Reference For Diagnosis Research Articles

Fault detection and diagnosis using tree-based ensemble learning methods and multivariate control charts for centrifugal chillers

Fault detection and diagnosis (FDD) of centrifugal chillers plays an essential role in reducing energy consumption and ensuring safe operation of heating, ventilation and air conditioning systems. In the existing chiller FDD strategy, Data-driven based system modelling methods and statistical analysis-based detection techniques have been widely discussed and applied in recent years. This paper studies the performance of tree-based ensemble learning methods in chiller modelling and analyses multivariate control charts' detection effect. Predictions from the reference model are used in tandem with multivariate control charts to isolate faulty behavior from normal behavior, and then specific failures are identified through the diagnosis model when anomalies are detected. Firstly, in order to establish the optimal chiller reference model and diagnosis model, three tree-based ensemble learning algorithms, namely (i) random forest (RF), (ii) extreme gradient boosting (XGBoost), and (iii) light gradient boosting machine (LightGBM), are evaluated and compared with commonly used support vector machine (SVM). Secondly, Hotelling's T2, multivariate cumulative sum (MCUSUM) and multivariate exponentially weighted moving average (MEWMA) are introduced and their performance in chiller fault detection is tested. Finally, the proposed LightGBM-MEWMA method is validated by the experimental data of ASHRAE RP-1043. Results show that the proposed method effectively identifies seven common chiller faults. Especially at low severity levels, the average detection rate is 88.71%, and the diagnosis accuracy rate is 82.3%.

Race- and Ethnicity-Stratified Analysis of an Artificial Intelligence–Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners

Background Many dermatologic cases are first evaluated by primary care physicians or nurse practitioners. Objective This study aimed to evaluate an artificial intelligence (AI)-based tool that assists with interpreting dermatologic conditions. Methods We developed an AI-based tool and conducted a randomized multi-reader, multi-case study (20 primary care physicians, 20 nurse practitioners, and 1047 retrospective teledermatology cases) to evaluate its utility. Cases were enriched and comprised 120 skin conditions. Readers were recruited to optimize for geographical diversity; the primary care physicians practiced across 12 states (2-32 years of experience, mean 11.3 years), and the nurse practitioners practiced across 9 states (2-34 years of experience, mean 13.1 years). To avoid memory effects from incomplete washout, each case was read once by each clinician either with or without AI assistance, with the assignment randomized. The primary analyses evaluated the top-1 agreement, defined as the agreement rate of the clinicians’ primary diagnosis with the reference diagnoses provided by a panel of dermatologists (per case: 3 dermatologists from a pool of 12, practicing across 8 states, with 5-13 years of experience, mean 7.2 years of experience). We additionally conducted subgroup analyses stratified by cases’ self-reported race and ethnicity and measured the performance spread: the maximum performance subtracted by the minimum across subgroups. Results The AI’s standalone top-1 agreement was 63%, and AI assistance was significantly associated with higher agreement with reference diagnoses. For primary care physicians, the increase in diagnostic agreement was 10% (P<.001), from 48% to 58%; for nurse practitioners, the increase was 12% (P<.001), from 46% to 58%. When stratified by cases’ self-reported race or ethnicity, the AI’s performance was 59%-62% for Asian, Native Hawaiian, Pacific Islander, other, and Hispanic or Latinx individuals and 67% for both Black or African American and White subgroups. For the clinicians, AI assistance–associated improvements across subgroups were in the range of 8%-12% for primary care physicians and 8%-15% for nurse practitioners. The performance spread across subgroups was 5.3% unassisted vs 6.6% assisted for primary care physicians and 5.2% unassisted vs 6.0% assisted for nurse practitioners. In both unassisted and AI-assisted modalities, and for both primary care physicians and nurse practitioners, the subgroup with the highest performance on average was Black or African American individuals, though the differences with other subgroups were small and had overlapping 95% CIs. Conclusions AI assistance was associated with significantly improved diagnostic agreement with dermatologists. Across race and ethnicity subgroups, for both primary care physicians and nurse practitioners, the effect of AI assistance remained high at 8%-15%, and the performance spread was similar at 5%-7%. Acknowledgments This work was funded by Google LLC. Conflicts of Interest AJ, DW, VG, YG, GOM, JH, RS, CE, KN, KBD, GSC, LP, DRW, RCD, DC, Yun Liu, PB, and Yuan Liu are/were employees at Google and own Alphabet stocks.

2022 American College of Rheumatology/European Alliance of Associations for Rheumatology Classification Criteria for Granulomatosis With Polyangiitis.

