BACKGROUND: Despite the established value of genomic testing strategies, practice guidelines for their use do not exist in many indications. OBJECTIVES: We sought to validate a recently introduced scoring algorithm for dystonia, predicting the diagnostic utility of whole-exome sequencing (WES) based on individual phenotypic aspects (age-at-onset, body distribution, presenting comorbidity). METHODS: We prospectively enrolled a set of 209 dystonia-affected families and obtained summary scores (0-5 points) according to the algorithm. Singleton (N = 146), duo (N = 11), and trio (N = 52) WES data were generated to identify genetic diagnoses. RESULTS: Diagnostic yield was highest (51%) among individuals with a summary score of 5, corresponding to a manifestation of early-onset segmental or generalized dystonia with coexisting non-movement disorder-related neurological symptoms. Sensitivity and specificity at the previously suggested threshold for implementation of WES (3 points) was 96% and 52%, with area under the curve of 0.81. CONCLUSIONS: The algorithm is a useful predictive tool and could be integrated into dystonia routine diagnostic protocols. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.

• Keywords
• diagnostic yield, dystonia, exome sequencing, prediction, rare disease, scoring algorithm,
• MeSH
• Algorithms MeSH
• Dystonic Disorders * genetics   MeSH
• Dystonia * diagnosis   genetics   MeSH
• Genetic Testing MeSH
• Humans MeSH
• Parkinson Disease * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

PURPOSE: Genetic testing in consanguineous families advances the general comprehension of pathophysiological pathways. However, short stature (SS) genetics remain unexplored in a defined consanguineous cohort. This study examines a unique pediatric cohort from Sulaimani, Iraq, aiming to inspire a genetic testing algorithm for similar populations. METHODS: Among 280 SS referrals from 2018-2020, 64 children met inclusion criteria (from consanguineous families; height ≤ -2.25 SD), 51 provided informed consent (30 females; 31 syndromic SS) and underwent investigation, primarily via exome sequencing. Prioritized variants were evaluated by the American College of Medical Genetics and Genomics standards. A comparative analysis was conducted by juxtaposing our findings against published gene panels for SS. RESULTS: A genetic cause of SS was elucidated in 31 of 51 (61%) participants. Pathogenic variants were found in genes involved in the GH-IGF-1 axis (GHR and SOX3), thyroid axis (TSHR), growth plate (CTSK, COL1A2, COL10A1, DYM, FN1, LTBP3, MMP13, NPR2, and SHOX), signal transduction (PTPN11), DNA/RNA replication (DNAJC21, GZF1, and LIG4), cytoskeletal structure (CCDC8, FLNA, and PCNT), transmembrane transport (SLC34A3 and SLC7A7), enzyme coding (CYP27B1, GALNS, and GNPTG), and ciliogenesis (CFAP410). Two additional participants had Silver-Russell syndrome and 1 had del22q.11.21. Syndromic SS was predictive in identifying a monogenic condition. Using a gene panel would yield positive results in only 10% to 33% of cases. CONCLUSION: A tailored testing strategy is essential to increase diagnostic yield in children with SS from consanguineous populations.

• Keywords
• Consanguinity, Genetic testing algorithm, Pediatric endocrinology, Short stature, Short stature genes,
• MeSH
• Algorithms MeSH
• Child MeSH
• Genetic Testing * methods   MeSH
• Humans MeSH
• Adolescent MeSH
• Dwarfism * genetics   epidemiology   diagnosis   MeSH
• Consanguinity MeSH
• Child, Preschool MeSH
• Pedigree MeSH
• Exome Sequencing MeSH
• Body Height genetics   MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Iraq epidemiology   MeSH

BACKGROUND: Breath detection, i.e. its precise delineation in time is a crucial step in lung function data analysis as obtaining any clinically relevant index is based on the proper localization of breath ends. Current threshold or smoothing algorithms suffer from severe inaccuracy in cases of suboptimal data quality. Especially in infants, the precise analysis is of utmost importance. The key objective of our work is to design an algorithm for accurate breath detection in severely distorted data. METHODS: Flow and gas concentration data from multiple breath washout test were the input information. Based on universal physiological characteristics of the respiratory tract we designed an algorithm for breath detection. Its accuracy was tested on severely distorted data from 19 patients with different types of breathing disorders. Its performance was compared to the performance of currently used algorithms and to the breath counts estimated by human experts. RESULTS: The novel algorithm outperformed the threshold algorithms with respect to their accuracy and had similar performance to human experts. It proved to be a highly robust and efficient approach in severely distorted data. This was demonstrated on patients with different pulmonary disorders. CONCLUSION: Our newly proposed algorithm is highly robust and universal. It works accurately even on severely distorted data, where the other tested algorithms failed. It does not require any pre-set thresholds or other patient-specific inputs. Consequently, it may be used with a broad spectrum of patients. It has the potential to replace current approaches to the breath detection in pulmonary function diagnostics.

