The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers.
We viewed \"infectious disease*\" and \"prediction\" or \"forecasting\" as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis.
1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases.
Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.

OBJECTIVE: To develop and validate a deep learning model based on routine magnetic resonance (MR) imaging obtained before uterine fibroid embolization to predict procedure outcome.
METHODS: Clinical data were collected on patients treated with uterine fibroid embolization at the Hospital of the University of Pennsylvania from 2007 to 2018. Fibroids for each patient were manually segmented by an abdominal radiologist on a T1-weighted contrast-enhanced (T1C) sequence and a T2-weighted sequence of MR imaging obtained before and after embolization. A residual convolutional neural network (ResNet) model to predict clinical outcome was trained using MR imaging obtained before the procedure.
RESULTS: Inclusion criteria were met by 727 fibroids in 409 patients. At clinical follow-up, 85.6% (n = 350) of 409 patients (590 of 727 fibroids; 81.1%) experienced symptom resolution or improvement, and 14.4% (n = 59) of 409 patients (137 of 727 fibroids; 18.9%) had no improvement or worsening symptoms. The T1C trained model achieved a test accuracy of 0.847 (95% confidence interval [CI], 0.745-0.914), sensitivity of 0.932 (95% CI, 0.833-0.978), and specificity of 0.462 (95% CI, 0.232-0.709). In comparison, the average of 4 radiologists achieved a test accuracy of 0.722 (95% CI, 0.609-0.813), sensitivity of 0.852 (95% CI, 0.737-0.923), and specificity of 0.135 (95% CI, 0.021-0.415).
CONCLUSIONS: This study demonstrates that deep learning based on a ResNet model achieves good accuracy in predicting outcome of uterine fibroid embolization. If further validated, the model may help clinicians better identify patients who can most benefit from this therapy and aid clinical decision making.

Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intelligence (AI) system for differentiating COVID-19 and other pneumonia at chest CT and assessing radiologist performance without and with AI assistance. Materials and Methods A total of 521 patients with positive reverse transcription polymerase chain reaction results for COVID-19 and abnormal chest CT findings were retrospectively identified from 10 hospitals from January 2020 to April 2020. A total of 665 patients with non-COVID-19 pneumonia and definite evidence of pneumonia at chest CT were retrospectively selected from three hospitals between 2017 and 2019. To classify COVID-19 versus other pneumonia for each patient, abnormal CT slices were input into the EfficientNet B4 deep neural network architecture after lung segmentation, followed by a two-layer fully connected neural network to pool slices together. The final cohort of 1186 patients (132 583 CT slices) was divided into training, validation, and test sets in a 7:2:1 and equal ratio. Independent testing was performed by evaluating model performance in separate hospitals. Studies were blindly reviewed by six radiologists without and then with AI assistance. Results The final model achieved a test accuracy of 96% (95% confidence interval [CI]: 90%, 98%), a sensitivity of 95% (95% CI: 83%, 100%), and a specificity of 96% (95% CI: 88%, 99%) with area under the receiver operating characteristic curve of 0.95 and area under the precision-recall curve of 0.90. On independent testing, this model achieved an accuracy of 87% (95% CI: 82%, 90%), a sensitivity of 89% (95% CI: 81%, 94%), and a specificity of 86% (95% CI: 80%, 90%) with area under the receiver operating characteristic curve of 0.90 and area under the precision-recall curve of 0.87. Assisted by the probabilities of the model, the radiologists achieved a higher average test accuracy (90% vs 85%, Δ = 5, P < .001), sensitivity (88% vs 79%, Δ = 9, P < .001), and specificity (91% vs 88%, Δ = 3, P = .001). Conclusion Artificial intelligence assistance improved radiologists\' performance in distinguishing coronavirus disease 2019 pneumonia from non-coronavirus disease 2019 pneumonia at chest CT. © RSNA, 2020 Online supplemental material is available for this article.

