Carter, Rickey E

The Omicron variant of SARS-CoV-2 is associated with milder symptoms and lower hospitalization and mortality rates than Delta variants, although the impact of Omicron on immunocompromised patients, especially solid organ transplant (SOT) recipients, is still unclear. This study compares the hospitalization rate and outcomes between immunocompromised, immunocompetent, and SOT patients during the Delta and Omicron periods. We included adult patients who tested positive for SARS-CoV-2 on PCR or nasopharyngeal antigen test between 26 June 2021 to 8 September 2022, at our institution. A total of 12,401 COVID-19 patients were included, of which 11,055 were immunocompetent, and 1346 were immunocompromised (375 SOT recipients). Throughout the Delta and Omicron outbreaks, immunocompromised patients exhibited higher comorbidities and 30-day hospitalizations, but rates of mechanical ventilation and ICU-level care were like immunocompetent patients. During the Omicron wave, immunocompromised patients had higher unadjusted relative risk estimates (RR = 2.37, 95% CI 1.96–2.87, p < 0.05) than Delta (RR = 1.58, 95% CI 1.24–2.01, p < 0.05), with higher adjusted relative risk for hospitalization in Omicron (RR = 1.50, 95% CI 1.10–2.03, p = 0.01). Analyses show increased hospitalization risk in immunocompromised during the Omicron wave compared to the Delta wave, with no significant difference in hospitalization outcomes. The relative risk of hospitalization for SOT patients was higher in both waves.

Background Patients with atrial fibrillation (AF) often complain of dyspnea, raising the question that symptoms could be related to unrecognized heart failure (HF) with preserved ejection fraction (HFpEF). Methods We used the HFpEF‐age, body mass index and history of AF algorithm to estimate the probability of undiagnosed HFpEF in CABANA (Catheter Ablation vs. Antiarrhythmic Drug Therapy), and its interaction with catheter ablation on quality of life (QOL). Probable HFpEF was defined as patient‐reported dyspnea with HFpEF‐age, body mass index and history of AF probability≥75%. Absence of dyspnea or HFpEF‐age, body mass index and history of AF probability<75% was considered to reflect patients without HFpEF. The effect of randomization to catheter ablation on QOL (Mayo Atrial Fibrillation‐Specific Symptom Inventory questionnaire and EuroQol‐5 Dimension‐3 Level score) was assessed using mixed models. Results Of participants without known HF, 70% (n=1225) had probable HFpEF and the remaining 30% (n=522) did not. Those with probable HFpEF had worse New York Heart Association class, EuroQol‐5 Dimension‐3 Level score, Mayo Atrial Fibrillation‐Specific Symptom Inventory severity, and Mayo Atrial Fibrillation‐Specific Symptom Inventory frequency scores ( P <0.0001 for all), with higher risk of HF hospitalization (hazard ratio [HR], 2.19 [95% CI, 1.11–4.31], P =0.01). Ablation resulted in greater improvement in EuroQol‐5 Dimension‐3 Level and Mayo Atrial Fibrillation‐Specific Symptom Inventory severity/frequency scores in probable HFpEF (interactions P =0.005, P =0.05, and P =0.04 respectively). In probable HFpEF, catheter ablation was associated with lower risk of cardiovascular hospitalization (HR, 0.78 [95% CI, 0.66–0.92], P =0.003, interaction P =0.03) but not HF hospitalization (HR, 0.94 [95% CI, 0.55–1.64], P =0.84). Conclusions Nearly three quarters of CABANA participants had potentially undiagnosed HFpEF, with worse QOL and risk of HF hospitalization. Catheter ablation in probable HFpEF resulted in greater improvement in QOL, but residual QOL impairment and HF risk remained elevated despite ablation. These data reinforce the importance of diligent consideration of HFpEF among patients with symptomatic AF to ensure optimal use of foundational treatments for HF.

