Predicting Intensive Care Unit Admission in COVID-19-Infected Pregnant Women Using Machine Learning DOI Open Access
Azamat Mukhamediya, Iliyar Arupzhanov, Amin Zollanvari

et al.

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(24), P. 7705 - 7705

Published: Dec. 17, 2024

Background: The rapid onset of COVID-19 placed immense strain on many already overstretched healthcare systems. unique physiological changes in pregnancy, amplified by the complex effects pregnant women, rendered prioritization infected expectant mothers more challenging. This work aims to use state-of-the-art machine learning techniques predict whether a COVID-19-infected woman will be admitted ICU (Intensive Care Unit). Methods: A retrospective study using data from women one hospital Astana and Shymkent, Kazakhstan, May July 2021. developed platform implements compares performance eight binary classifiers, including Gaussian naïve Bayes, K-nearest neighbors, logistic regression with L2 regularization, random forest, AdaBoost, gradient boosting, eXtreme linear discriminant analysis. Results: Data 1292 were analyzed. Of them, 10.4% ICU. Logistic regularization achieved highest F1-score during model selection phase while achieving an AUC 0.84 test set evaluation stage. Furthermore, feature importance analysis conducted calculating Shapley Additive Explanation values points leucocyte counts, C-reactive protein, pregnancy week, eGFR hemoglobin as most important features for predicting admission. Conclusions: predictive obtained here may efficient support tool prioritizing care clinical practice.

Language: Английский

Long COVID-19 and Peripheral Serotonin: A Commentary and Reconsideration DOI Creative Commons
George P. Anderson, Edwin H. Cook, Randy Blakely

et al.

Journal of Inflammation Research, Journal Year: 2024, Volume and Issue: Volume 17, P. 2169 - 2172

Published: April 1, 2024

Abstract: We believe there are serious problems with a recently published and highly publicized paper entitled "Serotonin reduction in post-acute sequelae of viral infection." The blood centrifugation procedure reportedly used by Wong et al would produce plasma that is substantially (over 95%) depleted platelets. Given this, their mean serotonin values 1.2 uM 2.4 for the control/contrast groups appear to be at least 30 60 times too high should disregarded. reported long COVID viremia patients also disregarded, as any comparisons groups. note means two not good agreement. In "Discussion" section, state results tend support use selective reuptake inhibitors (SSRIs) treatment COVID-19, they encourage further clinical trials SSRIs. While that, "Our animal models demonstrate levels can restored memory impairment reversed precursor supplementation or SSRI treatment", it noted no data presented showing an increase restoration circulating administration. fact, one expect marked decline platelet due SSRIs' effective inhibition transporter. hypothesize arise from little peripheral serotonin. However, given frequent presence hyperaggregation COVID, known augmenting effects on aggregation, plausible suggest reductions might associated lessening cardiovascular COVID-19. Keywords: serotonin, plasma, platelets, infection

Language: Английский

Citations

4
Secondary Neutropenias DOI Creative Commons
Alister C. Ward

Biomedicines, Journal Year: 2025, Volume and Issue: 13(2), P. 497 - 497

Published: Feb. 17, 2025

Neutrophils are a critical component of immunity, particularly against bacteria and other pathogens, but also in inflammation tissue repair. As consequence, individuals with neutropenia, defined by reduction absolute neutrophil counts, exhibit strong propensity to severe infections that typically present muted symptoms. Neutropenias encompass heterogeneous set disorders, comprising primary neutropenias, which specific genes mutated, the more common secondary have diverse non-genetic causes. These include hematological cancers, involving both direct effects cancer itself indirect impacts via chemotherapeutic, biological agents cell-based approaches used for treatment. Other significant causes neutropenias non-chemotherapeutic drugs, autoimmune immune diseases, nutrient deficiencies. collectively act impacting production bone marrow and/or destruction throughout body. This review describes clinical manifestations detailing their underlying management, discussion alternative emerging therapeutic approaches.

Language: Английский

Citations

0
Distinguishing Swine Flu (H1N1) from COVID-19: Clinical, Virological, and Immunological Perspectives DOI Open Access

Irene Batta,

Tejinder Kaur, Devendra K. Agrawal

et al.

Archives of Microbiology & Immunology, Journal Year: 2023, Volume and Issue: 07(04)

Published: Jan. 1, 2023

This article provides an in-depth examination on the differences between influenza A strain, H1N1 (also called Swine Flu) and Covid-19 focusing immune response clinical symptoms. Flu symptoms due to H1N1, were initially discovered in 2009. variant of is believed have emerged through reassortment, a process where resulting virus inherits gene segments from each its parental viruses. reassortment event has resulted with altered characteristics, potentially affecting level immunity humans. The this strain typically manifest 1-4 days after exposure include fever, cough, sore throat, runny/stuffy nose, body aches, fatigue, gastrointestinal such as diarrhea. transmission dynamics new variant, including human-to-human transmission, are still under investigation by health authorities. Individuals weakened systems generally more susceptible severe illness. Risk factors associated swine flu can older adults, young children, pregnant women, individuals obesity. Historical variants flu, 2015 India, been significant case numbers deaths, often respiratory failure. Since epidemic SARS-CoV2 early 2020, several COVID-19 overlap. In article, we critically reviewed similarities human.

