Pharmacotherapy of Systemic Autoimmune Diseases in Conditions of the Covid-19 Pandemic: Innovative Experimental Study

Hayduchok, Ihor

doi:10.31435/rsglobal_sr/30072021/7619

Cited by 8 publications

(4 citation statements)

References 10 publications

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Section: Methodsmentioning

confidence: 99%

“…However, the term "ABC analysis" is used ambiguously in the biomedical literature. "ABC analysis" is used for: (i) "Ap-proximate Bayesian Computation" (e.g., 3,4 ), (ii) "Antecedent-Behavior-Consequence", which is a method for analyzing behavior and comes from the field of psychology 5 , and (iii) an inventory categorization method originating in economics, where ABC occasionally stands for "Always Better Control", used in inventory control and management (e.g., [6][7][8][9] ).This report refers only to the idea underlying the latter meaning of ABC analysis, i.e., the item or inventory categorization method that aims to identify the most relevant items by dividing a set of non-negative numerical items into subsets "A", "B", and "C" 10 . However, the term "Always Better Control" for "ABC", which was never used by Juran, should not be associated with the present method.…”

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confidence: 99%

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Recursive computed ABC (cABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size

Lötsch

Ultsch

2023

Sci Rep

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Selecting the k best features is a common task in machine learning. Typically, a few features have high importance, but many have low importance (right-skewed distribution). This report proposes a numerically precise method to address this skewed feature importance distribution in order to reduce a feature set to the informative minimum of items. Computed ABC analysis (cABC) is an item categorization method that aims to identify the most important items by partitioning a set of non-negative numerical items into subsets "A", "B", and "C" such that subset "A" contains the "few important" items based on specific properties of ABC curves defined by their relationship to Lorenz curves. In its recursive form, the cABC analysis can be applied again to subset "A". A generic image dataset and three biomedical datasets (lipidomics and two genomics datasets) with a large number of variables were used to perform the experiments. The experimental results show that the recursive cABC analysis limits the dimensions of the data projection to a minimum where the relevant information is still preserved and directs the feature selection in machine learning to the most important class-relevant information, including filtering feature sets for nonsense variables. Feature sets were reduced to 10% or less of the original variables and still provided accurate classification in data not used for feature selection. cABC analysis, in its recursive variant, provides a computationally precise means of reducing information to a minimum. The minimum is the result of a computation of the number of k most relevant items, rather than a decision to select the k best items from a list. In addition, there are precise criteria for stopping the reduction process. The reduction to the most important features can improve the human understanding of the properties of the data set. The cABC method is implemented in the Python package "cABCanalysis" available at https://pypi.org/project/cABCanalysis/.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Recursive computed ABC (cABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size

Lötsch

Ultsch

2023

Sci Rep

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“…Some strategies (eg, reducing costs, linking vaccination with services for women, infants and children, home visits) work well to increase coverage in certain populations. Taking into account forensic pharmaceutical risks in the organization of vaccination practice and pharmacotherapy of covid, post-covid and long-covid disorders plays a decisive role in pandemic conditions [23][24][25][26][27][28][29].…”

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confidence: 99%

Forensic and Pharmaceutical Risks in the Organization of Pharmacotherapy of Covid, Post-Covid and Long-Covid Disorders. COVID-19 and Vaccination Practice Standards.

