Diagnostics

Follow-up care of patients in the community is an important topic for improving patient outcomes, especially when medical personnel receives a notification of the critical test result (CTR) when the CTR becomes available after patients have been out of hospital; how to recall the patient back to the hospital and follow-up treatment is essential for preventing the healthcare risk of neglecting or delayed intervention with respect to the patient’s CTR. We are concerned that the follow-up of CTR and timely recall of our patients in the community improves and facilitates patient safety. We built the CTR Recall Supporting System (RSS) to follow up and recall our patients in the community. Measures were introduced to evaluate the effectiveness of CTR RSS; the rate of return of patients within 7 days increased from 58.5% to 88.8%, an increase of 30.3%, the patients in the community’s return follow-up interval days decreased from 10.9 days to 6.2 days, reduced by 4.7 days (p < 0.001), and the mortality rate of the patients in the community within 48 h decreased from 8.0% to 1.9%, a decrease of 6.1%, p < 0.001. The implementation of the CTR RSS significantly increases the discharged patient in he community’s CTR return follow-up within 7 days rate, decreases CTR return follow-up interval days, and reduces the CTR mortality rate within 48 h. This effectively improves the effects of CTR on return follow-up visits and provides a prototype system for hospitals that intend to improve this issue. Full article

Neonatal ophthalmic screening should lead to early diagnosis of ocular abnormalities to reduce long-term visual impairment in selected diseases. If a treatable pathology is diagnosed within a few days after the birth, adequate therapy may be indicated to facilitate the best possible conditions for further development of visual functions. Traditional neonatal ophthalmic screening uses the red reflex test (RRT). It tests the transmittance of the light through optical media towards the retina and the general disposition of the central part of the retina. However, RRT has weaknesses, especially in posterior segment affections. Wide-field digital imaging techniques have shown promising results in detecting anterior and posterior segment pathologies. Particular attention should be paid to telemedicine and artificial intelligence. These methods can improve the specificity and sensitivity of neonatal eye screening. Both are already highly advanced in diagnosing and monitoring of retinopathy of prematurity. Full article

Background: The purpose of this study is to compare the morphology of six-month follow-up blebs created by a subconjunctival glaucoma surgical device (XEN45) to those created by a PreserFlo MicroShunt with a sub-Tenon insertion, utilizing AS-OCT. Methods: A retrospective study of 29 eyes who underwent XEN45 implantation and 29 eyes who underwent PreserFlo MicroShunt implantation. The patients were analyzed at 24 h, 1 week, 1 month, 3 months and 6 months. At each visit, the maturation and morphological alterations of the blebs were observed, as well as connections with the IOP. Results: In both groups, IOP showed significant reduction at all follow ups (p < 0.0001). In XEN group, the most common bleb morphology in the immediate postoperative was the subconjuntival separation type (42%) followed by the uniform type (34%), with a trend inversion at 6 month follow up (51% of uniform type). On the contrary, the most common morphology after PreserFlo was the multiple internal layer (55%), which showed a tendency to reduce over time and was substituted by the microcystic multiform, whose percentage increased over time (17% at day 1 vs. 44% at month 6). Uniform appearance was associated by the posterior episcleral fluid (PEF) lake presence. Both horizontal and vertical diameters significantly increased over time. Conclusion: XEN and PreserFlo implantation resulted in the production of diffuse blebs with different characteristics, which may influence IOP lowering capacity and bleb revisions necessity over time. Full article

Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. Methods: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. Summary: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients. Full article

