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BMC Pulmonary Medicine Dec 2018Guidelines currently do not recommend the routine use of chest x-ray (CXR) in bronchiolitis. However, CXR is still performed in a high percentage of cases, mainly to... (Clinical Trial)
Clinical Trial Comparative Study
BACKGROUND
Guidelines currently do not recommend the routine use of chest x-ray (CXR) in bronchiolitis. However, CXR is still performed in a high percentage of cases, mainly to diagnose or rule out pneumonia. The inappropriate use of CXR results in children exposure to ionizing radiations and increased medical costs. Lung Ultrasound (LUS) has become an emerging diagnostic tool for diagnosing pneumonia in the last decades. The purpose of this study was to assess the diagnostic accuracy and reliability of LUS for the detection of pneumonia in hospitalized children with bronchiolitis and to evaluate the agreement between LUS and CXR in diagnosing pneumonia in these patients.
METHODS
We enrolled children admitted to our hospital in 2016-2017 with a diagnosis of bronchiolitis and undergone CXR because of clinical suspicion of concomitant pneumonia. LUS was performed in each child by a pediatrician blinded to the patient's clinical, laboratory and CXR findings. An exploratory analysis was done in the first 30 patients to evaluate the inter-observer agreement between a pediatrician and a radiologist who independently performed LUS. The diagnosis of pneumonia was established by an expert clinician based on the recommendations of the British Thoracic Society guidelines.
RESULTS
Eighty seven children with bronchiolitis were investigated. A final diagnosis of concomitant pneumonia was made in 25 patients. Sensitivity and specificity of LUS for the diagnosis of pneumonia were 100% and 83.9% respectively, with an area under-the-curve of 0.92, while CXR showed a sensitivity of 96% and specificity of 87.1%. When only consolidation > 1 cm was considered consistent with pneumonia, the specificity of LUS increased to 98.4% and the sensitivity decreased to 80.0%, with an area under-the-curve of 0.89. Cohen's kappa between pediatrician and radiologist sonologists in the first 30 patients showed an almost perfect agreement in diagnosing pneumonia by LUS (K 0.93).
CONCLUSIONS
This study shows the good accuracy of LUS in diagnosing pneumonia in children with clinical bronchiolitis. When including only consolidation size > 1 cm, specificity of LUS was higher than CXR, avoiding the need to perform CXR in these patients. Added benefit of LUS included high inter-observer agreement.
TRIAL REGISTRATION
Identifier: NCT03280732 . Registered 12 September 2017 (retrospectively registered).
Topics: Bronchiolitis; Diagnosis, Differential; Dimensional Measurement Accuracy; Female; Humans; Infant; Infant, Newborn; Italy; Lung; Male; Pneumonia; Prospective Studies; Radiation Exposure; Radiography, Thoracic; Reproducibility of Results; Sensitivity and Specificity; Ultrasonography
PubMed: 30526548
DOI: 10.1186/s12890-018-0750-1 -
Chest May 2013Lung cancer is usually suspected in individuals who have an abnormal chest radiograph or have symptoms caused by either local or systemic effects of the tumor. The...
Establishing the diagnosis of lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines.
BACKGROUND
Lung cancer is usually suspected in individuals who have an abnormal chest radiograph or have symptoms caused by either local or systemic effects of the tumor. The method of diagnosis of lung cancer depends on the type of lung cancer (small cell lung cancer or non-small cell lung cancer [NSCLC]), the size and location of the primary tumor, the presence of metastasis, and the overall clinical status of the patient. The objective of this study was to determine the test performance characteristics of various modalities for the diagnosis of suspected lung cancer.
METHODS
To update previous recommendations on techniques available for the initial diagnosis of lung cancer, a systematic search of the MEDLINE, Healthstar, and Cochrane Library databases covering material to July 2011 and print bibliographies was performed to identify studies comparing the results of sputum cytology, conventional bronchoscopy, flexible bronchoscopy (FB), electromagnetic navigation (EMN) bronchoscopy, radial endobronchial ultrasound (R-EBUS)-guided lung biopsy, transthoracic needle aspiration (TTNA) or biopsy, pleural fluid cytology, and pleural biopsy with histologic reference standard diagnoses among at least 50 patients with suspected lung cancer. Recommendations were developed by the writing committee, graded by a standardized method (see the article "Methodology for Development of Guidelines for Lung Cancer" in this guideline), and reviewed by all members of the Lung Cancer Guideline Panel prior to approval by the Thoracic Oncology NetWork, the Guidelines Oversight Committee, and the Board of Regents of the American College of Chest Physicians.