To develop and validate revised classification criteria for granulomatosis with polyangiitis (GPA). Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in 5 phases: 1) identification of candidate criteria items using consensus methodology, 2) prospective collection of candidate items present at the time of diagnosis, 3) data-driven reduction of the number of candidate items, 4) expert panel review of cases to define the reference diagnosis, and 5) derivation of a points-based risk score for disease classification in a development set using least absolute shrinkage and selection operator logistic regression, with subsequent validation of performance characteristics in an independent set of cases and comparators. The development set for GPA consisted of 578 cases of GPA and 652 comparators. The validation set consisted of an additional 146 cases of GPA and 161 comparators. From 91 candidate items, regression analysis identified 26 items for GPA, 10 of which were retained. The final criteria and their weights were as follows: bloody nasal discharge, nasal crusting, or sino-nasal congestion (+3); cartilaginous involvement (+2); conductive or sensorineural hearing loss (+1); cytoplasmic antineutrophil cytoplasmic antibody (ANCA) or anti-proteinase 3 ANCA positivity (+5); pulmonary nodules, mass, or cavitation on chest imaging (+2); granuloma or giant cells on biopsy (+2); inflammation or consolidation of the nasal/paranasal sinuses on imaging (+1); pauci-immune glomerulonephritis (+1); perinuclear ANCA or antimyeloperoxidase ANCA positivity (-1); and eosinophil count ≥1 × 109 /liter (-4). After excluding mimics of vasculitis, a patient with a diagnosis of small- or medium-vessel vasculitis could be classified as having GPA if the cumulative score was ≥5 points. When these criteria were tested in the validation data set, the sensitivity was 93% (95% confidence interval [95% CI] 87-96%) and the specificity was 94% (95% CI 89-97%). The 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology classification criteria for GPA demonstrate strong performance characteristics and are validated for use in research.

2022 American College of Rheumatology/European Alliance of Associations for Rheumatology Classification Criteria for Eosinophilic Granulomatosis With Polyangiitis.

To develop and validate revised classification criteria for eosinophilic granulomatosis with polyangiitis (EGPA). Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in 5 phases: 1) identification of candidate criteria items using consensus methodology, 2) prospective collection of candidate items present at the time of diagnosis, 3) data-driven reduction of the number of candidate items, 4) expert panel review of cases to define the reference diagnosis, and 5) derivation of a points-based risk score for disease classification in a development set using least absolute shrinkage and selection operator logistic regression, with subsequent validation of performance characteristics in an independent set of cases and comparators. The development set for EGPA consisted of 107 cases of EGPA and 450 comparators. The validation set consisted of an additional 119 cases of EGPA and 437 comparators. From 91 candidate items, regression analysis identified 11 items for EPGA, 7 of which were retained. The final criteria and their weights were as follows: maximum eosinophil count ≥1 × 109 /liter (+5), obstructive airway disease (+3), nasal polyps (+3), cytoplasmic antineutrophil cytoplasmic antibody (ANCA) or anti-proteinase 3 ANCA positivity (-3), extravascular eosinophilic predominant inflammation (+2), mononeuritis multiplex/motor neuropathy not due to radiculopathy (+1), and hematuria (-1). After excluding mimics of vasculitis, a patient with a diagnosis of small- or medium-vessel vasculitis could be classified as having EGPA if the cumulative score was ≥6 points. When these criteria were tested in the validation data set, the sensitivity was 85% (95% confidence interval [95% CI] 77-91%) and the specificity was 99% (95% CI 98-100%). The 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology classification criteria for EGPA demonstrate strong performance characteristics and are validated for use in research.

2022 American College of Rheumatology/European Alliance of Associations for Rheumatology Classification Criteria for Microscopic Polyangiitis.

