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Frontiers in Oncology 2024Evolution of a patient-reported symptom-based risk stratification system to redesign the suspected head and neck cancer (HNC) referral pathway (EVEREST-HN) will use a...
INTRODUCTION
Evolution of a patient-reported symptom-based risk stratification system to redesign the suspected head and neck cancer (HNC) referral pathway (EVEREST-HN) will use a broad and open approach to the nomenclature and symptomatology. It aims to capture and utilise the patient reported symptoms in a modern way to identify patients' clinical problems more effectively and risk stratify the patient.
METHOD
The review followed the PRISMA checklist for scoping reviews. A search strategy was carried out using Medline, Embase and Web of Science between January 1st 2012 and October 31st 2023. All titles, abstracts and full paper were screened for eligibility, papers were assessed for inclusion using predetermined criteria. Data was extracted pertaining to the aims, type of study, cancer type, numbers of patients included and symptoms, presenting complaints or signs and symptoms.
RESULTS
There were 9,331 publications identified in the searches, following title screening 350 abstracts were reviewed for inclusion and 120 were considered for eligibility for the review. 48 publications met the eligibility criteria and were included in the final review. Data from almost 11,000 HNC patients was included. Twenty-one of the publications were from the UK, most were retrospective examination of patient records. Data was extracted and charted according to the anatomical area of the head and neck where the symptoms are subjectively and objectively found, and presented according to lay terms for symptoms, clinical terms for symptoms and the language of objective clinical findings.
DISCUSSION
Symptoms of HNC are common presenting complaints, interpreting these along with clinical history, examination and risk factors will inform a clinician's decision to refer as suspected cancer. UK Head and Neck specialists believe a different way of triaging the referrals is needed to assess the clinical risk of an undiagnosed HNC. EVEREST-HN aims to achieve this using the patient history of their symptoms. This review has highlighted issues in terms of what is considered a symptom, a presenting complaint and a clinical finding or sign.
PubMed: 38952557
DOI: 10.3389/fonc.2024.1404860 -
Biomedical Journal May 2024Transthoracic echocardiography (TTE) is currently recognized as the potential first-line imaging test for patients with suspected acute type A aortic syndrome (AAAS)....
BACKGROUND
Transthoracic echocardiography (TTE) is currently recognized as the potential first-line imaging test for patients with suspected acute type A aortic syndrome (AAAS). Direct TTE sign for detecting AAAS is positive if there is an intimal flap separating two aortic lumens or aortic wall thickening seen in the ascending aorta. Indirect TTE sign indicates high-risk features of AAAS, such as aortic root dilatation, pericardial effusion, and aortic regurgitation. Our aim is to summarize the existing clinical evidence regarding the diagnostic accuracy of TTE and to evaluate its potential role in the management of patients with suspected AAAS.
METHODS
We included prospective or retrospective diagnostic cohort studies, written in any language, that specifically focused on using TTE to diagnose AAAS from databases such as PubMed, EMBASE, MEDLINE, and the Cochrane Library. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio [1], and hierarchical summary receiver-operating characteristic (HSROC) curve were calculated for TTE in diagnosing AAAS. We applied Quality Assessment of Diagnostic Accuracy (QUADAS-2) tool and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) quality assessment criteria.
RESULTS
Ten studies (2886 patients) were included in the meta-analysis. The pooled sensitivity and specificity of direct TTE signs were 58% (95% CI, 38-76%) and 94% (95% CI, 89-97%). For any TTE signs, the pooled sensitivity and specificity were 91% (95% CI, 85-94%) and 74% (95% CI, 61-84%). The diagnostic accuracy of direct TTE signs was significantly higher than that of any TTE signs, as measured by the area under the HSROC curve [0.95 (95% CI, 0.92-0.96) vs. 0.87 (95% CI, 0.84-0.90)] in four studies.
CONCLUSIONS
Our study suggests that TTE could serve as the initial imaging test for patients with suspected AAAS. Given its high specificity, the presence of direct TTE signs may indicate AAAS, whereas the absence of any TTE signs, combined with low clinical suspicion, could suggest a lower likelihood of AAAS.