Central sensitization (CS) has been extensively researched as a cause of persistent pain after total knee arthroplasty (TKA). This systematic review study sought to investigate the diagnosis of CS in patients who underwent TKA for knee osteoarthritis (OA) and the effect of CS on clinical outcomes after TKA. Three comprehensive databases, including MEDLINE, EMBASE, and the Cochrane Library, were searched for studies that evaluated the outcomes of TKA in knee OA patients with CS. Data extraction, risk of bias assessment, and (where appropriate) meta-analysis were performed. The standardized mean difference (SMD) with a 95% confidence interval was used to assess the different scales of pain. A total of eight studies were selected, including two retrospective studies and five prospective observational studies. One study used additional randomized controlled trial data. Five studies were finally included in the meta-analysis. All studies had a minimum follow-up period of 3 months. The Central Sensitization Inventory (CSI), whole-body pain diagram, and quantitative sensory testing (QST) were used for measuring CS. The pooled analysis showed that patients with CS had more severe postoperative pain after TKA (SMD, 0.65; 95% CI, 0.40–0.90; p < 0.01) with moderate heterogeneity (I² = 60%). In patients who underwent TKA with knee OA, CSI is most often used for the diagnosis of CS, and the QST and whole-body pain diagram are also used. CS is closely associated with more severe and persistent pain after TKA. Full article

Background This study aims to explore a deep learning (DL) algorithm for developing a prognostic model and perform survival analyses in SBT patients. Methods The demographic and clinical features of patients with SBTs were extracted from the Surveillance, Epidemiology and End Results (SEER) database. We randomly split the samples into the training set and the validation set at 7:3. Cox proportional hazards (Cox-PH) analysis and the DeepSurv algorithm were used to develop models. The performance of the Cox-PH and DeepSurv models was evaluated using receiver operating characteristic curves, calibration curves, C-statistics and decision-curve analysis (DCA). A Kaplan–Meier (K–M) survival analysis was performed for further explanation on prognostic effect of the Cox-PH model. Results The multivariate analysis demonstrated that seven variables were associated with cancer-specific survival (CSS) (all p < 0.05). The DeepSurv model showed better performance than the Cox-PH model (C-index: 0.871 vs. 0.866). The calibration curves and DCA revealed that the two models had good discrimination and calibration. Moreover, patients with ileac malignancy and N2 stage disease were not responding to surgery according to the K–M analysis. Conclusions This study reported a DeepSurv model that performed well in CSS in SBT patients. It might offer insights into future research to explore more DL algorithms in cohort studies. Full article

Although various neuropsychiatric symptoms are frequently accompanied with Alzheimer’s disease (AD) and pose a substantial burden to both patients and caregivers, their neurobiological underpinnings remain unclear. This study investigated associations between regional cerebral blood flow (rCBF) and neuropsychiatric symptom domains in early AD. A total of 59 patients with early AD underwent brain technetium-99m hexamethylpropylene amine oxime (99mTc-HMPAO) single-photon emission computed tomography (SPECT) scans. Neuropsychiatric symptoms were assessed by the Neuropsychiatric Inventory and clustered into the affective, apathy, hyperactivity, and psychotic domains. A voxel-wise multiple regression analysis was performed with four domain scores as independent variables and age, sex, and Mini-Mental State Examination scores as covariates. The affective domain score was negatively correlated with rCBF in the prefrontal cortex, thalamus, and caudate. The apathy domain score showed inverse correlations with rCBF in the prefrontal and pre/postcentral gyri and midbrain. Patients with higher hyperactivity domain scores had increased rCBF in the prefrontal and temporal lobes. The psychotic symptom domain was positively correlated with rCBF in the cuneus and negatively associated with rCBF in the prefrontal, cingulate, and occipital regions and putamen. The score of each neuropsychiatric symptom domain showed the differential correlates of brain perfusion, while altered rCBF in the prefrontal cortex was found in all domains. Although preliminary, our results may suggest common and distinct patterns of rCBF underlying neuropsychiatric symptoms in early AD. Further studies with larger samples and control participants are warranted to confirm these findings. Full article