Language: Английский

Citations

2
Hematological Conditions Associated with COVID-19: Pathophysiology, Clinical Manifestations, and Therapeutic Approaches DOI
Nicholas A Kerna, John V. Flores,

Kevin D. Pruitt

et al.

European Journal of Medical and Health Research, Journal Year: 2024, Volume and Issue: 2(5), P. 27 - 47

Published: Sept. 1, 2024

This review highlights the significant impact of SARS-CoV-2 on hematological system, revealing complications such as thrombocytopenia, coagulopathy, venous thromboembolism (VTE), and hemolytic anemia, which contribute notably to morbidity mortality, especially in critically ill patients. The underlying mechanisms involve direct viral effects, inflammation, cytokine storms, hypercoagulability. exacerbation pre-existing malignancies common occurrence lymphopenia further illustrate complex interaction between COVID-19 immune system. emphasizes importance early recognition management for clinical practice. It discusses necessity monitoring biomarkers like D-dimer platelet counts, utilizing imaging techniques detecting thromboembolic events, employing timely interventions with anticoagulants immunomodulators. Tailoring treatment individual patient needs involving a multidisciplinary team are essential improving outcomes, particularly also focuses need ongoing research understand precise these complications, explore genetic environmental factors, assess long-term outcomes affected examines emerging variants developing innovative therapeutic approaches, including personalized medicine advanced therapies, address challenges medical

Language: Английский

Citations

0
Complete Blood Count in Children With COVID-19: A Predictor of Disease Severity DOI

Sandra Regina Loggetto,

Thiago de Souza Vilela, Julia Maimone Beatrice

et al.

Clinical Pediatrics, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 13, 2024

Blood count abnormalities are frequent in patients with severe COVID-19 disease and there is still a lack of information pediatric complete blood (CBC) results. Thus, this study aims to correlate the CBC emergency room children between 0 10 years old clinical severity disease. A retrospective cohort was performed who collected at CBC, C-reactive protein (CRP), platelet lymphocyte ratio (PLR), neutrophil (NLR), monocyte (NMR), (LNR), (LMR), (MNR) (MLR). In total, demographic data from 93 median age 19 months (0.3-126), 60.2% males, were included. The main changes atypical lymphocytes (51.6%) eosinopenia (49.5%). From 69 hospitalized children, 21 considered severe. There no association age, gender, CRP value severity. presence underlying five times higher (odds [OR] = 5.08) required hospitalization NLR 54% (OR 1.54) more likely occur. Eosinopenia three inpatients criteria 3.05). conclusion, younger than have room, mainly eosinopenia. comorbidity or increases chance hospitalization. addition, predictor inpatient due COVID-19.

Language: Английский

Citations

0
Strategies to Minimize Virus Transmission During Anesthesia Procedures in COVID-19 Patients DOI Open Access

Fihr Chaudhary,

Devendra K. Agrawal

Anesthesia and Critical Care, Journal Year: 2024, Volume and Issue: 6(4)

Published: Jan. 1, 2024

Anesthesiologists and the critical care team may be at increased risk of contracting severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, COVID-19) due to airway manipulations intubations performed during anesthesia administration management patient undergoing surgery. SARS-CoV-2 infections have been reported among healthcare workers. The virus is transmitted by close personal contact aerosols. During intubation other procedures involving airway, anesthesiologist especially susceptible We a systematic analysis published reports on potential effects COVID-19 surgery team. identified immunomodulatory general anesthetics in presence infection patients. article also provides discussion current medical highlights evidence-based key points for safer practice surgeries both children adults, including obstetric how it could affect pregnant women receiving anesthesia. With regional anesthesia, manipulation not necessary, workers patients are less likely contract same infection.

Language: Английский

Citations

0
Predicting Intensive Care Unit Admission in COVID-19-Infected Pregnant Women Using Machine Learning DOI Open Access
Azamat Mukhamediya, Iliyar Arupzhanov, Amin Zollanvari

et al.

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(24), P. 7705 - 7705

Published: Dec. 17, 2024

Background: The rapid onset of COVID-19 placed immense strain on many already overstretched healthcare systems. unique physiological changes in pregnancy, amplified by the complex effects pregnant women, rendered prioritization infected expectant mothers more challenging. This work aims to use state-of-the-art machine learning techniques predict whether a COVID-19-infected woman will be admitted ICU (Intensive Care Unit). Methods: A retrospective study using data from women one hospital Astana and Shymkent, Kazakhstan, May July 2021. developed platform implements compares performance eight binary classifiers, including Gaussian naïve Bayes, K-nearest neighbors, logistic regression with L2 regularization, random forest, AdaBoost, gradient boosting, eXtreme linear discriminant analysis. Results: Data 1292 were analyzed. Of them, 10.4% ICU. Logistic regularization achieved highest F1-score during model selection phase while achieving an AUC 0.84 test set evaluation stage. Furthermore, feature importance analysis conducted calculating Shapley Additive Explanation values points leucocyte counts, C-reactive protein, pregnancy week, eGFR hemoglobin as most important features for predicting admission. Conclusions: predictive obtained here may efficient support tool prioritizing care clinical practice.

Language: Английский

Citations

0