PubMed: 38735535
DOI: 10.1016/j.bj.2024.100747 -
PloS One 2024(i) To identify peer reviewed publications reporting the mental and/or physical health outcomes of Deaf adults who are sign language users and to synthesise evidence;...
OBJECTIVES
(i) To identify peer reviewed publications reporting the mental and/or physical health outcomes of Deaf adults who are sign language users and to synthesise evidence; (ii) If data available, to analyse how the health of the adult Deaf population compares to that of the general population; (iii) to evaluate the quality of evidence in the identified publications; (iv) to identify limitations of the current evidence base and suggest directions for future research.
DESIGN
Systematic review.
DATA SOURCES
Medline, Embase, PsychINFO, and Web of Science.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES
The inclusion criteria were Deaf adult populations who used a signed language, all study types, including methods-focused papers which also contain results in relation to health outcomes of Deaf signing populations. Full-text articles, published in peer-review journals were searched up to 13th June 2023, published in English or a signed language such as ASL (American Sign Language).
DATA EXTRACTION
Supported by the Rayyan systematic review software, two authors independently reviewed identified publications at each screening stage (primary and secondary). A third reviewer was consulted to settle any disagreements. Comprehensive data extraction included research design, study sample, methodology, findings, and a quality assessment.
RESULTS
Of the 35 included studies, the majority (25 out of 35) concerned mental health outcomes. The findings from this review highlighted the inequalities in health and mental health outcomes for Deaf signing populations in comparison with the general population, gaps in the range of conditions studied in relation to Deaf people, and the poor quality of available data.
CONCLUSIONS
Population sample definition and consistency of standards of reporting of health outcomes for Deaf people who use sign language should be improved. Further research on health outcomes not previously reported is needed to gain better understanding of Deaf people's state of health.
Topics: Adult; Humans; Sign Language; Outcome Assessment, Health Care
PubMed: 38625906
DOI: 10.1371/journal.pone.0298479 -
American Journal of Health-system... Jun 2024We aimed to systematically review and meta-analyze published evidence on modes of communication between healthcare professionals and patients with hearing loss. (Meta-Analysis)
Meta-Analysis
PURPOSE
We aimed to systematically review and meta-analyze published evidence on modes of communication between healthcare professionals and patients with hearing loss.
METHODS
MEDLINE/PubMed, Scopus, CINAHL, ScienceDirect, and Thai Journals Online Complete databases were searched. A meta-analysis was performed using a random-effects model. Data on the prevalence and types of communication between healthcare professionals and patients with any extent of hearing loss were extracted.
RESULTS
Twenty studies were included. Using a hearing aid (pooled prevalence, 57.4%; 95% CI, 11.4%-103.4%, N = 3, I2 = 99.33) and gestures (pooled prevalence = 54.8%, 95%CI: 17.4% to 92.1%, N = 7, I2 = 99.68) were the most commonly reported modes of communication. Few healthcare professionals could use sign language, and limited access to qualified interpreters was common.
CONCLUSION
Communication barriers exist. Qualified sign language interpreters and assistive technology should be used to improve communication.
Topics: Humans; Hearing Loss; Health Personnel; Communication; Professional-Patient Relations; Communication Barriers; Hearing Aids; Sign Language
PubMed: 38430534
DOI: 10.1093/ajhp/zxae045 -
Frontiers in Neuroscience 2024[This corrects the article DOI: 10.3389/fnins.2022.850245.].
[This corrects the article DOI: 10.3389/fnins.2022.850245.].
