HR Estimates Research Articles

To be or not to be, when synthetic data meet clinical pharmacology: A focused study on pharmacogenetics.

The use of synthetic data in pharmacology research has gained significant attention due to its potential to address privacy concerns and promote open science. In this study, we implemented and compared three synthetic data generation methods, CT-GAN, TVAE, and a simplified implementation of Avatar, for a previously published pharmacogenetic dataset of 253 patients with one measurement per patient (non-longitudinal). The aim of this study was to evaluate the performance of these methods in terms of data utility and privacy trade off. Our results showed that CT-GAN and Avatar used with k = 10 (number of patients used to create the local model of generation) had the best overall performance in terms of data utility and privacy preservation. However, the TVAE method showed a relatively lower level of performance in these aspects. In terms of Hazard ratio estimation, Avatar with k = 10 produced HR estimates closest to the original data, whereas CT-GAN slightly underestimated the HR and TVAE showed the most significant deviation from the original HR. We also investigated the effect of applying the algorithms multiple times to improve results stability in terms of HR estimation. Our findings suggested that this approach could be beneficial, especially in the case of small datasets, to achieve more reliable and robust results. In conclusion, our study provides valuable insights into the performance of CT-GAN, TVAE, and Avatar methods for synthetic data generation in pharmacogenetic research. The application to other type of data and analyses (data driven) used in pharmacology should be further investigated.

Emulations of Oncology Trials Using Real-World Data: A Systematic Literature Review.

By evaluating published emulations of oncology RCTs studies in which both the active and comparator groups are sourced from RWD and target trial results are available for benchmarking, this systematic review aims to gain insight into factors related to emulation performance. Thirteen oncology emulation studies using various types of RWD were identified through an online database search of PubMed through 2022. Based on the ROBINS-I tool, most studies (N=8) had a serious risk of overall bias driven by risk of bias from confounding. Approximately half of the studies (N=6) fully proxied the RCT entry criteria. Of 11 RWD studies that provided sufficient detail to quantify emulation performance, the emulation HR estimate fell within the 95% CI of the trial estimate in 9 of the studies. There were no clear trends between risk of bias or degree to which the entry criteria were proxied and emulation performance. Findings may have been influenced by publication bias and researcher degrees of freedom, as only one emulation study pre-registered its protocol. Tools for comprehensively characterizing factors that affect emulation performance, including the real-world clinical context as it relates to the RCT research question, are needed to evaluate the feasibility of a RCT emulation.

Facial Video-Based Non-Contact Stress Recognition Utilizing Multi-Task Learning With Peak Attention.

Negative emotional states, such as anxiety and depression, pose significant challenges in contemporary society, often stemming from the stress encountered in daily activities. Stress (state or level) recognition is a crucial prerequisite for effective stress management and intervention. Presently, wearable devices have been employed to capture physiological signals and analyze stress states. However, their constant skin contact can lead to discomfort and disturbance during prolonged monitoring. In this paper, a peak attention-based multitasking framework is presented for non-contact stress recognition. The framework extracts rPPG signals from RGB facial videos, utilizing them as inputs for a novel multi-task attentional convolutional neural network for stress recognition (MTASR). It incorporates peak detection and HR estimation as auxiliary tasks to facilitate stress recognition. By leveraging multi-task learning, MTASR can utilize information related to stress physiological responses, thereby enhancing feature extraction efficiency. For stress recognition, two binary classification tasks are applied: stress state recognition and stress level recognition. The model is validated on the UBFC-Phys public dataset and demonstrates an accuracy of 94.33% for stress state recognition and 83.83% for stress level recognition. The proposed method outperforms the dataset's baseline methods and other competing approaches.

Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes: A Multinational, Federated Analysis of LEGEND-T2DM

BackgroundSodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials. ObjectivesThe aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM. MethodsAcross the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis. ResultsOver 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13]). ConclusionsIn patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD.

