BACKGROUND: Sepsis remains a leading cause of mortality in intensive care units, and rapid and accurate pathogen detection is crucial for effective treatment. This study evaluated the clinical application of multi-site metagenomic next-generation sequencing (mNGS) for the diagnosis of sepsis, comparing its performance against conventional methods.
METHODS: A retrospective analysis was conducted on 69 patients with sepsis consecutively admitted to the Department of Intensive Care Medicine, Meizhou People\'s Hospital. Samples of peripheral blood and infection sites were collected for mNGS and conventional method tests to compare the positive rate of mNGS and traditional pathogen detection methods and the distribution of pathogens. The methods used in this study included a comprehensive analysis of pathogen consistency between peripheral blood and infection site samples. Additionally, the correlation between the pathogens detected and clinical outcomes was investigated.
RESULTS: Of the patients with sepsis, 57.97% experienced dyspnea, and 65.2% had underlying diseases, with hypertension being the most common. mNGS demonstrated a significantly higher pathogen detection rate (88%) compared to the conventional method tests (26%). The pathogen consistency rate was 60% between plasma and bronchoalveolar lavage fluid samples, and that of plasma and local body fluid samples was 63%. The most frequently detected pathogens were gram-negative bacteria, and Klebsiella pneumonia. There were no significant differences in the clinical features between the pathogens.
CONCLUSIONS: mNGS is significantly superior to conventional methods in pathogen detection. There was a notable high pathogen consistency detection between blood and local body fluid samples, supporting the clinical relevance of mNGS. This study highlights the superiority of mNGS in detecting a broad spectrum of pathogens quickly and accurately.
BACKGROUND: Not applicable.

Epithelioid hemangioendothelioma (EHE) is a rare vascular tumor with metastatic potential. EHE can have single- or multiorgan involvement, with presentations ranging from asymptomatic disease to pain and systemic symptoms. The extremely heterogeneous clinical presentation and disease progression complicates EHE diagnosis and management. We present the case of a 24-year-old woman with two periauricular erythematous papules, leading to the discovery of metastatic EHE through routine biopsy, despite a noncontributory medical history. Histology revealed the dermal proliferation of epithelioid cells and vacuoles containing red blood cells. Immunohistochemistry markers consistent with EHE solidified the diagnosis. Although extremely rare, prompt diagnosis of EHE is essential for informed decision-making and favorable outcomes. Key clinical and histopathological findings are highlighted to aid dermatologists in diagnosing and managing this uncommon condition.

UNASSIGNED: Increasing and substantial reliance on electronic health records (EHRs) and data types (ie, diagnosis, medication, and laboratory data) demands assessment of their data quality as a fundamental approach, especially since there is a need to identify appropriate denominator populations with chronic conditions, such as type 2 diabetes (T2D), using commonly available computable phenotype definitions (ie, phenotypes).
UNASSIGNED: To bridge this gap, our study aims to assess how issues of EHR data quality and variations and robustness (or lack thereof) in phenotypes may have potential impacts in identifying denominator populations.
UNASSIGNED: Approximately 208,000 patients with T2D were included in our study, which used retrospective EHR data from the Johns Hopkins Medical Institution (JHMI) during 2017-2019. Our assessment included 4 published phenotypes and 1 definition from a panel of experts at Hopkins. We conducted descriptive analyses of demographics (ie, age, sex, race, and ethnicity), use of health care (inpatient and emergency room visits), and the average Charlson Comorbidity Index score of each phenotype. We then used different methods to induce or simulate data quality issues of completeness, accuracy, and timeliness separately across each phenotype. For induced data incompleteness, our model randomly dropped diagnosis, medication, and laboratory codes independently at increments of 10%; for induced data inaccuracy, our model randomly replaced a diagnosis or medication code with another code of the same data type and induced 2% incremental change from -100% to +10% in laboratory result values; and lastly, for timeliness, data were modeled for induced incremental shift of date records by 30 days to 365 days.
UNASSIGNED: Less than a quarter (n=47,326, 23%) of the population overlapped across all phenotypes using EHRs. The population identified by each phenotype varied across all combinations of data types. Induced incompleteness identified fewer patients with each increment; for example, at 100% diagnostic incompleteness, the Chronic Conditions Data Warehouse phenotype identified zero patients, as its phenotypic characteristics included only diagnosis codes. Induced inaccuracy and timeliness similarly demonstrated variations in performance of each phenotype, therefore resulting in fewer patients being identified with each incremental change.
UNASSIGNED: We used EHR data with diagnosis, medication, and laboratory data types from a large tertiary hospital system to understand T2D phenotypic differences and performance. We used induced data quality methods to learn how data quality issues may impact identification of the denominator populations upon which clinical (eg, clinical research and trials, population health evaluations) and financial or operational decisions are made. The novel results from our study may inform future approaches to shaping a common T2D computable phenotype definition that can be applied to clinical informatics, managing chronic conditions, and additional industry-wide efforts in health care.

