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Evidence-based Medicine Jun 2015Musculoskeletal knee pain is a large and costly problem, and meniscal tears make up a large proportion of diagnoses. ‘Special tests’ to diagnose torn menisci are... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Musculoskeletal knee pain is a large and costly problem, and meniscal tears make up a large proportion of diagnoses. ‘Special tests’ to diagnose torn menisci are often used in the physical examination of the knee joint. A large number of publications within the literature have investigated the diagnostic accuracy of these tests, yet despite the wealth of research their diagnostic accuracy remains unclear.Aim To synthesise the most current literature on the diagnostic accuracy of special tests for meniscal tears of the knee in adults.
METHOD
An electronic search of MEDLINE, Cumulative Index to Nursing and Allies Health Literature (CINAHL), The Allied and Complementary Medicine Database (AMED) and SPORT Discus databases was carried out from inception to December 2014. Two authors independently selected studies and independently extracted data. Methodological quality was evaluated using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) 2 tool.
RESULTS
Nine studies were included (n=1234) and three special tests were included in the meta-analysis. The methodological quality of the included studies was generally poor. McMurray’s had a sensitivity of 61% (95% CI 45% to 74%) and a specificity of 84% (95% CI 69%to 92%). Joint line tenderness had a sensitivity of 83%(95% CI 73% to 90%) and a specificity of 83% (95% CI 61% to 94%). Thessaly 20° had a sensitivity of 75%(95% CI 53% to 89%) and a specificity of 87% (95% CI 65% to 96%).
CONCLUSIONS
The accuracy of the special tests to diagnose meniscal tears remains poor. However, these results should be used with caution, due to the poor quality and low numbers of included studies and high levels of heterogeneity.
Topics: Humans; Knee Injuries; Physical Examination; Tibial Meniscus Injuries
PubMed: 25724195
DOI: 10.1136/ebmed-2014-110160 -
World Journal of Emergency Surgery :... May 2023The diagnosis of cardiac contusion, caused by blunt chest trauma, remains a challenge due to the non-specific symptoms it causes and the lack of ideal tests to diagnose... (Meta-Analysis)
Meta-Analysis Review
INTRODUCTION
The diagnosis of cardiac contusion, caused by blunt chest trauma, remains a challenge due to the non-specific symptoms it causes and the lack of ideal tests to diagnose myocardial damage. A cardiac contusion can be life-threatening if not diagnosed and treated promptly. Several diagnostic tests have been used to evaluate the risk of cardiac complications, but the challenge of identifying patients with contusions nevertheless remains.
AIM OF THE STUDY
To evaluate the accuracy of diagnostic tests for detecting blunt cardiac injury (BCI) and its complications, in patients with severe chest injuries, who are assessed in an emergency department or by any front-line emergency physician.
METHODS
A targeted search strategy was performed using Ovid MEDLINE and Embase databases from 1993 up to October 2022. Data on at least one of the following diagnostic tests: electrocardiogram (ECG), serum creatinine phosphokinase-MB level (CPK-MB), echocardiography (Echo), Cardiac troponin I (cTnI) or Cardiac troponin T (cTnT). Diagnostic tests for cardiac contusion were evaluated for their accuracy in meta-analysis. Heterogeneity was assessed using the I and the QUADAS-2 tool was used to assess bias of the studies.
RESULTS
This systematic review yielded 51 studies (n = 5,359). The weighted mean incidence of myocardial injuries after sustaining a blunt force trauma stood at 18.3% of cases. Overall weighted mean mortality among patients with blunt cardiac injury was 7.6% (1.4-36.4%). Initial ECG, cTnI, cTnT and transthoracic echocardiography TTE all showed high specificity (> 80%), but lower sensitivity (< 70%). TEE had a specificity of 72.1% (range 35.8-98.2%) and sensitivity of 86.7% (range 40-99.2%) in diagnosing cardiac contusion. CK-MB had the lowest diagnostic odds ratio of 3.598 (95% CI: 1.832-7.068). Normal ECG accompanied by normal cTnI showed a high sensitivity of 85% in ruling out cardiac injuries.
CONCLUSION
Emergency physicians face great challenges in diagnosing cardiac injuries in patients following blunt trauma. In the majority of cases, joint use of ECG and cTnI was a pragmatic and cost-effective approach to rule out cardiac injuries. In addition, TEE may be highly accurate in identifying cardiac injuries in suspected cases.
