Citations

Abstract Background We aimed to determine if pre-existing immunocompromising conditions (ICCs) were associated with the presentation or outcome of patients with acute coronavirus disease 2019 (COVID-19) admitted for pediatric intensive care. Methods Fifty-five hospitals in 30 US states reported cases through the Overcoming COVID-19 public health surveillance registry. Patients <21 years admitted 12 March 2020–30 December 2021 to the pediatric intensive care unit (PICU) or high-acuity unit for acute COVID-19 were included. Results Of 1274 patients, 105 (8.2%) had an ICC, including 33 (31.4%) hematologic malignancies, 24 (22.9%) primary immunodeficiencies and disorders of hematopoietic cells, 19 (18.1%) nonmalignant organ failure with solid-organ transplantation, 16 (15.2%) solid tumors, and 13 (12.4%) autoimmune disorders. Patients with ICCs were older, had more underlying renal conditions, and had lower white blood cell and platelet counts than those without ICCs, but had similar clinical disease severity upon admission. In-hospital mortality from COVID-19 was higher (11.4% vs 4.6%, P = .005) and hospitalization was longer (P = .01) in patients with ICCs. New major morbidities upon discharge were not different between those with and without ICC (10.5% vs 13.9%, P = .40). In patients with ICCs, bacterial coinfection was more common in those with life-threatening COVID-19. Conclusions In this national case series of patients <21 years of age with acute COVID-19 admitted for intensive care, existence of a prior ICCs were associated with worse clinical outcomes. Reassuringly, most patients with ICCs hospitalized in the PICU for severe acute COVID-19 survived and were discharged home without new severe morbidities.

Cardiogenic shock continues to carry a high mortality rate despite contemporary care, with no breakthrough therapies shown to improve survival over the past few decades. It is a time‐sensitive condition that commonly results in cardiovascular complications and multisystem organ failure, necessitating multidisciplinary expertise. Managing patients with cardiogenic shock remains challenging even in well‐resourced settings, and an important subgroup of patients may require cardiac replacement therapy. As a result, the idea of leveraging the collective cognitive and procedural proficiencies of multiple providers in a collaborative, team‐based approach to care (the “shock team”) has been advocated by professional societies and implemented at select high‐volume clinical centers. A slowly maturing evidence base has suggested that cardiogenic shock teams may improve patient outcomes. Although several registries exist that are beginning to inform care, particularly around therapeutic strategies of pharmacologic and mechanical circulatory support, none of these are currently focused on the shock team approach, multispecialty partnership, education, or process improvement. We propose the creation of a Cardiogenic Shock Team Collaborative—akin to the successful Pulmonary Embolism Response Team Consortium—with a goal to promote sharing of care protocols, education of stakeholders, and discovery of how process and performance may influence patient outcomes, quality, resource consumption, and costs of care.

This cross-sectional study assesses list prices, cash prices, and negotiated rates for emergency department services.

Abstract Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive malignancy with poor outcomes. To investigate novel therapeutic strategies, we characterized three new metastatic prostate cancer patient derived-tumor xenograft (PDTX) models and developed 3D spheroids from each to investigate molecular targeted therapy combinations including CDK4/6 inhibitors (CDK4/6i) with AKT inhibitors (ATKi). Metastatic prostate cancer tissue was collected and three PDTX models were established and characterized using whole-exome sequencing. PDTX 3D spheroids were developed from these three PDTXs to show resistance patterns and test novel molecular-targeted therapies. CDK4/6i's were combined with AKTi's to assess synergistic antitumor response to prove our hypothesis that blockade of AKT overcomes drug resistance to CDK4/6i. This combination was evaluated in PDTX three-dimensional (3D) spheroids and in vivo experiments with responses measured by tumor volumes, PSA, and Ga-68 PSMA-11 PET-CT imaging. We demonstrated CDK4/6i's with AKTi's possess synergistic antitumor activity in three mCRPC PDTX models. These models have multiple unique pathogenic and deleterious genomic alterations with resistance to single-agent CDK4/6i's. Despite this, combination therapy with AKTi's was able to overcome resistance mechanisms. The IHC and Western blot analysis confirmed on target effects, whereas tumor volume, serum PSA ELISA, and radionuclide imaging demonstrated response to therapy with statistically significant SUV differences seen with Ga-68 PSMA-11 PET-CT. These preclinical data demonstrating antitumor synergy by overcoming single-agent CDK 4/6i as well as AKTi drug resistance provide the rational for a clinical trial combining a CDK4/6i with an AKTi in patients with mCRPC whose tumor expresses wild-type retinoblastoma 1.