UNASSIGNED: Chronic inflammatory demyelinating polyneuropathy (CIDP) is an acquired immune-mediated neuropathy defined by clinical progression for more than 2 months. 16-20% of CIDP patients may present with rapidly progressive weakness that resembles GBS, known as acute-onset CIDP (A-CIDP). However, it is challenging to distinguish from GBS-TRF because of their similar clinical symptom and features. In this case review, we report a patient with A-CIDP with the detection of anti-GM3 and anti-sulfatides antibodies, which rarely have been in A-CIDP and may account for her progressive and recurrent symptoms.
UNASSIGNED: We analyzed existing medical literature and described a clinical case of A-CIDP with antibodies positive.
UNASSIGNED: We reported a 56-year-old female presented with bilateral lower extremity weakness and distal numbness. She experienced similar symptoms four times and responded well to the IVIg therapy. Lumbar puncture demonstrated albumin-cytologic dissociation and EDX examination revealed multiple peripheral nerve damage. After ruling out other demyelination diseases, a diagnosis of A-CIDP was made.
UNASSIGNED: The antiganglioside and anti-sulfatide antibodies are involved in CIDP pathogenesis and can help to distinguish A-CIDP and other variants. To prevent secondary damage, it is important to monitor relapse and remission symptoms along the treatment line. A rare case of A-CIDP is discussed concerning the detection of anti-GM3 and anti-sulfatides antibodies, thus making a retrospective comparison of antibodies in some literature to understand A-CIDP better.

UNASSIGNED: To identify biomarkers in human blood or urine at an early stage of knee osteoarthritis (OA) and to elucidate if any can accurately differentiate between healthy controls and early knee OA patients and be considered as a candidate for widespread clinical use for early diagnosis of the disease.
UNASSIGNED: Medline, Embase and Web of Science were screened to identify comparative studies measuring differences in blood or urine biomarkers between healthy controls and knee OA patients at an early stage (grade 1 or 2 Kellgren-Laurence). Two independent reviewers screened the abstracts for eligibility, reviewed the full texts, assessed the methodological quality and extracted the data. The Joanna Briggs Institute critical appraisal tool for diagnostic test accuracy studies was used to assess the quality of the included studies. Due to relevant heterogeneity, meta-analysis was not appropriate.
UNASSIGNED: Five studies met the eligibility criteria. The examined biomarkers were adropin, collagen type II metabolite, C-terminal cross-linked telopeptide of type II collagen, C-terminal cross-linked telopeptide of type I collagen, cartilage oligomeric matrix protein, matrix metalloproteinase 3, N-terminal propeptide of procollagen type IIA, type I procollagen N-terminal propeptides, N-terminal osteocalcin, angiopoietin-2, follistatin, granulocyte colony-stimulating factor, hepatocyte growth factor, interleukin-8, leptin, platelet-derived growth factor-BB, platelet endothelial cell adhesion molecule-1, vascular endothelial growth factor and calprotectin and totalling 19 biomarkers. All of the biomarkers were studied only once in the selected papers.
UNASSIGNED: There is no reliable biomarker available to differentiate between early knee OA in patients and healthy controls, but a potential role of a cluster of biomarkers to close this gap. There are several limitations, including inappropriate study designs, small sample sizes, nonconsecutive patient groups and inadequate statistical methods for evaluating biomarker performance in studies included.
UNASSIGNED: Level III.