Topics: Humans; Thoracic Injuries; Wounds, Nonpenetrating; Heart Injuries; Myocardial Contusions; Troponin I; Troponin T; Diagnostic Tests, Routine
PubMed: 37245048
DOI: 10.1186/s13017-023-00504-9 -
The Journal of Orthopaedic and Sports... Jan 2024We aimed to evaluate the accuracy of clinical tests that are used to diagnose greater trochanteric pain syndrome (GTPS) in clinical practice. Diagnostic test accuracy... (Meta-Analysis)
Meta-Analysis
We aimed to evaluate the accuracy of clinical tests that are used to diagnose greater trochanteric pain syndrome (GTPS) in clinical practice. Diagnostic test accuracy systematic review with meta-analysis. MEDLINE, Embase, CINAHL, AMED, and SPORTDiscus were searched using key words mapped to diagnostic test accuracy for GTPS. Studies with published or derivable diagnostic accuracy data were included. Risk of bias was assessed using the QUADAS-2 tool, and certainty of evidence, via the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework. MetaDTA "R" random-effects models were used to summarize individual and pooled data including sensitivity, specificity, likelihood ratios, and pretest/posttest probabilities. From a database yield of 858 studies, 23 full texts were assessed. We included 6 studies for review, involving 15 tests and 272 participants (314 hips). Overall certainty of evidence ranged from very low to moderate. Meta-analysis of 6 tests revealed sequenced test clusters able to significantly shift pretest-posttest probability for or against a GTPS diagnosis. In people reporting lateral hip pain, a negative gluteal tendon (GT) palpation test followed by a negative resisted hip abduction test significantly reduced the posttest probability of GTPS from 59% to 14%. In those with a positive GT palpation test followed by a positive resisted hip abduction test, the posttest probability of GTPS significantly shifted from 59% to 96%. The value of magnetic resonance imaging for diagnosing GTPS is debated. We have identified a straightforward, clinically useful diagnostic test cluster to help confirm or refute the presence of GTPS in people reporting lateral hip pain. .
Topics: Humans; Hip; Hip Joint; Magnetic Resonance Imaging; Arthralgia; Pain; Bursitis
PubMed: 37561820
DOI: 10.2519/jospt.2023.11890 -
Heart (British Cardiac Society) Apr 2024In clinical practice, patients with eosinophilic myocarditis (EM) may forgo the gold standard diagnostic procedure, endomyocardial biopsy (EMB), although it is highly...
OBJECTIVE
In clinical practice, patients with eosinophilic myocarditis (EM) may forgo the gold standard diagnostic procedure, endomyocardial biopsy (EMB), although it is highly recommended in guidelines. This systematic review aims to summarise current approaches in diagnosing and treating EM with a particular emphasis on the utilisation and value of alternative diagnostic methods.
METHODS
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, we searched MEDLINE and EMBASE for all peer-reviewed articles using the keywords "eosinophilic myocarditis" from their inception to 10 September 2022.
RESULTS
We included 239 articles, including 8 observational studies and 274 cases, in this review. The median patient age was 45 years. Initial presentations were non-specific, including dyspnoea (50.0%) and chest pain (39.4%). The aetiologies of EM were variable with the most common being idiopathic (28.8%) and eosinophilic granulomatosis polyangiitis (19.3%); others included drug-induced (13.1%) and hypereosinophilic syndrome (12.8%). 82.4% received an EM diagnosis by EMB while 17.6% were diagnosed based on clinical reasoning and cardiac MRI (CMR). CMR-diagnosed patients exhibited a better risk profile at diagnosis, particularly higher left ventricular ejection fraction and less need for inotropic or mechanical circulatory supports. Glucocorticoids were the primary treatment with variability in dosages and regimens.
CONCLUSION
EMB is the mainstay for diagnostic testing for EM. CMR is potentially helpful for screening in appropriate clinical scenarios. Regarding treatment, there is no consensus regarding the optimal dosage of corticosteroids. Large clinical trials are warranted to further explore the utility of CMR in the diagnosis of EM and steroid regimen in treating EM.