Шаповалова

2022

SSPMPM

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The COVID-19 pandemic has strained the healthcare system. It is important to consider forensic and pharmaceutical risks in the organization of vaccination practices and pharmacotherapy of covid, post-covid and long-covid disorders. Scientific sources on the clinical characteristics of SARS-CoV-2, COVID-19 have been systematized. The standards of vaccination practice (immunization, vaccination) of different age categories of the population in Ukraine, England, USA, Belgium, Greece, Japan, and Portugal were analyzed. Proven that the organization of pharmacotherapy schemes is difficult due to the presence of mixed infections, comorbid and complicated forms of diseases, the formation of virus resistance to drugs, and the development of secondary immunological insufficiency. The risks of pharmacotherapy with regard to mortality in patients with COVID-19 due to the development of severe lung lesions and systemic multiorgan pathology are indicated. Schemes of combined pharmacotherapy including antiviral, anti-inflammatory drugs, glucocorticosteroids, genetically engineered biological drugs and "targeted" basic anti-inflammatory drugs were analyzed. The theoretical prerequisites for "repositioning" (drug repurposing) for the treatment of COVID-19 and ego complications are indicated. New directions of anti-inflammatory pharmacotherapy of COVID-19 Janus kinase with a range of anti-inflammatory and antiviral effects were noted. Emphasis was placed on the importance of informing health care professionals about forensic pharmaceutical risks in pharmacotherapy and vaccination practices. The relevance of legal support for medical activity in the conditions of a pandemic was noted. Further research is ongoing.

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“…Вступ. В умовах пандемії коронавірусної хвороби мультидисциплінарні дослідження у сфері охорони здоров'я об'єднують міждисциплінарні зв'язки вчених усього світу з медицини, фармації, права, економіки щодо належної медичної практики, фармацевтичного забезпечення та доступності лікарських засобів клініко-фармакологічних, класифікаційно-правових та номенклатурноправових груп для всіх контингентів пацієнтів [1][2][3][4][5]. Судово-фармацевтичні ризики виникають упродовж надання медичної допомоги, обігу лікарських засобів на рівні закладів охорони здоров'я (лікарні, аптеки, поліклініки), фармакотерапії супроводу розладів здоров'я, доступності для пацієнтів ліків всіх клініко-фармакологічних, класифікаційно-правових та номенклатурно-правових груп [6][7][8][9].…”

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Covid-19: Мультидисциплінарні дослідження судово-фармацевтичних ризиків та причинно-наслідкових зв’зків некваліфікованої медичної допомоги пацієнтам під час пандемії

Hayduchok¹,

Shapovalov²

2022

SSPMLP

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A multidisciplinary study was conducted to study the forensic and pharmaceutical risks and to establish the casual relationships of unqualified medical care (medical errors) to patients and the development of diseases during the COVID-19 pandemic. It was substantiated that in the context of the coronavirus pandemic, multidisciplinary research in the field of healthcare combines interdisciplinary links of scientists from around the world in medicine, pharmacy, law, economics on good medical practice, pharmaceutical provision and availability of clinical and pharmacological, nomenclature and legal groups for all contingents of patients. It was noted in examples from forensic and pharmaceutical practice that unqualified medical care (medical or medical errors) can lead to varying degrees of severity of health disorders, improper performance of professional duties by a medical or pharmaceutical worker contains in its content forensic pharmaceutical risks provision of medicines, ultimately leads to health offenses. Causation has been shown to be associated with pandemics of coronavirus infection in the context of COVID, long-COVID and post-COVID health disorders. It was noted that the pandemic to COVID-19 and its consequences have three characteristic features of traumatic events: unpredictability, uncontrollability, threat of death or serious injury. The experience of the USA, France, Israel, China, EU countries on the example of Estonia on the organization of the healthcare system during the COVID-19 pandemic were studied. It was shown that the commercialization of the system of legal relations "doctor-patient-pharmacist-lawyer" affects the quality of medical practice and the availability of medicines for patients. Emphasis was placed on the continuing of professional development for healthcare professionals in the casual relationship of unqualified medical care (medical errors) to patients and the development of COVID, long-COVID and post-COVID diseases during the COVID-19 pandemic. The prospects of using Estonia's experience in the digital healthcare system, which covers all medical institutions in the country and every citizen were mentioned.

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Pharmacotherapy of Systemic Autoimmune Diseases in Conditions of the Covid-19 Pandemic: Innovative Experimental Study

Cited by 8 publications

References 10 publications

Recursive computed ABC (cABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size

Recursive computed ABC (cABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size

Forensic and Pharmaceutical Risks in the Organization of Pharmacotherapy of Covid, Post-Covid and Long-Covid Disorders. COVID-19 and Vaccination Practice Standards.

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