Pub Date : 2023-08-17DOI: 10.32474/lojms.2023.06.000244
Peter Phiri
{"title":"Impact of SARS-Cov-2 on Clinical Trial Unit Workforce in the United Kingdom: An Observational Study","authors":"Peter Phiri","doi":"10.32474/lojms.2023.06.000244","DOIUrl":"https://doi.org/10.32474/lojms.2023.06.000244","url":null,"abstract":"","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136337639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-04DOI: 10.32474/lojms.2023.06.000243
Peter Phiri
{"title":"An Evidence-Based Methodological Framework for Pandemic Preparedness to Support the Clinical Trial Unit Workforce","authors":"Peter Phiri","doi":"10.32474/lojms.2023.06.000243","DOIUrl":"https://doi.org/10.32474/lojms.2023.06.000243","url":null,"abstract":"","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134973577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-16DOI: 10.32474/lojms.2022.06.000235
M. Ali Khan
{"title":"Spectrum of Thyroid Cancers & its Variants: An Exhaustive Analysis of the Literature","authors":"M. Ali Khan","doi":"10.32474/lojms.2022.06.000235","DOIUrl":"https://doi.org/10.32474/lojms.2022.06.000235","url":null,"abstract":"","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83710032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-14DOI: 10.32474/lojms.2021.05.000225
G. Delanerolle
Machine Learning (ML) is a common Artificial Intelligence (AI) method. The use of ML offers the opportunity to develop better data mining techniques in order to analyse complex clinical interactions with a large number of variables. ML models should provide “real-time” clinical support reducing clinical risk to patients with model-agnostic interpretation to deduce a more specific clinical decision. Whilst ML algorithms have been used as the relatively “new kid on the block” in healthcare practice, they have shown promising results in predicting disease outcomes or risks in a variety of diseases such as depressive disorder, Type 2 diabetes mellitus, postoperative complications and cardiovascular diseases. However, patients suffering from a chronic condition are likely to have more than one condition requiring simultaneous attention and care. Therefore, a risk assessment model developed using ML methods, in theory, would be suitable to evaluate multimorbid populations. While there are many AI/ML algorithms and methods to build such a risk assessment tool, an optimal ‘fit-for-purpose’ model is chosen by comparing and contrasting across many possible alternatives. Further, given the high-stake decisions associated with health, it is also important that the model is interpretable and explainable by the clinicians who are purported to use such a model as their decision support system. In this paper, we provide a perspective on the current landscape of multimorbidity treatment, potential benefit of employing AI/ML to enhance holistic care of multimorbid patients, and associated challenges, concerns that need to be addressed as we make progress in this direction.
{"title":"A Perspective: Use of Machine Learning Models to Predict the Risk of Multimorbidity","authors":"G. Delanerolle","doi":"10.32474/lojms.2021.05.000225","DOIUrl":"https://doi.org/10.32474/lojms.2021.05.000225","url":null,"abstract":"Machine Learning (ML) is a common Artificial Intelligence (AI) method. The use of ML offers the opportunity to develop better data mining techniques in order to analyse complex clinical interactions with a large number of variables. ML models should provide “real-time” clinical support reducing clinical risk to patients with model-agnostic interpretation to deduce a more specific clinical decision. Whilst ML algorithms have been used as the relatively “new kid on the block” in healthcare practice, they have shown promising results in predicting disease outcomes or risks in a variety of diseases such as depressive disorder, Type 2 diabetes mellitus, postoperative complications and cardiovascular diseases. However, patients suffering from a chronic condition are likely to have more than one condition requiring simultaneous attention and care. Therefore, a risk assessment model developed using ML methods, in theory, would be suitable to evaluate multimorbid populations. While there are many AI/ML algorithms and methods to build such a risk assessment tool, an optimal ‘fit-for-purpose’ model is chosen by comparing and contrasting across many possible alternatives. Further, given the high-stake decisions associated with health, it is also important that the model is interpretable and explainable by the clinicians who are purported to use such a model as their decision support system. In this paper, we provide a perspective on the current landscape of multimorbidity treatment, potential benefit of employing AI/ML to enhance holistic care of multimorbid patients, and associated challenges, concerns that need to be addressed as we make progress in this direction.","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"35 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78022872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-21DOI: 10.32474/lojms.2020.04.000200
Fatma Ibrahim Abdel-latif Megahed
{"title":"Most Effiecnt Factors Affecting Glycemic Control of Type II Diabetic Patients Attending Suez Canal University Hospitals in Egypt Applying Stepwise Regression","authors":"Fatma Ibrahim Abdel-latif Megahed","doi":"10.32474/lojms.2020.04.000200","DOIUrl":"https://doi.org/10.32474/lojms.2020.04.000200","url":null,"abstract":"","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81210073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-04DOI: 10.32474/lojms.2018.02.000148
J. Finsterer
{"title":"Left Ventricular Hypertrabeculation/Noncompaction is Not Unique in Trisomy 22","authors":"J. Finsterer","doi":"10.32474/lojms.2018.02.000148","DOIUrl":"https://doi.org/10.32474/lojms.2018.02.000148","url":null,"abstract":"","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81042097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-04DOI: 10.32474/LOJMS.2018.02.000149
J. Finsterer
{"title":"MELAS is Usually an Early Onset Disease","authors":"J. Finsterer","doi":"10.32474/LOJMS.2018.02.000149","DOIUrl":"https://doi.org/10.32474/LOJMS.2018.02.000149","url":null,"abstract":"","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87886581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-04DOI: 10.32474/lojms.2018.02.000150
L. Sarvananda
As per many findings, NCDs are the leading cause of death globally. In 2012, it was recorded as 60% to 68% of all deaths in 2000. About half were under the age of 70 and women population was high [1]. Every year, at least 5 million people die because of tobacco consumption and about 2.8 million die from being obese. At the same time, the death rates of Hypercholesteremia patients are roughly calculated as 2.6 million to 7.5 million because of high blood pressure [2]. There are several reasons resulting this, emerging trend-urbanization, lifestyle transformations, and related factors might be person’s background, lifestyle, genetics errors in genetic information and environmental factors such as sunlight, nutrition, exposure to air pollution, which can affect people, are known to increase the certain non-communicable diseases. It also includes age, gender, and unwanted behaviors like smoking, unhealthy diet and physical inactivity which can leads to increased risk of many NCDs [3]. According to World Health Report in 2002, they identified five important risk factors increasing the level of noncommunicable diseases in health environment. They are raising blood pressure, cholesterol, tobacco use, alcohol consumption, and overweight/obesity. The other factors associated with higher risk of NCDs include a person’s economic and social conditions.