Topics: Humans; Myocarditis; Eosinophilia; Biopsy; Myocardium
PubMed: 37963727
DOI: 10.1136/heartjnl-2023-323225 -
Health Technology Assessment... Oct 2019Osteomyelitis is an infection of the bone. Medical imaging tests, such as radiography, ultrasound, magnetic resonance imaging (MRI), single-photon emission computed...
BACKGROUND
Osteomyelitis is an infection of the bone. Medical imaging tests, such as radiography, ultrasound, magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT) and positron emission tomography (PET), are often used to diagnose osteomyelitis.
OBJECTIVES
To systematically review the evidence on the diagnostic accuracy, inter-rater reliability and implementation of imaging tests to diagnose osteomyelitis.
DATA SOURCES
We conducted a systematic review of imaging tests to diagnose osteomyelitis. We searched MEDLINE and other databases from inception to July 2018.
REVIEW METHODS
Risk of bias was assessed with QUADAS-2 [quality assessment of diagnostic accuracy studies (version 2)]. Diagnostic accuracy was assessed using bivariate regression models. Imaging tests were compared. Subgroup analyses were performed based on the location and nature of the suspected osteomyelitis. Studies of children, inter-rater reliability and implementation outcomes were synthesised narratively.
RESULTS
Eighty-one studies were included (diagnostic accuracy: 77 studies; inter-rater reliability: 11 studies; implementation: one study; some studies were included in two reviews). One-quarter of diagnostic accuracy studies were rated as being at a high risk of bias. In adults, MRI had high diagnostic accuracy [95.6% sensitivity, 95% confidence interval (CI) 92.4% to 97.5%; 80.7% specificity, 95% CI 70.8% to 87.8%]. PET also had high accuracy (85.1% sensitivity, 95% CI 71.5% to 92.9%; 92.8% specificity, 95% CI 83.0% to 97.1%), as did SPECT (95.1% sensitivity, 95% CI 87.8% to 98.1%; 82.0% specificity, 95% CI 61.5% to 92.8%). There was similar diagnostic performance with MRI, PET and SPECT. Scintigraphy (83.6% sensitivity, 95% CI 71.8% to 91.1%; 70.6% specificity, 57.7% to 80.8%), computed tomography (69.7% sensitivity, 95% CI 40.1% to 88.7%; 90.2% specificity, 95% CI 57.6% to 98.4%) and radiography (70.4% sensitivity, 95% CI 61.6% to 77.8%; 81.5% specificity, 95% CI 69.6% to 89.5%) all had generally inferior diagnostic accuracy. Technetium-99m hexamethylpropyleneamine oxime white blood cell scintigraphy (87.3% sensitivity, 95% CI 75.1% to 94.0%; 94.7% specificity, 95% CI 84.9% to 98.3%) had higher diagnostic accuracy, similar to that of PET or MRI. There was no evidence that diagnostic accuracy varied by scan location or cause of osteomyelitis, although data on many scan locations were limited. Diagnostic accuracy in diabetic foot patients was similar to the overall results. Only three studies in children were identified; results were too limited to draw any conclusions. Eleven studies evaluated inter-rater reliability. MRI had acceptable inter-rater reliability. We found only one study on test implementation and no evidence on patient preferences or cost-effectiveness of imaging tests for osteomyelitis.
LIMITATIONS
Most studies included < 50 participants and were poorly reported. There was limited evidence for children, ultrasonography and on clinical factors other than diagnostic accuracy.
CONCLUSIONS
Osteomyelitis is reliably diagnosed by MRI, PET and SPECT. No clear reason to prefer one test over the other in terms of diagnostic accuracy was identified. The wider availability of MRI machines, and the fact that MRI does not expose patients to harmful ionising radiation, may mean that MRI is preferable in most cases. Diagnostic accuracy does not appear to vary with the potential cause of osteomyelitis or with the body part scanned. Considerable uncertainty remains over the diagnostic accuracy of imaging tests in children. Studies of diagnostic accuracy in children, particularly using MRI and ultrasound, are needed.
STUDY REGISTRATION
This study is registered as PROSPERO CRD42017068511.
FUNDING
This project was funded by the National Institute for Health Research Health Technology Assessment programme and will be published in full in ; Vol. 23, No. 61. See the NIHR Journals Library website for further project information.