Inflammatory myofibroblastic tumors arising in infants are rare, poorly investigated and mostly reported as isolated cases or as a part of larger series thus, their clinicopathological and molecular features are essentially unknown. Archival files from two large pediatric institutions and a tumor registry were queried for pediatric inflammatory myofibroblastic tumors. Available material from patients ≤12 months of age was reviewed. Additional immunostains (ALK-1, D240, WT1) and ALK-FISH studies were performed as needed. Targeted anchored multiplex PCR with next-generation sequencing was done in all cases. A total of 12 of 131 infantile cases (mean 5.5 months) were identified (M:F of 2:1). Anatomic locations included intestinal/mesenteric (n = 6), head/neck (n = 3), and viscera (n = 3). Half of tumors showed a hypocellular myxoid pattern, perivascular condensation, and prominent vasculature with vague glomeruloid structures present in four of them. The remaining cases exhibited a more cellular pattern with minimal myxoid component. ALK-1 immunohistochemistry was positive in most cases (11/12) with cytoplasmic-diffuse (n = 6), cytoplasmic-granular (n = 2), and dot-like (n = 3) staining patterns. ALK fusion partners identified in five cases included EML4, TPM4, RANBP2, and a novel KLC1. Three inflammatory myofibroblastic tumors showed fusions with other kinases including TFG-ROS1 and novel FN1-ROS1 and RBPMS-NTRK3 rearrangements. Favorable outcome was documented in most cases (10/11) with available follow-up (median 17 months) while three patients were successfully treated with crizotinib. In summary, infantile inflammatory myofibroblastic tumors are rare and can exhibit paucicellular, extensively myxoid/vascular morphology with peculiar immunophenotype mimicking other mesenchymal or vascular lesions. All tumors harbored kinase fusions involving ALK, ROS1, and NTRK3 including three novel fusion partners (KLC1, FN1, and RBPMS, respectively). A favorable response to crizotinib seen in three cases supports its potential use in infants as seen in older patients. Awareness of these unusual morphologic, immunophenotypic, and molecular features is critical for appropriate diagnosis and optimized targeted therapy.

Effective treatments for relapsed Ph+ALL with T315I mutation are few; CD19 CAR T-cell therapy are a potential therapy for this condition. We reported 7 patients with relapsed Ph+ALL with T315I mutation, who were treated pre- or post-allo-HSCT with CD19-specific CAR T-cells. Of the 7 cases, 6 were in CR or CRp within 1 month after the first infusion of CAR T-cells. MRD revealed a rapid decline in 6 patients. BCR/ABL fusion transcripts were negative in 4/5 cases (not performed in 2). Three patients maintained remission without evidence of MRD by QPCR until the final follow-up, of which 2 received anti-CD19 CAR T-cells and ponatinib at the same time. Our study confirmed the efficacy of anti-CD19 CAR T-cell therapy in treatment of relapsed Ph+ALL with T315I mutation pre- or post-allo-HSCT and the concurrent applicability of this therapy with ponatinib.

Ventricular tachycardia (VT) is frequently encountered in patients with repaired and unrepaired congenital heart disease (CHD), causing significant morbidity and sudden cardiac death. Data regarding underlying VT mechanisms and optimal ablation strategies in these patients remain limited.
To describe the electrophysiologic mechanisms, ablation strategies, and long-term outcomes in patients with CHD undergoing VT ablation.
Forty-eight patients (mean age 41.3 ± 13.3 years, 77.1% male) with CHD underwent a total of 57 VT ablation procedures at two centers from 2000 to 2017. Electrophysiologic and follow-up data were analyzed.
Of the 77 different VTs induced at initial or repeat ablation, the underlying mechanism in 62 (81.0%) was due to scar-related re-entry; the remaining included four His-Purkinje system-related macrore-entry VTs and focal VTs mainly originating from the outflow tract region (8 of 11, 72.7%). VT-free survival after a single procedure was 72.9% (35 of 48) at a median follow-up of 53 months. VT-free survival after multiple procedures was 85.4% (41 of 48) at a median follow-up of 52 months. There were no major complications. Three patients died during the follow-up period from nonarrhythmic causes, including heart failure and cardiac surgery complication.
While scar-related re-entry is the most common VT mechanism in patients with CHD, importantly, nonscar-related VT may also be present. In experienced tertiary care centers, ablation of both scar-related and nonscar-related VT in patients with CHD is safe, feasible, and effective over long-term follow-up.

BACKGROUND: Store-and-forward (SAF) teledermatology (TD) has the potential to increase access to timely, high-quality care for underserved populations. However, the cost-effectiveness of TD for underserved populations is uncertain.
OBJECTIVE: This study evaluates the potential cost savings associated with an SAF TD program implemented for an underserved population in the city health clinics of urban Philadelphia.
METHODS: We performed a retrospective analysis of SAF TD consultations for 700 outpatients managed in 12 Philadelphia primary care clinics. Primary care providers were asked to specify a treatment plan, as well as the type of care for the patient, in the absence of the TD service. Analysis compared the cost of each patient case with use of the TD consult model versus with conventional care.
RESULTS: In all, 27% of in-person dermatology clinic visits (189 of 700) and 3.29% of emergency room visits (23 of 700) were avoided by using TD. Compared with conventional care, TD had a mean expected cost savings of $10.00 to $52.65 per TD consult. In sensitivity analyses, these estimated savings remained positive across a range of parameters.
CONCLUSIONS: The cost analysis relies on several assumptions regarding the cost of care, and indirect costs were not included.
CONCLUSIONS: TD can be a cost-saving model while increasing access to dermatologic care.

