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Allergologia Et Immunopathologia 2019The definition and diagnosis of asthma are the subject of controversy that is particularly intense in the case of individuals in the first years of life, due to reasons...
BACKGROUND AND AIM
The definition and diagnosis of asthma are the subject of controversy that is particularly intense in the case of individuals in the first years of life, due to reasons such as the difficulty of performing objective pulmonary function tests or the high frequency with which the symptoms subside in the course of childhood. Since there is no consensus regarding the diagnosis of asthma in preschool children, a systematic review has been carried out.
MATERIALS AND METHODS
A systematic search was made of the clinical guidelines published in the last 10 years and containing information referred to the concept or diagnosis of asthma in childhood - including the first years of life (infants and preschool children). A series of key questions were established, and each selected guide was analyzed in search of answers to those questions. The review protocol was registered in the international prospective register of systematic reviews (PROSPERO), with registration number CRD42017074872.
RESULTS
Twenty-one clinical guidelines were selected: 10 general guides (children and adults), eight pediatric guides and three guides focusing on preschool children. The immense majority accepted that asthma can be diagnosed from the first years of life, without requiring pulmonary function tests or other complementary techniques. The response to treatment and the exclusion of other alternative diagnoses are key elements for establishing the diagnosis. Only one of the guides denied the possibility of diagnosing asthma in preschool children.
CONCLUSIONS
There is generalized although not unanimous agreement that asthma can be diagnosed in preschool children.
Topics: Anti-Asthmatic Agents; Asthma; Child; Child, Preschool; Humans; Infant; Practice Guidelines as Topic; Respiratory Function Tests; Spain
PubMed: 30193886
DOI: 10.1016/j.aller.2018.05.002 -
European Geriatric Medicine Oct 2022Community-acquired pneumonia (CAP) is highly common across the world. It is reported that over 90% of CAP in older adults may be due to aspiration. However, the... (Review)
Review
PURPOSE
Community-acquired pneumonia (CAP) is highly common across the world. It is reported that over 90% of CAP in older adults may be due to aspiration. However, the diagnostic criteria for aspiration pneumonia (AP) have not been widely agreed. Is there a consensus on how to diagnose AP? What are the clinical features of patients being diagnosed with AP? We conducted a systematic review to answer these questions.
METHODS
We performed a literature search in MEDLINE, EMBASE, CINHAL, and Cochrane to review the steps taken toward diagnosing AP. Search terms for "aspiration pneumonia" and "aged" were used. Inclusion criteria were: original research, community-acquired AP, age ≥ 75 years old, acute hospital admission.
RESULTS
A total of 10,716 reports were found. Following the removal of duplicates, 7601 were screened, 95 underwent full-text review, and 9 reports were included in the final analysis. Pneumonia was diagnosed using a combination of symptoms, inflammatory markers, and chest imaging findings in most studies. AP was defined as pneumonia with some relation to aspiration or dysphagia. Aspiration was inferred if there was witnessed or prior presumed aspiration, episodes of coughing on food or liquids, relevant underlying conditions, abnormalities on videofluoroscopy or water swallow test, and gravity-dependent distribution of shadows on chest imaging. Patients with AP were older, more frailer, and had more comorbidities than in non-AP.
CONCLUSION
There is a broad consensus on the clinical criteria to diagnose AP. It is a presumptive diagnosis with regards to patients' general frailty rather than in relation to swallowing function itself.
Topics: Aged; Community-Acquired Infections; Deglutition; Humans; Pneumonia; Pneumonia, Aspiration; Water
PubMed: 36008745
DOI: 10.1007/s41999-022-00689-3 -
Journal of Hepatology Oct 2021Vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), 2-dimensional shear wave elastography (2DSWE), magnetic resonance elastography... (Meta-Analysis)
Meta-Analysis
BACKGROUND AND AIMS
Vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), 2-dimensional shear wave elastography (2DSWE), magnetic resonance elastography (MRE), and magnetic resonance imaging (MRI) have been proposed as non-invasive tests for patients with non-alcoholic fatty liver disease (NAFLD). This study evaluated their diagnostic accuracy for liver fibrosis and non-alcoholic steatohepatitis (NASH).
METHODS
PubMED/MEDLINE, EMBASE and the Cochrane Library were searched for studies examining the diagnostic accuracy of these index tests, against histology as the reference standard, in adult patients with NAFLD. Two authors independently screened and assessed methodological quality of studies and extracted data. Summary estimates of sensitivity, specificity and area under the curve (sAUC) were calculated for fibrosis stages and NASH, using a random effects bivariate logit-normal model.