The Association Between the Levels of Serum Phosphate and Mortality Rates in Pre-Dialysis and Dialysis Patients

Introduction: Discovering predictors to reduce morbidity and mortality in chronic kidney disease (CKD) is now a critical global priority. Serum phosphate level is considered to be a potential marker for mortality rate in patients with CKD. Previous studies examined the independent pathogenic role of phosphorus in the development of CKD and dialysis patients but have yielded contradictory findings. This study aims at evaluating the relationship between serum phosphate levels and death rates in pre-dialysis CKD and maintenance of dialysis patients. Method: PubMed, Scopus, and Web of Science were searched by using MeSH term keywords. The authors did screening, data extraction, and quality assessment in accordance with the inclusion criteria. STATA 14.2 was used for statistical analyses. The analysis was performed using the random- and fixed-effects model when the heterogeneity was >50% and ≤50%, respectively. For evaluating publication bias, Funnel plots and Egger tests were used. Result: Eleven original studies between 2005 and 2021 met the eligibility criteria. The overall estimate of unadjusted HR of all-cause mortality each 1 mg/dL increase in the serum phosphate concentration using the random-effects model in pre-dialysis CKD and dialysis patients was 1.33 (95% CI: 0.97, 1.82, I2 = 99.1%, P = 0.074), and for adjustment, Hazard ratio was 1.27 (95% CI: 1.15, 1.39, I2 = 75.4%, P < 0.001). Conclusion: The findings showed the association between serum phosphate levels and death rates in pre-dialysis individuals with CKD and dialysis patients.

COVID-19 vaccination initiation and completion in a multicenter cohort study of insured US transgender and cisgender adults

PurposeTransgender and gender-diverse (TGD) people may have been disproportionately impacted by the COVID-19 pandemic, yet little is known about vaccination status in this population. This multicenter cohort study of insured adults examined the rates of COVID-19 vaccine initiation and completion in TGD persons compared to matched cisgender persons. MethodsA cohort of TGD persons and matched cisgender persons enrolled in Kaiser Permanente health plans in Northern and Southern California between 12/1/2020 and 7/31/2021 were analyzed. COVID-19 vaccination initiation and completion rates were compared across groups using Cox regression models. ResultsAmong transmasculine persons, the HR (95 % CI) estimates for COVID-19 vaccination initiation and completion were, respectively, 1.35 (1.30–1.40) and 1.78 (1.71–1.85) compared with cisgender women and 1.34 (1.29–1.40) and 1.81 (1.73–1.88) compared with cisgender men. Among transfeminine persons, the corresponding HRs (95 % CIs) for vaccination initiation and completion were 1.35 (1.30–1.40) and 1.78 (1.71–1.85) compared with cisgender women and 1.34 (1.29–1.40) and 1.81 (1.73–1.88) compared with cisgender men. ConclusionFindings from this cohort of insured adults demonstrated that TGD persons initiated and completed COVID-19 vaccination at higher rates compared to matched cisgender persons. Further work is needed to understand vaccination rates and determinants in the broader TGD populations.

Interim results of the randomized phase 2 cohort of study FW-2020-01 assessing the efficacy, safety and pharmacodynamics of CM24 in combination with nivolumab and chemotherapy in advanced/metastatic pancreatic cancer.

