ABSTRACT Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to intensive care units (ICUs) of Mayo Clinic Hospitals over 8-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status. Of 19,177 patients, 42% were female with a median age of 65 (interquartile range [IQR], 55–76) years, The Acute Physiology, Age, and Chronic Health Evaluation III score of 70 (IQR, 56–87), hospital length of stay (LOS) of 7 (IQR, 4–12) days, and ICU LOS of 2 (IQR, 1–4) days. Four distinct trajectories were identified: fast recovery (27% with a mortality rate of 3.5% and median hospital LOS of 3 (IQR, 2–15) days), slow recovery (62% with a mortality rate of 3.6% and hospital LOS of 8 (IQR, 6–13) days), fast decline (4% with a mortality rate of 99.7% and hospital LOS of 1 (IQR, 0–1) day), and delayed decline (7% with a mortality rate of 97.9% and hospital LOS of 5 (IQR, 3–8) days). Distinct trajectories remained robust and were distinguished by Charlson Comorbidity Index, The Acute Physiology, Age, and Chronic Health Evaluation III scores, as well as day 1 and day 3 SOFA ( P < 0.001 ANOVA). These findings provide a foundation for developing prediction models and digital twin decision support tools, improving both shared decision making and resource planning.
A Hybrid Simulation Approach for Modeling Critical Care Delivery in ICU
Background Women with endometriosis are more likely to have migraine. The mechanisms underlying this co-morbidity are unknown. Prolactin, a neurohormone secreted and released into circulation from the anterior pituitary, can sensitize sensory neurons from female, but not male, rodents, monkeys and human donors. Methods We used a syngeneic model of endometriosis to determine whether elevated prolactin levels can sensitize trigeminal ganglion neurons and increase vulnerability to migraine pain. Results Mice with endometriotic lesions showed increased serum prolactin levels and developed persistent abdominal, but not cephalic, allodynia. However, inhalation of a transient receptor potential ankyrin 1 agonist, umbellulone, a known environmental trigger of headache in some patients, elicited cephalic allodynia in mice with endometriosis but not sham controls, suggesting that endometriosis can promote sensitization of trigeminal neurons and migraine attacks. Endometriosis dysregulated the expression of prolactin receptor isoforms in trigeminal neurons and increased their excitability measured by in vitro patch clamp electrophysiology. Inhibition of pituitary prolactin following a 2-week treatment with a dopamine receptor agonist, cabergoline, prevented cephalic allodynia elicited by activation of trigeminal afferents with umbellulone. Cabergoline treatment also normalized the expression of prolactin receptor isoforms in trigeminal ganglia and the hyperexcitability of trigeminal neurons. Conclusions These data demonstrate that circulating prolactin in endometriosis promotes vulnerability to migraine through sensitization of trigeminal afferents. Clinically available dopamine receptor agonists or novel monoclonal antibodies targeting prolactin signaling may be effective for migraine prevention in women with endometriosis.
