Telemedicine & Advanced Technology Research Center

Abstract Background: Combinations of antibody-drug conjugates and immunotherapy, such as trastuzumab deruxtecan (T-DXd) and rilvegostomig (rilve), respectively, offer promising efficacy but are associated with a heightened risk of drug-induced interstitial lung disease (ILD)/pneumonitis. Early detection and management are critical for optimizing patient safety, yet there are no standard protocols for real-time evaluation. We hypothesized that vigilant monitoring would enable early detection, prevent symptoms, and minimize the chance of treatment delays while testing novel therapeutic combinations that have a potential risk of ILD. Methods: We tested the combination of T-DXd and rilve administered every 3 weeks in the I-SPY2.2 phase 2 platform trial (NCT01042379), which enrolls patients with clinical stage II/III breast cancer commencing neoadjuvant systemic therapy. Given the potential risk of overlapping pulmonary toxicity of these two agents, we added rigorous monitoring with pulmonary function tests (PFTs), six-minute walk test (6MWT), and high-resolution chest CT (HRCT) scanning pretreatment and every 6 weeks thereafter. A real-time safety workflow was implemented, with pre-specified criteria for halting treatment and escalation to the next block of treatment. All abnormal findings reported on chest CT by site radiologist were centrally reviewed in real time by the study pulmonologist (T.K.) and cases of suspected ILD were adjudicated promptly by a safety committee consisting of the pulmonologist and several medical oncologists, enabling early study drug interruption and therapeutic interventions. Toxicity data were evaluated in the first 51 patients treated with T-DXd plus rilve, and a preplanned hold was initiated until safety was ascertained by the data and safety monitoring board. Results: Safety data were evaluated in the first 51 patients receiving T-DXd plus rilve. Eight ILD events were confirmed (15.68% incidence): 5 grade 1, 2 grade 2, and 1 grade 3. One patient had an early chest CT scan because of dyspnea. All cases were identified by HRCT scans; PFTs and 6MWT did not enhance early detection and were subsequently dropped from the monitoring protocol. No patient was symptomatic for more than 24 hours. Radiographic findings resolved within 14-55 days. Patients with grade 2 & 3 ILD were treated with corticosteroids. No cases of ILD required intensive care or escalated therapy beyond steroids. Early treatment escalation to the subsequent block of therapy occurred in 3 patients; all 3 patients were subsequently able to receive appropriate therapy. At the meeting, safety data from all 100 patients treated with this combination will be reported. Conclusion: Real-time, centralized monitoring and adjudication allowed for early detection and prompt management of ILD, which both mitigated severity and supported timely therapeutic management. Among the monitoring tools studied, HRCT scanning performed every 6 weeks proved most effective for early ILD identification; PFT and 6MWT did not enhance early detection. This approach offers a potential framework for future studies assessing pulmonary safety in regimens combining agents that have a known risk for inducing ILD. Citation Format: T. Kulkarni, R. Nanda, H. S. Rugo, C. C. OSullivan, K. M. Kalinsky, J. C. Boughey, P. R. Pohlmann, J. Perlmutter, D. Yee, A. Borowsky, F. Symmans, N. Hylton, L. Van ‘t Veer, C. Yau, L. Esserman. Real-time monitoring for drug-induced interstitial lung disease with Trastuzumab Deruxtecan and Rilvegostomig combination therapy prevents persistent, symptomatic disease: Safety insights from the I-SPY2.2 platform trial [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-01-09.

In the original article published: Kalayjian T, McNally BJ, Calkins MW, et al. The SMHP™ position statement on therapeutic carbohydrate reduction for type 1 diabetes. J. metab. health. 2024;7(1), a100. https://doi.org/10.4102/jmh.v7i1.100, an author’s name was incorrectly spelt. Instead of: Mirian Kalamian It should be: Miriam Kalamian The authors apologise for this error. The correction does not change the study’s findings, its significance or overall interpretation of the study’s results or the scientific conclusions of the article in any way.

