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Journal of Geriatric Oncology Jun 2023The number of older patients with cancer is expected to continue to increase owing to the aging population. Recently, the usefulness of geriatric assessment (GA)... (Review)
Review
Significance of the comprehensive geriatric assessment in the administration of chemotherapy to older adults with cancer: Recommendations by the Japanese Geriatric Oncology Guideline Committee.
INTRODUCTION
The number of older patients with cancer is expected to continue to increase owing to the aging population. Recently, the usefulness of geriatric assessment (GA) conducted by multiple staff members from different medical backgrounds has been reported; however, a consensus on the effectiveness of GA has not yet been achieved.
MATERIALS AND METHODS
We, as the Japanese Geriatric Oncology Guideline Committee for elderly patients with cancer, conducted a literature search of randomized controlled trials published before August 2021 that used GA or comprehensive GA (CGA) as an intervention for patients with cancer undergoing chemotherapy. As the key outcomes for answering the clinical question, we focused on survival benefit, adverse events, and quality of life (QOL). After a systematic review of these studies, the expert panel member developed recommendations according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system.
RESULTS
For older patients with cancer, GA or CGA is suggested during or before chemotherapy (weakly recommended). Chemotherapy-induced adverse events were significantly reduced by GA/CGA interventions without any adverse effects on survival. Health-related QOL tended to improve with the GA/CGA interventions.
DISCUSSION
Although, in our opinion, GA/CGA does require time and resources, it poses no harm patients. Therefore, we suggest expanding the human resources and educating skills of medical providers for clinical implementation of GA/CGA.
Topics: Aged; Humans; Aging; East Asian People; Geriatric Assessment; Neoplasms; Quality of Life; Randomized Controlled Trials as Topic
PubMed: 37062639
DOI: 10.1016/j.jgo.2023.101485 -
PloS One 2023Undernutrition (Body Mass Index < 18.5 kg/m2) is a common problem and a major cause of hospital admission for patients living with HIV. Though sub-Saharan Africa is the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Undernutrition (Body Mass Index < 18.5 kg/m2) is a common problem and a major cause of hospital admission for patients living with HIV. Though sub-Saharan Africa is the most commonly affected region with HIV and malnutrition, a meta-analysis study that estimates the prevalence and correlates of undernutrition among adults living with HIV has not yet been conducted. The objective of this study was to determine the pooled prevalence of undernutrition and associated factors among adults living with HIV/AIDS in sub-Saharan Africa.
METHODS
Studies published in English were searched systematically from databases such as PubMed, Google Scholar, and gray literature, as well as manually from references in published articles. Observational studies published from 2009 to November 2021 were included. The data extraction checklist was prepared using Microsoft Excel and includes author names, study area, publication year, sample size, prevalence/odds ratio, and confidence intervals. The results were presented and summarized in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) standard. Heterogeneity was investigated using the Q test, I2, τ2, τ and predictive interval. STATA version 17 was used to analyze the data. A meta-analysis using a random-effects model was used to determine the overall prevalence and adjusted odds ratio. The study has been registered in PROSPERO with a protocol number of CRD42021268603.
RESULTS
In this study, a total of 44 studies and 22,316 participants were included. The pooled prevalence of undernutrition among adult people living with HIV (PLWHIV) was 23.72% (95% CI: 20.69-26.85). The factors associated with undernutrition were participants' age (AOR = 0.5, 95% CI: 0.29-0.88), gender (AOR = 2.08, 95% CI: 0.22-20.00), World Health Organization (WHO) clinical stage (AOR = 3.25, 95% CI: 2.57-3.93), Cluster of Differentiation 4 (CD4 count) (AOR = 1.94, 95% CI: 1.53-2.28), and duration of ART (AOR = 2.32, 95% CI: 1.6-3.02).