Distinguishing Chronic Inflammatory Demyelinating Polyneuropathy From Mimic Disorders: The Role of Statistical Modeling
ABSTRACTBackground and AimsChronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is difficult to distinguish from mimicking disorders, with misdiagnosis resulting in IVIG overutilization. We evaluate a clinical‐electrophysiological model to facilitate CIDP versus mimic neuropathy prediction.MethodsUsing the European Academy of Neurology/Peripheral Nerve Society (EAN/PNS) 2021 CIDP guidelines we derived 26 clinical and 144 nerve conduction variables. The model was generated and validated utilizing total CIDP (n = 129) and mimics (n = 309); including (1) IgG4‐nodopathies; (2) POEMS (polyneuropathy–organomegaly–endocrinopathy–monoclonal protein‐skin changes); (3) anti‐myelin‐associated‐glycoprotein; (4) paraneoplastic; (5) Waldenström B‐cell lymphoma; (6) diabetic neuropathies; (7) amyloidosis; (8) Charcot–Marie–Tooth; (9) motor neuropathies/neuronopathies; and (10) idiopathic‐inflammatory‐myopathies.ResultsWe analyzed 9282 clinical and 51 408 electrophysiological data points. Univariate analysis identified 11 of 26 clinical variables with significant odds ratios. A multivariate regression model using four clinical and two electrophysiologic variables achieved 93% area‐under‐curve (95% CI 91–95): progression over 8 weeks (OR 40.66, 95% CI 5.31–311.36), absent autonomic involvement (OR 17.82, 95% CI 2.93–108.24), absent muscle atrophy (OR 16.65, 95% CI 3.27–84.73), proximal weakness (OR 3.63, 95% CI 1.58–8.33), ulnar motor conduction velocity slowing < 35.7 m/s (OR 5.21, 95% CI 2.13–12.76), and ulnar motor conduction block (OR 13.37, 95% CI 2.47–72.40). A web‐based probability calculator (https://news.mayocliniclabs.com/cidp‐calculator/) was developed, with 100% sensitivity and 68% specificity at a 92% probability threshold. Specificity improved to 93% when considering “red flags,” electrophysiologic criteria, and laboratory testing.InterpretationA probability calculator using clinical electrophysiological variables assists CIDP differentiation from mimics, with scores below 92% unlikely to have CIDP. The highest specificity is achieved by considering clinical “red flags,” electrophysiologic demyelination, and laboratory testing.
Behavioral and Physiological Responses of Therapy Dogs to Animal-Assisted Treatment in an Inpatient Stroke Rehabilitation Program
Therapy dogs have been increasingly incorporated into a variety of medical treatment programs to improve patients’ treatment outcomes and wellbeing. However, research investigating the stress level of therapy dogs in this setting is limited. This is the first randomized–controlled and prospective study that investigated the wellbeing of therapy dogs in an inpatient stroke rehabilitation program. In this study, 14 therapy dog–handler pairs were embedded in an inpatient stroke rehabilitation program to provide animal-assisted treatment (AAT). These therapy dog–handler pairs actively participated in stroke rehabilitation by walking with the patient, playing fetch with the patient, and being petted/brushed by the patient, amongst various other AAT activities. To measure canine stress responses during the rehabilitation sessions, salivary cortisol and oxytocin concentrations, heart rate and heart rate variability, tympanic membrane temperature, and a behavioral evaluation were recorded before and after interactions with the patient. The results demonstrated that therapy dogs had significantly decreased heart rate and increased heart rate variability after the AAT session. Right tympanic temperature significantly increased after the session, but there was no significant difference in terms of salivary cortisol or oxytocin levels, nor in stress-related behavioral evaluations after the AAT session. Taken together, the results suggest that incorporating AAT into an inpatient stroke rehabilitation program did not induce stress in the therapy dogs, and that the therapy dogs may have been more relaxed after the session.
The role of social, economic, and medical marginalization in cancer clinical trial participation inequities: A systematic review
Abstract Extant literature reveals how patients of marginalized social identities, socioeconomic status (SES), and medical experiences – especially patients of color and older adults – are underrepresented in cancer clinical trials (CCTs). Emerging evidence increasingly indicates CCT underrepresentation among patients of lower SES or rural origin, sexual and gender minorities, and patients with comorbid disability. This review applies an intersectional perspective to characterizing CCT representativeness across race and ethnicity, age, sexual and gender identity, SES, and disability. Four databases were systematically queried for articles addressing CCT participation inequities across these marginalizing indicators, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. One hundred one articles were included in a qualitative evaluation of CCT representativeness within each target population in the context of their intersectional impacts on participation. Findings corroborate strong evidence of CCT underrepresentation among patients of color, older age, lower SES, rural origin, and comorbid disabling conditions while highlighting systemic limitations in data available to characterize representativeness. Results emphasize how observed inequities interactively manifest through the compounding effects of minoritized social identity, inequitable economic conditions, and marginalizing medical experiences. Recommendations are discussed to more accurately quantify CCT participation inequities across underserved cancer populations and understand their underpinning mechanisms.