While the public health emergency is over, telehealth and telepractice will continue to play a pivotal role in supporting health equity for diverse and vulnerable individuals in underserved communities. The American Occupational Therapy Association, the American Physical Therapy Association, the American Speech-Language-Hearing Association, and the American Telemedicine Association are professional associations representing the interests of more than 564,000 rehabilitation services professionals in the United States. These organizations have shared priorities including legislative, regulatory, and state-based advocacy efforts. Continued advocacy and promotion by professional organizations, providers and patients alike is necessary to ensure that all rehabilitation providers are included in any telehealth lists of federally and state approved providers. In addition, key health care industry stakeholders want telehealth to be a permanent option for care delivery and ensure that telehealth will remain widely available to support health equity and access to critical rehabilitation services for all.

Introduction. Timely differential diagnosis between densely and sparsely granulated somatotrophic tumors allows predicting the most probable scenario of acromegaly course, receptor phenotype and proliferative potential of tumor cells, risk of continued postoperative growth, as well as the efficacy of planned drug therapy with first-generation somatostatin receptor ligands.Aim. To validate cytological, radiological and therapeutic predictors allowing to evaluate the morphofunctional composition of somatotrophic tumors and to predict sensitivity to first-generation somatostatin receptor ligands.Materials and methods. 525 patients (153 men) aged 60.2 ± 14.0 years receiving drug therapy with first-generation somatostatin receptor ligands for 72.0 ± 51.9 months were examined.Results. Treatment efficacy was evaluated according to the final level of IGF-1 index (≤1) and compared with the data of pathomorphologic (97 patients) and repeated radiologic (53 patients) examination. The influence of cellular composition of densely and sparsely granulated somatotrophic tumors on immunohistochemical and radiologic characteristics with the designation of leading predictors of morphologic identification of somatotrophic tumors was investigated. Additional radio markers for quantitative assessment of relative intensity of tumor signal on T2-, T1and (T2-T1)-weighted MRI for non-invasive differential diagnostics of densely and sparsely granulated somatotrophic tumors and determination of optimal treatment tactics were proposed. The expediency of using pharmacotherapeutic testing with short-term (3–6 months) first-generation somatostatin receptor ligands administration to assess the intactness of receptor and postreceptor mechanisms and to choose optimal drug therapy was substantiated.Conclusion. The precision approach based on comprehensive clinical, radiological, pathomorphological and functional characteristics allows stratification of patients with acromegaly to optimize treatment benefit. Achievement of acromegaly control in drug therapy with first-generation somatostatin receptor ligands depends on tumor volume and its hormonal activity, absolute and relative expression of the 2nd subtype of somatostatin receptors, severity of destructive changes and features of cellular composition. In case of refractoriness to first-generation somatostatin receptor ligands, the use of pegvisomant is expedient.

It is well established that individuals differ in their response to sleep loss. However, existing methods to predict an individual's sleep-loss phenotype are not scalable or involve effort-dependent neurobehavioural tests. To overcome these limitations, we sought to predict an individual's level of resilience or vulnerability to sleep loss using electroencephalographic (EEG) features obtained from routine night sleep. To this end, we retrospectively analysed five studies in which 96 healthy young adults (41 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects into sleep-loss phenotypic groups, we extracted two EEG features from the first sleep cycle (median duration: 1.6 h), slow-wave activity (SWA) power and SWA rise rate, from four channels during the baseline nights. Using these data, we developed two sets of logistic regression classifiers (resilient versus not-resilient and vulnerable versus not-vulnerable) to predict the probability of sleep-loss resilience or vulnerability, respectively, and evaluated model performance using test datasets not used in model development. Consistently, the most predictive features came from the left cerebral hemisphere. For the resilient versus not-resilient classifiers, we obtained an average testing performance of 0.68 for the area under the receiver operating characteristic curve, 0.72 for accuracy, 0.50 for sensitivity, 0.84 for specificity, 0.61 for positive predictive value, and 3.59 for likelihood ratio. We obtained similar performance for the vulnerable versus not-vulnerable classifiers. These results indicate that logistic regression classifiers based on SWA power and SWA rise rate from routine night sleep can largely predict an individual's sleep-loss phenotype.

