Citations

Abstract Background Postoperative nausea and vomiting (PONV) is frequent after bariatric surgery. We hypothesized that when compared with a volatile-based technique incorporating propofol infusions, the need for rescue antiemetics would be reduced by the use of two strategies: 1) the addition of dexmedetomidine infusions, and 2) the avoidance of opioid and volatile anesthetics, and that this reduction would be observed in the PACU following PACU discharge. Methods In this retrospective observational study we included patients undergoing bariatric surgery from 2018–2022 who received one of three anesthetic strategies: 1) volatile anesthetic and propofol infusion (VOL + PROP), 2) VOL + PROP with the addition of dexmedetomidine (DEX), or 3) opioid-sparing total intravenous anesthesia (PROP + DEX). Inverse probability of treatment weighting analysis determined the association between the need for rescue-antiemetics in the PACU following PACU discharge. Results 332 patients received VOL + PROP, 354 VOL + PROP + DEX, and 166 PROP + DEX. PROP + DEX received fewer rescue antiemetics in PACU compared to VOL + PROP (11% vs 24%, P = 0.002), and VOL + PROP + DEX fewer compared to VOL + PROP (16% vs 24%, P = 0.023). This differential effect was limited to PACU stay; antiemetic use increased across all groups following PACU discharge until midnight (ranging from 38–46% across groups, P = 0.71) and through the first postoperative day (ranging from 47–57%, P = 0.20). Conclusions The benefit associated with two PONV prevention strategies, the addition of dexmedetomidine infusion or avoidance of opioid and volatile anesthetics, did not persist after PACU discharge. These findings highlight the challenge of PONV on postoperative wards, and the need for a novel multimodal team approach to mitigate this complication.

Portal hypertension (PHTN) is a severe complication of liver cirrhosis and is associated with intrahepatic sinusoidal remodeling induced by sinusoidal resistance and angiogenesis. Collagen type IV (COL4), a major component of basement membrane, forms in liver sinusoids upon chronic liver injury. However, the role, cellular source, and expression regulation of COL4 in liver diseases are unknown. Here, we examined how COL4 is produced and how it regulates sinusoidal remodeling in fibrosis and PHTN. Human cirrhotic liver sample RNA sequencing showed increased COL4 expression, which was further verified via immunofluorescence staining. Single-cell RNA sequencing identified liver sinusoidal endothelial cells (LSECs) as the predominant source of COL4 upregulation in mouse fibrotic liver. In addition, COL4 was upregulated in a TNF-α/NF-κB–dependent manner through an epigenetic mechanism in LSECs in vitro. Indeed, by utilizing a CRISPRi-dCas9-KRAB epigenome-editing approach, epigenetic repression of the enhancer-promoter interaction showed silencing of COL4 gene expression. LSEC-specific COL4 gene mutation or repression in vivo abrogated sinusoidal resistance and angiogenesis, which thereby alleviated sinusoidal remodeling and PHTN. Our findings reveal that LSECs promote sinusoidal remodeling and PHTN during liver fibrosis through COL4 deposition.

Abstract Context Single-tier newborn screening (NBS) for congenital adrenal hyperplasia (CAH) using 17-hydroxyprogesterone (17OHP) measured by fluoroimmunoassay (FIA) in samples collected at 24 to 48 hours produces a high false-positive rate (FPR). Second-tier steroid testing can reduce the FPR and has been widely implemented. Objective We investigated the accuracy of an alternative multitier CAH NBS protocol that incorporates molecular testing of the CYP21A2 gene and reduces the first-tier 17OHP cutoff to minimize missed cases. Methods We create a Minnesota-specific CYP21A2 pathogenic variants panel; developed a rapid, high-throughput multiplex, allele-specific-primer-extension assay; and performed a 1-year retrospective analysis of Minnesota NBS results comparing metrics between a conventional steroid-based 2-tier protocol and a molecular-based multitier NBS protocol, applied post hoc. Results CYP21A2 gene sequencing of 103 Minnesota families resulted in a Minnesota-specific panel of 21 pathogenic variants. The Centers for Disease Control and Prevention created a molecular assay with 100% accuracy and reproducibility. Two-tier steroid-based screening of 68 659 live births during 2015 resulted in 2 false negatives (FNs), 91 FPs, and 1 true positive (TP). A 3-tier protocol with a lower first-tier steroid cutoff, second-tier 21-variant CYP21A2 panel, and third-tier CYP21A2 sequencing would have resulted in 0 FNs, 52 FPs, and 3 TPs. Conclusion Incorporation of molecular testing could improve the accuracy of CAH NBS, although some distinct challenges of molecular testing may need to be considered before implementation by NBS programs.