Topics: Adolescent; Adult; Aged; Aged, 80 and over; Child; Child, Preschool; Cost-Benefit Analysis; Female; Humans; Infant; Magnetic Resonance Imaging; Male; Middle Aged; Osteomyelitis; Positron-Emission Tomography; Reproducibility of Results; Technology Assessment, Biomedical; Ultrasonography; Young Adult
PubMed: 31670644
DOI: 10.3310/hta23610 -
World Journal of Emergency Surgery :... Dec 2023To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional... (Review)
Review
BACKGROUND
To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal surgeries. It is typically diagnosed through clinical assessments, laboratory tests, and imaging studies. However, traditional diagnostic methods can be time-consuming and inaccurate. Machine learning models have shown promise in improving diagnostic accuracy and predicting outcomes.
MAIN BODY
A systematic review following the PRISMA guidelines was conducted, searching PubMed, Embase, Scopus, and Web of Science databases. Studies were evaluated for risk of bias using the Prediction Model Risk of Bias Assessment Tool. Data points extracted included model type, input features, validation strategies, and key performance metrics.
RESULTS
In total, 29 studies were analyzed, out of which 21 focused on diagnosis, seven on prognosis, and one on both. Artificial neural networks (ANNs) were the most commonly employed algorithm for diagnosis. Both ANN and logistic regression were also widely used for categorizing types of AA. ANNs showed high performance in most cases, with accuracy rates often exceeding 80% and AUC values peaking at 0.985. The models also demonstrated promising results in predicting postoperative outcomes such as sepsis risk and ICU admission. Risk of bias was identified in a majority of studies, with selection bias and lack of internal validation being the most common issues.
CONCLUSION
AI algorithms demonstrate significant promise in diagnosing and prognosticating AA, often surpassing traditional methods and clinical scores such as the Alvarado scoring system in terms of speed and accuracy.
Topics: Adult; Humans; Artificial Intelligence; Appendicitis; Prognosis; Algorithms; Machine Learning; Acute Disease
PubMed: 38114983
DOI: 10.1186/s13017-023-00527-2 -
International Endodontic Journal Oct 2023The diagnosis of the status of the inflamed pulp is essential in clinical diagnosis and treatment provision. There are a limited number of well-designed and... (Review)
Review
BACKGROUND
The diagnosis of the status of the inflamed pulp is essential in clinical diagnosis and treatment provision. There are a limited number of well-designed and well-executed clinical trials on the diagnosis of the true status of the pulp.
OBJECTIVES
Three PICO questions were formulated and agreed a priori by the European Society of Endodontology to evaluate the clinical tests for sensibility testing, determination of biomarkers and pulp bleeding with regard to their suitability to correctly diagnose the condition of the pulp tissue for the development of S3-Level guidelines.
METHODS
A literature search was conducted using PubMed, Clarivate Analytics' Web of Science, Scopus, Google Scholar and Cochrane Central Register of Controlled Trials from inception to 21 January 2022. Additionally, a hand search was performed, and the contents of the major subject journals were also examined. Eligibility criteria followed the proposed PICO questions. Two independent reviewers were involved in study selection, data extraction and appraising the included studies; disagreements were resolved by a third reviewer. The risk of bias was assessed by the QUADAS-2 tool for diagnostic accuracy studies, the Newcastle-Ottawa scale for noncomparative, nonrandomized studies and the Newcastle-Ottawa Quality Assessment scale adapted for cross-sectional studies.
RESULTS
In total, 28 studies out of 29 publications were considered eligible and were included in the review. Twelve studies were identified to investigate the diagnostic accuracy of the pulp vitality. Ten studies fulfilled the criteria to evaluate the diagnostic accuracy of the pulpal conditions, while 6 studies investigating the expression of biomarkers were eligible. Three studies addressing the prognostic factors and therapeutic interventions relating to pulpal status were included.
DISCUSSION
The core problem in pulp diagnostics is that a reliable reference standard is lacking under clinical conditions. Based on limited evidence, the most promising current approach seems to define a combination of different clinical tests and symptoms, probably in future including molecular diagnosis ("diagnostic package") will be required to ascertain the best possible strategy to clinically diagnose true pulpal conditions.
CONCLUSIONS
The effectiveness of diagnosing pulpitis is low due to limited scientific evidence regarding the accuracy and reproducibility of diagnostic tests. There is a lack of evidence to determine the true status of the pulp or to identify prognostic indicators allowing for a reliable pre-operative estimation of the outcome of vital pulp treatment.