The lack of diagnostic markers limits the window of effectiveness for rheumatoid arthritis (RA) therapies. Here, we isolated exosomes of serum samples from four distinct groups RA patients, according to disease activity and with/without medication. Then, total RNA of exosomes was extracted for whole-transcriptome sequencing. Focusing on lncRNA sequencing, gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed. We found that the number of upregulated lncRNAs were significantly higher than that of downregulated lncRNAs in each four RA groups. And most importantly, we identified two specific lncRNAs from differentially expressed lncRNAs, TCONS_I2_00013502 (up-regulated) and ENST00000363624 (down-regulated) in RA. Receiver Operating Characteristic (ROC) curve analysis showed that the two lncRNAs were promising biomarkers for RA diagnosis. These findings highlight lncRNAs of the serum exosome are important biomarkers and provide application potential for diagnosis of RA.

UNASSIGNED: This paper was to assess the diagnostic performance and clinical value of three-dimensional ultrasonography (3DUS), three-dimensional ultrasonography power Doppler (3DPD), and 3DUS combined with 3DPD in ovarian cancer (OC).
UNASSIGNED: The study was registered with PROSPERO (CRD 42023405765). PubMed and Web of Science were searched from inception to 25 January 2022, and reference lists of potentially eligible studies were also manually searched. Patient and study characteristics were extracted by two independent reviewers. Any discrepancies were addressed through discussion. The sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR, respectively), and the area under the receiver operating characteristic curve (AUC) were pooled separately.
UNASSIGNED: We retrieved 2,566 studies, of which 18 were finally enrolled, with 2,548 cases. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS were 0.89 (95% CI: 0.85-0.93), 0.93 (95% CI: 0.88-0.96), 13.1 (95% CI: 7.3-23.4), 0.11 (95% CI: 0.08-0.16), and 0.90 (95% CI: 0.87-0.93), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DPD were 0.90 (95% CI: 0.80-0.95), 0.85 (95% CI: 0.71-0.92), 5.8 (95% CI: 3.0-11.2), 0.12 (95% CI: 0.06-0.24), and 0.94 (95% CI: 0.91-0.96), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS combined with 3DPD were 0.99 (95% CI: 0.73-1.00), 0.95 (95% CI: 0.85-0.99), 21.9 (95% CI: 6.1-78.9), 0.01 (95% CI: 0.00-0.37), and 0.99 (95% CI: 0.98-1.00), respectively.
UNASSIGNED: 3DUS, 3DPD, and 3DUS combined with 3DPD are promising diagnostic tools for OC, alongside elevated sensitivity and specificity. However, the combination of 3DUS and 3DPD techniques has higher diagnostic efficiency.
UNASSIGNED: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42023405765.

BACKGROUND: Alveolar echinococcosis (AE), caused by the larval forms of Echinococcus multilocularis, is a zoonotic disease affecting the liver, lungs, lymph nodes, kidneys, brain, bones, thyroid, and other organs. Diagnosing AE in a non-endemic area is usually challenging. With the rapid development and increasing application of sequencing techniques in recent years, metagenomic next-generation sequencing (mNGS) has become a powerful tool for diagnosing rare infectious diseases.
METHODS: A 45-year-old woman was admitted to the hospital for the presence of pulmonary shadows for more than 3 months. The lung computed tomography (CT) at a local hospital revealed scattered solid and quasi-circular nodules in the left upper lobe, left lower lobe, right middle lobe, and right lower lobe. The largest nodule was located in the dorsal part of the right lung, measuring 2.0 × 1.7 × 1.5 cm. Moreover, abdominal CT revealed one space-occupying lesion each in the left and right lobes. The pathological analysis of the lung biopsy specimen revealed infiltration of lymphocytes, plasma cells, and eosinophils in the alveolar wall and interstitial area. No pathogenic bacteria were observed in the sputum smear and culture tests. There were no parasite eggs in the stool. The mNGS of the lung puncture tissue revealed 6156 sequence reads matching E. multilocularis; thus, the condition was diagnosed as AE. Albendazole 400 mg was administered twice daily, and the patient was stable during follow-up.
CONCLUSIONS: This case emphasizes the role of mNGS in diagnosing AE. As a novel, sensitive, and accurate diagnostic method, mNGS could be an attractive approach for facilitating early diagnosis and prompt treatment of infectious diseases, especially when the infection was caused by rare pathogens.