This study demonstrates that students in kindergarten through eighth grade can use the XpressCollect nasal swab to self-collect a specimen under the guidance of a teacher. This phased study was conducted with parents, teachers, and students. Phases 1 and 2 were conducted as interviews with teachers and parents to assess the suitability of the XpressCollect for children in kindergarten through eighth grade. Additionally, teacher and parent feedback was obtained to develop and optimize the instructional materials for subsequent phases. In Phases 3 and 4, teachers guided small groups and full classes of students through the sample collection process with XpressCollect. The samples collected by the students were sent to a laboratory to analyze the effectiveness of specimen self-collection based on the presence of ribonuclease P (RNase P) on each nasal swab. The presence of RNase P enables disease determination; thus, student samples were analyzed for adequate or inadequate sampling. All students in kindergarten through eighth grade are capable of self-collecting an anterior nares specimen with XpressCollect, as the laboratory results identified acceptable RNase P Ct values for the samples collected in a classroom setting. Full article

We recently published some concerns with new technologies which are based on circulating tumor DNA (ctDNA) for early cancer detection. Most of our published criticism, including a commentary in this journal, has focused on tests developed by the biotechnology company GRAIL (their commercial product is also known as The Galleri Test). Scientists from GRAIL provided explanations and rebuttals to our criticism. They also posed some questions. Here, we reiterate our position and provide rebuttals, explanations and answers to these questions. We believe that constructive scientific debates, like this one, can profoundly contribute to advancements in scientific fields such as early cancer detection. Full article

Multicancer Early Detection (MCED) represents a new and exciting paradigm for the early detection of cancer, which is the leading cause of death worldwide. Current screening tests, recommended for only five cancer types (breast, lung, colon, cervical, and prostate), are limited by a lack of complete adherence to guideline-based use and by the fact that they have cumulative high false positive rates. MCED tests agnostically detect cancer signals in the blood with good sensitivity and low false positive rates, can predict the cancer site of origin with high accuracy, can detect highly lethal cancers that have no current screening tests, and promise to improve cancer screening by improving efficiency and reducing the overall number needed to screen. Herein we outline this promise and clarify several published misconceptions about this field. Full article

Kaposi’s sarcoma is a rare disease with four known variants: classic, epidemic, endemic and iatrogenic (transplant-related), all caused by an oncogenic virus named Human Herpes Virus 8. The viral infection in itself, along with the oncogenic properties of HHV8 and with immune system dysfunction, forms the grounds on which Kaposi’s Sarcoma may develop. Infection with HHV8 occurs through saliva via close contacts, blood, blood products, solid organ donation and, rarely, vertical transmission. Chronic inflammation and oncogenesis are promoted by a mix of viral genes that directly promote cell survival and transformation or interfere with the regular cell cycle and cell signaling (of particular note: LANA-1, v-IL6, vBCL-2, vIAP, vIRF3, vGPCR, gB, K1, K8.1, K15). The most common development sites for Kaposi’s sarcoma are the skin, mucocutaneous zones, lymph nodes and visceral organs, but it can also rarely appear in the musculoskeletal system, urinary system, endocrine organs, heart or eye. Histopathologically, spindle cell proliferation with slit-like vascular spaces, plasma cell and lymphocyte infiltrate are characteristic. The clinical presentation is heterogenic depending on the variant; some patients have indolent disease and others have aggressive disease. The treatment options include highly active antiretroviral therapy, surgery, radiation therapy, chemotherapy, and immunotherapy. A literature search was carried out using the MEDLINE/PubMed, SCOPUS and Google Scholar databases with a combination of keywords with the aim to provide critical, concise, and comprehensive insights into advances in the pathogenic mechanism of Kaposi’s sarcoma. Full article