{"title":"Influence of Body Mass Index to Avert Non-Communicable Diseases","authors":"L. Sarvananda","doi":"10.32474/lojms.2018.02.000150","DOIUrl":"https://doi.org/10.32474/lojms.2018.02.000150","url":null,"abstract":"As per many findings, NCDs are the leading cause of death globally. In 2012, it was recorded as 60% to 68% of all deaths in 2000. About half were under the age of 70 and women population was high [1]. Every year, at least 5 million people die because of tobacco consumption and about 2.8 million die from being obese. At the same time, the death rates of Hypercholesteremia patients are roughly calculated as 2.6 million to 7.5 million because of high blood pressure [2]. There are several reasons resulting this, emerging trend-urbanization, lifestyle transformations, and related factors might be person’s background, lifestyle, genetics errors in genetic information and environmental factors such as sunlight, nutrition, exposure to air pollution, which can affect people, are known to increase the certain non-communicable diseases. It also includes age, gender, and unwanted behaviors like smoking, unhealthy diet and physical inactivity which can leads to increased risk of many NCDs [3]. According to World Health Report in 2002, they identified five important risk factors increasing the level of noncommunicable diseases in health environment. They are raising blood pressure, cholesterol, tobacco use, alcohol consumption, and overweight/obesity. The other factors associated with higher risk of NCDs include a person’s economic and social conditions.","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86766606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-19DOI: 10.32474/LOJMS.2018.02.000147
J. Finsterer, C. Stöllberger
In a recent article, Pipitone et al. [1] reported about a fetus with calcified left ventricular hypertrabeculation / noncompaction (LVHT) and persistence of the abnormality after delivery [1]. We have the following comments and concerns regarding this paper. LVHT is frequently associated with other cardiac abnormalities or diseases of organs other than the heart. Was the index patient or any of the relatives investigated for multisystem involvement? Was there any indication for cerebral, ocular, otologic, endocrine, cardiac, intestinal, renal, haematological, or cutaneous abnormalities in addition to LVHT?
{"title":"Cause and Management of Calcified Left Ventricular Hyper trabeculation / Noncompaction","authors":"J. Finsterer, C. Stöllberger","doi":"10.32474/LOJMS.2018.02.000147","DOIUrl":"https://doi.org/10.32474/LOJMS.2018.02.000147","url":null,"abstract":"In a recent article, Pipitone et al. [1] reported about a fetus with calcified left ventricular hypertrabeculation / noncompaction (LVHT) and persistence of the abnormality after delivery [1]. We have the following comments and concerns regarding this paper. LVHT is frequently associated with other cardiac abnormalities or diseases of organs other than the heart. Was the index patient or any of the relatives investigated for multisystem involvement? Was there any indication for cerebral, ocular, otologic, endocrine, cardiac, intestinal, renal, haematological, or cutaneous abnormalities in addition to LVHT?","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87377039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-18DOI: 10.32474/LOJMS.2018.02.000146
D. Sisk
Gifted Individuals have a unique perception of their world and of themselves, and they can be intense and highly sensitive to moral issues with a keen sense of justice [1,2]. These moral issues affect them deeply and they often feel helpless in being able to make a difference. In Making Great Kids Greater: Easing the Burden of Being Gifted (2009) Sisk addressed the unique perception of gifted students and suggested ways that great kids can become greater. One way to provide a lens of understanding of the intense nature of gifted individuals is to apply the Theory of Positive Disintegration of Kazimierz Dabrowski [3]. Mendaglio [4] asserts that Dabrowski’s theory is a personality theory for the 2lst century and this article will explore its application to gifted students.
{"title":"Applying the Dabrowski Theory to Build an Understanding of the Intensities and Sensitivity of Gifted Individuals","authors":"D. Sisk","doi":"10.32474/LOJMS.2018.02.000146","DOIUrl":"https://doi.org/10.32474/LOJMS.2018.02.000146","url":null,"abstract":"Gifted Individuals have a unique perception of their world and of themselves, and they can be intense and highly sensitive to moral issues with a keen sense of justice [1,2]. These moral issues affect them deeply and they often feel helpless in being able to make a difference. In Making Great Kids Greater: Easing the Burden of Being Gifted (2009) Sisk addressed the unique perception of gifted students and suggested ways that great kids can become greater. One way to provide a lens of understanding of the intense nature of gifted individuals is to apply the Theory of Positive Disintegration of Kazimierz Dabrowski [3]. Mendaglio [4] asserts that Dabrowski’s theory is a personality theory for the 2lst century and this article will explore its application to gifted students.","PeriodicalId":18057,"journal":{"name":"LOJ Medical Sciences","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82259755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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