The Impact of Engaging Transplant Recipients in Health Care Policy Deliberations
Introduction: There are discrepant definitions of both iron deficiency and anemia in pregnancy. It is recognized that iron requirements increase during pregnancy, particularly in the third trimester, and that deficiencies should be corrected to avoid adverse maternal-fetal outcomes. While low dose iron supplementation is recommended for all pregnant persons (ACOG Bulletin 233), dosing through prenatal vitamins varies widely. Additionally, despite the epidemic of iron deficiency in reproductive-age females globally and availability of high-value biomarkers (e.g., ferritin), current guidelines only recommend screening for iron deficiency during pregnancy in the presence of anemia. As anemia is the terminal manifestation of iron deficiency and reference ranges vary by organization, these guidelines and practices warrant further investigation and discussion. Methods: Retrospective review and analysis of the electronic health record at Mayo Clinic (Rochester, MN) was performed for obstetric deliveries between June 2022 and May 2023. Iron deficiency was defined as a ferritin <50 mcg/L and anemia was defined as a hemoglobin <11 g/dL. Results: A total of 2,141 unique deliveries were identified. The median age at delivery was 31 years old (range: 15 - 45) with 82% identifying as white. Anemia was documented in 42% (n=904) of pregnancies at least once throughout gestation, with an increasing frequency of 2% (n=43) in the first trimester, 11% (n=230) in the second trimester, 17% (n=361) in the third trimester, and 38% (n=803) from admission for delivery through the peri-partum period. There were five documented pRBC transfusions prior to admission for delivery; however, from admission for delivery through the peri-partum period, there were a total of 102 documented pRBC transfusions. In total, 15% (n=318) of pregnancies were screened for iron deficiency through ferritin testing. Ferritin levels were measured 415 times with 23% (n=96) occurring between the last menstrual period and 12 weeks gestational age (WGA), 24% (n=100) occurring between 13-27 WGA, 40% (n=164) occurring between 28-40 WGA, and 13% (n=55) occurring post-partum. Iron deficiency was found in 70% (n=67), 79% (n=79), 80% (n=164), and 78% (n=43) of measured ferritin levels, respectively. Despite the paucity of screening, prescriptions for oral iron increased throughout gestation with supplementation in pregnancy for 8% (n=170) prior to 12 WGA, 14% (n=290) for those 13-27 WGA, and 23% (n=489) for those 28-40 WGA. Similarly, intravenous iron infusions increased throughout gestation with supplementation in pregnancy for 0.3% (n=7) prior to 12 WGA, 0.7% (n=16) for those 13-27 WGA, and 4% (n=95) for those 28-40 WGA. Prenatal vitamins were documented in over 90% of pregnancies throughout gestation, although the majority were non-prescription and contained variable amounts of elemental iron. Conclusions: Iron deficiency in pregnancy is underrecognized and undertreated. It follows that the accuracy of current reference ranges for anemia in pregnancy are suspect without rigorous verification of replete iron stores in the reference population. Given potential implications for blood product utilization and prenatal care, additional studies are warranted to better characterize iron deficiency in pregnancy as well as clinical sequelae for both mothers and infants. Simultaneously, discussions are needed around current guidelines and recommendations for both screening and treating iron deficiency in pregnancy. Providers, institutions, and professional societies should pursue pragmatic quality improvement initiatives and equitable healthcare delivery efforts to optimize care for this vulnerable patient population at high risk of iron deficiency.