RESULTS
We included 82 studies (14,609 patients). Meta-analysis for diagnosing fibrosis stages was possible in 53 VCTE, 11 MRE, 12 pSWE and 4 2DSWE studies, and for diagnosing NASH in 4 MRE studies. sAUC for diagnosis of significant fibrosis were: 0.83 for VCTE, 0.91 for MRE, 0.86 for pSWE and 0.75 for 2DSWE. sAUC for diagnosis of advanced fibrosis were: 0.85 for VCTE, 0.92 for MRE, 0.89 for pSWE and 0.72 for 2DSWE. sAUC for diagnosis of cirrhosis were: 0.89 for VCTE, 0.90 for MRE, 0.90 for pSWE and 0.88 for 2DSWE. MRE had sAUC of 0.83 for diagnosis of NASH. Three (4%) studies reported intention-to-diagnose analyses and 15 (18%) studies reported diagnostic accuracy against pre-specified cut-offs.
CONCLUSIONS
When elastography index tests are acquired successfully, they have acceptable diagnostic accuracy for advanced fibrosis and cirrhosis. The potential clinical impact of these index tests cannot be assessed fully as intention-to-diagnose analyses and validation of pre-specified thresholds are lacking.
LAY SUMMARY
Non-invasive tests that measure liver stiffness or use magnetic resonance imaging (MRI) have been suggested as alternatives to liver biopsy for assessing the severity of liver scarring (fibrosis) and fatty inflammation (steatohepatitis) in patients with non-alcoholic fatty liver disease (NAFLD). In this study, we summarise the results of previously published studies on how accurately these non-invasive tests can diagnose liver fibrosis and inflammation, using liver biopsy as the reference. We found that some techniques that measure liver stiffness had a good performance for the diagnosis of severe liver scarring.
Topics: Adult; Area Under Curve; Elasticity Imaging Techniques; Humans; Magnetic Resonance Imaging; Non-alcoholic Fatty Liver Disease; ROC Curve
PubMed: 33991635
DOI: 10.1016/j.jhep.2021.04.044 -
Critical Care (London, England) Sep 2014The understanding of coagulopathies in trauma has increased interest in thromboelastography (TEG®) and thromboelastometry (ROTEM®), which promptly evaluate the entire... (Review)
Review
Effect of thromboelastography (TEG®) and rotational thromboelastometry (ROTEM®) on diagnosis of coagulopathy, transfusion guidance and mortality in trauma: descriptive systematic review.
INTRODUCTION
The understanding of coagulopathies in trauma has increased interest in thromboelastography (TEG®) and thromboelastometry (ROTEM®), which promptly evaluate the entire clotting process and may guide blood product therapy. Our objective was to review the evidence for their role in diagnosing early coagulopathies, guiding blood transfusion, and reducing mortality in injured patients.
METHODS
We considered observational studies and randomized controlled trials (MEDLINE, EMBASE, and Cochrane databases) to February 2014 that examined TEG®/ROTEM® in adult trauma patients. We extracted data on demographics, diagnosis of early coagulopathies, blood transfusion, and mortality. We assessed methodologic quality by using the Newcastle-Ottawa scale (NOS) for observational studies and QUADAS-2 tool for diagnostic accuracy studies.
RESULTS
Fifty-five studies (12,489 patients) met inclusion criteria, including 38 prospective cohort studies, 15 retrospective cohort studies, two before-after studies, and no randomized trials. Methodologic quality was moderate (mean NOS score, 6.07; standard deviation, 0.49). With QUADAS-2, only three of 47 studies (6.4%) had a low risk of bias in all domains (patient selection, index test, reference standard and flow and timing); 37 of 47 studies (78.8%) had low concerns regarding applicability. Studies investigated TEG®/ROTEM® for diagnosis of early coagulopathies (n = 40) or for associations with blood-product transfusion (n = 25) or mortality (n = 24). Most (n = 52) were single-center studies. Techniques examined included rapid TEG® (n =12), ROTEM® (n = 18), TEG® (n = 23), or both TEG® and rapid TEG® (n = 2). Many TEG®/ROTEM® measurements were associated with early coagulopathies, including some (hypercoagulability, hyperfibrinolysis, platelet dysfunction) not assessed by routine screening coagulation tests. Standard measures of diagnostic accuracy were inconsistently reported. Many abnormalities predicted the need for massive transfusion and death, but predictive performance was not consistently superior to routine tests. One observational study suggested that a ROTEM®-based transfusion algorithm reduced blood-product transfusion, but TEG®/ROTEM®-based resuscitation was not associated with lower mortality in most studies.