Background/Goal: Parkinson’s disease (PD) disrupts dopaminergic transmission, leading to motor deficits and altered activity in the primary motor cortex (M1). While M1 modulation is critical for motor control, its response to dopaminergic degeneration and treatment remains unclear. This study aimed to characterize M1 neuronal activity and motor behavior in hemiparkinsonian rats using in vivo calcium imaging across naïve, lesioned, and levodopa-treated states. Methods: Thirteen Sprague Dawley rats were injected with GCaMP6f in the M1 and implanted with a GRIN lens and guide cannula targeting the medial forebrain bundle. Calcium imaging and motor behavior were assessed longitudinally using a single pellet reaching test (SPRT) before and after unilateral 6-hydroxydopamine (6-OHDA) lesioning and subsequent levodopa/carbidopa treatment. Dopaminergic lesion severity was quantified via tyrosine hydroxylase immunohistochemistry. Calcium event frequency and influx were analyzed with CNMF-E and statistical modeling. Results: Levodopa treatment improved fine motor performance as shown by a significant reduction in grasp errors (mean difference: −8.91, 95% CI: −16.66 to −1.16, p = 0.031) and increased reaching duration (mean difference: 4.13, 95% CI: 0.94 to 7.32, p = 0.019) compared to the lesioned state. M1 calcium activity showed modulation dependent on lesion severity: low-lesion rats exhibited reduced event frequency (mean difference: 0.04 Hz, 95% CI: 0.001 to 0.08, p = 0.045) and increased influx post-lesion (mean difference: −0.20 z·s, 95% CI: −0.38 to −0.02, p = 0.038), while high-lesion rats showed increased influx only after levodopa treatment (mean difference: −0.34 z·s, 95% CI: −0.52 to −0.16, p = 0.003). Correlation analyses revealed that calcium influx, but not frequency, was negatively correlated with lesion severity during levodopa treatment (Spearman r = −0.857, p = 0.024). Conclusion: M1 neuronal activity appears to be differentially modulated by dopaminergic degeneration and levodopa treatment in a lesion-dependent manner. These preliminary findings suggest dynamic cortical responses in PD and support the utility of calcium imaging for monitoring circuit-level changes in disease and therapy. Further research with larger cohorts and complementary methodologies will be necessary to validate and extend these observations.

Abstract Insulin resistance (IR) is a modifiable risk factor for dementia, yet its effects on brain metabolism and function remain unclear. In older adults, greater IR was associated with reduced cerebral glucose uptake (indicating impaired mitochondrial metabolism), atrophy, and weakened connectivity between brain regions critical for cognition. In neuron-specific insulin receptor knockout mice, brain IR produced deficits in hippocampal- and prefrontal-dependent tasks accompanied by reduced brain mitochondrial ATP and elevated reactive oxygen species. To evaluate reversibility of IR-induced brain deficits, forty older adults with IR were randomized to 40-weeks of metformin or placebo. Metformin improved insulin sensitivity, increased brain glucose uptake, strengthened cognitive network connectivity, and preserved whole-brain and regional volumes implicated in decision-making and learning. Metformin also improved processing speed and working memory. Collectively, these findings highlight IR as a driver of brain metabolism and support the concept that insulin sensitization can prevent neurobiological deficits in older people with IR.

Abstract Neurofibrillary tangles are dynamic neuropathologic hallmarks of Alzheimer’s disease with a hypothesized lifespan morphologically-defined by three maturity levels: pretangles, mature tangles, and ghost tangles. To better understand the progression of tangle pathophysiology, we characterized tangle maturity level predilection of 15 tau antibodies recognizing a broad range of linear, phosphorylation, conformational, and truncation epitopes in the hippocampus of 24 postmortem brains. We developed the tangle maturity scoring system to semi-quantitatively evaluate each tangle maturity level. Based on proportions of tangle maturity levels, we classified antibodies as “early” (mostly pretangles and mature tangles), “middling” (mature tangles with pretangles and ghost tangles), and “advanced” (mostly ghost tangles and mature tangles) tangle maturity markers. To summarize tangle maturity predilection, we developed the tangle maturity scale to integrate individual tangle maturity scores. Correlations showed stronger relationships between tangle maturity scale and subsector thickness for more advanced tangle maturity markers in CA1 and subiculum, whereas Braak tangle stage remained consistently correlated throughout markers of the tangle lifespan. To aid in scoring hippocampi, we used machine learning to recognize tangle maturity levels, which performed comparably to a domain expert and showed similar relationships by Spearman correlation. Pattern recognition software was used to assess tangle and neuritic tau burden separately, which generally correlated with Braak stage and neuronal counts. However, tangle-derived tau burden more consistently correlated with hippocampal subsector thickness. In conclusion, we developed manual and automated scoring systems to evaluate tangle maturity levels, demonstrating early 4R, phosphorylated, and oligomeric tau accumulation preceding more advanced 3R and truncated tau. Our study provides supportive evidence of disease-relevant ordering of tau posttranslational modifications in the brain, which may have implications for theragnostic development. These findings underscore the promise of computerized quantitative analyses (i.e., pathomics) for high-throughput feature extraction from whole-slide images to enhance our understanding of microscopically observed morphologic changes.

