4 articles
Currently, extensive research has shown that almost all published prediction models are poorly studied and have significant limitations, leading to their predictive performance often being overestimated. Additionally, there is still no universally accepted scoring system, primarily due to the need for adaptation to heterogeneous patient samples (including patient numbers, clinical profiles, and risk factors) and/or ongoing differences in the organization of healthcare systems across various countries.
This is a narrative literature review. A bibliographic search was conducted in the PubMed, Hinari, SpringerLink, National Center for Biotechnology Information, and Medline databases. Articles published between 2000 and 2024 were selected based on keyword combinations such as "artificial intelligence", "prediction model", "algorithm", "machine learning", and "COVID-19". Information on machine learning predictive models was selected and processed to identify characteristics that can be used to predict diagnosis, severity, length of hospital stay, ICU admission, treatment, vaccination, and mortality in COVID-19 patients. After processing the data according to the search criteria, 125 full-text articles were identified. The final bibliography includes 52 relevant sources, which were considered representative of the literature on this synthesis article topic.
Artificial intelligence techniques are increasingly being used to predict outcomes in COVID-19 patients, particularly in estimating mortality among individuals infected with SARS-CoV-2, which can rapidly and effectively support clinical decision-making. According to the analysis of multiple studies, strong predictors of mortality in COVID-19 patients include advanced age, male gender, comorbidities, reduced levels of calcium, albumin, red blood cells, and oxygen saturation, as well as lymphopenia, elevated blood urea nitrogen, creatinine, lactate dehydrogenase, D-dimers, neutrophils, interleukin-6, procalcitonin, bilirubin, ferritin, aspartate aminotransferase, and troponin.
Artificial intelligence techniques provide potential advantages over conventional assessment methods. The information obtained from machine learning and deep learning algorithms, including easily accessible and interpretable data, can assist healthcare workers in making accurate decisions for the appropriate and timely care of COVID- 19 patients. This can improve patient outcomes, reduce the burden on healthcare systems, and ultimately decrease mortality rates.
Ozone therapy can be used as a monotherapy or as an adjunctive treatment to standard COVID-19 treatment protocols. Current evidence indicates that this approach may improve clinical outcomes, paraclinical markers, and reduce radiological signs of inflammation, with no side effects.
he study included 100 consecutive patients aged 18 and older with COVID-19, admitted to the Intensive Care Unit at the Institute of Emergency Medicine. Patients were randomly divided into two groups: 50 patients underwent treatment according to the National Clinical Protocol along with major ozonated autohemotherapy (the study group), while the other 50 patients were treated only according to the National Clinical Protocol (the control group).
Although the initial oxygenation index (PaO2/FiO2) values were similar in both study groups, a dynamic analysis revealed a clear efficacy of ozone therapy. By the end of the first-week treatment, the mean oxygenation index in the ozone-treated group was significantly higher than in the standard treatment group: 296.8±105.1 mm Hg versus 232.8±110.6 mm Hg (p<0.01). The use of oxygen therapy (70.0% vs. 78.0%), non-invasive ventilation (70.0% vs. 76.0%), and invasive mechanical ventilation (22.0% vs. 38.0%) tended to be lower in the ozone group, though this difference was not statistically significant (p>0.05). Both treatment groups showed a significant clinical improvement, with 54.0% of COVID-19 patients in the ozone group and 50.0% in the conventional treatment group achieving a two-point reduction in clinical severity score (p>0.05).
The mean oxygenation index significantly increased in the study patient group (246.86±30.3 mm Hg on day 1 and 296.75±105.1 mm Hg on day 7 of treatment; p<0.01) and remained unchanged in the control group (235.86±33.4 mm Hg on day 1 and 232.82±110.6 mm Hg on day 7 of treatment; p>0.05). Although the mortality rate was lower among COVID-19 patients treated with ozone therapy (24.0%) compared to those receiving standard treatment (34.0%), this difference did not achieve any statistical significance.