PubMed: 38318466
DOI: 10.3389/fnins.2024.1354571 -
The Cochrane Database of Systematic... Nov 2023Many preterm infants require respiratory support to maintain an optimal level of oxygenation, as oxygen levels both below and above the optimal range are associated with... (Review)
Review
BACKGROUND
Many preterm infants require respiratory support to maintain an optimal level of oxygenation, as oxygen levels both below and above the optimal range are associated with adverse outcomes. Optimal titration of oxygen therapy for these infants presents a major challenge, especially in neonatal intensive care units (NICUs) with suboptimal staffing. Devices that offer automated oxygen delivery during respiratory support of neonates have been developed since the 1970s, and individual trials have evaluated their effectiveness.
OBJECTIVES
To assess the benefits and harms of automated oxygen delivery systems, embedded within a ventilator or oxygen delivery device, for preterm infants with respiratory dysfunction who require respiratory support or supplemental oxygen therapy.
SEARCH METHODS
We searched CENTRAL, MEDLINE, CINAHL, and clinical trials databases without language or publication date restrictions on 23 January 2023. We also checked the reference lists of retrieved articles for other potentially eligible trials.
SELECTION CRITERIA
We included randomised controlled trials and randomised cross-over trials that compared automated oxygen delivery versus manual oxygen delivery, or that compared different automated oxygen delivery systems head-to-head, in preterm infants (born before 37 weeks' gestation).
DATA COLLECTION AND ANALYSIS
We used standard Cochrane methods. Our main outcomes were time (%) in desired oxygen saturation (SpO) range, all-cause in-hospital mortality by 36 weeks' postmenstrual age, severe retinopathy of prematurity (ROP), and neurodevelopmental outcomes at approximately two years' corrected age. We expressed our results using mean difference (MD), standardised mean difference (SMD), and risk ratio (RR) with 95% confidence intervals (CIs). We used GRADE to assess the certainty of evidence.
MAIN RESULTS
We included 18 studies (27 reports, 457 infants), of which 13 (339 infants) contributed data to meta-analyses. We identified 13 ongoing studies. We evaluated three comparisons: automated oxygen delivery versus routine manual oxygen delivery (16 studies), automated oxygen delivery versus enhanced manual oxygen delivery with increased staffing (three studies), and one automated system versus another (two studies). Most studies were at low risk of bias for blinding of personnel and outcome assessment, incomplete outcome data, and selective outcome reporting; and half of studies were at low risk of bias for random sequence generation and allocation concealment. However, most were at high risk of bias in an important domain specific to cross-over trials, as only two of 16 cross-over trials provided separate outcome data for each period of the intervention (before and after cross-over). Automated oxygen delivery versus routine manual oxygen delivery Automated delivery compared with routine manual oxygen delivery probably increases time (%) in the desired SpO range (MD 13.54%, 95% CI 11.69 to 15.39; I = 80%; 11 studies, 284 infants; moderate-certainty evidence). No studies assessed in-hospital mortality. Automated oxygen delivery compared to routine manual oxygen delivery may have little or no effect on risk of severe ROP (RR 0.24, 95% CI 0.03 to 1.94; 1 study, 39 infants; low-certainty evidence). No studies assessed neurodevelopmental outcomes. Automated oxygen delivery versus enhanced manual oxygen delivery There may be no clear difference in time (%) in the desired SpO range between infants who receive automated oxygen delivery and infants who receive manual oxygen delivery (MD 7.28%, 95% CI -1.63 to 16.19; I = 0%; 2 studies, 19 infants; low-certainty evidence). No studies assessed in-hospital mortality, severe ROP, or neurodevelopmental outcomes. Revised closed-loop automatic control algorithm (CLACfast) versus original closed-loop automatic control algorithm (CLACslow) CLACfast allowed up to 120 automated adjustments per hour, whereas CLACslow allowed up to 20 automated adjustments per hour. CLACfast may result in little or no difference in time (%) in the desired SpO range compared to CLACslow (MD 3.00%, 95% CI -3.99 to 9.99; 1 study, 19 infants; low-certainty evidence). No studies assessed in-hospital mortality, severe ROP, or neurodevelopmental outcomes. OxyGenie compared to CLiO Data from a single small study were presented as medians and interquartile ranges and were not suitable for meta-analysis.