Animal studies are typically utilized to understand the complex mechanisms associated with toxicant-induced hepatotoxicity. Among the alternative approaches to animal studies, in vitro pooled human hepatocytes have the potential to capture population variability. Here, we examined the effect of the hepatotoxicant thioacetamide on pooled human hepatocytes, divided into five lots, obtained from forty diverse donors. For 24 h, pooled human hepatocytes were exposed to vehicle, 1.33 mM (low dose), and 12 mM (high dose) thioacetamide, followed by RNA-seq analysis. We assessed gene expression variability using heat maps, correlation plots, and statistical variance. We used KEGG pathways and co-expression modules to identify underlying physiological processes/pathways. The co-expression module analysis showed that the majority of the lots exhibited activation for the bile duct proliferation module. Despite lot-to-lot variability, we identified a set of common differentially expressed genes across the lots with similarities in their response to amino acid, lipid, and carbohydrate metabolism. We also examined efflux transporters and found larger lot-to-lot variability in their expression patterns, indicating a potential for alteration in toxicant bioavailability within the cells, which could in turn affect the gene expression patterns between the lots. Overall, our analysis highlights the challenges in using pooled hepatocytes to understand mechanisms of toxicity.

Toxidromes constitute patterns of symptoms and signs caused by specific toxic effects that guide emergency treatments. Computational identification of chemicals that cause different toxidromes allows us to rapidly screen novel compounds and compound classes as to their potential toxicity. The aim of the current study was to create a computational toolset that can map chemicals to their potential toxidromes. Hence, we evaluated the performance of a state-of-the-art deep learning method—the recently developed communicative message passing neural network (CMPNN)—for its ability to overcome the use of small datasets for training deep learning models. Our results indicated that multi-task training—a technique known for its ability to use multiple small datasets to train conventional deep neural networks—works equally well with CMPNN. We also showed that CMPNN-based ensemble learning results in more reliable predictions than those obtained using a single CMPNN model. In addition, we showed that the standard deviations of individual model predictions from an ensemble of CMPNN models correlated with the errors of ensemble predictions and could be used to estimate the reliability of ensemble predictions. For toxidromes that do not have well-defined molecular mechanisms or sufficient data to train a deep learning model, we used the similarity ensemble approach to develop molecular structural similarity-based toxidrome models. We made the toolset developed in this study publicly accessible via a web user interface at https://toxidrome.bhsai.org/.

Sleep loss impairs cognition; however, individuals differ in their response to sleep loss. Current methods to identify an individual's vulnerability to sleep loss involve time-consuming sleep-loss challenges and neurobehavioural tests. Here, we sought to identify electroencephalographic markers of sleep-loss vulnerability obtained from routine night sleep. We retrospectively analysed four studies in which 50 healthy young adults (21 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects as resilient or vulnerable to sleep loss, we extracted three electroencephalographic features from four channels during the baseline nights, evaluated the discriminatory power of these features using the first two studies (discovery), and assessed reproducibility of the results using the remaining two studies (reproducibility). In the discovery analysis, we found that, compared to resilient subjects, vulnerable subjects exhibited: (1) higher slow-wave activity power in channel O1 (p < 0.0042, corrected for multiple comparisons) and in channels O2 and C3 (p < 0.05, uncorrected); (2) higher slow-wave activity rise rate in channels O1 and O2 (p < 0.05, uncorrected); and (3) lower sleep spindle frequency in channels C3 and C4 (p < 0.05, uncorrected). Our reproducibility analysis confirmed the discovery results on slow-wave activity power and slow-wave activity rise rate, and for these two electroencephalographic features we observed consistent group-difference trends across all four channels in both analyses. The higher slow-wave activity power and slow-wave activity rise rate in vulnerable individuals suggest that they have a persistently higher sleep pressure under normal rested conditions.