Oxygen-ozone therapy stands as a medically endorsed practice confirmed by numerous international clinical studies. Various authors have illustrated the beneficial clinical outcomes of ozone therapy in terms of its capacity to regulate redox balance, cellular inflammatory responses, and adaptation to ischemia/reperfusion processes. Ozone therapy extends to encompass a range of viral infections, inflammatory disorders, and degenerative ailments, used as both monotherapy and as an adjunct to unified conventional therapies.
Narrative literature review study. Bibliographic search was conducted using the PubMed, Hinari, and SpringerLink databases, as well as the National Center of Biotechnology Information and Medline. Articles published between 1990 and 2022 were selected using various combinations of keywords, including “ozone”, “ozone therapy”, “mechanisms of ozone action”, “biological effects of ozone”, “antioxidant effect”, “anti-inflammatory effect” and “immunomodulatory effect.” Information regarding ozone's mechanisms of action was identified and processed. Following the database information processing and search criteria, a total of 475 full-text articles were found. The final bibliography consists of 52 relevant sources that were deemed representative of the materials published on the topic of this synthesis article.
The effects of ozone on oxygen metabolism are explained by changes in the rheological properties of blood, including inhibition of erythrocyte aggregation and stimulation of 2,3-diphosphoglycerate in erythrocytes, favoring the transport and delivery of oxygen to tissues while facilitating the substantial elimination of nitric oxide and increasing blood flow. Intracellular triatomic oxygen enhances the oxidative carboxylation of pyruvate, stimulating ATP production, which also contributes to reducing peripheral vascular resistance.
Ozone generates a moderate oxidative stress. Yet, it can set off several beneficial biochemical mechanisms that reactivate both the intra- and extracellular antioxidant systems and reverse chronic oxidative stress in various inflammatory and degenerative processes. Ozone induces a mild activation of the immune system by triggering neutrophil activation and stimulating the synthesis of certain cytokines (IL-2, TNF-α, IL-6, and IFN-γ), thereby initiating a complete cascade of immune responses. Ozone therapy yields the following biological reactions: optimization of blood circulation and oxygen delivery to ischemic tissue, regulation of cellular antioxidant enzymes, initiation of a slight immune system activation, and enhancing the release of growth factors.
A major role and, at the same time, a question mark, both for patients and doctors, is the possibility that drugs and anesthetic techniques influence cancer metastasis. Cancer is the leading cause of death worldwide. This trend will continue in the future. Most of the deaths of cancer patients are due to complications arising from metastases. The metastasis process of a tumor depends on its intrinsic properties and interaction with the host. The treatment of tumors by performing a surgical intervention, radical or palliative, has a significant impact. For these reasons, the rate of survival and migration of cancer cells in the perioperative period is studied quite insistently and complexly. Thus, surgical intervention and anesthetic support in cancer patients becomes of great importance, because it represents the vulnerable link, both from the point of view of the operation itself, as well as the possibility that drugs, anesthetic techniques may or may not influence tumor metastasis.
Primary scientific studies published from 1996 to 2021 dedicated to loco-regional anesthesia and its influence on the perioperative period and on cancer metastasis were studied. To achieve the proposed goal, scientific sources PubMed, Medscape, SCOPUS, MEDLINE were researched. Keywords used for searching: loco-regional anesthesia, fascia plane anesthesia, metastasis. More than 80 reference sources were identified, 67 were selected for analysis.
The surgical procedure, itself, performed for curative purposes, also known as tumor resection – is a risk factor for metastasis by creating an environment with high potential for tumor cell survival. This stimulates tumor growth and angiogenesis, can remodel lymphatic pathways, allowing metastasis of tumor cells. Hemotransfusion is associated with increased risk of metastasis. Regional anesthesia could reduce cancer recurrence through several mechanisms.
Regional anesthesia could reduce cancer recurrence by reducing the need for opioids or inhaled anesthetics, or by reducing the stress response during surgery. There is scientific in vitro evidence of a protective effect of systemic lidocaine on recurrent cancer, although relevant clinical data are limited.