• Keywords
• Automated breath detection, Breath end, Lung function testing, Medical algorithm design, Multiple breath washout test, Tidal breathing,
• MeSH
• Algorithms * MeSH
• Diagnosis, Computer-Assisted methods   MeSH
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Signal Processing, Computer-Assisted * MeSH
• Child, Preschool MeSH
• Respiratory Function Tests MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND AND AIM: Assessment of appropriateness of CT pulmonary angiograms (CTPA) in patients with suspected pulmonary embolism (PE) is based on risk stratification algorithms such as simplified the Geneva Score (sGS) in combination with D-dimer blood tests. The aim of this study was to validate the diagnostic yield and appropriateness of CTPA examinations in accordance with 2014 European Society of Cardiology (ESC) guidelines. MATERIALS AND METHODS: Data from 155 outpatients who underwent CTPA for clinical suspicion of PE were gathered from the radiology information system (RIS) and the clinical information system (CIS). We assessed the presence of sGS items and D-dimer blood test results in RIS from CTPA request forms and from clinical documentation in CIS. RESULTS: Based on the RIS, there were 2.6% patients with high (sGS≥3) and 97.4% patients with low pre-test PE probability (sGS<3), and CTPA indication was formally comprehendible in 75.5% using sGS and D-dimer blood tests. Based on RIS and CIS data in combination, there were 41.3% patients with high and 58.7% patients with low pre-test PE probability, and CTPA indication was formally comprehendible in 88.4%. Using RIS and CIS in combination, PE probability was upgraded from low to high probability in 39.7% compared with RIS alone. In 12.9%, there was a lack of data in RIS for CTPA justification. CONCLUSION: There is a high diagnostic yield when applying current diagnostic guidelines to our data. There was however a notable discrepancy between the data transferred to the CTPA request forms from the full clinical documentation, therefore not readily available for clinical decision making.

• Keywords
• CT examination justification, CT pulmonary angiography, D-Dimers, acute pulmonary embolism, clinical decision making, diagnostic guidelines,
• MeSH
• Computed Tomography Angiography * MeSH
• Fibrin Fibrinogen Degradation Products analysis   MeSH
• Risk Assessment MeSH
• Middle Aged MeSH
• Humans MeSH
• Pulmonary Embolism blood   diagnostic imaging   MeSH
• Retrospective Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Practice Guidelines as Topic MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Validation Study MeSH
• Names of Substances
• fibrin fragment D MeSH Browser
• Fibrin Fibrinogen Degradation Products MeSH

Clostridium difficile, a causative agent of intestinal infections (CDI) of varying severity, is an important nosocomial pathogen. Microbiological diagnosis, including an appropriate test algorithm and the corresponding interpretation of the results, is crucial for CDI confirmation. This update is based on the European guidance document for CDI laboratory diagnosis, taking into account the current CDI epidemiology and laboratory diagnostic approaches in the Czech Republic. Any diarrhoeal patient should be tested for CDI. The rectal swabs can only be used for testing in patients with paralytic ileus. Currently, a two-step test algorithm is recommended for CDI diagnosis. Due to a low positive predictive value, a single commercial test is not recommended as a stand-alone test for diagnosing CDI. Samples with a positive screening test (glutamate dehydrogenase or toxigenic strain nucleic acid) and a subsequent negative EIA (enzyme immunoassay) test for the presence of free toxins are diagnostically inconclusive. An option is to use a third confirmatory test; however, the current clinical status of the patient along with other laboratory findings should be considered in order to differentiate between ongoing CDI, carriage of a toxigenic strain of C. difficile, and other causes of diarrhoea. In general, when implementing a new diagnostic test, its sensitivity and specificity should be compared against the reference method. Diagnostic tests should refer to the data from published comparative studies and should not rely solely on information provided by the manufacturer. Currently, there is no commercial test available for detection of free C. difficile toxins in stool samples with 100 % sensitivity. Moreover, the pre-analytical conditions (storage and transport temperature of stool samples) and/or the initiation of an empirical therapy prior to the sampling may decrease the sensitivity of the assay.