LBA4143 Background: The novel monoclonal antibody CM24 blocks the activity of Carcinoembryonic Antigen Cell Adhesion Molecule 1 (CEACAM1), known to have key roles in cancer progression, immune evasion, and metastasis. We present the interim efficacy and safety data from the global multi-center, open label, randomized Phase 2 study (NCT 04731467) in patients (pts) with advanced/metastatic pancreatic ductal adenocarcinoma (PDAC) who progressed after 1st line therapy, treated with CM24, nivolumab (nivo) and chemotherapy vs. chemotherapy (CH). Methods: Patients with advanced/metastatic PDAC progressing after 1 prior line of systemic therapy including fluoropyrimidine/irinotecan or gemcitabine/nab-paclitaxel, having ≥1 measurable lesion, ≥18-year-old, ECOG ≤1 and adequate organ function were randomized 1:1 based on the class of prior CH received. Randomization was either to the experimental groups (EX) receiving CM24 (20mg/kg, q2wk), nivo (240mg/kg, q2wk) with one of the following CH regimens, liposomal irinotecan, 5 fluorouracil and leucovorin (Nal-IRI; q2wk) or gemcitabine/nab-paclitaxel (gem/nab; q1wk x3) or the control groups (C) with one of the CH regimens alone. This is a Bayesian design with an overall planned sample size of 60 pts with Overall Survival (OS) as the primary endpoint. Secondary endpoints include progression free survival (PFS), objective response rate (ORR) and disease control rate (DCR). An interim estimate of PFS HR, ORR and DCR based on data cut-off date of 21 Feb 2024 is reported. The analysis compares the EX vs. the respective C arm using log-rank test stratified by CH regimen. Results: A total of 63 PDAC pts were evenly randomized across the study arms. At data cut-off date, a total of 18 pts, 9 per treatment regimen remain on treatment. The median follow-up time for the Nal-IRI regimen is 6.3 months (95% CI: 5.5-8.4) and 5.2 months (95% CI: 4.0-6.7) for the gem/nab regimen. Median PFS ORR and DCR for the Nal-IRI EX arm were 3.8m (1.9-5.1; HR 0.70; p=0.213), 18.8% and 62.6%, and for the Nal-IRI C arm 1.9m (1.8-5.6), 6.3% and 40%, respectively (Table). Data for the gem/nab regimen and OS data for both regimens are not mature. Overall Grade ≥3 AE rate was 50% in the Nal-IRI EX arm and 13% in the C arm. The most common treatment-emergent grade ≥3 AEs EX vs. C were diarrhea (18.8% vs 6.7%), fatigue (18.8% vs 6.7%) and anemia (6.3% vs 0%). Conclusions: The interim analysis suggests that the combination of CM24/nivo/Nal-IRI/5FU/LV has a manageable safety profile with a longer PFS supported by higher ORR and DCR. OS Data continues to mature and will be reported once available. Clinical trial information: NCT04731467 . [Table: see text]

#2652 Hemoglobin excursion outside of the target range and their associations with all-cause mortality in hemodialysis patients

Abstract Background and Aims Based on earlier analyses (Mermelstein et al., ASN Renal Week 2023), where we found an improved survival with hemoglobin levels above the currently targeted range of 10 to 11 g/dL quantified as an area under the excursion curve, we hypothesized an independent association between all-cause mortality hazard ratio and a) the number of excursions, and b) the number of days outside of the target range. Method We explored this relationship in a retrospective cohort study of incident hemodialysis patients receiving erythropoietin stimulating agent (ESA) commencing treatment Fresenius Kidney Care clinics in the US. We included patients who were given a long-acting erythropoietin stimulating agent within 90 days of dialysis initiation, considered the first six months as baseline and the following 18 months as the follow-up period. Only patients with at least 5 hemoglobin values over the first 75 days were included. We calculated the ‘area under the curve’ (AUC) above and below the target hemoglobin range of 10-11 g/dL for each patient during the baseline period, as well as days below and above range, and number of excursions below and above range. Cox proportional hazard models additionally adjusted for age, race, sex, diabetes, serum albumin, and phosphate were developed, and the hazard ratio estimates depicted in a forest plot. Results We studied 62,181 patients (57% male, 39% diabetic, mean baseline hgb 10.42 ± 0.72 g/dL, baseline AUC above target 44.36 ± 49.44 g/dL * days and 78.06 ± 86.26 g/dL * days below target). Forest plot of the HR estimates showed an increased risk of death with AUC below the lower limit of the target range (i.e. 10 g/dL), which also held true both for number of excursions and days exposed to lower hgb levels). Conversely, AUC, conversions and days spent at hgb levels higher than the upper limit of the target range (i.e. 11 g/dL), associated with a significant survival advantage. Conclusion In an effort to validate the robustness of our previously shown association between higher hgb levels and survival advantage, and to corroborate the accuracy of the utilized AUC quantification method, we separated both components of the AUC, namely into time and magnitude and quantified the independent associations with the risk of death. This allowed to discern between the associations of both to the risk of death. Consistent with the earlier results, avoiding levels below 10 g/dL and aiming for levels above the upper limit of 11 g/dL, seems to be beneficial for the anemia management of incident hemodialysis patients treated with a long-acting ESA.

Nitrosyl-heme and Heme Iron Intake from Processed Meats and Risk of Colorectal Cancer in the EPIC-Spain Cohort.