To develop and validate classification criteria for microscopic polyangiitis (MPA). Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in 5 phases: 1) identification of candidate items using consensus methodology, 2) prospective collection of candidate items present at the time of diagnosis, 3) data-driven reduction of the number of candidate items, 4) expert panel review of cases to define the reference diagnosis, and 5) derivation of a points-based risk score for disease classification in a development set using least absolute shrinkage and selection operator logistic regression, with subsequent validation of performance characteristics in an independent set of cases and comparators. The development set for MPA consisted of 149 cases of MPA and 408 comparators. The validation set consisted of an additional 142 cases of MPA and 414 comparators. From 91 candidate items, regression analysis identified 10 items for MPA, 6 of which were retained. The final criteria and their weights were as follows: perinuclear antineutrophil cytoplasmic antibody (ANCA) or anti-myeloperoxidase-ANCA positivity (+6), pauci-immune glomerulonephritis (+3), lung fibrosis or interstitial lung disease (+3), sino-nasal symptoms or signs (-3), cytoplasmic ANCA or anti-proteinase 3 ANCA positivity (-1), and eosinophil count ≥1 × 109 /liter (-4). After excluding mimics of vasculitis, a patient with a diagnosis of small- or medium-vessel vasculitis could be classified as having MPA with a cumulative score of ≥5 points. When these criteria were tested in the validation data set, the sensitivity was 91% (95% confidence interval [95% CI] 85-95%) and the specificity was 94% (95% CI 92-96%). The 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology classification criteria for MPA are now validated for use in clinical research.

Computerized migraine diagnostic tools: a systematic review.

Background:Computerized migraine diagnostic tools have been developed and validated since 1960. We conducted a systematic review to summarize and critically appraise the quality of all published studies involving computerized migraine diagnostic tools.Methods:We performed a systematic literature search using PubMed, Web of Science, Scopus, snowballing, and citation searching. Cutoff date for search was 1 June 2021. Published articles in English that evaluated a computerized/automated migraine diagnostic tool were included. The following summarized each study: publication year, digital tool name, development basis, sample size, sensitivity, specificity, reference diagnosis, strength, and limitations. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was applied to evaluate the quality of included studies in terms of risk of bias and concern of applicability.Results:A total of 41 studies (median sample size: 288 participants, median age = 43 years; 77% women) were included. Most (60%) tools were developed based on International Classification of Headache Disorders criteria, half were self-administered, and 82% were evaluated using face-to-face interviews as reference diagnosis. Some of the automated algorithms and machine learning programs involved case-based reasoning, deep learning, classifier ensemble, ant-colony, artificial immune, random forest, white and black box combinations, and hybrid fuzzy expert systems. The median diagnostic accuracy was concordance = 89% [interquartile range (IQR) = 76–93%; range = 45–100%], sensitivity = 87% (IQR = 80–95%; range = 14–100%), and specificity = 90% (IQR = 77–96%; range = 65–100%). Lack of random patient sampling was observed in 95% of studies. Case–control designs were avoided in all studies. Most (76%) reference tests exhibited low risk of bias and low concern of applicability. Patient flow and timing showed low risk of bias in 83%.Conclusion:Different computerized and automated migraine diagnostic tools are available with varying accuracies. Random patient sampling, head-to-head comparison among tools, and generalizability to other headache diagnoses may improve their utility.

THE IDEAL PROFILE (INCREASE IN B-LINES/DELTA B-LINES) ON LUNG ULTRASOUND FOR DIAGNOSING WEANING INDUCED PULMONARY EDEMA IN VENTILATED PATIENTS

Objective: To ascertain the ideal number of B-lines on lung ultrasound for the diagnosis of weaning induced pulmonary edema in ventilated patients.
 Study Design: Prospective observational study.
 Place and Duration of Study: Department of Medicine, Shifa International Hospital, Islamabad, from Jan to Aug 2020.
 Methodology: All the patients over the age of 18 years who were on mechanical ventilation in a medical intensive care unit were included in the study. The patients were given spontaneous breathing trials as a protocol for weaning from mechanical ventilation. Lung ultrasound was performed on 4 points of anterior chest wall before and after spontaneous breathing trials. Before and after spontaneous breathing trials counting of B lines was done on ultrasound of lung and comparison of increase in B lines (Delta-B-lines) was done with reference diagnosis of weaning induced pulmonary edema diagnosed by intensivist who was blinded to the results of lung ultrasound.
 Results: The study included 42 patients including 23 (54.8%) men and 19 (45.2%) women. 14 cases failed spontaneous breathing trials. Seven cases (16.7%) had weaning induced pulmonary edema. Delta-B-lines ≥6 diagnosed weaning induced pulmonary edema with 100% accuracy. Out of the remaining seven patients with weaning failure but without weaning induced pulmonary edema, 6 (28.6%) had Delta-B-lines ≥6. The ultrasound lung technique had a 100% sensitivity profile to detect weaning induced pulmonary edema and a specificity of 77.78%.
 Conclusion: The study indicates that Delta-B-lines ≥6 diagnosed the weaning induced pulmonary edema with the best accuracy.

Monitoring and detection of new endemic foci of canine leishmaniosis in northern continental Italy: An update from a study involving five regions (2018-2019).