Abstract Objectives The objective of this study was to explore the prevalence, characteristics and risk factors of COVID-19 breakthrough infections (BIs) in idiopathic inflammatory myopathies (IIMs) using data from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study. Methods A validated patient self-reporting e-survey was circulated by the COVAD study group to collect data on COVID-19 infection and vaccination in 2022. BIs were defined as COVID-19 occurring ≥14 days after two vaccine doses. We compared BI characteristics and severity among patients with IIMs, patients with other autoimmune rheumatic and non-rheumatic diseases (AIRD, nrAID), and healthy controls (HCs). Multivariable Cox regression models were used to assess the risk factors for BI, severe BI ,and hospitalizations among patients with IIMs. Results Among the 9449 included responses, BIs occurred in 1447 respondents (15.3%). The median age was 44 years [interquartile range (IQR) 21], 77.4% were female, and 182 BIs (12.9%) occurred among the 1406 patients with IIMs. Multivariable Cox regression among the data for patients with IIMs showed increasing age to be a protective factor for BIs [hazard ratio (HR) = 0.98, 95% CI = 0.97–0.99], and HCQ and SSZ use were risk factors (HR = 1.81, 95% CI = 1.24–2.64, and HR = 3.79, 95% CI = 1.69–8.42, respectively). Glucocorticoid use was a risk factor for a severe BI (HR = 3.61, 95% CI = 1.09–11.8). Non-white ethnicity (HR = 2.61, 95% CI = 1.03–6.59) was a risk factor for hospitalization. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIMs = 6.0% vs AIRDs = 1.8%, nrAIDs = 2.2% and HCs = 0.9%), intensive care unit admission (IIMs = 2.2% vs AIRDs = 0.6%, nrAIDs and HCs = 0%), advanced treatment with antiviral or monoclonal antibodies (IIMs = 34.1% vs AIRDs = 25.8%, nrAIDs = 14.6% and HCs = 12.8%) and had more hospitalization (IIMs = 7.7% vs AIRDs = 4.6%, nrAIDs = 1.1% and HCs = 1.5%). Conclusion Patients with IIMs are susceptible to severe COVID-19 BIs. Age and immunosuppressive treatments were related to the risk of BIs.

AbstractDeep learning is a subset of artificial intelligence (AI) with enormous potential to transform orthopaedic surgery. As has already become evident with the deployment of Large Language Models (LLMs) like ChatGPT (OpenAI Inc.), deep learning can rapidly enter clinical and surgical practices. As such, it is imperative that orthopaedic surgeons acquire a deeper understanding of the technical terminology, capabilities and limitations associated with deep learning models. The focus of this series thus far has been providing surgeons with an overview of the steps needed to implement a deep learning‐based pipeline, emphasizing some of the important technical details for surgeons to understand as they encounter, evaluate or lead deep learning projects. However, this series would be remiss without providing practical examples of how deep learning models have begun to be deployed and highlighting the areas where the authors feel deep learning may have the most profound potential. While computer vision applications of deep learning were the focus of Parts I and II, due to the enormous impact that natural language processing (NLP) has had in recent months, NLP‐based deep learning models are also discussed in this final part of the series. In this review, three applications that the authors believe can be impacted the most by deep learning but with which many surgeons may not be familiar are discussed: (1) registry construction, (2) diagnostic AI and (3) data privacy. Deep learning‐based registry construction will be essential for the development of more impactful clinical applications, with diagnostic AI being one of those applications likely to augment clinical decision‐making in the near future. As the applications of deep learning continue to grow, the protection of patient information will become increasingly essential; as such, applications of deep learning to enhance data privacy are likely to become more important than ever before.Level of Evidence: Level IV.

Abstract Objectives To investigate health-related quality of life in patients with idiopathic inflammatory myopathies (IIMs) compared with those with non-IIM autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs) and without autoimmune diseases (controls) using Patient-Reported Outcome Measurement Information System (PROMIS) instrument data obtained from the second COVID-19 vaccination in autoimmune disease (COVAD-2) e-survey database. Methods Demographics, diagnosis, comorbidities, disease activity, treatments and PROMIS instrument data were analysed. Primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores. Factors affecting GPH and GMH scores in IIMs were identified using multivariable regression analysis. Results We analysed responses from 1582 IIM, 4700 non-IIM AIRD and 545 nrAID patients and 3675 controls gathered through 23 May 2022. The median GPH scores were the lowest in IIM and non-IIM AIRD patients {13 [interquartile range (IQR) 10–15] IIMs vs 13 [11–15] non-IIM AIRDs vs 15 [13–17] nrAIDs vs 17 [15–18] controls, P < 0.001}. The median GMH scores in IIM patients were also significantly lower compared with those without autoimmune diseases [13 (IQR 10–15) IIMs vs 15 (13–17) controls, P < 0.001]. Inclusion body myositis, comorbidities, active disease and glucocorticoid use were the determinants of lower GPH scores, whereas overlap myositis, interstitial lung disease, depression, active disease, lower PROMIS Physical Function 10a and higher PROMIS Fatigue 4a scores were associated with lower GMH scores in IIM patients. Conclusion Both physical and mental health are significantly impaired in IIM patients, particularly in those with comorbidities and increased fatigue, emphasizing the importance of patient-reported experiences and optimized multidisciplinary care to enhance well-being in people with IIMs.