RESULTS
Sputum cytology is an acceptable method of establishing the diagnosis of lung cancer, with a pooled sensitivity rate of 66% and a specificity rate of 99%. However, the sensitivity of sputum cytology varies according to the location of the lung cancer. For central, endobronchial lesions, the overall sensitivity of FB for diagnosing lung cancer is 88%. The diagnostic yield of bronchoscopy decreases for peripheral lesions. Peripheral lesions < 2 or > 2 cm in diameter showed a sensitivity of 34% and 63%, respectively. R-EBUS and EMN are emerging technologies for the diagnosis of peripheral lung cancer, with diagnostic yields of 73% and 71%, respectively. The pooled sensitivity of TTNA for the diagnosis of lung cancer was 90%. A trend toward lower sensitivity was noted for lesions < 2 cm in diameter. TTNA is associated with a higher rate of pneumothorax compared with bronchoscopic procedures. In a patient with a malignant pleural effusion, pleural fluid cytology is reported to have a mean sensitivity of about 72%. A definitive diagnosis of metastatic disease to the pleural space can be estalished with a pleural biopsy. The diagnostic yield for closed pleural biopsy ranges from 38% to 47% and from 75% to 88% for image-guided closed biopsy. Thoracoscopic biopsy of the pleura carries the highest diagnostic yield, 95% to 97%. The accuracy in differentiating between small cell and non-small cell cytology for the various diagnostic modalities was 98%, with individual studies ranging from 94% to 100%. The average false-positive and false-negative rates were 9% and 2%, respectively. Although the distinction between small cell and NSCLC by cytology appears to be accurate, NSCLCs are clinically, pathologically, and molecularly heterogeneous tumors. In the past decade, clinical trials have shown us that NSCLCs respond to different therapeutic agents based on histologic phenotypes and molecular characteristics. The physician performing diagnostic procedures on a patient suspected of having lung cancer must ensure that adequate tissue is acquired to perform accurate histologic and molecular characterization of NSCLCs.
CONCLUSIONS
The sensitivity of bronchoscopy is high for endobronchial disease and poor for peripheral lesions < 2 cm in diameter. The sensitivity of TTNA is excellent for malignant disease, but TTNA has a higher rate of pneumothorax than do bronchoscopic modalities. R-EBUS and EMN bronchoscopy show potential for increasing the diagnostic yield of FB for peripheral lung cancers. Thoracoscopic biopsy of the pleura has the highest diagnostic yield for diagnosis of metastatic pleural effusion in a patient with lung cancer. Adequate tissue acquisition for histologic and molecular characterization of NSCLCs is paramount.
Topics: Biopsy; Bronchoscopy; Cytodiagnosis; Diagnosis, Differential; Diagnostic Imaging; Humans; Lung Neoplasms; Review Literature as Topic; Sensitivity and Specificity; Sputum
PubMed: 23649436
DOI: 10.1378/chest.12-2353 -
Multiple Sclerosis and Related Disorders Mar 2022In recent years Artificial intelligence (AI) techniques are rapidly evolving into clinical practices such as diagnosis and prognosis processes, assess treatment... (Review)
Review
BACKGROUND
In recent years Artificial intelligence (AI) techniques are rapidly evolving into clinical practices such as diagnosis and prognosis processes, assess treatment effectiveness, and monitoring of diseases. The previous studies showed interesting results regarding the diagnostic efficiency of AI methods in differentiating Multiple sclerosis (MS) patients from healthy controls or other demyelinating diseases. There is a great lack of a comprehensive systematic review study on the role of AI in the diagnosis of MS. We aimed to perform a systematic review to document the performance of AI in MS diagnosis.
METHODS
A systematic search was performed using four databases including PubMed, Scopus, Web of Science, and IEEE on August 2021. All original studies which focused on deep learning or AI to analyze any modalities with the purpose of diagnosing MS were included in our study.
RESULTS
Finally, 38 studies were included in our systematic review after the abstract and full-text screening. A total of 5433 individuals were included, including 2924 cases of MS and 2509 healthy controls. Sensitivity and specificity were reported in 29 studies which ranged from 76.92 to 100 for sensitivity and 74 to 100 for specificity. Furthermore, 34 studies reported accuracy ranged 81 to 100. Among included studies, Magnetic Resonance Imaging (MRI) (20 studies), OCT (six studies), serum and cerebrospinal fluid markers (six studies), movement function (three studies), and other modalities such as breathing and evoked potential was used for detecting MS via AI.