Canine leishmaniosis (CanL) is an emerging zoonosis caused by Leishmania infantum and transmitted in southern Europe by phlebotomine sand flies of the subgenus Phlebotomus (Larroussius). Endemic foci of CanL have been recorded in northern continental Italy since early 1990s and attributed to the northward expansion of vector populations due to climatic changes in association with travelling/relocated infected dogs from the southern Mediterranean littoral. In this study, further spread of endemic Leishmania foci was monitored during 2018-2019 in five regions (Aosta Valley, Piedmont, Lombardy, Veneto and Friuli-Venezia Giulia), with focus to territories where investigations were not performed, or they have been inconclusive. Clinical cases of CanL identified by local veterinary practitioners and confirmed by reference diagnosis centers were regarded as autochthonous if their origin from, or travel to, areas endemic for CanL were excluded in the previous ≥2years. Around these index cases, i) serosurveys for L infantum were carried out where indicated, ii) sampling from potential autochthonous cases in healthy or clinically-suspected resident dogs was intensified by collaborating veterinary practitioners, and iii) suitable sites were investigated for the presence of competent phlebotomine vectors. Fifty-seven municipalities whose enzootic status of CanL was unreported before 2018, were identified as endemic. The stability of 27 foci recorded over the past decade, was also confirmed. Competent phlebotomine vectors, mainly Phlebotomus perniciosus, were collected for the first time in 23 municipalities. The newly recorded endemic municipalities appear to be distributed over a west-to-east decreasing gradient: 30 in Piedmont, 21 in Lombardy, 4 in Veneto and 2 in Friuli-Venezia Giulia. As regards Veneto, it should be noted that a relatively restricted territory was investigated as several municipalities of the region had already been surveyed and detected as endemic for CanL in the past. Cold climate conditions of the easternmost region of Friuli-Venezia Giulia bordering non-endemic territories of Slovenia, are probably less favorable to L infantum transmission.

Evaluation of an improved Giemsa staining technique for blood borne parasite in thick and thin blood film from dogs

Many a times the use of rapid diagnostic tests for blood borne parasites like trypanosomiasis and Babesiosis is increasingly being used, but the gold standard for its detection is still the use of microscopy both as reference and confirmatory diagnosis. To determine the effectiveness of the adjusted stock giemsa staining technique over the conventional methods. Venous Blood samples were collected from 10 dogs in EDTA and then used for the simultaneous preparation of two thin and thick smear slides, one stained according to Giemsa 1:20 dilution for 30 mins while the other was stained using the Stock Solution for 30seconds the diluted with buffered saline for 20seconds and rinsed. Fixation of the thin smear was done in a covered staining jar containing anhydrous methanol for 1 to 2 min, after which the slides were air-dried. From the result obtained from 10 dogs blood samples gotten from the veterinary clinic, the adjusted giemsa staining technique showed a positive differentiation when compared to the 1:20 dilution, a total of 7 blood samples tested positive for blood borne parasites, Trypanosoma evansi, Babesiosis cani and Heart worm. The highest percentage occurrence was T.evansi (40%), Babesiosis cani(20%) and Heart worm (10%).The adjusted Giemsa staining technique serves as a fast, easy and less complex alternative to the 1:20 dilution, where the solution has to be diluted from the stock solution and then stained, although the only disadvantage to this technique would be easy contamination of the stock solution, but the advantages here is that it saves time, quicker result output and better differentiation microscopically.

Efficiency of Hardware and Software Systems in the Assessment of Psychophysiological State of Persons in Extreme Conditions Professions