CONCLUSION
The pooled prevalence of undernutrition among adult PLWHIV in sub-Saharan Africa remained high. WHO clinical stage, CD4 count, duration of ART treatment, age, and sex were found to be the factors associated with undernutrition. Reinforcing nutrition counseling, care, and support for adults living with HIV is recommended. Priority nutritional screening and interventions should be provided for patients with advanced WHO clinical stages, low CD4 counts, the male gender, younger age groups, and ART beginners.
Topics: Humans; Adult; Male; Nutrition Assessment; Prevalence; Nutritional Status; HIV Infections; Malnutrition; Africa South of the Sahara
PubMed: 36961844
DOI: 10.1371/journal.pone.0283502 -
Frontiers in Oncology 2023The uncommon -altered primary central nervous system (CNS) tumors were recently added to the World Health Organization 2021 classification under the name Astroblastoma,...
The uncommon -altered primary central nervous system (CNS) tumors were recently added to the World Health Organization 2021 classification under the name Astroblastoma, -altered. Another term used to describe them, "High-grade neuroepithelial tumor with alteration" (HGNET-MN1), makes reference to their distinct epigenetic profile but is currently not a recommended name. Thought to occur most commonly in children and predominantly in females, -altered CNS tumors are associated with typical but not pathognomonic histological patterns and are characterized by a distinct DNA methylation profile and recurrent fusions implicating the (meningioma 1) gene. Diagnosis based on histological features alone is challenging: most cases with morphological features of astroblastoma (but not all) show these molecular features, whereas not all tumors with fusions show astroblastoma morphology. There is large variability in reported outcomes and detailed clinical and therapeutic information is frequently missing. Some patients experience multiple recurrences despite multimodality treatment, whereas others experience no recurrence after surgical resection alone, suggesting large clinical and biological heterogeneity despite unifying epigenetic features and recurrent fusions. In this report, we present the demographics, tumor characteristics, treatment, and outcome (including patient-reported outcomes) of three adults with -altered primary CNS tumors diagnosed genome-wide DNA methylation and RNA sequencing. All three patients were females and two of them were diagnosed as young adults. By reporting our neuropathological and clinical findings and comparing them with previously published cases we provide insight into the clinical heterogeneity of this tumor. Additionally, we propose a model for prospective, comprehensive, and systematic collection of clinical data in addition to neuropathological data, including standardized patient-reported outcomes.
PubMed: 36741001
DOI: 10.3389/fonc.2023.1099618 -
Annals of Vascular Surgery May 2023We noted distinct differences between the demographics among the presidents of various vascular societies. To help characterize these among the present United States,...
BACKGROUND
We noted distinct differences between the demographics among the presidents of various vascular societies. To help characterize these among the present United States, Canadian, and European vascular societies, we queried the websites for the United States, Canadian, and European vascular societies in a systematic review for the names of their presidents since their respective inceptions.
METHODS
Age and ethnicity were determined by a search on healthgrades.com, Google, and online obituaries. The year of ascendency to the presidency and the year of birth were used as identifying time points.
RESULTS
There are significant differences between the ages of the presidents of the various vascular societies. While the presidents of Vascular and Endovascular Surgical Society were significantly younger than those of every other vascular society examined, Midwestern Vascular Surgical Society, Canadian Society for Vascular Surgery, and Society of Vascular Medicine were also significantly younger than the remainder of the societies examined (P < 0.0001). The presidents of the remaining societies were not significantly different in age from each other. When comparing the ages of the presidents in the first and last decades of each society, 2 were found to have significantly increased (Society of Vascular Medicine [P = 0.0029] and Vascular and Endovascular Surgical Society [P < 0.0001]), while 2 others were found to have significantly decreased (New England Society for Vascular Surgery [P = 0.0092] and Eastern Vascular Society [P = 0.0085]). Of the 532 total entries for these presidents examined over these 13 societies, 19 (3.6%) of these were filled by women and 37 (7%) with minorities.