During U.S. Army basic combat training (BCT), women are more prone to lower-extremity musculoskeletal injuries, including stress fracture (SF) of the tibia, with injury rates two to four times higher than those in men. There is evidence to suggest that the different injury rates are, in part, due to sex-specific differences in running biomechanics, including lower-extremity joint kinematics and kinetics, which are not fully understood, particularly when running with external load. To address this knowledge gap, we collected computed tomography images and motion-capture data from 41 young, healthy adults (20 women and 21 men) running on an instrumented treadmill at 3.0 m/s with loads of 0.0 kg, 11.3 kg, or 22.7 kg. Using individualized computational models, we quantified the running biomechanics and estimated tibial SF risk over 10 weeks of BCT, for each load condition. Across all load conditions, compared to men, women had a significantly smaller flexion angle at the trunk (16.9%–24.6%) but larger flexion angles at the ankle (14.0%–14.7%). Under load-carriage conditions, women had a larger flexion angle at the hip (17.7%–23.5%). In addition, women had a significantly smaller hip extension moment (11.8%–20.0%) and ankle plantarflexion moment (10.2%–14.3%), but larger joint reaction forces (JRFs) at the hip (16.1%–22.0%), knee (9.1%–14.2%), and ankle (8.2%–12.9%). Consequently, we found that women had a greater increase in tibial strain and SF risk than men as load increases, indicating higher susceptibility to injuries. When load carriage increased from 0.0 kg to 22.7 kg, SF risk increased by about 250% in women but only 133% in men. These results provide quantitative evidence to support the Army’s new training and testing doctrine, as it shifts to a more personalized approach that shall account for sex and individual differences.

The ADvanced VIrtual Support for OpeRational Forces (ADVISOR) program is a synchronous telemedicine system developed in 2017 to provide 24/7 remote expert support to U.S. Military and NATO clinicians engaged in medical care in austere locations. Infectious disease (ID) remains the highest consulted service since 2018 and is currently staffed by 10 adult and pediatric ID physicians within the Military Health System. We conducted a retrospective review of the ID ADVISOR calls between 2017 and 2022 to identify trends and better prepare military ID physicians to address urgent ID consultations in overseas settings. Health records of the ID consultations between July 2017 and January 2022 were reviewed for local caregiver and patient demographics, case descriptions, consultant recommendations, and outcomes. A "not research" determination was made by the Brooke Army Medical Center Human Research Protections Office. ID physicians received 57 calls for 60 urgent patient consultations. Most calls were from countries in the Middle East or in Southwest Asia (United States Central Command (USCENTCOM)), followed by countries in Africa (United States Africa Command (USAFRICOM)). The majority of patients were active duty U.S. Military and were generally male with median age of 25 years. All consults involved an initial phone consultation and 30% continued over email. Ninety percent of the calls were initiated by physicians, and the median time from injury or illness-onset to consult was 3 days. Seventy percent of the consult questions involved treatment and further diagnostics, but one-third of cases required assistance with management of disease prevention. Multidrug-resistant or nosocomial infections, animal or bite exposure, malaria and malaria prevention, febrile illness, and blood-borne pathogen exposure accounted for 63% of the consults. Collaboration with other specialties took place in a minority of cases, and follow-up contact was recommended 20% of the time. Most recommendations involved adjusting drug regimens or further testing. Medical evacuation was only recommended in five of the cases. Although there was limited ability for follow-up, no known deaths occurred. A high proportion of calls to the ID ADVISOR line are relevant to the overlapping content areas of infection prevention, force protection, and outbreak response. Most patients requiring urgent ID consultation were managed successfully without evacuation. The current military-unique ID fellowship curriculum is consistent with the encountered diagnoses per the ID ADVISOR line, and high-yield individual topics have been identified.