AUTHORS' CONCLUSIONS
Automated oxygen delivery compared to routine manual oxygen delivery probably increases time in desired SpO ranges in preterm infants on respiratory support. However, it is unclear whether this translates into important clinical benefits. The evidence on clinical outcomes such as severe retinopathy of prematurity are of low certainty, with little or no differences between groups. There is insufficient evidence to reach any firm conclusions on the effectiveness of automated oxygen delivery compared to enhanced manual oxygen delivery or CLACfast compared to CLACslow. Future studies should include important short- and long-term clinical outcomes such as mortality, severe ROP, bronchopulmonary dysplasia/chronic lung disease, intraventricular haemorrhage, periventricular leukomalacia, patent ductus arteriosus, necrotising enterocolitis, and long-term neurodevelopmental outcomes. The ideal study design for this evaluation is a parallel-group randomised controlled trial. Studies should clearly describe staffing levels, especially in the manual arm, to enable an assessment of reproducibility according to resources in various settings. The data of the 13 ongoing studies, when made available, may change our conclusions, including the implications for practice and research.
Topics: Humans; Infant; Infant, Newborn; Bronchopulmonary Dysplasia; Infant, Premature; Oxygen; Randomized Controlled Trials as Topic; Reproducibility of Results; Retinopathy of Prematurity
PubMed: 38032241
DOI: 10.1002/14651858.CD013294.pub2 -
Archives of Public Health = Archives... Nov 2023People with hearing impairment have many problems with healthcare use, which is associated with health literacy. Research on health literacy is less focused on people...
BACKGROUND
People with hearing impairment have many problems with healthcare use, which is associated with health literacy. Research on health literacy is less focused on people with hearing impairments. This research aimed to explore the levels of health literacy in people with hearing impairment, find the barriers to health literacy, and summarize methods for improving health literacy.
METHODS
A systematic review was conducted using three databases (PubMed, Cochrane, and Embase) to search the relevant articles and analyze them. The studies were selected using pre-defined inclusion/exclusion criteria in two steps: first, selection by examining the title and abstract; and second, after reading the study in full. The Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS) was used to assess the quality of the articles.
RESULTS
Twenty-nine studies were synthesized qualitatively. Individuals with hearing impairment were found to have lower health literacy, when compared to those without impairment, which can lead to a higher medical cost. Most of the people with hearing impairment faced barriers to obtaining health-related information and found it difficult to communicate with healthcare providers. To improve their health literacy, it is essential to explore new ways of accessing health information and improving the relationship between patients and healthcare providers.
CONCLUSIONS
Our findings show that people with hearing impairment have lower health literacy than those without. This suggests that developing new technology and policies for people with hearing impairment is necessary not to mention promoting provision of information via sign language.
TRIAL REGISTRATION
OSF: https://doi.org/10.17605/OSF.IO/V6UGW .
PROSPERO ID
CRD42023395556.
PubMed: 37993969
DOI: 10.1186/s13690-023-01216-x -
Community Dental Health Feb 2024Individuals with special needs requiring special care are more vulnerable to oral health problems. Sign language is a communication medium and language of instruction... (Meta-Analysis)
Meta-Analysis
Sign language based educational interventions vs. other educational interventions to improve the oral health of hearing-impaired individuals: A systematic review and meta-analysis.
OBJECTIVE
Individuals with special needs requiring special care are more vulnerable to oral health problems. Sign language is a communication medium and language of instruction for individuals with hearing impairments. The purpose of this systematic review and meta-analysis was to assess the effectiveness of sign language-based educational interventions compared to other educational interventions in improving the oral health of hearing-impaired individuals.
METHODS
PubMed, Scopus, Embase, and Cochrane Central Register of Controlled Trials databases were searched without any restriction on the publication date. Analytical and experimental studies that evaluated and compared the effectiveness of sign language with other educational intervention groups such as videos, posters etc were included.
RESULTS
Initially, 5568 records were identified. Three relevant publications from India were eligible and included in the systematic review and meta-analysis. Differences were reported in favour of sign language over other interventions concerning plaque status, gingival health, and oral hygiene status.