CONCLUSIONS
Limited evidence from observational data suggest that TEG®/ROTEM® tests diagnose early trauma coagulopathy and may predict blood-product transfusion and mortality in trauma. Effects on blood-product transfusion, mortality, and other patient-important outcomes remain unproven in randomized trials.
Topics: Blood Coagulation Disorders; Blood Transfusion; Humans; Thrombelastography; Wounds and Injuries
PubMed: 25261079
DOI: 10.1186/s13054-014-0518-9 -
BMJ Open Nov 2019To estimate the prevalence and incidence of placenta previa complicated by placenta accreta spectrum (PAS) and to examine the different criteria being used for the... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To estimate the prevalence and incidence of placenta previa complicated by placenta accreta spectrum (PAS) and to examine the different criteria being used for the diagnosis.
DESIGN
Systematic review and meta-analysis.
DATA SOURCES
PubMed, Google Scholar, ClinicalTrials.gov and MEDLINE were searched between August 1982 and September 2018.
ELIGIBILITY CRITERIA
Studies reporting on placenta previa complicated by PAS diagnosed in a defined obstetric population.
DATA EXTRACTION AND SYNTHESIS
Two independent reviewers performed the data extraction using a predefined protocol and assessed the risk of bias using the Newcastle-Ottawa scale for observational studies, with difference agreed by consensus. The primary outcomes were overall prevalence of placenta previa, incidence of PAS according to the type of placenta previa and the reported clinical outcomes, including the number of peripartum hysterectomies and direct maternal mortality. The secondary outcomes included the criteria used for the prenatal ultrasound diagnosis of placenta previa and the criteria used to diagnose and grade PAS at birth.
RESULTS
A total of 258 articles were reviewed and 13 retrospective and 7 prospective studies were included in the analysis, which reported on 587 women with placenta previa and PAS. The meta-analysis indicated a significant (p<0.001) heterogeneity between study estimates for the prevalence of placenta previa, the prevalence of placenta previa with PAS and the incidence of PAS in the placenta previa cohort. The median prevalence of placenta previa was 0.56% (IQR 0.39-1.24) whereas the median prevalence of placenta previa with PAS was 0.07% (IQR 0.05-0.16). The incidence of PAS in women with a placenta previa was 11.10% (IQR 7.65-17.35).
CONCLUSIONS
The high heterogeneity in qualitative and diagnostic data between studies emphasises the need to implement standardised protocols for the diagnoses of both placenta previa and PAS, including the type of placenta previa and grade of villous invasiveness.
PROSPERO REGISTRATION NUMBER
CRD42017068589.
Topics: Female; Humans; Hysterectomy; Incidence; Peripartum Period; Placenta Accreta; Placenta Previa; Pregnancy; Prevalence; Ultrasonography, Prenatal
PubMed: 31722942
DOI: 10.1136/bmjopen-2019-031193 -
The Journal of Prosthetic Dentistry Dec 2023Artificial intelligence (AI) models have been developed for periodontal applications, including diagnosing gingivitis and periodontal disease, but their accuracy and... (Review)
Review
STATEMENT OF PROBLEM
Artificial intelligence (AI) models have been developed for periodontal applications, including diagnosing gingivitis and periodontal disease, but their accuracy and maturity of the technology remain unclear.
PURPOSE
The purpose of this systematic review was to evaluate the performance of the AI models for detecting dental plaque and diagnosing gingivitis and periodontal disease.
MATERIAL AND METHODS
A review was performed in 4 databases: MEDLINE/PubMed, World of Science, Cochrane, and Scopus. A manual search was also conducted. Studies were classified into 4 groups: detecting dental plaque, diagnosis of gingivitis, diagnosis of periodontal disease from intraoral images, and diagnosis of alveolar bone loss from periapical, bitewing, and panoramic radiographs. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus.
RESULTS
Twenty-four articles were included: 2 studies developed AI models for detecting plaque, resulting in accuracy ranging from 73.6% to 99%; 7 studies assessed the ability to diagnose gingivitis from intraoral photographs reporting an accuracy between 74% and 78.20%; 1 study used fluorescent intraoral images to diagnose gingivitis reporting 67.7% to 73.72% accuracy; 3 studies assessed the ability to diagnose periodontal disease from intraoral photographs with an accuracy between 47% and 81%, and 11 studies evaluated the performance of AI models for detecting alveolar bone loss from radiographic images reporting an accuracy between 73.4% and 99%.
