A gene expression analysis of hypoxic rat retina was undertaken to gain a deeper understanding of the possible molecular mechanisms that underlie hypoxia-induced retinal pathologies and identify possible therapeutic targets.Rats were made severely hypoxic (6%-7% O(2)) for 3 h. Some rats were sacrificed at this time, and others were allowed to recover for 24 h under normoxic conditions. A focused oligonucleotide microarray of 1,178 genes, qRT-PCR of selected transcripts, and western analysis of hypoxia inducible factor-1alpha (HIF-1alpha) were used to compare retinas from the hypoxic and recovery groups to control animals that were not made hypoxic. SAM analysis was used to identify statistically significant changes in microarray data, and the bioinformatics programs GoMiner, Gene Set Enrichment Analysis (GSEA), and HiMAP were used to identify significant ontological categories and analyze the N-methyl-D-aspartate (NMDA) receptor interactome.HIF-1alpha protein, but not mRNA, was elevated up to 15-fold during hypoxia, beginning at 0.5 h, the shortest duration examined. Of the total of 1,178 genes examined by microarray, 119 were significantly upregulated following hypoxia. Of these, 86 were still significantly upregulated following recovery. However, 24 genes were significantly downregulated following hypoxia, with 12 still significantly downregulated after recovery. Of the 1035 genes that did not change with hypoxia, the expression of 36 genes was significantly changed after recovery. Ontological analyses showed significant upregulation of a large number of genes in the glutamate receptor family, including 3 of the 5 NMDA subunits. qRT-PCR analysis further corroborated these findings. Genes known to directly interact specifically with the NR1 subunit of the NMDA receptor were identified using HiMAP databases. GSEA analysis revealed that these genes were not affected by either hypoxia or altered after recovery.The identification of gene expression alterations as a function of hypoxia and recovery from hypoxia is important to understand the molecular mechanisms underlying retinal dysfunction associated with a variety of diseases. Gene changes were identified in hypoxic retina that could be linked to specific networks. Retinas recovering from hypoxia also showed distinct patterns of gene expression that were different from both normoxic control retinas and hypoxic retinas, indicating that hypoxia initiates a complex pattern of gene expression. Diseases of which hypoxia is a component may exhibit the several changes found here. Several potential therapeutic targets have been identified by our approach, including modulation of NMDA receptor expression and signaling, which until now have only been shown to play a role in responding to ischemia.
Introduction: Patients (pts) with a history of syncope are at high risk for sudden death with a reported 1-year mortality rate of 30%. Triaging relevant arrhythmias (ars) in a timely manner in this population is critical to allow for potential life-saving interventions. For example screening atrial fibrillation (AF) studies of pts with no known AF, reported an AF detection of 4.5% to 5.3%. It is unknown if these findings extend to a syncope population. A recent syncope study reported most significant ars occurred outside the typical window of a hospital stay. Therefore, this study aims to analyze a proprietary Zio AT database containing arrhythmia findings of pts monitored for the diagnosis of syncope. Methods: Data retrospectively analyzed 10,643 pts from US institutions with a syncope indication for monitoring. Pts with recordings between July 2017 to December 2021 were analyzed. All ars transmitted via cellular gateway during the wear period and full ECG download at end of wear were analyzed with a validated proprietary AI algorithm, then followed by a certified cardiographic technician review. Ars were defined as: AF, ≥30 seconds at any heart rate; SVT, ≥90 bpm for ≥4 S beats; Pause, ≥3 second; AV Block, any 3rd or 2nd degree AV Block (Mobitz I or II); VT, ≥100 bpm for ≥4 V beats or PVT, TdP, VF. Detected ars were characterized by duration, episode counts, rates, and/or burden (where applicable). Results: Of the 10,643 pts studied (49% female, mean age 65.4 years, mean wear 11.9 ± 3.6 days), 8,442 (79%) had at least 1 arrhythmia detected, with 3,107 (29%) having 2 or more arrhythmia types. Most common ars detected in this patient population were SVT (69%; 7365/10643), VT (26%; 2716/10643), and AF (9.5%; 1015/10643). AV Blocks (3.6%; 382/10643) and Pauses (6.2%; 662/10643) were not uncommon. Surprisingly, the most common arrhythmia to trigger a notification alert was AF/AFL (8.5%). Average time until first AF detection was 1.4 ± 2.8 days for all AF subjects and 2.8 ± 3.5 days for paroxysmal AF subjects. Conclusions: In this large retrospective study, ambulatory ECG monitoring with ZIO AT in syncope indicated pts revealed an unexpectedly high incidence of AF and SVT. Further analysis of this group may help clinicians focus a heightened awareness of atrial ars in this population.