Real World First-Line Treatment Strategies and Outcomes in TP53 Mutated and Unmutated Mantle Cell Lymphoma
Introduction: Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) Prognosis is highly variable due to underlying biological and molecular heterogeneity. The first-line (1L) treatment paradigm for MCL continues to evolve with increasing use of bruton tyrosine kinase inhibitors (BTKi) and decreasing use of autologous stem cell transplant (ASCT). TP53 alterations are associated with inferior outcomes in MCL. The aim of this retrospective study is to determine treatment strategies and clinical outcomes in MCL patients based on TP53 gene mutation status. Methods: Retrospective data were collected from 19 institutions in the United States from 1/1993 to 1/2024. We examined treatment patterns and outcomes among MCL patients >18 years of age with known TP53 mutation status by sequencing. Patients who did not receive treatment were excluded. The analysis was stratified based on presence of TP53 mutations. Systemic therapies were categorized as chemo-immunotherapy (CIT), non-chemotherapy (including monoclonal antibodies, lenalidomide, venetoclax, and novel agents on clinical trial), and regimens containing BTKi. The primary outcome was overall survival (OS) and secondary outcomes were progression free survival (PFS) and time to next treatment (TTNT). OS and PFS were estimated with the Kaplan-Meier method and log-rank tests were used to compare groups. Results: 645 patients were included in the study, with 468 men (72.6%) and median age was 64 years (range 30-89). 230/645 patients (35.7%) had a TP53 mutation, of which 182 (79%) were identified prior to 1L. While the male/female distribution was the same between the mutated and unmutated groups, median age at diagnosis and MIPI risk score was higher in the TP53 mutated group (age 65.9 vs 63.1 yrs, p= 0.015; MIPI 6.4 vs 6.1, p<0.001). TP53 unmutated patients had a median of 1 line of therapy vs. 2 for the mutated group (p<0.001, range 1-8). Blastoid histology and higher ki67 were also associated with the TP53 mutated group (p=0.045, 0.01 respectively) The median OS was 14.2 years for TP53 unmutated and 8.3 years for TP53 mutated patients (p<0.0001). PFS in 1L was 0.95 years in TP53 mutated compared to 2.02 years in TP53 unmutated group (p<0.0001). Selection of 1L therapeutic strategy was not associated with presence of TP53 mutation (Χ2 p= 0.21) although more patients in the TP53 unmutated group underwent ASCT (119/415 vs 38/230; Χ2 p=0.0006) TP53 mutation was associated with inferior survival compared to TP53 unmutated patients for CIT in 1L but the difference did not reach statistical significance when non-chemotherapy regimens and regimens containing BTKi were used. For CIT in 1L, 5 year OS was 78% [71-84%] for unmutated compared to 58% [48-67%] for the mutated group (p=0.0001 ). For non-chemotherapy regimens, 5 year OS for unmutated patients was 73% [52- 86%] compared to 52% [25-73%] for the mutated group (p=0.09). For regimens containing BTKi, 5 year OS for unmutated was 93% [81-97%] compared to 57% [28-78%] for mutated (p=0.07). Within the TP53 mutated group, there were no differences in any clinical outcomes between those receiving CIT, non-chemotherapy, or BTKi in 1L. While median OS appeared numerically longer in the BTKi group (14.4 yrs vs 8.8 yrs for CIT and 6.8 yrs for non-chemotherapy), the difference did not reach statistical significance (p=0.58). In contrast,TP53 unmutated patients who received CIT in 1L had better TTNT (p=0.0039) compared to those in non-chemotherapy and BTKi groups. There was no improvement in PFS (p=0.79) or OS (p=0.47). Conclusions To our knowledge this is the largest retrospective real world dataset of MCL treatment outcomes stratified by TP53 mutation. As in prior studies, TP53 mutation portends a worse prognosis in MCL compared to TP53 unmutated patients, but outcomes are better than historically reported. CIT in 1L was not associated with improved OS in either group. Irrespective of TP53 mutation status, incorporation of BTKi in first line was not associated with improved clinical outcomes. The gap in OS between TP53 mutated and unmutated MCL may be narrowing as treatment paradigms shift away from intensive induction chemotherapy and ASCT, and due to an increasing number of effective therapies for relapsed patients. Clinical trials of novel agents are needed to further improve the OS of TP53 mutated MCL patients.