The International Agency for Research on Cancer classified processed meats (PM) as "carcinogenic" and red meat as "probably carcinogenic" for humans. The possible relationship between colorectal cancer risk and the mechanisms involved in the carcinogenesis of PMs have not been established yet. Nitrosyl-heme and heme iron have been proposed as potential-related compounds. The aim of this study was to determine the association between nitrosyl-heme and heme iron intake and colorectal cancer risk among participants from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain study. This prospective study included 38,262 men and women from the EPIC-Spain study. Food consumption was assessed using diet history and food composition tables. Heme iron and nitrosyl-heme intake were determined by estimating the intake of PM items and conducting laboratory analyses. HR estimates were obtained by proportional hazard models, stratified by age at recruitment and study center and adjusted for sex, total energy intake, education, smoking, body mass index, waist size, physical activity, lifetime alcohol, fibre, calcium, and familiar colorectal cancer history. During a mean follow-up of 16.7 years, 577 participants were diagnosed with colorectal cancer. We found no overall association between nitrosyl-heme [HRT3vsT1, 0.98; 95% confidence interval (CI), 0.79-1.21] or heme iron intakes (HRT3vsT1, 0.88; 95% CI, 0.70-1.10) with colorectal cancer risk, nor according to tumor subtypes. Our study found no evidence supporting a link between nitrosyl-heme or heme iron intake and colorectal cancer risk in Spanish subjects. As research on nitrosyl-heme is preliminary, more heterogeneous studies are necessary to provide more convincing evidence on their role in colorectal cancer carcinogenesis.

Development and prognostic validation of a three-level NHG-like deep learning-based model for histological grading of breast cancer

BackgroundHistological grade is a well-known prognostic factor that is routinely assessed in breast tumours. However, manual assessment of Nottingham Histological Grade (NHG) has high inter-assessor and inter-laboratory variability, causing uncertainty in grade assignments. To address this challenge, we developed and validated a three-level NHG-like deep learning-based histological grade model (predGrade). The primary performance evaluation focuses on prognostic performance.MethodsThis observational study is based on two patient cohorts (SöS-BC-4, N = 2421 (training and internal test); SCAN-B-Lund, N = 1262 (test)) that include routine histological whole-slide images (WSIs) together with patient outcomes. A deep convolutional neural network (CNN) model with an attention mechanism was optimised for the classification of the three-level histological grading (NHG) from haematoxylin and eosin-stained WSIs. The prognostic performance was evaluated by time-to-event analysis of recurrence-free survival and compared to clinical NHG grade assignments in the internal test set as well as in the fully independent external test cohort.ResultsWe observed effect sizes (hazard ratio) for grade 3 versus 1, for the conventional NHG method (HR = 2.60 (1.18–5.70 95%CI, p-value = 0.017)) and the deep learning model (HR = 2.27, 95%CI 1.07–4.82, p-value = 0.033) on the internal test set after adjusting for established clinicopathological risk factors. In the external test set, the unadjusted HR for clinical NHG 2 versus 1 was estimated to be 2.59 (p-value = 0.004) and clinical NHG 3 versus 1 was estimated to be 3.58 (p-value < 0.001). For predGrade, the unadjusted HR for predGrade 2 versus 1 HR = 2.52 (p-value = 0.030), and 4.07 (p-value = 0.001) for preGrade 3 versus 1 was observed in the independent external test set. In multivariable analysis, HR estimates for neither clinical NHG nor predGrade were found to be significant (p-value > 0.05). We tested for differences in HR estimates between NHG and predGrade in the independent test set and found no significant difference between the two classification models (p-value > 0.05), confirming similar prognostic performance between conventional NHG and predGrade.ConclusionRoutine histopathology assessment of NHG has a high degree of inter-assessor variability, motivating the development of model-based decision support to improve reproducibility in histological grading. We found that the proposed model (predGrade) provides a similar prognostic performance as clinical NHG. The results indicate that deep CNN-based models can be applied for breast cancer histological grading.

Echo-derived hemodynamic categorization for risk stratification in transthyretin cardiac amyloidosis