CONCLUSIONS
AI models for periodontology applications are still in development but might provide a powerful diagnostic tool.
Topics: Humans; Dental Plaque; Alveolar Bone Loss; Artificial Intelligence; Periodontal Diseases; Gingivitis
PubMed: 35300850
DOI: 10.1016/j.prosdent.2022.01.026 -
Academic Emergency Medicine : Official... Mar 2016Acute heart failure (AHF) is one of the most common diagnoses assigned to emergency department (ED) patients who are hospitalized. Despite its high prevalence in the... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Acute heart failure (AHF) is one of the most common diagnoses assigned to emergency department (ED) patients who are hospitalized. Despite its high prevalence in the emergency setting, the diagnosis of AHF in ED patients with undifferentiated dyspnea can be challenging.
OBJECTIVES
The primary objective of this study was to perform a systematic review and meta-analysis of the operating characteristics of diagnostic elements available to the emergency physician for diagnosing AHF. Secondary objectives were to develop a test-treatment threshold model and to calculate interval likelihood ratios (LRs) for natriuretic peptides (NPs) by pooling patient-level results.
METHODS
PubMed, EMBASE, and selected bibliographies were searched from January 1965 to March 2015 using MeSH terms to address the ability of the following index tests to predict AHF as a cause of dyspnea in adult patients in the ED: history and physical examination, electrocardiogram, chest radiograph (CXR), B-type natriuretic peptide (BNP), N-terminal proB-type natriuretic peptide (NT-proBNP), lung ultrasound (US), bedside echocardiography, and bioimpedance. A diagnosis of AHF based on clinical data combined with objective test results served as the criterion standard diagnosis. Data were analyzed using Meta-DiSc software. Authors of all NP studies were contacted to obtain patient-level data. The Quality Assessment Tool for Diagnostic Accuracy Studies-2 (QUADAS-2) for systematic reviews was utilized to evaluate the quality and applicability of the studies included.
RESULTS
Based on the included studies, the prevalence of AHF ranged from 29% to 79%. Index tests with pooled positive LRs ≥ 4 were the auscultation of S3 on physical examination (4.0, 95% confidence interval [CI] = 2.7 to 5.9), pulmonary edema on both CXR (4.8, 95% CI = 3.6 to 6.4) and lung US (7.4, 95% CI = 4.2 to 12.8), and reduced ejection fraction observed on bedside echocardiogram (4.1, 95% CI = 2.4 to 7.2). Tests with low negative LRs were BNP < 100 pg/mL (0.11, 95% CI = 0.07 to 0.16), NT-proBNP < 300 pg/mL (0.09, 95% CI = 0.03 to 0.34), and B-line pattern on lung US LR (0.16, 95% CI = 0.05 to 0.51). Interval LRs of BNP concentrations at the low end of "positive" results as defined by a cutoff of 100 pg/mL were substantially lower (100 to 200 pg/mL; 0.29, 95% CI = 0.23 to 0.38) than those associated with higher BNP concentrations (1000 to 1500 pg/mL; 7.12, 95% CI = 4.53 to 11.18). The interval LR of NT-proBNP concentrations even at very high values (30,000 to 200,000 pg/mL) was 3.30 (95% CI = 2.05 to 5.31).
CONCLUSIONS
Bedside lung US and echocardiography appear to the most useful tests for affirming the presence of AHF while NPs are valuable in excluding the diagnosis.
Topics: Acute Disease; Diagnosis, Differential; Dyspnea; Echocardiography; Electrocardiography; Emergency Service, Hospital; Heart Failure; Humans; Lung; Natriuretic Peptide, Brain; Peptide Fragments; Physical Examination; Radiography, Thoracic
PubMed: 26910112
DOI: 10.1111/acem.12878 -
JAMA Network Open Mar 2023Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and... (Meta-Analysis)
Meta-Analysis
IMPORTANCE
Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and potential impact of these newly developed algorithms are currently unknown.
OBJECTIVE
To evaluate the performance of AI algorithms designed to diagnose hip fractures on radiographs and predict postoperative clinical outcomes following hip fracture surgery relative to current practices.
DATA SOURCES
A systematic review of the literature was performed using the MEDLINE, Embase, and Cochrane Library databases for all articles published from database inception to January 23, 2023. A manual reference search of included articles was also undertaken to identify any additional relevant articles.