Background: Based in part on the results of randomized controlled trials (RCTs) that suggest a beneficial effect over alternative treatment options, the use of platelet-rich plasma (PRP) for the management of knee osteoarthritis (OA) is widespread and increasing. However, the extent to which these studies are vulnerable to slight variations in the outcomes of patients remains unknown. Purpose: To evaluate the statistical fragility of conclusions from RCTs that reported outcomes of patients with knee OA who were treated with PRP versus alternative nonoperative management strategies. Study Design: Systematic review and meta-analysis; Level of evidence, 2. Methods: All RCTs comparing PRP with alternative nonoperative treatment options for knee OA were identified. The fragility index (FI) and reverse FI were applied to assess the robustness of conclusions regarding the efficacy of PRP for knee OA. Meta-analyses were performed to determine the minimum number of patients from ≥1 trials included in the meta-analysis for which a modification on the event status would change the statistical significance of the pooled treatment effect. Results: In total, this analysis included outcomes from 1993 patients with a mean ± SD age of 58.0 ± 3.8 years. The mean number of events required to reverse significance of individual RCTs (FI) was 4.57 ± 5.85. Based on random-effects meta-analyses, PRP demonstrated a significantly higher rate of successful outcomes when compared with hyaluronic acid ( P = .002; odds ratio [OR], 2.19; 95% CI, 1.33-3.62), as well as higher rates of patient-reported symptom relief ( P = .019; OR, 1.55; 95% CI, 1.07-2.24), not requiring a reintervention after the initial injection treatment ( P = .002; OR, 2.17; 95% CI, 1.33-3.53), and achieving the minimal clinically important difference (MCID) for pain improvement ( P = .007; OR, 6.19; 95% CI, 1.63-23.42) when compared with all alternative nonoperative treatments. Overall, the mean number of events per meta-analysis required to change the statistical significance of the pooled treatment effect was 8.67 ± 4.50. Conclusion: Conclusions drawn from individual RCTs evaluating PRP for knee OA demonstrated slight robustness. On meta-analysis, PRP demonstrated a significant advantage over hyaluronic acid as well as improved symptom relief, lower rates of reintervention, and more frequent achievement of the MCID for pain improvement when compared with alternative nonoperative treatment options. Statistically significant pooled treatment effects evaluating PRP for knee OA are more robust than approximately half of all comparable meta-analyses in medicine and health care. Future RCTs and meta-analyses should consider reporting FIs and fragility quotients to facilitate interpretation of results in their proper context.

Single-cell analyses of viral infections reveal heterogeneity that is not detected by traditional population-level studies. This study applies drop-based microfluidics to investigate the dynamics of herpes simplex virus type 1 (HSV-1) infection of neurons at the single-cell level. We used micrometer-scale Matrigel beads, termed microgels, to culture individual murine superior cervical ganglia (SCG) neurons or epithelial cells. Microgel-cultured cells are encapsulated in individual media-in-oil droplets with a dual–fluorescent reporter HSV-1, enabling real-time observation of viral gene expression and replication. Infection within drops revealed that the kinetics of initial viral gene expression and replication were dependent on the inoculating dose. Notably, increasing inoculating doses led to earlier onset of viral gene expression and more frequent productive viral replication. These observations provide crucial insights into the complexity of HSV-1 infection in neurons and emphasize the importance of studying single-cell outcomes of viral infection. These techniques for cell culture and infection in drops provide a foundation for future virology and neurobiology investigations.

AbstractBackgroundAutosomal dominant polycystic kidney disease (ADPKD) is the most prevalent monogenic renal disease progressing to end‐stage renal disease. There is a pressing need for the identification of early ADPKD biomarkers to enable timely intervention and the development of effective therapeutic approaches. Here, we profiled human urinary extracellular vesicles small RNAs by small RNA sequencing in patients with ADPKD and compared their differential expression considering healthy control individuals to identify dysregulated small RNAs and analyze downstream interaction to gain insight about molecular pathophysiology.MethodsThis is a cross‐sectional study where urine samples were collected from a total of 23 PKD1‐ADPKD patients and 28 healthy individuals. Urinary extracellular vesicles were purified, and small RNA was isolated and sequenced. Differentially expressed Small RNA were identified and functional enrichment analysis of the critical miRNAs was performed to identify driver genes and affected pathways.ResultsmiR‐320b, miR‐320c, miR‐146a‐5p, miR‐199b‐3p, miR‐671‐5p, miR‐1246, miR‐8485, miR‐3656, has_piR_020497, has_piR_020496 and has_piR_016271 were significantly upregulated in ADPKD patient urine extracellular vesicles and miRNA‐29c was significantly downregulated. Five ‘driver’ target genes (FBRS, EDC3, FMNL3, CTNNBIP1 and KMT2A) were identified.ConclusionsThe findings of the present study make significant contributions to the understanding of ADPKD pathogenesis and to the identification of novel biomarkers and potential drug targets aimed at slowing disease progression in ADPKD.