Abstract Background Transthyretin cardiac amyloidosis (TTR-CA) is a rare disease characterized by the deposition of abnormal proteins in the heart, which can lead to heart failure (HF) and death. Echocardiography provides valuable diagnostic and prognostic information in CA, but indices of left ventricular performance alone cannot thoroughly characterise patients with restrictive cardiomyopathy. Evaluating the hemodynamic profile by studying the forward flow and left ventricular filling pressure (LVFP) already proved its value in stratifying disease severity in patients with heart failure (HF). Purpose This study evaluated the prognostic relevance of a non-invasive hemodynamic categorization of TTR-CA patients based on the estimation of stroke volume index (SVi) and systolic pulmonary artery pressure (PAPs). Methods Baseline clinical, transthoracic echocardiogram and laboratory data were collected prospectively in patients with diagnosed TTR-CA. Patients were classified into four groups based on forward flow (SVi &amp;lt; or ≥30 ml/m2) and systolic pulmonary artery pressure (PAPs ≥ or &amp;lt;40 mmHg). The four profiles obtained were Profile-A, normal-flow, normal-pressure; Profile-B, low-flow, normal-pressure; Profile-C, normal-flow, high-pressure; Profile-D, low-flow, high-pressure. We assessed the incidence of the composite endpoint of cardiovascular death and HF hospitalization accordingly to the hemodynamic profile. We performed univariate and multivariate Cox regression using profile A as a reference for HR estimation (profile A corresponding to HR=1). Results Fifty-nine patients were enrolled in the analysis (Table). Over a mean follow-up of 35.9 months (IQR 11.7 - 51.2 months) 23 patients met the composite endpoint (10%, 23%, 43%, 60% for Profile A, B, C and D respectively). Compared to Profile A, Profile D showed the greatest risk of CV mortality and HF hospitalization (HR 10.17), followed by Profile C (HR 6.77) and B (HR 3.45), with P-value=0.015. The C-statistic for the model was 0.72. Kaplan-Meier curves confirmed that patients with PAPs &amp;gt;40 mmHg and SVi&amp;lt; 30 ml/m2 presented the highest risk of the composite endpoint (Log-rank P = 0.010) (Figure). Hemodynamic profiling remained an independent predictor of outcome even after adjusting for the NAC stage (Profile B, HR 2.26; Profile C, HR 6.96; Profile D, HR 17.13; P-value=0.0012). Conclusions The proposed echocardiographically-derived hemodynamic classification based on forward-flow and LVFP estimation is useful for TTR-CA patients risk stratification. Patients with low SVi and high PAPs have the greatest risk of CV death and HF hospitalization, even after adjustment for NAC stage. These findings highlight the importance of early detection and monitoring of hemodynamic changes in TTR-CA patients for tailored management and to improve outcomes.Table.Figure.

Urinary peptides provide information about the risk of mortality across a spectrum of diseases and scenarios

BackgroundThere is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, although the mechanisms causing this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to vulnerabilities that are already present. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides.MethodsUrinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated.ResultsIn the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death [adjusted HR 1.2 (95% CI 1.17–1.24)]. The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% [adjusted HR 1.61 (95% CI 1.47–1.76)], consistent with adjusted meta-analytic HR estimate of 1.55 [95% CI 1.39–1.73]. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I (I).ConclusionThe COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. This prediction is mainly based on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as a basis for proteomics-guided intervention aiming towards manipulating/ improving collagen turnover, thereby reducing the risk of death.

Strain-derived myocardial work in wild-type transthyretin cardiac amyloidosis with aortic stenosis-diagnosis and prognosis.

Several echocardiographic parameters have been suggested to differentiate wild-type transthyretin cardiac amyloidosis (ATTRwt) from other causes of hypertrophy. These studies have all been performed in small samples of mixed cardiac amyloidosis. The purpose of this study was to investigate the role of echocardiographic parameters in patients with ATTRwt and aortic stenosis (AS) versus patients with AS. The secondary aim was to investigate the role of myocardial work in the prognosis of patients with ATTRwt. The sensitivity and specificity of the relative apical sparing ratio (RAS), the apical-to-basal ratio (AB), the ejection-fraction-to-global-longitudinal-strain ratio (EF/GLS), and the global myocardial work index (GWI) were calculated using receiver-operated characteristics curves and area under the curve (AUC) in patients with ATTRwt and AS (n=50) versus patients with AS (n=354). Multivariable regression was used to assess the prognostic value of GWI in patients with ATTRwt (n=212). When used to identify AS from ATTRwt+AS, GWI had a sensitivity of 80% and specificity of 70%. The AUC of GWI was larger than that of AB (p=.01) and EF/GLS (p>.01) but not RAS (p=.15). In patients with ATTRwt multivariable regression found age predicted mortality with an estimate of HR=1.086 (CI: 1.034-1.141) while GWI predicted survival with an estimate of HR=.837 (CI: .733-.956) per 100mmHg*% increase. GWI was demonstrated to be a viable classifier in ATTRwt and AS versus AS. GWI was demonstrated to independently predict survival in patients with ATTRwt. Further studies examining the role of myocardial work in ATTRwt are warranted.