Abstract Lung diseases, including lung cancer, are rising causes of global mortality. Despite novel imaging technologies and the development of biomarker assays, the detection of lung cancer remains a significant challenge. However, the lung communicates directly with the external environment and releases aerosolized droplets during normal tidal respiration, which can be collected, stored and analzsed as exhaled breath condensate (EBC). A few studies have suggested that EBC contains extracellular vesicles (EVs) whose microRNA (miRNA) cargos may be useful for evaluating different lung conditions, but the cellular origin of these EVs remains unknown. In this study, we used nanoparticle tracking, transmission electron microscopy, Western blot analyses and super resolution nanoimaging (ONi) to detect and validate the identity of exhaled EVs (exh‐EVs). Using our customizable antibody‐purification assay, EV‐CATCHER, we initially determined that exh‐EVs can be selectively enriched from EBC using antibodies against three tetraspanins (CD9, CD63 and CD81). Using ONi we also revealed that some exh‐EVs harbour lung‐specific proteins expressed in bronchiolar Clara cells (Clara Cell Secretory Protein [CCSP]) and Alveolar Type II cells (Surfactant protein C [SFTPC]). When conducting miRNA next generation sequencing (NGS) of airway samples collected at five different anatomic levels (i.e., mouth rinse, mouth wash, bronchial brush, bronchoalveolar lavage [BAL] and EBC) from 18 subjects, we determined that miRNA profiles of exh‐EVs clustered closely to those of BAL EVs but not to those of other airway samples. When comparing the miRNA profiles of EVs purified from matched BAL and EBC samples with our three tetraspanins EV‐CATCHER assay, we captured significant miRNA expression differences associated with smoking, asthma and lung tumor status of our subjects, which were also reproducibly detected in EVs selectively purified with our anti‐CCSP/SFTPC EV‐CATCHER assay from the same samples, but that confirmed their lung tissue origin. Our findings underscore that enriching exh‐EV subpopulations from EBC allows non‐invasive sampling of EVs produced by lung tissues.

Background: Myocardial reperfusion following prolonged ischemia may paradoxically cause additional injury, including edema and microvascular damage. These structural alterations augment tissue echogenicity measurable by integrated backscatter (IB). We sought to characterize alterations of myocardial IB in an ischemic and then reperfused region of the rat heart. Methods: Myocardial IB in 12 adult male Sprague-Dawley rats was studied at baseline, 60 minutes after left anterior descending coronary artery occlusion, and chronologically after coronary reopening. Short-axis scans of the mid left ventricle were acquired at a frequency of 8 MHz. Mean±SD values of IB were measured in the region of interest at baseline, ischemia, and reperfusion, and assessed by a paired t-test. Results: See figure and table. IB did not significantly change between baseline and ischemia. However, within 1 minute of reperfusion, IB significantly increased, as compared to both baseline and ischemia, and continued to increase until 10 minutes after reperfusion, when a plateau was reached. Conclusions: Myocardial reperfusion following acute prolonged ischemia in a rat heart significantly augments tissue echogenicity. A continuing increase of IB within minutes of the reperfusion onset and the subsequent plateau of elevated IB values suggest progression and completion, respectively, of reperfusion injury, detectable by a high-frequency transducer.