CONCLUSIONS
There was a great deal of variability in terms of age, gender, and minority representation of the presidents among the vascular societies examined. While the share of women and minorities to serve as presidents in vascular societies varied between societies, both groups were under-represented across the board. However, in recent years, the number of women and minorities elected as presidents of vascular societies has been trending upwards.
Topics: Humans; Female; United States; Societies, Medical; Canada; Treatment Outcome; Specialties, Surgical; Vascular Surgical Procedures; Leadership
PubMed: 36642170
DOI: 10.1016/j.avsg.2022.12.094 -
Journal of Affective Disorders Mar 2023Currently, there is no clear answer to the question of how long antidepressants should be continued or when they can be safely discontinued. (Review)
Review
BACKGROUND
Currently, there is no clear answer to the question of how long antidepressants should be continued or when they can be safely discontinued.
METHODS
Pubmed/Medline was systematically searched from inception to Feb 20, 2021. Double-blind, randomized placebo-controlled trials (RCTs) with maintenance phase were selected to examine the relationship between relapse rate and treatment duration. Among 5351 screened records, 37 RCTs meeting inclusion criteria were selected. Odds ratios were calculated from relapse rates for each study and pooled in random-effect models. Possible predictors of effect sizes, i.e., open-label treatment duration, double-blind phase duration, age, medication type, history of recurrence, were analyzed by meta-regression.
RESULTS
The random-effects model showed the superiority of active medication over placebo for relapse during the follow-up phase (OR = 0.37; 95 % CI, 0.32-0.42). The meta-regression did not show a relationship between treatment duration and the effect sizes. Other clinical variables were not related with effect sizes. Subgroup analysis revealed that, for atypical ADs the effect size increased as the treatment duration increased. Further analysis showed that the relapse rate in the placebo group decreased as function of time, which reduced the absolute benefit of continued treatment.
CONCLUSION
The results may indicate that long term use of antidepressants may not be justified, and this strategy may expose the patients to more adverse effects.
Topics: Humans; Randomized Controlled Trials as Topic; Antidepressive Agents; Depressive Disorder, Major; Double-Blind Method; Recurrence
PubMed: 36623560
DOI: 10.1016/j.jad.2023.01.024 -
Heliyon Dec 2022The advancement of information and communication technologies has led to an increasing use of conversational chatbots in the learning and teaching sector, especially for...
The advancement of information and communication technologies has led to an increasing use of conversational chatbots in the learning and teaching sector, especially for the second language (L2) acquisition. In the field of second language acquisition, the use of AI chatbots has been explored, mainly studying pedagogical approaches. However, there is a limited study in the development of empathetic strategies for dealing with learners' emotional discomfort, the impact of humor and the consideration of learners' cultural backgrounds. Thus, this study reviews the existing studies on AI second language (L2) chatbots to investigate the development of empathetic strategies for enhancing learners' learning outcomes. To achieve the aim of this study, prior studies from 2012 and 2022 of several popular databases, including Web of Science, ProQuest, IEEE and ScienceDirect are collected and analyzed. This study found that three dimensions such as cultural, empathetic and humorous dimensions have a positive influence on the application of AI L2 chatbots for enhancing learners' learning outcomes. This study also found that the development of an AI chatbot in L2 education has plenty of room for improvement. Several recommendations are made for enhancing the use of AI L2 chatbots which include integrating cross-cultural empathetic responses in conversational L2 chatbots, identifying how learners perceive and react to the learning content, and investigating the effects of cross-culture humor on learners' language proficiency.
PubMed: 36531630
DOI: 10.1016/j.heliyon.2022.e12056 -
Journal of Orthopaedic Surgery and... Dec 2022In the emergency room, clinicians spend a lot of time and are exposed to mental stress. In addition, fracture classification is important for determining the surgical...