Heritability is well documented for psychiatric disorders and cognitive abilities which are, however, complex, involving both genetic and environmental factors. Hence, it remains challenging to discover which and how genetic variations contribute to such complex traits. In this article, they propose to use mediation analysis to bridge this gap, where neuroimaging phenotypes were utilized as intermediate variables. The Philadelphia Neurodevelopmental Cohort was investigated using genome-wide association studies (GWAS) and mediation analyses. Specifically, 951 participants were included with age ranging from 8 to 21 years. Two hundred and four neuroimaging measures were extracted from structural magnetic resonance imaging scans. GWAS were conducted for each measure to evaluate the SNP-based heritability. Furthermore, mediation analyses were employed to understand the mechanisms in which genetic variants have influence on pathological behaviors implicitly through neuroimaging phenotypes, and identified SNPs that would not be detected otherwise. Our analyses found that rs10494561, located in the intron region within NMNAT2, was associated with the severity of the prodromal symptoms of psychosis implicitly, mediated through the volume of the left hemisphere of the superior frontal region ( P=2.38×10-8). The gene NMNAT2 is known to be associated with brainstem degeneration, and produce cytoplasmic enzyme which is mainly expressed in the brain. Another SNP rs2285351 was found in the intron region of gene IFT122 which may be potentially associated with human spatial orientation ability through the area of the left hemisphere of the isthmuscingulate region ( P=3.70×10-8). Hum Brain Mapp 38:4088-4097, 2017. © 2017 Wiley Periodicals, Inc.

Cardiovascular magnetic resonance (CMR) imaging is often considered the reference method to assess cardiac tumors. However, little data exists concerning the effectiveness of CMR for the accurate diagnosis of cardiac masses. We sought to understand the diagnostic value of CMR for evaluation of suspected cardiac mass. A total of 249 consecutive CMR cases performed at a single center from January 2005 to June 2013 for evaluation of masses found on echocardiography or computed tomography (CT) were included. All the clinical data and imaging features of these patients were retrospectively reviewed and medical records were verified for follow up care. More than half of the patients referred for evaluation of masses found at echocardiography or CT were found to have no evidence of mass by CMR. CMR correctly differentiated between thrombus and myxoma in 88.4 % cases. Malignant masses were accurately diagnosed on CMR. However, CMR missed or misdiagnosed a few cases of benign masses. Diagnosing cardiac masses remains an important use for imaging, despite technical difficulties with current imaging modalities. CMR can play a key role in confirming presence or absence of a mass. Additionally, in the presence of a mass, CMR can provide accurate differentiation of pseudomasses, benign and malignant masses. However, the limitations of CMR must be recognized.

BACKGROUND: The incidence of perioperative infection after segmental tumor endoprosthetic replacement in previous reports varies from a high of 7.4% to a low of 2.6%. Appropriate antibiotic use for this group is unknown and controversial, whereas the relationship of antibiotic use and perioperative infection is unclear.
OBJECTIVE: We determined the incidence of perioperative infection in patients with osteosarcoma treated with segmental prosthetic replacement using a standard perioperative antibiotic regimen and the incidence of late infections and wound complications.
METHODS: We retrospectively reviewed the records of 53 patients with osteosarcoma undergoing segmental prosthetic replacements from 1993 to 2008. There were 30 males and 23 females ranging from 10 to 78 years of age. All patients were given intraoperative antibiotics (intravenous cefazolin), continued for 3 days postoperatively and then given orally for 5 days. Patients who were allergic to penicillin or cefazolin were given vancomycin followed by clindamycin. A perioperative infection was defined as a deep infection within 2 months after prosthetic reconstruction. The minimum followup was 1 year (range, 1-15 years).
RESULTS: We identified one confirmed perioperative prosthetic infection (1/53; 1.9%) (Enterobacter cloacae and methicillin-resistant Staphylococcus) in a 78-year-old woman after proximal tibial replacement, gastrocnemius flap, and skin graft. Her infection was controlled with débridement, drainage, and intravenous antibiotics. Three patients had late infections, two of which were culture negative. Four patients had wound complications that required further surgery.
CONCLUSIONS: The antibiotic regimen we used is longer than that recommended for patients having routine total joint arthroplasty. Its appropriateness will require comparison with alternate regimens, including those of shorter duration.
METHODS: Level IV, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.