BACKGROUND: Machine learning (ML) models can yield faster and more accurate medical diagnoses; however, developing ML models is limited by a lack of high-quality labeled training data. Crowdsourced labeling is a potential solution but can be constrained by concerns about label quality.
OBJECTIVE: This study aims to examine whether a gamified crowdsourcing platform with continuous performance assessment, user feedback, and performance-based incentives could produce expert-quality labels on medical imaging data.
METHODS: In this diagnostic comparison study, 2384 lung ultrasound clips were retrospectively collected from 203 emergency department patients. A total of 6 lung ultrasound experts classified 393 of these clips as having no B-lines, one or more discrete B-lines, or confluent B-lines to create 2 sets of reference standard data sets (195 training clips and 198 test clips). Sets were respectively used to (1) train users on a gamified crowdsourcing platform and (2) compare the concordance of the resulting crowd labels to the concordance of individual experts to reference standards. Crowd opinions were sourced from DiagnosUs (Centaur Labs) iOS app users over 8 days, filtered based on past performance, aggregated using majority rule, and analyzed for label concordance compared with a hold-out test set of expert-labeled clips. The primary outcome was comparing the labeling concordance of collated crowd opinions to trained experts in classifying B-lines on lung ultrasound clips.
RESULTS: Our clinical data set included patients with a mean age of 60.0 (SD 19.0) years; 105 (51.7%) patients were female and 114 (56.1%) patients were White. Over the 195 training clips, the expert-consensus label distribution was 114 (58%) no B-lines, 56 (29%) discrete B-lines, and 25 (13%) confluent B-lines. Over the 198 test clips, expert-consensus label distribution was 138 (70%) no B-lines, 36 (18%) discrete B-lines, and 24 (12%) confluent B-lines. In total, 99,238 opinions were collected from 426 unique users. On a test set of 198 clips, the mean labeling concordance of individual experts relative to the reference standard was 85.0% (SE 2.0), compared with 87.9% crowdsourced label concordance (P=.15). When individual experts\' opinions were compared with reference standard labels created by majority vote excluding their own opinion, crowd concordance was higher than the mean concordance of individual experts to reference standards (87.4% vs 80.8%, SE 1.6 for expert concordance; P<.001). Clips with discrete B-lines had the most disagreement from both the crowd consensus and individual experts with the expert consensus. Using randomly sampled subsets of crowd opinions, 7 quality-filtered opinions were sufficient to achieve near the maximum crowd concordance.
CONCLUSIONS: Crowdsourced labels for B-line classification on lung ultrasound clips via a gamified approach achieved expert-level accuracy. This suggests a strategic role for gamified crowdsourcing in efficiently generating labeled image data sets for training ML systems.

UNASSIGNED: Rabson-Mendenhall syndrome (RMS) is a rare autosomal, recessive disorder characterized by severe insulin resistance due to mutations in the insulin receptor (INSR) gene. This study aims to analyze the clinical features and gene mutations in RMS, which have not been extensively studied.
UNASSIGNED: PubMed, Embase, the China National Knowledge Infrastructure, and Wanfang were searched for \"Rabson-Mendenhall syndrome\" or \"Black acanthosis hirsutism insulin resistance syndrome.\"
UNASSIGNED: A total of 42 cases from 33 articles were included. The body mass index ranged from 18.50 to 20.00 kg/m2 with an average of 16.00 kg/m2. There were no overweight (25.00∼29.90 kg/m2) or obese (≥30.00 kg/m2) patients. Acanthosis was present in 29 cases (29/42, 69.05%); growth retardation in 25 cases (25/42, 59.52%); dental anomalies including absence of teeth, crowding, and malocclusion in 23 cases (23/42, 54.76%); and hirsutism in 17 cases (17/42, 40.48%). The average glycosylated hemoglobin was 9.35%, and the average fasting blood-glucose was 8.44 mmol/L; the mean fasting insulin was 349.96 μIU/mL, and the average fasting C-peptide was 6.00 ng/mL. Diabetes was reported in 25 cases (25/33, 75.76%) all of which were diagnosed before 23 years old. All 42 patients had recorded gene mutations, with 22 patients (22/42, 52.38%) having ≥ 2 mutations and 20 cases (20/42, 47.62%) having only 1 mutation. No statistical differences were found in clinical features and laboratory parameters between patients with different mutations.
UNASSIGNED: The study indicates that RMS should be considered in young patients with hyperinsulinemia, hyperglycemia with low weight, acanthosis nigricans, growth retardation, dental anomalies, and hirsutism.