Introduction: Prior to COVID-19, ECG patches (ECGp) were applied almost exclusively in-clinic (CA) by technicians which required an office visit and fee. Since the pandemic, direct-to-patient, self-applied patch use (SA) has substantially increased, though the metrics surrounding SA are unknown. This study compares monitoring completion rates and data quality between CA and SA ECGp prior to and during COVID-19. Hypothesis: CA and SA ECGp have similar data quality and monitoring completion metrics. Methods: We performed a retrospective cohort analysis of patients prescribed an iRhythm Zio XT patch at Northwestern Memorial Hospital during the “pre-COVID” (3/1/2019-3/1/2020) and “COVID” (4/1/2020-4/1/2021) timeframes. Differences in ECGp with data available, actual vs prescribed wear time, and analyzable data between groups were assessed. ECGp without data was defined as devices which were not returned or not activated. Results: The cohort included 29,118 ECGp prescriptions; 13,180 pre-COVID (45%). The cohort was 56% female with mean age of 59.3 + 17.7 years. Palpitations (29%) and atrial fibrillation (19%) were the most common indications. In the pre-COVID cohort, there were no (0%) SA ECGp and data were available for 12,932 CA patches. In the COVID cohort, 34% of ECGp were SA; data were available for 10,231 CA ECGp and 4,902 SA ECGp. Average delay between prescription and SA ECGp activation was 8.1 ± 12.2 days. Comparisons between percent analyzable data, wear times, and ECGp with data available are shown in figure 1. Conclusions: COVID-19 resulted in a rapid adoption of SA ECGp use. Compared to CA, SA was associated with an inherent delay in ECGp application and a higher proportion of ECGp without data. However, there was no difference in actual vs prescribed wear time and a small but statistically significant decrease in percent analyzable data. These differences must be balanced with the additional cost and need for in-person visit for CA vs SA.
Introduction: Atrial fibrillation (AF) is an established risk factor for stroke, hospitalization and mortality. Whether AF differs by race has not been well characterized in the real world setting due to inherent challenges in linking large datasets across multiple databases. Methods: Extended ambulatory electrocardiographic (AECG) monitoring with Zio XT allows for continuous recording of cardiac rhythm data for up to 14 days in indicated patients. A preliminary dataset from the Ascension Health System electronic health records (EHR) archive on patients prescribed the Zio XT patch was retrospectively analyzed. The study population consisted of 6,293 patients treated at 34 Ascension centers in 6 states between January 2020 and April 2022. Patient EHR data were linked to proprietary device-specific rhythm reports for analyses. Results: Among 6,293 patients in whom EHR data were matched to Zio XT findings, the median (IQR) age was 63 (47, 73) years, 3,816 (60.6%) were female, and 1,038 (16.5%) were non-Caucasian. Median device wear time was 7.2 (5.0, 13.9) days. AF was detected in 749 (11.9%) patients, including 326 (5.2%) with 100% AF. Median AF burden was 37.0% (3.4%, 100%). Older white males had the highest risk of AF events, whereas younger non-white females had the lowest risk (Figure 1). Non-white subgroups demonstrated greater freedom from AF compared to whites. Conclusions: In these preliminary findings, the use of Zio XT for extended AECG monitoring in the Ascension Health System is in predominantly older patients. Patients were racially and geographically diverse, and females were well represented. More than 10% of patients had AF detected during the monitoring period. Despite small sample sizes, differences in AF detection by subgroups demonstrate that a tailored approach to managing AF remains a critically important research question. Linkage of patient EHR data with device-specific outcomes can be a useful approach to address this important unmet need.