Gestational diabetes mellitus (GDM) affects a total of 3% to 9% of all pregnancies. It has a high impact on both mother and baby, increases the perinatal risks, and predicts the presence of long-term chronic metabolic complications. The aim of our study is to determine the incidence of GDM in tertiary hospitals in the west part of Romania to lay out the risk factors associated with GDM and to observe the evolution of pregnancy among patients with this pathology by emphasizing the state of birth of the fetus, the birth weight, and the way of birth. We also want to compare the prevalence of GDM in preCOVID-19 (Coronavirus disease) versus COVID-19 years. The study took place between January 2017 and December 2021 at the Municipal Emergency Hospital of Timisoara, Romania. The proportion of births with GDM was significantly increased during the COVID-19 period compared to the preCOVID-19 period (chi2 Fisher exact test, p < 0.001). The period 2020–2021 represents a significant risk factor for GDM births (OR = 1.87, with 95% CI = [1.30, 2.67]). COVID years represent a risk period for developing gestational diabetes, which can be explained by reduced physical activity, anxiety, or modified dietary habits, even if the follow-up period was not impacted. Full article

Background: Dual-energy computed tomography (DECT) allows direct visualization of monosodium urate (MSU) deposits in joints and soft tissues. Purpose: To describe the distribution of MSU deposits in cadavers using DECT in the head, body trunk, and feet. Materials and Methods: A total of 49 cadavers (41 embalmed and 8 fresh cadavers; 20 male, 29 female; mean age, 79.5 years; SD ± 11.3; range 52–95) of unknown clinical history underwent DECT to assess MSU deposits in the head, body trunk, and feet. Lens, thoracic aorta, and foot tendon dissections of fresh cadavers were used to verify MSU deposits by polarizing light microscopy. Results: 33/41 embalmed cadavers (80.5%) showed MSU deposits within the thoracic aorta. 11/41 cadavers (26.8%) showed MSU deposits within the metatarsophalangeal (MTP) joints and 46.3% of cadavers demonstrated MSU deposits within foot tendons, larger than and equal to 5 mm. No MSU deposits were detected in the cranium/intracerebral vessels, or the coronary arteries. Microscopy used as a gold standard could verify the presence of MSU deposits within the lens, thoracic aorta, or foot tendons in eight fresh cadavers. Conclusions: Microscopy confirmed the presence of MSU deposits in fresh cadavers within the lens, thoracic aorta, and foot tendons, whereas no MSU deposits could be detected in cranium/intracerebral vessels or coronary arteries. DECT may offer great potential as a screening tool to detect MSU deposits and measure the total uric acid burden in the body. The clinical impact of this cadaver study in terms of assessment of MSU burden should be further proven. Full article

The COVID-19 pandemic has strongly highlighted the need for more digitalization in healthcare. Teaching ultrasound skills in online courses is a key challenge in this context. The aim of this study was to establish an online video-based head and neck ultrasound course with an evaluation of the quality, effectiveness, and feasibility of this teaching method compared to in-person teaching. Twenty-two medical students were taught head and neck ultrasound in two groups: one group in an in-person course and the other one in a video-based course. Learning success was analyzed using self-evaluation forms and external assessment by an experienced ultrasonographer. Comparing pre- and post-training self-evaluation, all participants showed statistically significant learning progress. In the external assessment, the overall scores in both groups did not differ significantly. The courses themselves were positively evaluated by all participants. Herein, we present the first feasibility study of a web-based head and neck-ultrasound course for medical students. The methodology provides the potential for future changes in telemedical education and sustainable improvements in telemedical teaching and global intra-clinical and interdisciplinary patient care. Full article

The pathophysiological background of chronic thromboembolic pulmonary hypertension (CTEPH) has not been fully elucidated. Evidence suggests that abnormal platelet function and ineffective fibrinolysis may play a key role in the development of the disease. The purpose of this study was to evaluate platelet and coagulation function in CTEPH, using non-conventional global coagulation assays, and platelet activation and endothelial dysfunction laboratory markers. A total of 40 newly-diagnosed CTEPH patients were studied, along with 35 healthy controls. Blood samples from CTEPH patients were taken directly from the pulmonary artery. All subjects were assessed with platelet function analyzer-100, light transmission aggregometry, thromboelastometry, endogenous thrombin potential. von Willebrand antigen and activity, p-selectin, thromboxane A2 and serotonin levels were also assessed. The results showed that CTEPH patients present diminished platelet aggregation, presence of disaggregation, decreased rate of fibrinolysis, defective thrombin generation and increased levels of thromboxane A2, p-selectin, von Willebrand antigen and activity. Serotonin levels did not present any differences between the two groups. The results of this study suggest that CTEPH patients present platelet function, fibrinolytic, thrombin generation and other clot formation abnormalities. Well-designed clinical studies are needed to further evaluate the complex hemostatic abnormalities in the CTEPH setting and assess their potential clinical applications. Full article