CONCLUSION
Sign language-based interventions were found to be effective. However, further studies in different locations and populations are required to support their effectiveness.
Topics: Humans; Dental Plaque; Hearing; Oral Health; Oral Hygiene; Sign Language; Deafness
PubMed: 37988657
DOI: 10.1922/CDH_00109Bhadauria06 -
The Cochrane Database of Systematic... Nov 2023Keratoconus remains difficult to diagnose, especially in the early stages. It is a progressive disorder of the cornea that starts at a young age. Diagnosis is based on... (Review)
Review
BACKGROUND
Keratoconus remains difficult to diagnose, especially in the early stages. It is a progressive disorder of the cornea that starts at a young age. Diagnosis is based on clinical examination and corneal imaging; though in the early stages, when there are no clinical signs, diagnosis depends on the interpretation of corneal imaging (e.g. topography and tomography) by trained cornea specialists. Using artificial intelligence (AI) to analyse the corneal images and detect cases of keratoconus could help prevent visual acuity loss and even corneal transplantation. However, a missed diagnosis in people seeking refractive surgery could lead to weakening of the cornea and keratoconus-like ectasia. There is a need for a reliable overview of the accuracy of AI for detecting keratoconus and the applicability of this automated method to the clinical setting.
OBJECTIVES
To assess the diagnostic accuracy of artificial intelligence (AI) algorithms for detecting keratoconus in people presenting with refractive errors, especially those whose vision can no longer be fully corrected with glasses, those seeking corneal refractive surgery, and those suspected of having keratoconus. AI could help ophthalmologists, optometrists, and other eye care professionals to make decisions on referral to cornea specialists. Secondary objectives To assess the following potential causes of heterogeneity in diagnostic performance across studies. • Different AI algorithms (e.g. neural networks, decision trees, support vector machines) • Index test methodology (preprocessing techniques, core AI method, and postprocessing techniques) • Sources of input to train algorithms (topography and tomography images from Placido disc system, Scheimpflug system, slit-scanning system, or optical coherence tomography (OCT); number of training and testing cases/images; label/endpoint variable used for training) • Study setting • Study design • Ethnicity, or geographic area as its proxy • Different index test positivity criteria provided by the topography or tomography device • Reference standard, topography or tomography, one or two cornea specialists • Definition of keratoconus • Mean age of participants • Recruitment of participants • Severity of keratoconus (clinically manifest or subclinical) SEARCH METHODS: We searched CENTRAL (which contains the Cochrane Eyes and Vision Trials Register), Ovid MEDLINE, Ovid Embase, OpenGrey, the ISRCTN registry, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP). There were no date or language restrictions in the electronic searches for trials. We last searched the electronic databases on 29 November 2022.
SELECTION CRITERIA
We included cross-sectional and diagnostic case-control studies that investigated AI for the diagnosis of keratoconus using topography, tomography, or both. We included studies that diagnosed manifest keratoconus, subclinical keratoconus, or both. The reference standard was the interpretation of topography or tomography images by at least two cornea specialists.
DATA COLLECTION AND ANALYSIS
Two review authors independently extracted the study data and assessed the quality of studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. When an article contained multiple AI algorithms, we selected the algorithm with the highest Youden's index. We assessed the certainty of evidence using the GRADE approach.