BACKGROUND
In the emergency room, clinicians spend a lot of time and are exposed to mental stress. In addition, fracture classification is important for determining the surgical method and restoring the patient's mobility. Recently, with the help of computers using artificial intelligence (AI) or machine learning (ML), diagnosis and classification of hip fractures can be performed easily and quickly. The purpose of this systematic review is to search for studies that diagnose and classify for hip fracture using AI or ML, organize the results of each study, analyze the usefulness of this technology and its future use value.
METHODS
PubMed Central, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE, and AHRQ databases were searched to identify relevant studies published up to June 2022 with English language restriction. The following search terms were used [All Fields] AND (", "[MeSH Terms] OR (""[All Fields] AND "bone"[All Fields]) OR "bone fractures"[All Fields] OR "fracture"[All Fields]). The following information was extracted from the included articles: authors, publication year, study period, type of image, type of fracture, number of patient or used images, fracture classification, reference diagnosis of fracture diagnosis and classification, and augments of each studies. In addition, AI name, CNN architecture type, ROI or important region labeling, data input proportion in training/validation/test, and diagnosis accuracy/AUC, classification accuracy/AUC of each studies were also extracted.
RESULTS
In 14 finally included studies, the accuracy of diagnosis for hip fracture by AI was 79.3-98%, and the accuracy of fracture diagnosis in AI aided humans was 90.5-97.1. The accuracy of human fracture diagnosis was 77.5-93.5. AUC of fracture diagnosis by AI was 0.905-0.99. The accuracy of fracture classification by AI was 86-98.5 and AUC was 0.873-1.0. The forest plot represented that the mean AI diagnosis accuracy was 0.92, the mean AI diagnosis AUC was 0.969, the mean AI classification accuracy was 0.914, and the mean AI classification AUC was 0.933. Among the included studies, the architecture based on the GoogLeNet architectural model or the DenseNet architectural model was the most common with three each. Among the data input proportions, the study with the lowest training rate was 57%, and the study with the highest training rate was 95%. In 14 studies, 5 studies used Grad-CAM for highlight important regions.
CONCLUSION
We expected that our study may be helpful in making judgments about the use of AI in the diagnosis and classification of hip fractures. It is clear that AI is a tool that can help medical staff reduce the time and effort required for hip fracture diagnosis with high accuracy. Further studies are needed to determine what effect this causes in actual clinical situations.
Topics: Humans; Artificial Intelligence; Hip Fractures; Machine Learning; Databases, Factual; Emergency Service, Hospital
PubMed: 36456982
DOI: 10.1186/s13018-022-03408-7 -
Infection and Drug Resistance 2022The use of poor quality drugs will have multiple consequences with an extended hazard of growing drug-resistant strains. (Review)
Review
BACKGROUND
The use of poor quality drugs will have multiple consequences with an extended hazard of growing drug-resistant strains.
PURPOSE
The review aimed to provide the quality status of antimalarial drugs in East Africa.
DATA SOURCE
PubMed, Scopus, Web of Science, and Google Scholar were searched from September 5 to September 12, 2021.
STUDY SELECTION
The review included articles available as original research targeted at evaluating the quality of antimalarial drugs. For inclusion, data on at least one of the following quality control parameters were required: packaging and labeling, hardness, friability, weight variation/uniformity of weight, disintegration, dissolution, and assay/percentage purity. Mendeley citation manager version 1.19.4 was used to avoid duplication and organize references, and titles and abstracts were primarily used for screening.
DATA EXTRACTION
The sample collection site, drug name, and the quality control parameters tested were retrieved from the selected studies.
DATA SYNTHESIS
Totally, 300 antimalarial drug samples from Ethiopia, Kenya and Tanzania were included in this review. No antimalarial drug tested failed the identification and disintegration test. However, 15.93% (36/226), 5.00% (15/300), and 1.90% (3/158) of antimalarial samples failed the dissolution, assay and mass uniformity test, respectively. Moreover, amodiaquine and sulfadoxine/pyrimethamine samples failed dissolution and assay tests. In addition, amodiaquine samples failed the mass uniformity test. However, artemether/lumefantrine and quinine passed all quality control parameters tested. Overall, 19.67% (59/300) of antimalarial drug samples did not meet at least one quality control parameter. And the higher faller rate was reported for sulfadoxine/pyrimethamine accounting for 52.86% (37/70).