CONCLUSION
In conclusion, diagnosis of MS based on new markers and AI is a growing field of research with MRI images, followed by images obtained from OCT, serum and CSF biomarkers, and motor associated markers. All of these results show that with advances made in AI, the way we monitor and diagnose our MS patients can change drastically.
Topics: Artificial Intelligence; Humans; Magnetic Resonance Imaging; Multiple Sclerosis
PubMed: 35180619
DOI: 10.1016/j.msard.2022.103673 -
Critical Care (London, England) 2008Early, accurate diagnosis is fundamental in the management of patients with ventilator-associated pneumonia (VAP). The aim of this qualitative review was to compare... (Review)
Review
INTRODUCTION
Early, accurate diagnosis is fundamental in the management of patients with ventilator-associated pneumonia (VAP). The aim of this qualitative review was to compare various criteria of diagnosing VAP in the intensive care unit (ICU) with a special emphasis on the value of clinical diagnosis, microbiological culture techniques, and biomarkers of host response.
METHODS
A MEDLINE search was performed using the keyword 'ventilator associated pneumonia' AND 'diagnosis'. Our search was limited to human studies published between January 1966 and June 2007. Only studies of at least 25 adult patients were included. Predefined variables were collected, including year of publication, study design (prospective/retrospective), number of patients included, and disease group.
RESULTS
Of 572 articles fulfilling the initial search criteria, 159 articles were chosen for detailed review of the full text. A total of 64 articles fulfilled the inclusion criteria and were included in our review. Clinical criteria, used in combination, may be helpful in diagnosing VAP, however, the considerable inter-observer variability and the moderate performance should be taken in account. Bacteriologic data do not increase the accuracy of diagnosis as compared to clinical diagnosis. Quantitative cultures obtained by different methods seem to be rather equivalent in diagnosing VAP. Blood cultures are relatively insensitive to diagnose pneumonia. The rapid availability of cytological data, including inflammatory cells and Gram stains, may be useful in initial therapeutic decisions in patients with suspected VAP. C-reactive protein, procalcitonin, and soluble triggering receptor expressed on myeloid cells are promising biomarkers in diagnosing VAP.
CONCLUSION
An integrated approach should be followed in diagnosing and treating patients with VAP, including early antibiotic therapy and subsequent rectification according to clinical response and results of bacteriologic cultures.
Topics: Biopsy; Bronchoalveolar Lavage Fluid; Colony Count, Microbial; Cross Infection; Humans; Intensive Care Units; Pneumonia, Bacterial; Radiography, Thoracic; Respiration, Artificial; Risk Factors
PubMed: 18426596
DOI: 10.1186/cc6877 -
Telemedicine Journal and E-health : the... Jun 2019p (Randomized Controlled Trial)
Randomized Controlled Trial
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Topics: Acute Disease; Child, Preschool; Female; Humans; Infant; Male; Otitis Media; Otitis Media with Effusion; Otoscopy; Parents; Risk Factors; Smartphone; Socioeconomic Factors; Telemedicine
PubMed: 30040525
DOI: 10.1089/tmj.2018.0062 -
International Journal of Infectious... Jul 2020Diagnosing pulmonary blastomycosis (PB) requires the detection of Blastomyces dermatitidis in pulmonary secretions or tissue, which can be achieved via bronchoscopic...
OBJECTIVES
Diagnosing pulmonary blastomycosis (PB) requires the detection of Blastomyces dermatitidis in pulmonary secretions or tissue, which can be achieved via bronchoscopic procedures like bronchoalveolar lavage (BAL) or brush and transbronchial biopsy (TBBx). This descriptive study retrieved the data of PB that was diagnosed by bronchoscopy to define which bronchoscopic procedure produced the highest yield.
METHODS
Retrospectively, all patients diagnosed with PB via bronchoscopic approach were identified. Non-invasive BAL was referred to when performed first in the order of bronchoscopic procedures, and invasive BAL was used when it was performed after other bronchoscopic procedures.
RESULTS
A total of 111 patients were included in the study. BAL produced the highest yield of all bronchoscopic procedures (>87%), regardless if it was performed first in order (non-invasive, 87.3%) or not (invasive BAL, 89.6%) (p = 0.43). Performing bronchoscopy and BAL earlier in the course of the disease resulted in a significantly better diagnostic yield.
CONCLUSIONS
BAL is probably enough to diagnose PB. Also, it had the best yield when performed earlier, regardless of whether it was performed first in order or not. BAL culture had a better yield in detecting Blastomyces dermatitidis over fungal stain and cytology.