Comprehensive Characterization of the Plasma Proteome of Multiple Myeloma and Its Precursor Conditions and Identification of a Proteomic Signature to Improve Risk Prediction of Disease Progression
Introduction Multiple Myeloma (MM) precursors Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM) have variable risk of progression to active MM, and identifying which patients may progress remains a clinical challenge. Deep proteome profiling of peripheral blood (PB) plasma may advance non-invasive precursor disease staging, monitoring and characterization. Here, we performed plasma proteomic profiling on patients across the MM disease continuum as well as progressive and stable disease to provide insights into MM disease biology and identify protein-based high-risk disease features that may improve prognostication. Methods We performed high-throughput profiling of >5400 proteins using the Olink® Explore HT library and Proximity Extension Assay (PEA) technology. We profiled 529 PB plasma samples from 485 individuals, including MGUS (n=100), SMM (n=203), MM (n=100), and healthy donors (HDs) (n=82). Sequential samples from SMM-MM progressors (n=32) and stable SMM-SMM non-progressors (n=32) were also profiled, where precursor samples ranged 1.04-6.91 years (median 2.33 years) prior to MM progression. T-tests, ANOVAs, and linear mixed effect (LME) models were used to identify significant proteins across disease stages, progression status, and time. Results were adjusted for multiple testing using Benjamini-Hochberg procedure. A subset of 86 individuals (13 HDs, 14 MGUS, 41 SMM, 18 MM) also had single-cell RNA sequencing (scRNA-seq) performed on tumor and immune cells from paired PB/BM collected at the same timepoint to enable cellular mapping of signals detected in plasma. Results We successfully captured significantly dysregulated proteins including proteins highly expressed on the surface of plasma cells, such as BCMA, SLAMF7 and CD38, highlighting the utility of PEA technology to monitor soluble levels of clinically relevant targets. Given SMM patients are clinically heterogeneous and can resemble MGUS or MM, we aimed to improve discrimination of disease states using biological features obtained from the plasma proteome. We developed a classifier using an Elastic Net model for each stage, where plasma proteins such as SLAMF7, BCMA, TACI, FCRL5 and others had the highest importance scores for the model. We demonstrated 97% SMM/MM samples could be identified from healthy samples (AUC=0.82), indicating our classifier could reliably screen disease-related cases. Moreover, 84% of SMM cases were correctly classified as clinically defined SMM, while misclassified samples were labelled as MM cases. Interestingly, the misclassified patients had consistently rising M-spike levels during clinical follow-up but without a shift in clinical stage or risk status, suggesting the plasma proteome may provide earlier indication of evolving disease. Since proteomic information may also hold value for improved risk stratification, we evaluated protein levels in precursor stage timepoint samples from SMM-MM progressors and stable SMM non-progressors. We identified a prognostic five-protein signature that was significantly elevated in SMM-MM progressors, of which BCMA and TACI were top proteins, as well as proteins vital for calcium homeostasis and integrin-mediated cell adhesion. BCMA and TACI levels also had a strong positive correlation with BM plasma cell infiltration, which suggests these proteins may be useful surrogates of BM tumor burden during routine blood-based assessment of precursor patients. Lastly, integrative analysis of scRNA-seq of tumor and immune cells was used to elucidate cell origin level information of the prognostic signature proteins. Four proteins were highly expressed in malignant versus non-malignant plasma cells, suggesting our prognostic signature partially provides a readout of plasma cell biology. Meanwhile, one protein was constitutively expressed on most leukocytes, suggesting that the interplay of other cell types in the immune microenvironment involved in progression may also be reflected in the plasma. Conclusion We performed the first comprehensive analysis of the plasma proteome of MM and its precursor conditions. Overall, we developed a classifier that utilizes plasma proteins alone to accurately classify disease stages and identified a prognostic protein signature associated with progressive disease.