MAIN RESULTS
We included 63 studies, published between 1994 and 2022, that developed and investigated the accuracy of AI for the diagnosis of keratoconus. There were three different units of analysis in the studies: eyes, participants, and images. Forty-four studies analysed 23,771 eyes, four studies analysed 3843 participants, and 15 studies analysed 38,832 images. Fifty-four articles evaluated the detection of manifest keratoconus, defined as a cornea that showed any clinical sign of keratoconus. The accuracy of AI seems almost perfect, with a summary sensitivity of 98.6% (95% confidence interval (CI) 97.6% to 99.1%) and a summary specificity of 98.3% (95% CI 97.4% to 98.9%). However, accuracy varied across studies and the certainty of the evidence was low. Twenty-eight articles evaluated the detection of subclinical keratoconus, although the definition of subclinical varied. We grouped subclinical keratoconus, forme fruste, and very asymmetrical eyes together. The tests showed good accuracy, with a summary sensitivity of 90.0% (95% CI 84.5% to 93.8%) and a summary specificity of 95.5% (95% CI 91.9% to 97.5%). However, the certainty of the evidence was very low for sensitivity and low for specificity. In both groups, we graded most studies at high risk of bias, with high applicability concerns, in the domain of patient selection, since most were case-control studies. Moreover, we graded the certainty of evidence as low to very low due to selection bias, inconsistency, and imprecision. We could not explain the heterogeneity between the studies. The sensitivity analyses based on study design, AI algorithm, imaging technique (topography versus tomography), and data source (parameters versus images) showed no differences in the results.
AUTHORS' CONCLUSIONS
AI appears to be a promising triage tool in ophthalmologic practice for diagnosing keratoconus. Test accuracy was very high for manifest keratoconus and slightly lower for subclinical keratoconus, indicating a higher chance of missing a diagnosis in people without clinical signs. This could lead to progression of keratoconus or an erroneous indication for refractive surgery, which would worsen the disease. We are unable to draw clear and reliable conclusions due to the high risk of bias, the unexplained heterogeneity of the results, and high applicability concerns, all of which reduced our confidence in the evidence. Greater standardization in future research would increase the quality of studies and improve comparability between studies.
Topics: Humans; Artificial Intelligence; Keratoconus; Cross-Sectional Studies; Physical Examination; Case-Control Studies
PubMed: 37965960
DOI: 10.1002/14651858.CD014911.pub2 -
Sensors (Basel, Switzerland) Oct 2023The analysis and recognition of sign languages are currently active fields of research focused on sign recognition. Various approaches differ in terms of analysis... (Review)
Review
The analysis and recognition of sign languages are currently active fields of research focused on sign recognition. Various approaches differ in terms of analysis methods and the devices used for sign acquisition. Traditional methods rely on video analysis or spatial positioning data calculated using motion capture tools. In contrast to these conventional recognition and classification approaches, electromyogram (EMG) signals, which measure muscle electrical activity, offer potential technology for detecting gestures. These EMG-based approaches have recently gained attention due to their advantages. This prompted us to conduct a comprehensive study on the methods, approaches, and projects utilizing EMG sensors for sign language handshape recognition. In this paper, we provided an overview of the sign language recognition field through a literature review, with the objective of offering an in-depth review of the most significant techniques. These techniques were categorized in this article based on their respective methodologies. The survey discussed the progress and challenges in sign language recognition systems based on surface electromyography (sEMG) signals. These systems have shown promise but face issues like sEMG data variability and sensor placement. Multiple sensors enhance reliability and accuracy. Machine learning, including deep learning, is used to address these challenges. Common classifiers in sEMG-based sign language recognition include SVM, ANN, CNN, KNN, HMM, and LSTM. While SVM and ANN are widely used, random forest and KNN have shown better performance in some cases. A multilayer perceptron neural network achieved perfect accuracy in one study. CNN, often paired with LSTM, ranks as the third most popular classifier and can achieve exceptional accuracy, reaching up to 99.6% when utilizing both EMG and IMU data. LSTM is highly regarded for handling sequential dependencies in EMG signals, making it a critical component of sign language recognition systems. In summary, the survey highlights the prevalence of SVM and ANN classifiers but also suggests the effectiveness of alternative classifiers like random forests and KNNs. LSTM emerges as the most suitable algorithm for capturing sequential dependencies and improving gesture recognition in EMG-based sign language recognition systems.
Topics: Humans; Sign Language; Reproducibility of Results; Pattern Recognition, Automated; Neural Networks, Computer; Algorithms; Electromyography; Gestures
PubMed: 37837173
DOI: 10.3390/s23198343