ECG augmented pulse oximetry in Atlantic salmon (Salmo salar)—A pilot study

Understanding the tolerance limits of fish is crucial for developing aquaculture operations that ensure good animal welfare. However, there exist little data describing the physiological responses in farmed Atlantic salmon, much because the technological tools for taking such measurements have not existed. Recent advances in electronic implants have enabled concurrent measurement of electrocardiogram (ECG) and photoplethysmograms (PPG) in salmon that can be used for robust estimation of HR and oxygen saturation in arterial blood (i.e., SpO2/pulse oximetry) if appropriate strategies for motion artifact and light scattering compensation can be realized. To enable pulse oximetry for farmed Atlantic salmon (and fish in general), two experiments have been conducted. In Experiment 1, PPGs were obtained from salmon induced to swim at two different water currents under normoxic conditions. By using two water currents, the resulting data provided a foundation for developing methods for motion artifact compensation. Data from this experiment were also used to calculate an average light scattering parameter using the modified Beer–Lambert law, under the assumption that SpO2 was 100% for individual fish. In Experiment 2, fish were placed in a swim tunnel and subjected to hypoxic conditions and corresponding changes in SpO2 were estimated using the motion artifact and light scattering compensation approaches from Experiment 1.Results show that the suggested compensation approaches gives SpO2 estimates within the expected range (95% to 100%) under normoxic conditions. Under hypoxic conditions, changes in SpO2 that coincide with experiment events were observed, demonstrating that PPGs can be used to quantify such changes. The results from this pilot study therefore extend the selection of physiological parameters feasible to measure using electronic implants for Atlantic salmon. In doing so, the scope for physiological measurements is extended such that an improved understanding of physiological responses and tolerances in Atlantic salmon farming can be acquired, and ultimately be used to improve animal welfare in fish production.

A comprehensive analysis of CO2 exchanges in agro-ecosystems based on a generic soil-crop model-derived methodology

Carbon emissions in agriculture play a major role in climate change. Modelling studies enable to investigate the impacts of climate change in crops, accounting for soil organic carbon feedbacks and CO2 concentrations. But it is primordial that crop models properly consider the CO2 exchanges at the level of crop rotations beyond the cycle of a single crop. With this goal in mind, we used the outputs of the soil-crop model STICS in its standard pre-parameterized version to model (i) the Gross Primary Productivity (GPP), derived from the autotrophic respiration and the Net Primary Productivity, which is computed through the daily change in plant carbon (C) pools; (ii) the Ecosystem Respiration (RECO), with the autotrophic component being derived from the plant biomass, plant nitrogen concentration and GPP, and the heterotrophic component from the mineralization of residues and organic matter; and (iii) the Net Ecosystem Exchange, equal to the sum of GPP and RECO. The comparison of simulations with field observations indicates that the model is able to simulate accurately daily CO2 fluxes originating from a long-term and diversified crop rotation (efficiency EF equal to 0.79 for GPP, 0.59 for RECO and 0.67 for NEE). Concerning the evaluation of the cumulated fluxes over the 16-year rotation, the model is able to evaluate it accurately for RECO, with a slight underestimation (normalized deviation ND = 15.7%), and very accurately for GPP (ND = 5.12%). But for NEE, the relative overestimation is higher (ND = 62.2%), indicating that a more precise estimation of HR is required to obtain reliable net C budgets. The model also succeeds to capture the trends in the influence of several environmental drivers on CO2 fluxes. It globally proves to be a valuable tool in the investigation of CO2 exchanges of crop rotations in historical and future climatic conditions.