Abstract Context Higher gluconeogenesis (GNG) contributes to higher nocturnal endogenous glucose production (EGP) in type 2 diabetes (T2D). Studies using 13C magnetic resonance spectroscopy (MRS) have confirmed lower hepatic glycogen content in subjects with T2D than in subjects with no diabetes (ND). Objective We determined the role of glycogen loading (GL) vs nonglycogen loading (NGL) on the contribution of GNG to nocturnal EGP in T2D. Methods In total, 14 subjects with T2D and 15 matched subjects with ND were studied on 2 occasions, with GL (60% carbohydrate) vs NGL (40% carbohydrate) isocaloric meals for 3 days, in random order in the overnight state. [6,6-2H2] glucose was infused to measure EGP, deuterium labelled water was used to measure GNG, and 13C MRS scans were performed in fed and fasted states to measure hepatic glycogen content. Results Hepatic glycogen content and nocturnal EGP were higher (P &lt; .05) in GL vs NGL in both cohorts. The % GNG to EGP averaged ∼50% in subjects with ND throughout the night after both meals. In contrast, % GNG to nocturnal EGP in T2D was lower with GL vs NGL and matched the pattern observed in subjects with ND with GL lowering overnight rates of GNG in subjects with T2D. Conclusion Selective targeting of GNG at night with appropriate medications could reduce nocturnal and early morning fasting hyperglycemia and hepatic insulin resistance in people with T2D.

BACKGROUND: Plasma NT-proBNP (N-terminal pro-B-type natriuretic peptide) is commonly used to diagnose heart failure with preserved ejection fraction (HFpEF), but its diagnostic performance in the ambulatory/outpatient setting is unknown because previous studies lacked objective reference standards. METHODS: Among patients with chronic dyspnea, diagnosis of HFpEF or noncardiac dyspnea was determined conclusively by exercise catheterization in a derivation cohort (n=414), multicenter validation cohort 1 (n=560), validation cohort 2 (n=207), and a nonobese Japanese validation cohort 3 (n=77). Optimal NT-proBNP cut points for HFpEF rule out (optimizing sensitivity) and rule in (optimizing specificity) were derived and tested, stratified by obesity and atrial fibrillation. Derived cut points were tested in 3 additional validation cohorts (cohorts 4–6) in whom HFpEF was diagnosed by resting catheterization only (n=260), previous hospitalization for heart failure (n=447), or exercise echocardiography (n=517), respectively. RESULTS: Current recommended rule-out NT-proBNP threshold <125 pg/mL had 82% sensitivity (95% CI, 77%–88%) with a body mass index (BMI) <35 kg/m 2 , decreasing to 67% (95% CI, 58%–77%) with a BMI ≥35 kg/m 2 . A lower rule-out NT-proBNP threshold <50 pg/mL displayed good sensitivity with a BMI <35 kg/m 2 (97% [95% CI, 95%–99%]), with a modest decline in sensitivity with a BMI ≥35 kg/m 2 (86% [95% CI, 79%–93%]); diagnostic thresholds were confirmed in validation cohorts 1 and 2 (91% [95% CI, 88%–95%] and 86% [95% CI, 80%–93%] with a BMI <35 kg/m 2 ; 80% [95% CI, 74%–87%] and 84% [95% CI, 74%–93%] with a BMI ≥35 kg/m 2 ). Current consensus age- and BMI-stratified rule-in thresholds demonstrated only 65% specificity (95% CI, 57%–72%). Rule-in NT-proBNP threshold ≥500 pg/mL had 85% specificity (95% CI, 78%–91%) with a BMI <35 kg/m 2 (87% [95% CI, 80%–94%] and 90% [95% CI, 81%–99%] in validation cohorts), with 100% specificity at a BMI ≥35 kg/m 2 (93% [95% CI, 81%–100%] and 100% in validation cohorts). With a BMI ≥35 kg/m 2 , lower rule-in thresholds (≥220 pg/mL) provided good specificity (88% [95% CI, 73%–100%]; 93% [95% CI, 81%–100%] and 100% in validation cohorts). Findings were consistent in validation cohorts 3 through 6 (sensitivity of <50 pg/mL, 93%–98%; specificity of ≥500 pg/mL, 82%–89%). NT-proBNP provided no incremental discrimination among patients with history of AF; ≥98% of patients with AF and dyspnea were found to have HFpEF in our cohorts. CONCLUSIONS: In patients with chronic unexplained dyspnea, current rule-in and rule-out NT-proBNP diagnostic thresholds lead to unacceptably high error rates, with important interactions by obesity and AF status. In our study, NT-proBNP provided little value in those with AF and dyspnea because the presence of AF is by itself a robust biomarker of HFpEF. Use of separate rule-in and rule-out diagnostic thresholds stratified by BMI reduces miscategorization and can guide more appropriate use of exercise testing for possible HFpEF.