• Keywords
• Clostridium difficile - laboratory diagnosis - laboratory testing algorithm - result interpretation.,
• MeSH
• Bacterial Toxins analysis   MeSH
• Clostridioides difficile * MeSH
• Feces microbiology   MeSH
• Immunoenzyme Techniques MeSH
• Clinical Laboratory Techniques * standards   MeSH
• Clostridium Infections * diagnosis   MeSH
• Humans MeSH
• Sensitivity and Specificity MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Guideline MeSH
• Geographicals
• Czech Republic MeSH
• Names of Substances
• Bacterial Toxins MeSH

PURPOSE: Sarcopenic obesity (SO) as a new diagnostic entity defined by presence of obesity in combination with sarcopenia represents serious health condition negatively affecting quality of life in old age. Despite the rapidly increasing incidence of SO associated with demographic aging, clear diagnostic criteria for SO have not yet been established. We describe here the applicability of the EWGSOP2 and EWGSOP1 diagnostic criteria in identifying sarcopenia and SO and the development of a refinement algorithm for SO detection. METHODS: In total 156 subjects were pre-screened, 126 had a complete dataset and were included, 20.6% (n = 26) were men and 79.4% (n = 100) women, mean age 81 ± 6.3 years in tertiary hospital, Prague, Czech Republic. Testing of physical performance (hand-grip test, 400 m walk test, chair stand test, gait speed), anthropometric measures and SARC-F, SPPB and MNA-SF were used to determine physical, functional, and nutritional status, while muscle mass and fat mass were measured by DXA scans to confirm sarcopenia and SO diagnosis. RESULTS: The prevalence of sarcopenia (BMI adjusted ALM < 0.789 for men, < 0.512 for women) was 26.2% (n = 33), SO in 20.6% (n = 26). 78.8% of all sarcopenic subjects fulfilled the criteria of SO (FM > 27% for men and > 38% for women; waist circumference > 90 cm for men and > 85 cm for women). EWGSOP1 criteria for diagnosing sarcopenia showed better sensitivity of 97.0% than the EWGSOP2 66.7%, while specificity reached 100% for both criteria. According to DXA measurement, EWGSOP1 identified 3.0% cases (1 out of 33) as false negative meanwhile EWGSOP2 identified 33.3% cases as false negative and this difference was statistically significant (McNemar's test, p < 0.001). An algorithm for SO was developed (which uses sex, BMI, height, waist circumference and SPPB) with sensitivity and specificity of 88.5 and 91.0%, respectively. CONCLUSION: High prevalence of obesity among elderly people and rather low sensitivity of current diagnostic criteria for SO call for ongoing research. Broader international consensus for SO diagnostic criteria, screening and diagnosis algorithm are crucial for early detection of SO in older people in clinical practice so that optimal multi-component therapy can be initiated.

• Keywords
• EWGSOP1, EWGSOP2, Modelling, Sarcopenia, Sarcopenic obesity,
• MeSH
• Algorithms MeSH
• Quality of Life MeSH
• Humans MeSH
• Obesity complications   diagnosis   epidemiology   MeSH
• Sarcopenia * diagnosis   epidemiology   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Hand Strength physiology   MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