Happy people live longer because they are healthy people

ObjectivesHigher levels of happiness are associated with longer life expectancy. Our study assessed the extent to which various factors explain the protective effect of happiness on all-cause mortality risk, and whether the association differs between older men and women.MethodsUsing data from the Singapore Longitudinal Aging Studies (N = 6073) of community-dwelling older adults aged ≥ 55 years, we analyzed the association of baseline Likert score of happiness (1 = very sad to 5 = very happy) and mortality from mean 11.7 years of follow up. Cox regression models were used to assess the extent to which confounding risk factors attenuated the hazard ratio of association in the whole sample and sex-stratified analyses.ResultsHappiness was significantly associated with lower mortality (p < .001) adjusted for age, sex and ethnicity: HR = 0.85 per integer score and HR = 0.57 for fairly-or-very happy versus fairly-or-very sad. The HR estimate (0.90 per integer score) was modestly attenuated (33.3%) in models that included socio-demographic and support, lifestyle or physical health and functioning factor, but remained statistically significant. The HR estimate (0.94 per integer score) was substantially attenuated (60%) and was insignificant in the model that included psychological health and functioning. Including all co-varying factors in the model resulted in statistically insignificant HR estimate (1.04 per integer score). Similar results were obtained for HR estimates for fairly-to-very happy versus fairly-to- very sad).DiscussionMuch of the association between happiness and increased life expectancy could be explained by socio-demographic, lifestyle, health and functioning factors, and especially psychological health and functioning factors.

Development of Non-Invasive Technique for Heart Rate Detection Using Facial Videos

Mortality rate in Chhattisgarh state due to ischemic heart disease is 43.6% and growing exponentially every year. Early detection of cardiac health plays a major role in decreasing this rate. Due to the insufficient hospitals and accessibility of the dedicated equipment, remote health monitoring has become quite inevitable after SARC-CoV-2 pandemic. Due to its excellent capability is it going to be cardiac rate measurement method of future. However, the difficulty in HR measurement is that, it gets affected with noise very easily because the amplitude of physiological signal is very weak. remote Photoplethysmography (rPPG) is a technique to measure the cardiac activity in a contact-less manner using digital cameras. However, the HR estimation suffers from two major artifacts, motion artifact and illumination artifact. Denoising of rPPG signal is a fundamental problem and needs to be addressed very carefully. In this article we have proposed a novel HR estimation network using a combination of wavelet decomposition and Convolutional Neural Network (CNN). This approach provides distinct features at different frequency levels, which facilitates the removal of noisy signal. Performance evaluation of the proposed method is done on self-collected dataset. Lower values of RMSE and MAE proves the efficacy of the proposed method.

BAP1-related signature predicts benefits from immunotherapy over VEGFR/mTOR inhibitors in ccRCC: a retrospective analysis of JAVELIN Renal 101 and checkmate-009/010/025 trials.

In patients with advanced clear cell renal cell carcinoma, despite the undoubted benefits from immune checkpoint inhibitor (ICI)-based therapies over monotherapies of angiogenic/mTOR inhibitors in the intention-to-treat population, approximately a quarter of the patients can scarcely gain advantage from ICIs, prompting the search for predictive biomarkers for patient selection. Clinical and multi-omic data of 2428 ccRCC patients were obtained from The Cancer Genome Atlas (TCGA, n = 537), JAVELIN Renal 101 (avelumab plus axitinib vs. sunitinib, n = 885), and CheckMate-009/010/025 (nivolumab vs. everolimus, n = 1006). BAP1 mutations were associated with large progression-free survival (PFS) benefits from ICI-based immunotherapies over sunitinib/everolimus (pooled estimate of interaction HR = 0.71, 95% CI 0.51-0.99, P = 0.045). Using the top 20 BAP1 mutation-associated differentially expressed genes (DEGs) generated from the TCGA cohort, we developed the BAP1-score, negatively correlated with angiogenesis and positively correlated with multiple immune-related signatures concerning immune cell infiltration, antigen presentation, B/T cell receptor, interleukin, programmed death-1, and interferon. A high BAP1-score indicated remarkable PFS benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors (avelumab plus axitinib vs. sunitinib: HR = 0.55, 95% CI 0.43-0.70, P < 0.001; nivolumab vs. everolimus: HR = 0.72, 95% CI 0.52-1.00, P = 0.045), while these benefits were negligible in the low BAP1-score subgroup (HR = 1.16 and 1.02, respectively). In advanced ccRCCs, the BAP1-score is a biologically and clinically significant predictor of immune microenvironment and the clinical benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors, demonstrating its potential utility in optimizing the personalized therapeutic strategies in patients with advanced ccRCC.