Background: Effective pain management is crucial for both comfort and outcomes, yet predicting and managing this pain is difficult. This study aimed to analyze postoperative pain in patients undergoing hand surgery at the Mayo Clinic Florida, examining how patient characteristics and anxiety affect pain outcomes. Methods: We conducted a single-arm clinical trial at Mayo Clinic Florida, recruiting patients undergoing hand surgery. Preoperative pain and anxiety were assessed using the Pain Catastrophizing Scale (PCS) and State-Trait Anxiety Inventory (STAI). Postoperatively, patients used an iPhone app to record pain levels and medication use every four hours. Devices were collected three days after surgery. We analyzed the relationship between demographics, PCS, STAI scores, and pain levels using linear and logistic regression models. All statistical tests were two-sided with significance set at p < 0.05, analyzed with R4.2.2. Results: Data were collected from 62 patients (62.9% women, 37.1% men) undergoing hand surgery. Participants were mainly White (90.3%), with 50% being in the middle-aged adult group. Most had low anxiety levels (80.6% STAI-S, 82.3% STAI-T) and low catastrophizing (61.3% PCS). Postoperative pain was low, with median scores between 1.0 and 2.0 over three days. Demographics, anxiety, and catastrophizing were not significant predictors of pain levels. Logistic regression showed time as a significant factor, with pain levels peaking on Day 3. Conclusions: Postoperative pain after hand surgery was generally low, with time being a significant predictor of increased pain. Demographic factors, anxiety, and catastrophizing did not significantly affect pain levels. Pain management should emphasize time-sensitive interventions and ongoing monitoring.

Abstract Background We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented kidney stone composition test system for potential improvements in test quality, efficiency, cost-effectiveness, and staff satisfaction. Methods We compared quality, efficiency, staff satisfaction, and financial data from the 6 months after the AI-augmented laboratory test system was deployed (test period) with data from the same 6-month period in the previous year (control period) to determine if AI-augmentation improved key performance indicators of this laboratory test. Results In the 6 months following the deployment (test period) of the AI-augmented kidney stone composition test system, 44 830 kidney stones were analyzed. Of these, 92% of kidney stones were eligible for AI-assisted interpretation. Out of these AI-eligible stones, 45% were able to be auto-released by the AI-augmented test system without human secondary review. Furthermore, the new AI-augmented kidney stone test system resulted in an apparent 40% reduction in incorrect laboratory results. Additionally, the new AI-augmented test system improved laboratory efficiency by 20%, improved staff satisfaction, and reduced the average analysis cost per kidney stone by $0.23. Conclusions The AI-augmented test system improved test quality, efficiency, cost-effectiveness and staff satisfaction related to this kidney stone composition test.

Abstract: Background: Allergic contact dermatitis is a common, pruritic, debilitating skin disease, affecting at least 20% of the population. Objective: To prospectively validate a computer vision algorithm across all Fitzpatrick skin types. Methods: Each participant was exposed to 10 allergens. The reference criterion was obtained 5 days after initial patch placement by a board-certified dermatologist. The algorithm processed photographs of the test site obtained on Day 5. Human performance in reading the photographs was also evaluated. Results: A total of 206 evaluable participants [mean age 39 years, 66% (136/206) female, and 47% with Fitzpatrick skin types IV–VI] completed testing. Forty-two percent (87/206) of participants experienced 1 or more allergic reaction resulting in a total of 132 allergic reactions. The model provided high discrimination (AUROC 0.86, 95% CI: 0.82–0.90) and specificity (93%, 95% CI: 92%–94%) but with lower sensitivity (58%, 95% CI: 49%–67%). Human performance interpreting the photographs ranged from providing similar performance to the algorithm to providing superior performance when combined across readers. There were no serious adverse events. Conclusions: The combination of a smartphone capture of patch testing sites with deep learning yielded high discrimination across a diverse sample.