Cardiac amyloidosis (CA) is an underdiagnosed form of infiltrative cardiomyopathy caused by abnormal amyloid fibrils deposited extracellularly in the myocardium and cardiac structures. There can be high variability in its clinical manifestations, and diagnosing CA requires expertise and often thorough evaluation; as such, the diagnosis of CA can be challenging and is often delayed. The application of artificial intelligence (AI) to different diagnostic modalities is rapidly expanding and transforming cardiovascular medicine. Advanced AI methods such as deep-learning convolutional neural networks (CNNs) may enhance the diagnostic process for CA by identifying patients at higher risk and potentially expediting the diagnosis of CA. In this review, we summarize the current state of AI applications to different diagnostic modalities used for the evaluation of CA, including their diagnostic and prognostic potential, and current challenges and limitations.

Background: The implications of delaying surgical intervention for patients with adolescent idiopathic scoliosis (AIS) wishing to undergo vertebral body tethering (VBT) have not yet been explored. It is important to understand how these delays can impact surgical planning and patient outcomes. Methods: This was a retrospective review that analyzed all AIS patients treated between 2015 and 2021 at a single tertiary center. Time to surgery from initial surgical consultation and ultimate surgical plan were assessed. Patient characteristics, potential risk factors associated with increased curve progression, and reasons for delay were also analyzed. Results: 174 patients were evaluated and 95 were scheduled for VBT. Four patients later required a change to posterior spinal fusion (PSF) due to excessive curve progression. Patients requiring PSF were shown to have significantly longer delays than those who received VBT. Additionally, longer delays, younger age, greater curve progression, and lower skeletal maturity were correlated with significant curve progression (≥5 degrees). Conclusions: Surgical delays for AIS patients awaiting VBT may lead to significant curve progression and necessitate more invasive procedures. Patients with longer delays experienced an increased risk of needing PSF instead of VBT. Of those requiring PSF, the majority were due to insurance denials. Optimizing surgical timing and shared decision-making among patients, families, and healthcare providers are essential for achieving the best outcomes.

Purpose To develop a deep learning model for the detection of Segond fractures on anteroposterior (AP) knee radiographs and to compare model performance to that of trained human experts. Methods AP knee radiographs were retrieved from the Hospital for Special Surgery ACL Registry, which enrolled patients between 2009 and 2013. All images corresponded to patients who underwent anterior cruciate ligament reconstruction by 1 of 23 surgeons included in the registry data. Images were categorized into 1 of 2 classes based on radiographic evidence of a Segond fracture and manually annotated. Seventy percent of the images were used to populate the training set, while 20% and 10% were reserved for the validation and test sets, respectively. Images from the test set were used to compare model performance to that of expert human observers, including an orthopaedic surgery sports medicine fellow and a fellowship‐trained orthopaedic sports medicine surgeon with over 10 years of experience. Results A total of 324 AP knee radiographs were retrieved, of which 34 (10.4%) images demonstrated evidence of a Segond fracture. The overall mean average precision (mAP) was 0.985, and this was maintained on the Segond fracture class (mAP = 0.978, precision = 0.844, recall = 1). The model demonstrated 100% accuracy with perfect sensitivity and specificity when applied to the independent testing set and the ability to meet or exceed human sensitivity and specificity in all cases. Compared to an orthopaedic surgery sports medicine fellow, the model required 0.3% of the total time needed to evaluate and classify images in the independent test set. Conclusions A deep learning model was developed and internally validated for Segond fracture detection on AP radiographs and demonstrated perfect accuracy, sensitivity, and specificity on a small test set of radiographs with and without Segond fractures. The model demonstrated superior performance compared with expert human observers. Clinical Relevance Deep learning can be used for automated Segond fracture identification on radiographs, leading to improved diagnosis of easily missed concomitant injuries, including lateral meniscus tears. Automated identification of Segond fractures can also enable large‐scale studies on the incidence and clinical significance of these fractures, which may lead to improved management and outcomes for patients with knee injuries.