STUDY SELECTION
Studies developing machine learning (ML) models for the diagnosis of hip fractures from hip or pelvic radiographs or to predict any postoperative patient outcome following hip fracture surgery were included.
DATA EXTRACTION AND SYNTHESIS
This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and was registered with PROSPERO. Eligible full-text articles were evaluated and relevant data extracted independently using a template data extraction form. For studies that predicted postoperative outcomes, the performance of traditional predictive statistical models, either multivariable logistic or linear regression, was recorded and compared with the performance of the best ML model on the same out-of-sample data set.
MAIN OUTCOMES AND MEASURES
Diagnostic accuracy of AI models was compared with the diagnostic accuracy of expert clinicians using odds ratios (ORs) with 95% CIs. Areas under the curve for postoperative outcome prediction between traditional statistical models (multivariable linear or logistic regression) and ML models were compared.
RESULTS
Of 39 studies that met all criteria and were included in this analysis, 18 (46.2%) used AI models to diagnose hip fractures on plain radiographs and 21 (53.8%) used AI models to predict patient outcomes following hip fracture surgery. A total of 39 598 plain radiographs and 714 939 hip fractures were used for training, validating, and testing ML models specific to diagnosis and postoperative outcome prediction, respectively. Mortality and length of hospital stay were the most predicted outcomes. On pooled data analysis, compared with clinicians, the OR for diagnostic error of ML models was 0.79 (95% CI, 0.48-1.31; P = .36; I2 = 60%) for hip fracture radiographs. For the ML models, the mean (SD) sensitivity was 89.3% (8.5%), specificity was 87.5% (9.9%), and F1 score was 0.90 (0.06). The mean area under the curve for mortality prediction was 0.84 with ML models compared with 0.79 for alternative controls (P = .09).
CONCLUSIONS AND RELEVANCE
The findings of this systematic review and meta-analysis suggest that the potential applications of AI to aid with diagnosis from hip radiographs are promising. The performance of AI in diagnosing hip fractures was comparable with that of expert radiologists and surgeons. However, current implementations of AI for outcome prediction do not seem to provide substantial benefit over traditional multivariable predictive statistics.
Topics: Humans; Artificial Intelligence; Hip Fractures; Prognosis; Algorithms; Length of Stay
PubMed: 36930153
DOI: 10.1001/jamanetworkopen.2023.3391 -
Journal of Foot and Ankle Research 2018Flexible flat foot is a normal observation in typically developing children, however, some children with flat feet present with pain and impaired lower limb function.... (Review)
Review
BACKGROUND
Flexible flat foot is a normal observation in typically developing children, however, some children with flat feet present with pain and impaired lower limb function. The challenge for health professionals is to identify when foot posture is outside of expected findings and may warrant intervention. Diagnoses of flexible flat foot is often based on radiographic or clinical measures, yet the validity and reliability of these measures for a paediatric population is not clearly understood. The aim of this systematic review was to investigate how paediatric foot posture is defined and measured within the literature, and if the psychometric properties of these measures support any given diagnoses.
METHODS
Electronic databases (MEDLINE, CINAHL, EMBASE, Cochrane, AMED, SportDiscus, PsycINFO, and Web of Science) were systematically searched in January 2017 for empirical studies where participants had diagnosed flexible flat foot and were aged 18 years or younger. Outcomes of interest were the foot posture measures and definitions used. Further articles were sought where cited in relation to the psychometric properties of the measures used.
RESULTS
Of the 1101 unique records identified by the searches, 27 studies met the inclusion criteria involving 20 foot posture measures and 40 definitions of paediatric flexible flat foot. A further 18 citations were sought in relation to the psychometric properties of these measures. Three measures were deemed valid and reliable, the FPI-6 > + 6 for children aged three to 15 years, a Staheli arch index of > 1.07 for children aged three to six and ≥ 1.28 for children six to nine, and a Chippaux-Smirak index of > 62.7% in three to seven year olds, > 59% in six to nine year olds and ≥ 40% for children aged nine to 16 years. No further measures were found to be valid for the paediatric population.
CONCLUSION
No universally accepted criteria for diagnosing paediatric flat foot was found within existing literature, and psychometric data for foot posture measures and definitions used was limited. The outcomes of this review indicate that the FPI - 6, Staheli arch index or Chippaux-Smirak index should be the preferred method of paediatric foot posture measurement in future research.
Topics: Anthropometry; Child; Child Development; Flatfoot; Foot; Humans; Posture; Psychometrics; Reproducibility of Results; Research Design
PubMed: 29854006
DOI: 10.1186/s13047-018-0264-3 -
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