High annotation costs are a substantial bottleneck in applying deep learning architectures to clinically relevant use cases, substantiating the need for algorithms to learn from unlabeled data. In this work, we propose employing self-supervised methods. To that end, we trained with three self-supervised algorithms on a large corpus of unlabeled dental images, which contained 38K bitewing radiographs (BWRs). We then applied the learned neural network representations on tooth-level dental caries classification, for which we utilized labels extracted from electronic health records (EHRs). Finally, a holdout test-set was established, which consisted of 343 BWRs and was annotated by three dental professionals and approved by a senior dentist. This test-set was used to evaluate the fine-tuned caries classification models. Our experimental results demonstrate the obtained gains by pretraining models using self-supervised algorithms. These include improved caries classification performance (6 p.p. increase in sensitivity) and, most importantly, improved label-efficiency. In other words, the resulting models can be fine-tuned using few labels (annotations). Our results show that using as few as 18 annotations can produce ≥45% sensitivity, which is comparable to human-level diagnostic performance. This study shows that self-supervision can provide gains in medical image analysis, particularly when obtaining labels is costly and expensive. Full article

Inflammatory bowel disease (IBD) is the term used to identify a form of chronic inflammation of the gastrointestinal tract that primarily contemplates two major entities: ulcerative colitis (UC) and Crohn’s disease (CD). The classic signs are abdominal pain and diarrhoea that correlate with the localization of gastro-enteric disease, although in this pathology extraintestinal symptoms may coexist. The diagnosis of CD relies on a synergistic combination of clinical, laboratory (stool and biochemical), cross-sectional imaging evaluation, as well as endoscopic and histologic assessments. The purpose of this paper is to prove the role of imaging in the diagnosis and follow-up of patients with CD with particular focus on recent innovations of magnetic resonance enterography (MRE) as a pivotal diagnostic tool, analysing the MRE study protocol and imaging features during the various phases of disease activity and its complications. Full article

Background: Sleep stage scoring, which is an essential step in the quantitative analysis of sleep monitoring, relies on human experts and is therefore subjective and time-consuming; thus, an easy and accurate method is needed for the automatic scoring of sleep stages. Methods: In this study, we constructed a deep convolutional recurrent (DCR) model for the automatic scoring of sleep stages based on a raw single-lead electrocardiogram (ECG). The DCR model uses deep convolutional and recurrent neural networks to apply the complex and cyclic rhythms of human sleep. It consists of three convolutional and two recurrent layers and is optimized by dropout and batch normalization. The constructed DCR model was evaluated using multiclass classification, including five-class sleep stages (wake, N1, N2, N3, and rapid eye movement (REM)) and three-class sleep stages (wake, non-REM (NREM), and REM), using a raw single-lead ECG signal. The single-lead ECG signal was collected from 112 subjects in two groups: control (52 subjects) and sleep apnea (60 subjects). The single-lead ECG signal was preprocessed, segmented at a duration of 30 s, and divided into a training set of 89 subjects and test set of 23 subjects. Results: We achieved an overall accuracy of 74.2% for five classes and 86.4% for three classes. Conclusions: These results show the DCR model’s superior performance over those in the previous studies, highlighting that the model can be an alternative tool for sleep monitoring and sleep screening. Full article

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework. Full article