CONCLUSIONS
An unneglected amount of antimalarial drug failed to meet at least one quality control parameter. Strengthening pharmaceutical management systems, including post-marketing surveillance, and providing the resources required for medication quality assurance, are recommended.
PubMed: 36277242
DOI: 10.2147/IDR.S373059 -
Nurse Education in Practice Nov 2022To explore factors that influence fathers' experiences of childbirth and implications for their subsequent postnatal mental health. (Review)
Review
AIM
To explore factors that influence fathers' experiences of childbirth and implications for their subsequent postnatal mental health.
BACKGROUND
Fathers who attend the birth of their baby often have very rewarding experiences. However, those who witness a difficult birth may progress to develop subsequent mental health problems, e.g., trauma symptoms that can affect future relationships with partner and infant.
METHOD
A narrative systematic review of literature was carried out. Two overarching themes were identified, each with 3 underpinning sub-themes: (1) Interpersonal relationships with maternity care professionals; (1b) Communication; (1b) Feeling isolated during labour; (1c) Being prepared; (2) The aftermath; (2a) Support provision; (2b) Effects on relationships; (2c) Psychological trauma.
CONCLUSIONS
Findings emphasise that good communication between fathers and midwives is a fundamental part of providing excellent care before, during and post-childbirth, as it can reduce partners' feelings of isolation, improve their relationships and limit development and impact of psychological trauma.
RECOMMENDATIONS FOR PRACTICE
It is important to develop more on-line partner sites, parenthood education programmes and support groups, which include education about how to prevent, recognise, support and treat mental health complications. Also, further in-depth qualitative studies would enhance understanding of specific aspects of labour that traumatise fathers.
Topics: Female; Humans; Infant; Male; Pregnancy; Fathers; Maternal Health Services; Mental Health; Parturition; Qualitative Research
PubMed: 36244315
DOI: 10.1016/j.nepr.2022.103460 -
Artificial Intelligence in Medicine Oct 2022Early detection and prediction of suicidal behaviour are key factors in suicide control. In conjunction with recent advances in the field of artificial intelligence,... (Review)
Review
BACKGROUND
Early detection and prediction of suicidal behaviour are key factors in suicide control. In conjunction with recent advances in the field of artificial intelligence, there is increasing research into how machine learning can assist in the detection, prediction and treatment of suicidal behaviour. Therefore, this study aims to provide a comprehensive review of the literature exploring machine learning techniques in the study of suicidal behaviour prediction.
METHODS
A search of four databases was conducted: Web of Science, PubMed, Dimensions, and Scopus for research papers dated between January 2016 and September 2021. The search keywords are 'data mining', 'machine learning' in combination with 'suicidal behaviour', 'suicide', 'suicide attempt', 'suicidal ideation', 'suicide plan' and 'self-harm'. The studies that used machine learning techniques were synthesized according to the countries of the articles, sample description, sample size, classification tasks, number of features used to develop the models, types of machine learning techniques, and evaluation of performance metrics.
RESULTS
Thirty-five empirical articles met the criteria to be included in the current review. We provide a general overview of machine learning techniques, examine the feature categories, describe methodological challenges, and suggest areas for improvement and research directions. Ensemble prediction models have been shown to be more accurate and useful than single prediction models.
CONCLUSIONS
Machine learning has great potential for improving estimates of future suicidal behaviour and monitoring changes in risk over time. Further research can address important challenges and potential opportunities that may contribute to significant advances in suicide prediction.
Topics: Artificial Intelligence; Data Mining; Humans; Machine Learning; Suicidal Ideation
PubMed: 36207078
DOI: 10.1016/j.artmed.2022.102395