United States

Background
Dementia is a pressing global health challenge affecting more than 50 million people worldwide with a net impact on the global economy of 1 trillion USD. One aspect of the condition is the potential for deterioration to the point where a crisis situation occurs requiring emergency intense psychiatric support, either in the form of intense community care or admission to an inpatient facility. Such care is only needed for a minority of patients. If patients can be identified at the point of diagnosis it raises the potential for stratified care pathways for those at highest risk with the aim of improving outcomes. Our previous work from two United Kingdom sites found that younger, male patients, and those with impaired cognition were at risk of deteriorating. In this study, we aimed to create mathematical models of risk and use the results to develop a mobile application that is ready for clinical use. 

Methods
Using on our retrospective cohort study (n=25,326) we have identified several epidemiological, and behavioural factors that showed the highest association with subsequent need for enhanced care. The top 10 variables were selected using dominance analysis and systematic regression in Cambridgeshire and the models externally validated in a second data set from London. The same threshold was used for classifying patients into the high and low risk groups as in our previous retrospective study. 

Results
The top predictive variables in Cambridgeshire were age (OR:0.97, p&lt;0.001), gender (OR:1.74, p&lt;0.001), marital status (OR: 1.34, p&lt;0.05), dementia subtype (OR&lt;0.61, p&lt;0.05), and the following 6 Health of the Nation Outcome Score (HoNOS) subcategories: behaviour (OR: 1.43, p&lt;0.001), hallucinations (OR:1.20, p&lt;0.05), cognitive (OR:1.19, p&lt;0.05), disability (OR: 0.79, p&lt;0.001), other mental and behavioural problems (OR:1.23, p&lt;0.01) and relationships(OR: 1.26, p&lt;0.01). The AUC was 0.74-0.79 for 1 to 4 years after diagnosis in Cambridgeshire with a similar AUC of 0.74 in the validation dataset in London. The resulting PREDICDEM app is a tool which can be used to stratify people in terms of risk at the point of dementia diagnosis.

Conclusion
We have used routinely collected clinical data to model risk of needing enhanced care in dementia. This data can be incorporated into models of risk prediction and into a smartphone app. This will allow stratification of patients at the time of diagnosis and facilitate trials of interventions to decrease the risk of crisis events.


AMA Research Challenge 2025 

The development of a mobile app to predict the need for enhanced care for people with dementia


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Join the AMA Research Challenge poster symposium and semifinals to explore top research posters and score posters in the semifinals (an AMA member exclusive opportunity).

Background
Dementia is a pressing global health challenge affecting more than 50 million people worldwide with a net impact on the global economy of 1 trillion USD. One aspect of the condition is the potential for deterioration to the point where a crisis situation occurs requiring emergency intense psychiatric support, either in the form of intense community care or admission to an inpatient facility. Such care is only needed for a minority of patients. If patients can be identified at the point of diagnosis it raises the potential for stratified care pathways for those at highest risk with the aim of improving outcomes. Our previous work from two United Kingdom sites found that younger, male patients, and those with impaired cognition were at risk of deteriorating. In this study, we aimed to create mathematical models of risk and use the results to develop a mobile application that is ready for clinical use. 

Methods
Using on our retrospective cohort study (n=25,326) we have identified several epidemiological, and behavioural factors that showed the highest association with subsequent need for enhanced care. The top 10 variables were selected using dominance analysis and systematic regression in Cambridgeshire and the models externally validated in a second data set from London. The same threshold was used for classifying patients into the high and low risk groups as in our previous retrospective study. 

Results
The top predictive variables in Cambridgeshire were age (OR:0.97, p<0.001), gender (OR:1.74, p<0.001), marital status (OR: 1.34, p<0.05), dementia subtype (OR<0.61, p<0.05), and the following 6 Health of the Nation Outcome Score (HoNOS) subcategories: behaviour (OR: 1.43, p<0.001), hallucinations (OR:1.20, p<0.05), cognitive (OR:1.19, p<0.05), disability (OR: 0.79, p<0.001), other mental and behavioural problems (OR:1.23, p<0.01) and relationships(OR: 1.26, p<0.01). The AUC was 0.74-0.79 for 1 to 4 years after diagnosis in Cambridgeshire with a similar AUC of 0.74 in the validation dataset in London. The resulting PREDICDEM app is a tool which can be used to stratify people in terms of risk at the point of dementia diagnosis.