The EuroFlow PID consortium developed a set of flow cytometry tests for evaluation of patients with suspicion of primary immunodeficiency (PID). In this technical report we evaluate the performance of the SCID-RTE tube that explores the presence of recent thymic emigrants (RTE) together with T-cell activation status and maturation stages and discuss its applicability in the context of the broader EuroFlow PID flow cytometry testing algorithm for diagnostic orientation of PID of the lymphoid system. We have analyzed peripheral blood cells of 26 patients diagnosed between birth and 2 years of age with a genetically defined primary immunodeficiency disorder: 15 severe combined immunodeficiency (SCID) patients had disease-causing mutations in RAG1 or RAG2 (n = 4, two of them presented with Omenn syndrome), IL2RG (n = 4, one of them with confirmed maternal engraftment), NHEJ1 (n = 1), CD3E (n = 1), ADA (n = 1), JAK3 (n = 3, two of them with maternal engraftment) and DCLRE1C (n = 1) and 11 other PID patients had diverse molecular defects [ZAP70 (n = 1), WAS (n = 2), PNP (n = 1), FOXP3 (n = 1), del22q11.2 (DiGeorge n = 4), CDC42 (n = 1) and FAS (n = 1)]. In addition, 44 healthy controls in the same age group were analyzed using the SCID-RTE tube in four EuroFlow laboratories using a standardized 8-color approach. RTE were defined as CD62L+CD45RO-HLA-DR-CD31+ and the activation status was assessed by the expression of HLA-DR+. Naïve CD8+ T-lymphocytes and naïve CD4+ T-lymphocytes were defined as CD62L+CD45RO-HLA-DR-. With the SCID-RTE tube, we identified patients with PID by low levels or absence of RTE in comparison to controls as well as low levels of naïve CD4+ and naïve CD8+ lymphocytes. These parameters yielded 100% sensitivity for SCID. All SCID patients had absence of RTE, including the patients with confirmed maternal engraftment or oligoclonally expanded T-cells characteristic for Omenn syndrome. Another dominant finding was the increased numbers of activated CD4+HLA-DR+ and CD8+HLA-DR+ lymphocytes. Therefore, the EuroFlow SCID-RTE tube together with the previously published PIDOT tube form a sensitive and complete cytometric diagnostic test suitable for patients suspected of severe PID (SCID or CID) as well as for children identified via newborn screening programs for SCID with low or absent T-cell receptor excision circles (TRECs).

• Keywords
• EuroFlow, diagnosis, flow cytometric immunophenotyping, primary immunodeficiencies (PID), severe combined immune deficiency (SCID), standardization,
• MeSH
• HLA-DR Antigens analysis   MeSH
• Immunophenotyping methods   MeSH
• Infant MeSH
• Humans MeSH
• Infant, Newborn MeSH
• Child, Preschool MeSH
• Primary Immunodeficiency Diseases diagnosis   immunology   MeSH
• Flow Cytometry methods   MeSH
• T-Lymphocytes immunology   MeSH
• Severe Combined Immunodeficiency immunology   MeSH
• Thymus Gland immunology   MeSH
• Check Tag
• Infant MeSH
• Humans MeSH
• Male MeSH
• Infant, Newborn MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• HLA-DR Antigens MeSH

The lethal novel coronavirus disease 2019 (COVID-19) pandemic is affecting the health of the global population severely, and a huge number of people may have to be screened in the future. There is a need for effective and reliable systems that perform automatic detection and mass screening of COVID-19 as a quick alternative diagnostic option to control its spread. A robust deep learning-based system is proposed to detect the COVID-19 using chest X-ray images. Infected patient's chest X-ray images reveal numerous opacities (denser, confluent, and more profuse) in comparison to healthy lungs images which are used by a deep learning algorithm to generate a model to facilitate an accurate diagnostics for multi-class classification (COVID vs. normal vs. bacterial pneumonia vs. viral pneumonia) and binary classification (COVID-19 vs. non-COVID). COVID-19 positive images have been used for training and model performance assessment from several hospitals of India and also from countries like Australia, Belgium, Canada, China, Egypt, Germany, Iran, Israel, Italy, Korea, Spain, Taiwan, USA, and Vietnam. The data were divided into training, validation and test sets. The average test accuracy of 97.11 ± 2.71% was achieved for multi-class (COVID vs. normal vs. pneumonia) and 99.81% for binary classification (COVID-19 vs. non-COVID). The proposed model performs rapid disease detection in 0.137 s per image in a system equipped with a GPU and can reduce the workload of radiologists by classifying thousands of images on a single click to generate a probabilistic report in real-time.

• Keywords
• Chest X-ray radiographs, Coronavirus, Deep learning, Image processing, Pneumonia,
• Publication type
• Journal Article MeSH