Aim. To determine the effectiveness of hardware and software complexes in assessing the psychophysiological state of persons in extreme conditions professions. Material and methods. The post-hoc comparative analysis of sensitivity, specificity, and overall accuracy of five hardware and software complexes was performed involving 459 patients of different medical and preventive care institutions that received the rehabilitation medical care. The simulation of altered reactivity in 6 athletes of cyclic kinds of sport was carried out within a daily experiment (5 men, mean age 21.1±0.7 years and one woman, 22 years; sport rank not lower than 1 senior degree). Psychophysiological testing was conducted at five time points using the following methods: hardware and software complex “Diamed-MBS”, ASD (Radix), Lusher colorchoice test (Radix), reaction to a moving object (Multipsychometer), static and dynamic tremorometry (Multipsychometer). Results and discussion. The diagnostic effectiveness of these psychophysiological examination data automated processing complexes were determined by their informative value, the ability to recognize signs of the disease with a so-called reference or benchmark diagnosis. The highest indicators of sensitivity (82.5%), specificity (79.3%) and overall accuracy (80.6%) were found in the Diamed-MBS hardware and software complex. A tendency to decrease in the main indicators, such as heart rate, stress index, activity, well-being, working capacity with a minimum at 3:00-5:00 hours, was revealed. During the day, the possibility of the athletes’ psycho-emotionalstate dynamic assessment during the day (somatic and psychological components) was evaluated according to the parameters of heart rate variability, electrosomatography and bioelectrography. The dynamics of psychological and psychophysiological diagnostics indicators was of the multidirectional nature, which does not allow us to assert unequivocally about the negative impact of daily rhythms on the condition of athletes. All athletes showed negative results in one way or another at different intermediate diagnostic points, but by the end of the study they managed to compensate and reach the results of the primary diagnosis. Conclusion. The diagnostic efficiency of complex screening diagnostics when using hardware and software complex “Diamed-MBS” is 80.6%, which is 25-35% higher than the same parameter for similar devices. No negative psychological and psychophysiological effects of stress stimulation on daily rhythms of athletes were defined.

Imperative role of electron microscopy in toxicity assessment: A review.

Electron microscope (EM) was developed in 1931 and since then microscopical examination of both the biological and non-biological samples has been revolutionized. Modifications in electron microscopy techniques, such as scanning EM and transmission EM, have widened their applicability in the various sectors such as understanding of drug toxicity, development of mechanism, criminal site investigation, and characterization of the nano-molecule. The present review summarizes its role in important aspects such as toxicity assessment and disease diagnosis in special reference to SARS-COV2. In the biological system, EM studies have elucidated the impact of toxicants at the ultra-structural level in various tissue in conformity to physiological alterations. Thus, EM can be concluded as an important tool in toxicity assessment and disease prognosis.

Inter-observer agreement for the histological diagnosis of invasive lobular breast carcinoma.

Invasive lobular breast carcinoma (ILC) is the second most common breast carcinoma (BC) subtype and is mainly driven by loss of E‐cadherin expression. Correct classification of BC as ILC is important for patient treatment. This study assessed the degree of agreement among pathologists for the diagnosis of ILC. Two sets of hormone receptor (HR)‐positive/HER2‐negative BCs were independently reviewed by participating pathologists. In set A (61 cases), participants were provided with hematoxylin/eosin (HE)‐stained sections. In set B (62 cases), participants were provided with HE‐stained sections and E‐cadherin immunohistochemistry (IHC). Tumor characteristics were balanced. Participants classified specimens as non‐lobular BC versus mixed BC versus ILC. Pairwise inter‐observer agreement and agreement with a pre‐defined reference diagnosis were determined with Cohen's kappa statistics. Subtype calls were correlated with molecular features, including CDH1/E‐cadherin mutation status. Thirty‐five pathologists completed both sets, providing 4,305 subtype calls. Pairwise inter‐observer agreement was moderate in set A (median κ = 0.58, interquartile range [IQR]: 0.48–0.66) and substantial in set B (median κ = 0.75, IQR: 0.56–0.86, p < 0.001). Agreement with the reference diagnosis was substantial in set A (median κ = 0.67, IQR: 0.57–0.75) and almost perfect in set B (median κ = 0.86, IQR: 0.73–0.93, p < 0.001). The median frequency of CDH1/E‐cadherin mutations in specimens classified as ILC was 65% in set A (IQR: 56–72%) and 73% in set B (IQR: 65–75%, p < 0.001). Cases with variable subtype calls included E‐cadherin‐positive ILCs harboring CDH1 missense mutations, and E‐cadherin‐negative ILCs with tubular elements and focal P‐cadherin expression. ILCs with trabecular growth pattern were often misclassified as non‐lobular BC in set A but not in set B. In conclusion, subtyping of BC as ILC achieves almost perfect agreement with a pre‐defined reference standard, if assessment is supported by E‐cadherin IHC. CDH1 missense mutations associated with preserved E‐cadherin protein expression, E‐ to P‐cadherin switching in ILC with tubular elements, and trabecular ILC were identified as potential sources of discordant classification.