REGISTRATION
PROSPERO database (CRD42021265366).
Topics: Humans; Pulpitis; Cross-Sectional Studies; Reproducibility of Results; Dental Pulp; Dental Pulp Diseases; Biomarkers
PubMed: 35536159
DOI: 10.1111/iej.13762 -
American Journal of Rhinology & Allergy May 2022Cerebrospinal fluid (CSF) rhinorrhea results from abnormal communications between the subarachnoid and sinonasal spaces. Accurate preoperative diagnosis and localization...
BACKGROUND
Cerebrospinal fluid (CSF) rhinorrhea results from abnormal communications between the subarachnoid and sinonasal spaces. Accurate preoperative diagnosis and localization are vital for positive clinical outcomes. However, the diagnosis and localization of CSF rhinorrhea remain suboptimal due to a lack of accurate understanding of test characteristics.
OBJECTIVE
This systematic review aims to assess the diagnostic accuracy of various tests and imaging modalities for diagnosing and localizing CSF rhinorrhea.
METHODS
A systematic review of the MEDLINE and EMBASE databases was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
RESULTS
Our search identified 4039 articles-53 cohort studies and 24 case series describing 1622 patients were included. The studies were heterogeneous and had a wide range of sensitivities and specificities. Many specificities were incalculable due to a lack of true negative and false positive results, thus precluding a meta-analysis. Median sensitivities and specificities were calculated for cohort studies of the following investigations: high-resolution computed tomography (HRCT) 0.93/0.50 (sensitivity/specificity), magnetic resonance cisternography (MRC) 0.94/0.77, computed tomography cisternography (CTC) 0.95/1.00, radionuclide cisternography (RNC) 0.90/0.50, and contrast-enhanced magnetic resonance cisternography (CEMRC) 0.99/1.00, endoscopy 0.58/1.00, topical intranasal fluorescein (TIF) 1.00/incalculable, intrathecal fluorescein (ITF) 0.96/1.00. Case series were reviewed separately. Etiology and site-specific data were also analyzed.
CONCLUSION
MR cisternography is more accurate than high-resolution CT at diagnosing and localizing CSF rhinorrhea. CT cisternography, contrast-enhanced MR cisternography, and radionuclide cisternography have good diagnostic characteristics but are invasive. Intrathecal fluorescein shows promising data but has not been widely adopted for purely diagnostic use. Office endoscopy has limited data but does not sufficiently diagnose CSF rhinorrhea independently. These findings confirm with current guidelines and evidence.
Topics: Cerebrospinal Fluid Rhinorrhea; Fluorescein; Humans; Magnetic Resonance Imaging; Sensitivity and Specificity; Tomography, X-Ray Computed
PubMed: 34846218
DOI: 10.1177/19458924211060918 -
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 -
International Ophthalmology Feb 2021To review the basic principles of ultra-widefield fundus autofluorescence (UWF-FAF) and discuss its clinical application for a variety of retinal and choroidal disorders. (Review)
Review
PURPOSE
To review the basic principles of ultra-widefield fundus autofluorescence (UWF-FAF) and discuss its clinical application for a variety of retinal and choroidal disorders.
METHODS
A systematic review of the PubMed database was performed using the search terms "ultra-widefield," "autofluorescence," "retinal disease" and "choroidal disease."
RESULTS
UWF-FAF imaging is a recently developed noninvasive retinal imaging modality with a wide imaging range that can locate peripheral fundus lesions that traditional fundus autofluorescence cannot. Multiple commercially available ultra-widefield imaging systems, including Heidelberg Spectralis and Optomap Ultra-Widefield systems, are available to the clinician. Imaging by UWF-FAF is more comprehensive; it can reflect the content and distribution of the predominant ocular fluorophore in retinal pigment epithelial cells and evaluate the metabolic status of RPE of various retinal and choroidal disorders.
CONCLUSION
UWF-FAF can detect abnormalities that traditional fundus autofluorescence cannot; therefore, it can be used to better elucidate disease pathogenesis, analyze genotype-phenotype correlations, diagnose and monitor disease.
Topics: Fluorescein Angiography; Fundus Oculi; Humans; Optical Imaging; Retina; Retinal Diseases
PubMed: 33040254
DOI: 10.1007/s10792-020-01609-9