first 24 h post-admission and/or death during the hospital stay. This score was compared to the usual prognostic scores, i.e., SAPS II and III, SOFA score, and PSS. RESULTS: During the 10-year study period, 2,514 poisoned patients were admitted, 1,011 excluded as requiring ICU treatment on admission, and 1,503 included. Among these patients, 232 met the endpoint whereas only 23/510 patients with IRS < 6 (4.5%) presented the endpoint and one patient died. The area under the curve of the IRS ROC curve was 0.736 (95% confidence interval (CI), 0.702-0.770). The negative predictive value of IRS < 6 was 95% (95% CI, 93-97), sensitivity 89% (95% CI, 85-93), specificity 38% (95% CI, 36-41), and positive predictive value 21% (95% CI, 18-24). IRS performance was similar to those of the other tested scores, which are however not readily available on admission. CONCLUSION: Our data demonstrate the excellent negative predictive value of the IRS, allowing the exclusion of ICU requirements for poisoned patients with IRS < 6. IRS usefulness should be confirmed based on a prospective multicenter cohort study before extensive routine use.

Oral Microbiome and Innate Immunity in Health and Disease: Building a Predictive, Preventive and Personalized Therapeutic Approach

An average person carries 1 to 2 kg of microbes in the alimentary track, including the oral cavity. There are more bacteria in a person's mouth than the total human population in the entire world. Oral health is critical to the general systemic health of an individual. The harmonious co-existence between more than 1000 bacterial species and the host's immune system underpins sustained, long-term homeostasis, the sine qua non of oral health. In a similar manner, global oral health is essential for general population health of the world. Since our last review of this subject in 2019, while significant clinical advances continue, the disparity, lack of prevention, insufficient care, and political unrest have persisted or significantly deteriorated. This review focuses on the following important questions: 1.What is oral microbiome? How to detect, characterize, compare, report, and interpret the results?2.How does oral microbiome affect and respond to local and systemic innate immunity?3.What is the role of oral microbiome in the pathogenesis of diseases of the mouth?4.What are the impacts of oral health or the lack of it at the systemic level?5.Why is oral health important at the population level?6.How can the healthcare providers restore and sustain harmonious co-existence between host and oral microbiome?Copyright © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Automatic detection of novel corona virus (SARS-CoV-2) infection in computed tomography scan based on local adaptive thresholding and kernel-support vectors

The recent studies have indicated the requisite of computed tomography scan analysis by radiologists extensively to find out the suspected patients of SARS-CoV-2 (COVID-19). The existing deep learning methods distribute one or more of the subsequent bottlenecks. Therefore, a straight forward method for detecting COVID-19 infection using real-world computed tomography scans is presented. The detection process consists of image processing techniques such as segmentation of lung parenchyma and extraction of effective texture features. The kernel-based support vector machine is employed over feature vectors for classification. The performance parameters of the proposed method are calculated and compared with the existing methodology on the same dataset. The classification results are found outperforming and the method is less probabilistic which can be further exploited for developing more realistic detection system.Copyright © 2023 Inderscience Enterprises Ltd.

Predictive value of the duration of positive nucleic acid test on the clinical outcome of COVID‑19 patients

Objective: To explore the predictive value of the duration of positive SARS‐CoV‐2 nucleic acid test in patients with coronavirus disease 2019 (COVID‐19) on clinical outcome. Methods: A total of 128 COVID‐19 patients admitted to Renmin Hospital of Wuhan University from March 2020 to May 2020 were selected and received symptomatic treatment. According to the clinical outcome of the patients, they were divided into a cured group (88 cases) and a death group (40 cases). The gender, age, time from onset to first diagnosis, clinical manifestations, past history, chest CT manifestations, respiratory support methods, blood gas indexes, the first laboratory test result after admission, and the duration of nucleic acid positive were compared between the two groups. Multivariate logistic regression analysis was used to determine the influencing factors of the clinical outcome of patients, and the ROC curve for each index was drawn to predict the clinical outcome of COVID‐19 patients. Results: Statistically significant difference between cure group and death group was found in age, arterial oxygen partial pressure, blood oxygen saturation, white blood cell count, neutrophil count, lymphocyte count, platelet count, urea nitrogen, blood potassium, D‐dimer, lactic acid, serum IL‐10, TNF‐α, and nucleic acid positive duration (P<0. 05). Multivariate logistic regression analysis showed that arterial blood oxygen partial pressure (OR=0. 602, 95%CI: 0. 411 ‐ 0. 882), lymphocyte count (OR= 0. 710, 95%CI: 0. 534 ‐ 0. 944), blood potassium (OR=2. 166, 95%CI: 1. 223 ‐ 3. 836), lactic acid (OR=2. 675, 95%CI: 1. 311 ‐ 5. 458), and nucleic acid positive duration (OR=1. 894, 95%CI: 1. 248‐2. 874) were the influencing factors of the clinical outcome of patients (P<0. 05). The areas under the ROC curve of lactate, arterial partial pressure of oxygen, nucleic acid positive duration, blood potassium, and lymphocyte count to predict the clinical outcome of patients were 0. 922 (95%CI: 0. 8867 ‐ 0. 968) and 0. 897 (95%CI: 0. 837 ‐ 0.957), 0.854 (95%CI: 0. 778 ‐ 0. 931), 0. 731 (95%CI: 0. 637‐0. 826), and 0. 704 (95%CI: 0. 608‐0. 812), respectively, which showed higher predictive value, and their best cut‐off values were 3. 35 mmol/L, 62 mmHg, 31 d, 4. 22 mmol/L, and 0. 91×109/ L, respectively, the sensitivities were 0. 914, 0. 906, 0. 844, 0. 750, and 0. 711, respectively, and the specificities were 0. 766, 0. 797, 0. 813, 0. 836, and 0. 820, respectively. Conclusion: Arterial partial pressure of oxygen, lymphocyte count, blood potassium, lactic acid, and nucleic acid positive duration are the influencing factors for the clinical outcome of COVID‐19 patients, and have a high predictive value for the death of the patients. © 2022 Editorial Board of Medical Journal of Wuhan University. All rights reserved.