The timely and exact diagnosis of prosthetic joint infection (PJI) is crucial for surgical decision-making. Intraoperatively, delivery of the result within an hour is required. Alpha-defensin lateral immunoassay of joint fluid (JF) is precise for the intraoperative exclusion of PJI; however, for patients with a limited amount of JF and/or in cases where the JF is bloody, this test is unhelpful. Important information is hidden in periprosthetic tissues that may much better reflect the current status of implant pathology. We therefore investigated the utility of the gene expression patterns of 12 candidate genes (TLR1, -2, -4, -6, and 10, DEFA1, LTF, IL1B, BPI, CRP, IFNG, and DEFB4A) previously associated with infection for detection of PJI in periprosthetic tissues of patients with total joint arthroplasty (TJA) (n = 76) reoperated for PJI (n = 38) or aseptic failure (n = 38), using the ultrafast quantitative reverse transcription-PCR (RT-PCR) Xxpress system (BJS Biotechnologies Ltd.). Advanced data-mining algorithms were applied for data analysis. For PJI, we detected elevated mRNA expression levels of DEFA1 (P < 0.0001), IL1B (P < 0.0001), LTF (P < 0.0001), TLR1 (P = 0.02), and BPI (P = 0.01) in comparison to those in tissues from aseptic cases. A feature selection algorithm revealed that the DEFA1-IL1B-LTF pattern was the most appropriate for detection/exclusion of PJI, achieving 94.5% sensitivity and 95.7% specificity, with likelihood ratios (LRs) for positive and negative results of 16.3 and 0.06, respectively. Taken together, the results show that DEFA1-IL1B-LTF gene expression detection by use of ultrafast qRT-PCR linked to an electronic calculator allows detection of patients with a high probability of PJI within 45 min after sampling. Further testing on a larger cohort of patients is needed.

• Keywords
• diagnostics, gene expression, intraoperative test, prosthetic joint infection, pseudosynovial tissues,
• MeSH
• alpha-Defensins analysis   genetics   MeSH
• Biomarkers analysis   MeSH
• Adult MeSH
• Prosthesis-Related Infections diagnosis   microbiology   MeSH
• Interleukin-1beta analysis   genetics   MeSH
• Carboxylic Ester Hydrolases analysis   MeSH
• Lactoferrin analysis   genetics   MeSH
• Middle Aged MeSH
• Humans MeSH
• Arthroplasty, Replacement, Hip adverse effects   MeSH
• Polymerase Chain Reaction MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Sensitivity and Specificity MeSH
• Gene Expression Profiling MeSH
• Synovial Fluid chemistry   MeSH
• Arthroplasty, Replacement, Knee adverse effects   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• alpha-Defensins MeSH
• Biomarkers MeSH
• human neutrophil peptide 1 MeSH Browser
• IL1B protein, human MeSH Browser
• Interleukin-1beta MeSH
• Carboxylic Ester Hydrolases MeSH
• Lactoferrin MeSH
• leukocyte esterase MeSH Browser
• LTF protein, human MeSH Browser

AIMS: Permanent His-bundle (HB) pacing is usually accompanied by simultaneous capture of the adjacent right ventricular (RV) myocardium-this is described as a non-selective (ns)-HB pacing. It is of clinical importance to confirm HB capture using standard electrocardiogram (ECG). Our aim was to identify ECG criteria for loss of HB capture during ns-HB pacing. METHODS AND RESULTS: Patients with permanent HB pacing were recruited. Electrocardiograms during ns-HB pacing and loss of HB capture (RV-only capture) were obtained. Electrocardiogram criteria for loss/presence of HB capture were identified. In the validation phase, these criteria and the 'HB ECG algorithm' were tested using a separate, sizable set of ECGs. A total of 353 ECG (226 ns-HB and 128 RV-only) were obtained from 226 patients with permanent HB pacing devices. QRS notch/slur in left ventricular leads and R-wave peak time (RWPT) in lead V6 were identified as the best features for differentiation. The 'HB ECG algorithm' based on these features correctly classified 87.1% of cases with sensitivity and specificity of 93.2% and 83.9%, respectively. The criteria for definitive diagnosis of ns-HB capture (no QRS slur/notch in Leads I, V1, V4-V6, and the V6 RWPT ≤ 100 ms) presented 100% specificity. CONCLUSION: A novel ECG algorithm for the diagnosis of loss of HB capture and criteria for definitive confirmation of HB capture were formulated and validated. The algorithm might be useful during follow-up and the criteria for definitive confirmation of ns-HB capture offer a simple and reliable ancillary procedural endpoint during HB device implantation.

• Keywords
• Electrocardiogram, His-bundle pacing, Loss of capture, Non-selective pacing,
• MeSH
• Algorithms * MeSH
• Atrioventricular Block therapy   MeSH
• Electrocardiography methods   MeSH
• Atrial Fibrillation therapy   MeSH
• Bundle of His * MeSH
• Cardiac Pacing, Artificial * MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Heart Failure therapy   MeSH
• Sick Sinus Syndrome therapy   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Validation Study MeSH