Topics: Adolescent; Adult; Aged; Aged, 80 and over; Blastomycosis; Bronchoalveolar Lavage; Bronchoscopy; Female; Humans; Male; Middle Aged; Retrospective Studies; Young Adult
PubMed: 32371194
DOI: 10.1016/j.ijid.2020.04.077 -
Medical Decision Making : An... May 2016The unconscious thought theory argues that making complex decisions after a period of distraction can lead to better decision quality than deciding either immediately or...
The unconscious thought theory argues that making complex decisions after a period of distraction can lead to better decision quality than deciding either immediately or after conscious deliberation. Two studies have tested this unconscious thought effect (UTE) in clinical diagnosis with conflicting results. The studies used different methodologies and had methodological weaknesses. We attempted to replicate the UTE in medical diagnosis by providing favorable conditions for the effect while maintaining ecological validity. Family physicians (N= 116) diagnosed 3 complex cases in 1 of 3 thinking modes: immediate, unconscious (UT), and conscious (CT). Cases were divided into short sentences, which were presented briefly and sequentially on computer. After each case presentation, the immediate response group gave a diagnosis, the UT group performed a 2-back distraction task for 3 min before giving a diagnosis, and the CT group could take as long as necessary before giving a diagnosis. We found no differences in diagnostic accuracy between groups (P= 0.95). The CT group took a median of 7 s to diagnose, which suggests that physicians were able to diagnose "online," as information was being presented. The lack of a difference between the immediate and UT groups suggests that the distraction had no additional effect on performance. To assess the decisiveness of the evidence of this null result, we computed a Bayes factor (BF01) for the 2 comparisons of interest. We found a BF01of 5.76 for the UT versus immediate comparison and of 3.61 for the UT versus CT comparison. Both BFs provide substantial evidence in favor of the null hypothesis: physicians' diagnoses made after distraction are no better than diagnoses made either immediately or after self-paced deliberation.
Topics: Adult; Aged; Bayes Theorem; Clinical Decision-Making; Diagnosis; Female; Humans; Male; Middle Aged; Models, Psychological; Physicians, Family; Reproducibility of Results; Unconscious, Psychology
PubMed: 25852079
DOI: 10.1177/0272989X15581352 -
Transfusion Medicine Reviews Jan 2020Heparin-induced thrombocytopenia (HIT) affects some of the patients exposed to heparin. It is mediated by antibodies that recognize neoepitopes on platelet factor 4... (Review)
Review
Heparin-induced thrombocytopenia (HIT) affects some of the patients exposed to heparin. It is mediated by antibodies that recognize neoepitopes on platelet factor 4 (PF4)/heparin complexes. A HIT diagnosis requires both clinical and laboratory evaluation and remains a challenge. Since many patients develop antibodies in response to heparin, but only a few of them generate anti-PF4/heparin antibodies capable of activating platelets which consequently cause clinical complications, the performance of serologic assays is not enough to diagnose HIT. Functional assays can identify pathogenic antibodies capable of platelet activation, but they are more demanding and their limited availability contributes to the problem of diagnosing HIT. Restricted laboratories usually collect sera of multiple patients to perform functional assays only once or twice a week; hence, a HIT diagnosis can take several days. The use of flow cytometry appears to be a promising alternative in the confirmation of pathogenic anti-PF4/heparin antibodies. Flow cytometric assays detect either activation markers on a healthy donor's platelet surfaces or platelet derived microparticles formed after platelet incubation with a patient's serum. Flow cytometers are readily available in many clinical laboratories, so this technology introduces the possibility of an earlier HIT diagnosis. The objective of this review was to collect findings on flow cytometric HIT confirmations to the present date, and to review the currently available flow cytometric assays used in the diagnosis of HIT.
Topics: Diagnosis, Differential; Flow Cytometry; Heparin; Humans; Platelet Activation; Thrombocytopenia
PubMed: 31575433
DOI: 10.1016/j.tmrv.2019.08.001 -
BMC Medical Informatics and Decision... Mar 2022Acute Rheumatic Fever (ARF) is a critically important condition for which there is no diagnostic test. Diagnosis requires the use of a set of criteria comprising...
BACKGROUND
Acute Rheumatic Fever (ARF) is a critically important condition for which there is no diagnostic test. Diagnosis requires the use of a set of criteria comprising clinical, laboratory, electrocardiographic and echocardiographic findings. The complexity of the algorithm and the fact that clinicians lack familiarity with ARF, make ARF diagnosis ideally suited to an electronic decision support tool. The ARF Diagnosis Calculator was developed to assist clinicians in diagnosing ARF and correctly assign categories of 'possible, 'probable' or 'definite' ARF. This research aimed to evaluate the acceptability, accuracy, and test performance of the ARF Diagnosis Calculator.