MP65-01 RISK FACTORS FOR PARASTOMAL HERNIATION: A SURVEILLANCE, EPIDEMIOLOGY AND END RESULTS-MEDICARE DATA ANALYSIS

You have accessJournal of UrologyCME1 Apr 2023MP65-01 RISK FACTORS FOR PARASTOMAL HERNIATION: A SURVEILLANCE, EPIDEMIOLOGY AND END RESULTS-MEDICARE DATA ANALYSIS Diboro Kanabolo, Sarah Holt, Jonathan Wright, and George Schade Diboro KanaboloDiboro Kanabolo More articles by this author , Sarah HoltSarah Holt More articles by this author , Jonathan WrightJonathan Wright More articles by this author , and George SchadeGeorge Schade More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003323.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: A frequent complication of stoma creation is parastomal herniation (PSH), defined as any palpable bulge or radiologic defect containing bowel in the parastomal region. Reported incidence rates are up to 50% for patients in the 24 months following ileal conduit (IC) surgery. To better understand risk factors for PSH in those undergoing cystectomy and ileal conduit (RC/IC) procedure, we examined a contemporary cohort of patients through combined Surveillance, Epidemiology and End Results-Medicare data (SEER-MD). METHODS: Using SEER-MD, patients with PSH after cystectomy and IC were identified. This was performed using CPT codes to identify surgery patients and subsequent diagnostic the new ICD-10 PSH specific code (K43.5) post-surgery, for those with surgery between 2015 and 2019. Risk factors of interest included: race, sex, socioeconomic status, marital status, COPD, smoking, obesity status, neoadjuvant chemotherapy administration, and tumor stage. An adjusted Cox Proportional-Hazards model was utilized for statistical analysis, enabling assessment of time to PSH from receipt of surgery and to account for censored patients. RESULTS: Of 1,838 patients identified as having undergone RC/IC, 132 patients (7 %) developed PSH in the followup period. The median time to PSH was 11.5 months (IQR: 6.5-18.7 months). The greatest risk factor in our cohort of patients for development of PSH was obesity (HR 2.05, 95% CI 1.48-2.98). The lowest socioeconomic quartile was also associated with greater risk of PSH (HR 1.49, 95% CI 1.01-2.22). Sex, COPD diagnosis, gender, race, smoking status, neoadjuvant chemotherapy, and tumor stage were not significantly associated with risk of PSH, although the female sex, Black/Hispanic race, and pT4 lesions showed elevated HR estimates. Marital status of “Divorced/Separated/Widowed” was significantly associated with PSH (HR 1.66, 95% CI 1.04-2.66) vs. “Married”, however due to a large portion of “unknown” marital status in our cohort, this finding may not be clinically meaningful. CONCLUSIONS: While the SEER-MD incidence rate is far below 50%, this reflects a mutable coding process subject to variation in capture by provider. With the available cohort, our model demonstrated an increased risk of PSH for obese and low SES patients undergoing RC/IC surgery. Both weight loss prevention strategies and careful symptom monitoring must be pursued in this population. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e890 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Diboro Kanabolo More articles by this author Sarah Holt More articles by this author Jonathan Wright More articles by this author George Schade More articles by this author Expand All Advertisement PDF downloadLoading ...

Feasibility of Electrodermal Activity and Photoplethysmography Data Acquisition at the Foot Using a Sock Form Factor.

Wearable devices have been shown to play an important role in disease prevention and health management, through the multimodal acquisition of peripheral biosignals. However, many of these wearables are exposed, limiting their long-term acceptability by some user groups. To overcome this, a wearable smart sock integrating a PPG sensor and an EDA sensor with textile electrodes was developed. Using the smart sock, EDA and PPG measurements at the foot/ankle were performed in test populations of 19 and 15 subjects, respectively. Both measurements were validated by simultaneously recording the same signals with a standard device at the hand. For the EDA measurements, Pearson correlations of up to 0.95 were obtained for the SCL component, and a mean consensus of 69% for peaks detected in the two locations was obtained. As for the PPG measurements, after fine-tuning the automatic detection of systolic peaks, the index finger and ankle, accuracies of 99.46% and 87.85% were obtained, respectively. Moreover, an HR estimation error of 17.40±14.80 Beats-Per-Minute (BPM) was obtained. Overall, the results support the feasibility of this wearable form factor for unobtrusive EDA and PPG monitoring.