Explainability of Convolutional Neural Networks for Dermatological Diagnosis

Background Convolutional neural networks (CNNs) are regarded as state-of-the-art artificial intelligence (AI) tools for dermatological diagnosis, and they have been shown to achieve expert-level performance when trained on a representative dataset. CNN explainability is a key factor to adopting such techniques in practice and can be achieved using attention maps of the network. However, evaluation of CNN explainability has been limited to visual assessment and remains qualitative, subjective, and time consuming. Objective This study aimed to provide a framework for an objective quantitative assessment of the explainability of CNNs for dermatological diagnosis benchmarks. Methods We sourced 566 images available under the Creative Commons license from two public datasets—DermNet NZ and SD-260, with reference diagnoses of acne, actinic keratosis, psoriasis, seborrheic dermatitis, viral warts, and vitiligo. Eight dermatologists with teledermatology expertise annotated each clinical image with a diagnosis, as well as diagnosis-supporting characteristics and their localization. A total of 16 supporting visual characteristics were selected, including basic terms such as macule, nodule, papule, patch, plaque, pustule, and scale, and additional terms such as closed comedo, cyst, dermatoglyphic disruption, leukotrichia, open comedo, scar, sun damage, telangiectasia, and thrombosed capillary. The resulting dataset consisted of 525 images with three rater annotations for each. Explainability of two fine-tuned CNN models, ResNet-50 and EfficientNet-B4, was analyzed with respect to the reference explanations provided by the dermatologists. Both models were pretrained on the ImageNet natural image recognition dataset and fine-tuned using 3214 images of the six target skin conditions obtained from an internal clinical dataset. CNN explanations were obtained as activation maps of the models through gradient-weighted class-activation maps. We computed the fuzzy sensitivity and specificity of each characteristic attention map with regard to both the fuzzy gold standard characteristic attention fusion masks and the fuzzy union of all characteristics. Results On average, explainability of EfficientNet-B4 was higher than that of ResNet-50 in terms of sensitivity for 13 of 16 supporting characteristics, with mean values of 0.24 (SD 0.07) and 0.16 (SD 0.05), respectively. However, explainability was lower in terms of specificity, with mean values of 0.82 (SD 0.03) and 0.90 (SD 0.00) for EfficientNet-B4 and ResNet-50, respectively. All measures were within the range of corresponding interrater metrics. Conclusions We objectively benchmarked the explainability power of dermatological diagnosis models through the use of expert-defined supporting characteristics for diagnosis. Acknowledgments This work was supported in part by the Danish Innovation Fund under Grant 0153-00154A. Conflict of Interest None declared.

Serological diagnosis in hydatidosis: Searching standardized antigenic support. Systematic review and meta-analysis

Background: Hydatidosis is a worldwide distributed parasitic zoonosis caused by Echinococcus granulosus s.l. In humans, the diagnosis is based on epidemiological nexus, clinical findings, ultrasound images, and second-line serology. Hydatid fluid is the most widely used source of antigens in serology, but it shows high variability. This review analyzes the diagnostic utility of serology for the diagnosis of hydatidosis, particularly ELISA and Western Blot techniques. Material and methods: Systematic review and meta-analysis of studies with data of diagnostic validity. The reference diagnosis was ultrasound and / or parasitological medical finding. The reproducibility in the studies selection and data extraction was guaranteed, the quality was evaluated according to the QUADAS-2 guide, global results and SROC were obtained under a random effects model in Meta-Disc1.4. Results: Forty-one articles published between 1981 and 2019 were included. Elisa was performed in 33 articles; Western Blot was performed in 14 articles and some of the articles included both techniques. The included articles presented high heterogeneity. The SROC parameters were AUC = 0.9511 and Q=0.8919 for ELISA and AUC=0.9693 and Q = 0.9186 for Western Blot. Conclusion: ELISA and Western Blot have good diagnostic accuracy

Referral Patterns in Oral Medicine: A Retrospective Analysis of an Oral Medicine University Center in Southern Italy.

Referral of a patient from one healthcare provider to another is an important part of the medical practice. The aim of this study was to analyze the referral process to the Oral Medicine Unit in a university-based tertiary center in Southern Italy. A chart review of new referrals to the Oral Medicine Unit during a 24-month period was conducted. The following data were recorded: demographic characteristics, medical history, number of physicians seen prior to Oral Medicine assessment, referral source, diagnostic procedures ordered by referrals, reason for referral, site of lesion/condition, final diagnosis. Then, the rates of correct identification for health-care professionals and the appropriateness of the reference diagnosis based on the disease were calculated with descriptive statistic indicators. There were 583 new first consultations. A total of 62.9% of patients were referred by general dental practitioners, 27.4% by physicians, and 9.7% did not have a referral. The most common diseases for referral were immune-mediated diseases (39.6%) and oro-facial pain disorders (25.2%). Only 28.5% of patients had a correct provisional diagnosis. The results of this study show the need to implement curricula in the field of oral medicine among dentistry and medical students, and to support the continuing education among healthcare providers to reduce diagnostic delay for oral diseases.