The Importance of Acute Phase Proteins in the Evaluation of Critical Covid-19 Patient Prognosis

Objectives: Identifying COVID-19 patients with risk of adverse outcomes at first admission to the intensive care unit has several diagnostic challenges. The concentration of acute phase proteins synthesized by the liver increases or decreases markedly in the serum following inflammation and infection. This study aimed to investigate the predictive value of acute phase proteins in critically ill COVID-19 patients and to evaluate the efficacy of inflammatory markers in predicting mortality risk in the intensive care unit. Material-Methods: A retrospective study was conducted in critically ill COVID-19 patients treated in the intensive care unit. Overall, 123 patients with ARDS and/or multi-organ dysfunction were included in the first 24 hours of admission to intensive care unit. After 28 days, groups of survived (n=54) and dead patient (n=69) or groups of patients with (n=83) and without (n=40) invasive mechanical ventilation were formed. Serum amyloid A, C-reactive protein, albumin, and prealbumin values considered as acute phase proteins within the first 24 hours of admission to the intensive care unit were compared between groups. Result(s): Albumin and prealbumin levels significantly decreased in dead patients (p=0.011, p<0.001, respectively) and were mechanically ventilated patients (p=0.010, p=0.006, respectively). The Serum amyloid A levels in mechanically ventilated patients significantly increased (p=0.022). Conclusion(s): Low prealbumin and albumin levels and high serum amyloid A levels during admission to ICU can be used as a prognostic marker of disease severity and mortality.

Prognostic Accuracy of News 2 in Geriatric Patients with COVID-19 in a Tertiary Care Hospital

Introduction: COVID-19 is a widespread disease having more impact on elderly as compared to younger age group. [2] Although many parameters have emerged as predictors of prognosis of COVID-19, a simple clinical score at baseline can be used for early risk stratification. NEWS2 (National Early Warning Score) is one such scoring system which was originally developed to improve detection of deterioration in acutely ill patients.[8] Therefore, the present study has been conducted to assess the effectiveness of NEWS2 in predicting critical outcomes and mortality in geriatric patients with COVID-19. Material(s) and Method(s): A cross sectional Observational study was done on 200 Geriatric patients hospitalised with confirmed COVID-19 between December 2020 to November 2022. Baseline NEWS2 score was calculated. The sensitivity, specificity, Positive Predictive Value and Negative Predictive Value were established for NEWS2 score of 5 or above. Result(s): In critical group, all 109 (100%) patients' deterioration was predicted, and in non-critical group, in 14 (15.4%) patients non deterioration was predicted while 77 (84.6%) patients' deterioration was predicted. Statistically significant association has been observed between the critical, non-critical groups and NEWS2 scale (P=0.001). Deterioration was predicted by NEWS2 scale in all the critical patients. Conclusion(s): NEWS2 score of 5 or more on admission predicts poor prognosis in geriatric patients with COVID-19 with good sensitivity and it can easily be applied for risk stratification at baseline. We recommend further studies in the Indian setting to validate this simple score and use it further in Geriatric patients with COVID-19.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.

Evaluation with Roc Analysis, Logistics Regression Analysis and Other Statistical Tests Analysis of Retrospective Results of Biochemistry Laboratory Results, Analysised in Covid-19 Infected Serum or Plasma (Crp, Procalcitonin, Ferritin, D-Dimer, Fibrinogen, Ast, Alt, Ldh)