METHODS
Three strategies were used to provide triangulation of data. Users of the calculator employed at Top End Health Service, Northern Territory, Australia were invited to participate in an online survey, and clinicians with ARF expertise were invited to participate in semi-structured interviews. Qualitative data were analysed using inductive analysis. Performance of the calculator in correctly diagnosing ARF was assessed using clinical data from 35 patients presenting with suspected ARF. Diagnoses obtained from the calculator were compared using the Kappa statistic with those obtained from a panel of expert clinicians.
RESULTS
Survey responses were available from 23 Top End Health Service medical practitioners, and interview data were available from five expert clinicians. Using a 6-point Likert scale, participants highly recommended the ARF Diagnosis Calculator (median 6, IQR 1), found it easy to use (median 5, IQR 1) and believed the calculator helped them diagnose ARF (median 5, IQR 1). Clinicians with ARF expertise noted that electronic decision making is not a substitute for clinical experience. There was high agreement between the ARF Diagnosis Calculator and the 'gold standard' ARF diagnostic process (κ = 0.767, 95% CI: 0.568-0.967). Incorrect assignment of diagnosis occurred in 4/35 (11%) patients highlighting the greater accuracy of expert clinical input for ambiguous presentations. Sixteen changes were incorporated into a revised version of the calculator.
CONCLUSIONS
The ARF Diagnosis Calculator is an easy-to-use, accessible tool, but it does not replace clinical expertise. The calculator performed well amongst clinicians and is an acceptable tool for use within the clinical setting with a high level of accuracy in comparison to the gold standard diagnostic process. Effective resources to support clinicians are critically important for improving the quality of care of ARF.
Topics: Echocardiography; Humans; Northern Territory; Rheumatic Fever; Surveys and Questionnaires
PubMed: 35346167
DOI: 10.1186/s12911-022-01816-7 -
BMC Oral Health Jun 2023Artificial intelligence (AI) has been introduced to interpret the panoramic radiographs (PRs). The aim of this study was to develop an AI framework to diagnose multiple...
BACKGROUND
Artificial intelligence (AI) has been introduced to interpret the panoramic radiographs (PRs). The aim of this study was to develop an AI framework to diagnose multiple dental diseases on PRs, and to initially evaluate its performance.
METHODS
The AI framework was developed based on 2 deep convolutional neural networks (CNNs), BDU-Net and nnU-Net. 1996 PRs were used for training. Diagnostic evaluation was performed on a separate evaluation dataset including 282 PRs. Sensitivity, specificity, Youden's index, the area under the curve (AUC), and diagnostic time were calculated. Dentists with 3 different levels of seniority (H: high, M: medium, L: low) diagnosed the same evaluation dataset independently. Mann-Whitney U test and Delong test were conducted for statistical analysis (ɑ=0.05).
RESULTS
Sensitivity, specificity, and Youden's index of the framework for diagnosing 5 diseases were 0.964, 0.996, 0.960 (impacted teeth), 0.953, 0.998, 0.951 (full crowns), 0.871, 0.999, 0.870 (residual roots), 0.885, 0.994, 0.879 (missing teeth), and 0.554, 0.990, 0.544 (caries), respectively. AUC of the framework for the diseases were 0.980 (95%CI: 0.976-0.983, impacted teeth), 0.975 (95%CI: 0.972-0.978, full crowns), and 0.935 (95%CI: 0.929-0.940, residual roots), 0.939 (95%CI: 0.934-0.944, missing teeth), and 0.772 (95%CI: 0.764-0.781, caries), respectively. AUC of the AI framework was comparable to that of all dentists in diagnosing residual roots (p > 0.05), and its AUC values were similar to (p > 0.05) or better than (p < 0.05) that of M-level dentists for diagnosing 5 diseases. But AUC of the framework was statistically lower than some of H-level dentists for diagnosing impacted teeth, missing teeth, and caries (p < 0.05). The mean diagnostic time of the framework was significantly shorter than that of all dentists (p < 0.001).
CONCLUSIONS
The AI framework based on BDU-Net and nnU-Net demonstrated high specificity on diagnosing impacted teeth, full crowns, missing teeth, residual roots, and caries with high efficiency. The clinical feasibility of AI framework was preliminary verified since its performance was similar to or even better than the dentists with 3-10 years of experience. However, the AI framework for caries diagnosis should be improved.
Topics: Humans; Radiography, Panoramic; Artificial Intelligence; Tooth, Impacted; Dental Caries; Tooth
PubMed: 37270488
DOI: 10.1186/s12903-023-03027-6