Variability in the Histopathological Diagnosis of Non-Melanocytic Lesions Excised to Exclude Melanoma.

The differential diagnosis of lesions excised to exclude melanoma include a variety of benign and malignant melanocytic and non-melanocytic lesions. We examined the variability between pathologists in diagnosing non-melanocytic lesions. As part of a larger study prospectively examining the diagnosis of lesions excised to exclude melanoma in 198 patients at a primary care skin cancer clinic in Newcastle, Australia, we compared diagnosis made by 5 experienced dermatopathologists, of 44 non-melanocytic lesions in 44 patients aged 22-90. Forty-four lesions (out of 217 in total) were non-melanocytic. Among the 5 pathologists who examined each case there was marked variability in the terminology used to diagnose each case. The most common variability was found between seborrheic keratosis, large cell acanthoma, solar lentigo, and lichenoid keratosis. The diagnosis made by the majority of the pathologists was deemed to be the reference diagnosis. Versus majority diagnosis, 4% of benign lesions were considered malignant, and 7% of malignant diagnoses were considered as benign. The different terminology adopted and lack of consensus in the diagnosis of these non-melanocytic lesions in this setting suggests that training AI systems using gold standards may be problematic. We propose a new management classification scheme called MOLEM (Management of Lesions Excised to exclude Melanoma) which expands the previously described MPATH-dx to include non-melanocytic lesions.

Cost-Benefit Analysis and Resource Implications of Endoscopic Ultrasound-Guided Confocal Endomicroscopy in Pancreatic Cysts

Background and AimsEUS-guided needle-based confocal laser endomicroscopy (nCLE) improves the diagnostic accuracy of pancreatic cystic lesions (PCLs) but concerns regarding its expense have limited widespread adoption of this technology. We conducted a cost-benefit analysis to assess the healthcare resource implications of adding EUS-nCLE to the standard of care (SOC) management of PCLs. MethodsA post-hoc analysis of a prospective study (2015-2018) evaluating EUS-nCLE for the diagnosis of PCLs was performed. The SOC diagnosis was based on clinical history, PCL morphology, and cyst fluid analysis. A minimum of 5-years surveillance was included, the cost of EUS and MRI/MRCP was derived from institutional billing data (US$), and the total hospital costs (adjusted for inflation) for pancreatic operations were derived from the National (US) Readmission Database. ResultsA reference diagnosis was available in 93 subjects (mean cyst size = 36.4 ± 15.7 mm; surgical histopathology, n = 67 and diagnostic molecular markers in cyst fluid, n = 26). SOC and nCLE were discordant in 13 (14%) subjects. The addition of nCLE led to 11 subjects being clinically down-staged from mucinous to non-mucinous not warranting surgery (total cost savings = $1,080,418), 1 subject upstaged from non-mucinous to mucinous, warranting surgical resection (cost savings of 5-years surveillance: $46,200), and 1 subject incorrectly classified as non-mucinous (cost excess of 5-years surveillance: $46,200). Overall, the addition of nCLE led to a net savings of $ 442,438 (mean: $ 4757.40/patient) for this cohort. ConclusionEUS-nCLE is potentially cost-beneficial in the management of PCLs (≥3 cm) by preventing at least one unnecessary pancreatic surgery for every 10 subjects undergoing evaluation by current practices. ClinicalTrials.gov number: NCT02516488.

Performance of primary health care workers in detection of mental disorders comorbid with epilepsy in rural Ethiopia