Objectives: A new type of coronavirus that emerged in Wuhan, China at the end of 2019, caused the Covid-19 (SARS-COV2) pandemic. Common cold symptoms are seen, but in more severe cases, pneumonia, Acute Respiratory Distress Syndrome (ARDS), coagulopathy, multi-organ failure are seen, and it causes death in the course of time. In this study, among the laboratory parameters followed in cases diagnosed with Covid-19 and followed in home isolation, service and intensive care unit;It is aimed to retrospectively evaluate CRP, procalcitonin, ferritin, D-Dimer, fibrinogen AST, ALT and LDH levels with ROC and other statistical analyzes in terms of predicting mortality in the treatment and follow-up of the disease. Materials-Methods: Between 01.04.2020 and 01.10.2020, the patients who applied to Necmettin Erbakan University Meram Medical Faculty Hospital with cold symptoms and were diagnosed with Covid-19 with RT-PCR positivity, were analyzed from Covid-19 infected serum and plasma. The results of the biomarkers were examined. Demographic data, vital signs and laboratory findings of the cases were compared. The results were statistically evaluated with the SPSS 22.0 package program. Result(s): 300 cases who received home isolation, service and supportive treatment in the intensive care unit were included in the study. Crp, Pct, D-dimer, ferritin, fibrinogen, LDH, AST and ALT values were found to be statistically significant. According to the results of ROC (Receiver Operating Characteristic) analysis performed to determine the predictive values of laboratory parameters that were significant as a result of univariate statistical analysis, Crp (0.890775), Pct (0.86795), D-dimer (0.856975), ferritin (0.836975), LDH (0.7829), fibrinogen (0.773925), AST (0.685925) and ALT (0.594025) were found. Conclusion(s): The high mutation ability of SARS-CoV-2 makes it difficult to control the pandemic. Therefore, early diagnosis of the disease has gained importance for the treatment of patients with high mortality risk. According to the ROC results we obtained in this study, it supports that CRP, Procalcitonin, Ferritin, D-dimer and LDH levels can be used as effective parameters in determining the prognosis and mortality risk in Covid-19 patients.

APACHE II score as a predictor of outcome in critically ill COVID-19 patients

Introduction: APACHE II severity scoring system has been successfully used for mortality risk assessment in the ICU, however its validity in the subgroup of COVID-19 patients has been questionable. We aimed to examine the predictive value of APACHE II score in a cohort of critically ill COVID-19 patients. Method(s): We performed a retrospective analysis of prospectively collected data in a cohort of COVID-19 patients admitted to our 50-bed ICU between October 2020 and April 2022. Using a ROC analysis we assessed the performance of APACHE II score and identified the optimal cut-off value for mortality prediction. Result(s): Our cohort included 783 patients (66% male) with positive PCR forSARS-Cov-2 and respiratory failure. Mean age was 66 years. Invasive mechanical ventilation was used in 92%of patients and 89.3% had at least one comorbidity. The mean APACHE II score of the whole cohort was 20.3 (+/- 8.5). ICU mortality was 44.7%. Death rate was similar between sexes but significantly higher in those who were older and those suffering from COPD, chronic renal or heart failure, atrial fibrillation or any kind of malignancy. Non-survivors had a significantly higher APACHE II score compared to survivors (25.2 +/- 7.9 vs 16.3 +/- 6.7, p < 0.001). ROC analysis showed an AUC 0.81 (95% CI 0.78-0.84, p < 0.001). At a cut-off value of 19.5 APACHE II score could predict death with a sensitivity of 77.1% (95% CI 72.4-81.4%), a specificity of 70.7% (95% CI 66.1-74.9%), PPV 68% (95% CI 63.2-72.6%) and NPV 79.3% (95% CI 74.9-83.2%). Conclusion(s): APACHE II score is an effective tool for mortality prediction in critically ill COVID-19 patients. A cut-off value of 19.5 can be used for risk stratification in this patient population.

A new score to predict severe respiratory failure and guide anakinra treatment in COVID-19 pneumonia: analysis of the randomized SAVE-MORE trial

Introduction: Anakinra treatment is approved for the treatment of COVID-19 pneumonia in hospitalized adults in need of oxygen and at risk for progression into severe respiratory failure (SRF) defined as circulating concentrations of the biomarker suPAR (soluble urokinase plasminogen activator receptor) >= 6 ng/mL by the EMA and has been authorized for emergency use by FDA under an EUA [1]. This is based on the results of the randomized SAVE-MORE trial where suPAR >= 6 ng/ mL was used to select patients at risk for SRF [2]. The suPAR test is not commercially available in the USA and an alternative method of patient selection was needed. Method(s): In collaboration with the US FDA, an alternative method to select patients most likely to have suPAR >= 6 ng/mL based on commonly measured patient characteristics was developed. Patients with at least 3 of the following criteria are considered likely to have suPAR >= 6 ng/ ml: age >= 75 years, severe pneumonia by WHO criteria, current/previous smoking status, Sequential Organ Failure Assessment score >= 3, neutrophil-to-lymphocyte ratio >= 7, hemoglobin <= 10.5 g/dl, history of ischemic stroke, blood urea >= 50 mg/dl and/or history of renal disease. Result(s): The positive predictive value of this new score was 95.4% in SAVE-MORE population. However, a lower sensitivity meant a small proportion of patients with suPAR >= 6 ng/ml will not be identified by the new score. The adjusted hazard ratio for survival at 60 days for patients meeting this score and who receive anakinra is 0.45 (Fig. 1). Conclusion(s): The developed score predicts accurately patients with suPAR levels >= 6 ng/mL and may be used as an alternative to guide anakinra treatment in patients with COVID-19 pneumonia. Based on these subgroup results, patients in SAVE-MORE who met the new score appeared to show beneficial efficacy results with treatment of anakinra consistent with the overall studied population.