BackgroundTimely detection and management of comorbid mental disorders in people with epilepsy is essential to improve outcomes. The objective of this study was to measure the performance of primary health care (PHC) workers in identifying comorbid mental disorders in people with epilepsy against a standardised reference diagnosis and a screening instrument in rural Ethiopia.MethodsPeople with active convulsive epilepsy were identified from the community, with confirmatory diagnosis by trained PHC workers. Documented diagnosis of comorbid mental disorders by PHC workers was extracted from clinical records. The standardized reference measure for diagnosing mental disorders was the Operational Criteria for Research (OPCRIT plus) administered by psychiatric nurses. The mental disorder screening scale (Self-Reporting Questionnaire; SRQ-20), was administered by lay data collectors. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of PHC worker diagnosis against the reference standard diagnosis was calculated. Logistic regression was used to examine the factors associated with misdiagnosis of comorbid mental disorder by PHC workers.ResultsA total of 237 people with epilepsy were evaluated. The prevalence of mental disorders with standardised reference diagnosis was 13.9% (95% confidence interval (CI) 9.6, 18.2%) and by PHC workers was 6.3% (95%CI 3.2, 9.4%). The prevalence of common mental disorder using SRQ-20 at optimum cut-off point (9 or above) was 41.5% (95% CI 35.2, 47.8%). The sensitivity and specificity of PHC workers diagnosis was 21.1 and 96.1%, respectively, compared to the standardised reference diagnosis. In those diagnosed with comorbid mental disorders by PHC workers, only 6 (40%) had SRQ-20 score of 9 or above. When a combination of both diagnostic methods (SRQ-20 score ≥ 9 and PHC diagnosis of depression) was compared with the standardised reference diagnosis of depression, sensitivity increased to 78.9% (95% (CI) 73.4, 84.4%) with specificity of 59.7% (95% CI 53.2, 66.2%). Only older age was significantly associated with misdiagnosis of comorbid mental disorders by PHC (adjusted odds ratio, 95% CI = 1.06, 1.02 to 1.11).ConclusionRoutine detection of co-morbid mental disorder in people with epilepsy was very low. Combining clinical judgement with use of a screening scale holds promise but needs further evaluation.

90-Gene Expression Profiling for Tissue Origin Diagnosis of Cancer of Unknown Primary.

Cancer of unknown primary (CUP), in which metastatic diseases exist without an identifiable primary location, accounts for about 3–5% of all cancer diagnoses. Successful diagnosis and treatment of such patients are difficult. This study aimed to assess the expression characteristics of 90 genes as a method of identifying the primary site from CUP samples. We validated a 90-gene expression assay and explored its potential diagnostic utility in 44 patients at Jiangsu Cancer Hospital. For each specimen, the expression of 90 tumor-specific genes in malignant tumors was analyzed, and similarity scores were obtained. The types of malignant tumors predicted were compared with the reference diagnosis to calculate the accuracy. In addition, we verified the consistency of the expression profiles of the 90 genes in CUP secondary malignancies and metastatic malignancies in The Cancer Genome Atlas. We also reported a detailed description of the next-generation coding sequences for CUP patients. For each clinical medical specimen collected, the type of malignant tumor predicted and analyzed by the 90-gene expression assay was compared with its reference diagnosis, and the overall accuracy was 95.4%. In addition, the 90-gene expression profile generally accurately classified CUP into the cluster of its primary tumor. Sequencing of the exome transcriptome containing 556 high-frequency gene mutation oncogenes was not significantly related to the 90 genes analysis. Our results demonstrate that the expression characteristics of these 90 genes can be used as a powerful tool to accurately identify the primary sites of CUP. In the future, the inclusion of the 90-gene expression assay in pathological diagnosis will help oncologists use precise treatments, thereby improving the care and outcomes of CUP patients.

Gene Expression Profiling for Differential Diagnosis of Liver Metastases: A Multicenter, Retrospective Cohort Study.

BackgroundLiver metastases (LM) are the most common tumors encountered in the liver and continue to be a significant cause of morbidity and mortality. Identification of the primary tumor of any LM is crucial for the implementation of effective and tailored treatment approaches, which still represents a difficult problem in clinical practice.MethodsThe resection or biopsy specimens and associated clinicopathologic data were archived from seven independent centers between January 2017 and December 2020. The primary tumor sites of liver tumors were verified through evaluation of available medical records, pathological and imaging information. The performance of a 90-gene expression assay for the determination of the site of tumor origin was assessed.ResultA total of 130 LM covering 15 tumor types and 16 primary liver tumor specimens that met all quality control criteria were analyzed by the 90-gene expression assay. Among 130 LM cases, tumors were most frequently located in the colorectum, ovary and breast. Overall, the analysis of the 90-gene signature showed 93.1% and 100% agreement rates with the reference diagnosis in LM and primary liver tumor, respectively. For the common primary tumor types, the concordance rate was 100%, 95.7%, 100%, 93.8%, 87.5% for classifying the LM from the ovary, colorectum, breast, neuroendocrine, and pancreas, respectively.ConclusionThe overall accuracy of 93.8% demonstrates encouraging performance of the 90-gene expression assay in identifying the primary sites of liver tumors. Future incorporation of the 90-gene expression assay in clinical diagnosis will aid oncologists in applying precise treatments, leading to improved care and outcomes for LM patients.