Conclusion
We have used routinely collected clinical data to model risk of needing enhanced care in dementia. This data can be incorporated into models of risk prediction and into a smartphone app. This will allow stratification of patients at the time of diagnosis and facilitate trials of interventions to decrease the risk of crisis events.


poster

Abstract Title: The Interface Between Host Microbiome and Common Medications 

Background: The human gut microbiome plays a critical role in drug metabolism, efficacy, and safety. While host genetics and comorbidities are known contributors to pharmacologic variability, emerging research highlights gut microbiota as a modifiable and underrecognized determinant. This narrative review synthesizes current evidence on bidirectional interactions between the gut microbiome and commonly prescribed medications in the U.S., including selective serotonin reuptake inhibitors (SSRIs), antihyperglycemics, ACE inhibitors, beta blockers, calcium channel blockers, Proton pump inhibitors (PPIs), and statins. 

Methods: A literature review was conducted using peer-reviewed primary research from PubMed and Google Scholar, limited to the past 20 years. Commonly prescribed medications were selected based on United States government’s Medical Expenditure Panel Survey (MEPS) data using the ClinCalc DrugStats database. The included drugs were fluoxetine, escitalopram, sertraline, duloxetine, quinapril, metoprolol, amlodipine, metformin, simvastatin, rosuvastatin, and esomeprazole. Eligible studies encompassed animal models, human interventional and observational studies, in vitro experiments, reviews, and meta-analyses. Non-peer-reviewed sources were excluded. 

Results: Studies show that antidepressants, particularly SSRIs such as fluoxetine and duloxetine, exhibit antimicrobial effects and reduce microbial diversity; meanwhile, gut bacteria like Streptococcus salivarius can bioaccumulate or inactivate these drugs, altering systemic concentrations and therapeutic responses. ACE inhibitors like quinapril are metabolized by Coprococcus comes, reducing oral bioavailability and potentially contributing to treatment-resistant hypertension, while also decreasing the abundance of pro-inflammatory microbes such as Klebsiella, which may support cardiometabolic health. Metformin improves glucose control partly by enriching beneficial microbes (e.g., Akkermansia, Butyricimonas); additionally, fecal microbiota transplantation from metformin-treated mice improves insulin sensitivity in humans. Beta blockers such as metoprolol undergo microbial metabolism that reduces drug bioavailability, while concurrently modulating microbial composition by increasing butyrate-producing taxa and decreasing pro-inflammatory species. Amlodipine is directly metabolized by gut microbes in fecalase models reducing drug availability; while also shifting microbial populations in ways that enhance gut barrier function. Statins influence bile acid metabolism and gut microbial profiles, contributing to their lipid-lowering effects; however, antibiotic-induced dysbiosis impairs statin efficacy in mice. PPIs reduce microbial diversity and increase pathogenic taxa such as Streptococcus, while the presence of Helicobacter pylori modulates PPI efficacy and associated risks. 

Conclusion: Drug-microbiome interactions are both class-specific and mechanistically diverse, involving microbial metabolism, drug bioaccumulation, immune modulation, and metabolic pathway shifts. These findings support a growing role for microbiome informed pharmacology and reinforce the need for further human studies to advance precision medicine and individualized treatment strategies.

The Interface Between Host Microbiome and Common Medications

Background
Chronic endometritis (CE) is defined by persistent inflammation of the endometrium, typically associated with microbial infections, including LPS-producing E. coli and Chlamydia. CE diagnosis occurs mainly in the setting of infertility. CE is commonly diagnosed by counting CD138+ plasma cells in stromal-dense areas of an endometrial biopsy. However, there is no standardized diagnostic criteria and plasma cells alone may be insufficient to reliably diagnose CE. Pathological diagnosis may be improved by measuring endometrial edema and increased endometrial stromal cell (eSC) density. Human eSCs express TLRs, including TLR4 and thus, are targets of LPS and other pathogen-associated molecular patterns (PAMPs). While previous studies identified increased eSC density and aberrant eSC functions in the setting of CE, these alterations have not been well-defined. In humans and the few species that menstruate, eSCs proliferate during the luteal phase and then eSCs decidualize (a differentiation process critical for implantation) during the mid-secretory phase. Our laboratory has pioneered the use of menstrual effluent (ME, shed endometrial tissue) for studying endometriosis. We hypothesize that infection-related alterations in eSCs will help better understand and diagnose CE.

Methods
Using ME collected from women (18-40 years) with no history of pelvic inflammatory disease, polycystic ovary syndrome, or endometriosis, eSCs were isolated and grown in culture media until confluency. Low passage ME-derived eSCs were treated with LPS (0-500 ng/ml) for 3 days and then analyzed for proliferation by CyQuant assay and decidualization potential by measuring the production of Insulin-like Growth Factor Binding Protein 1 (IGFBP1, a decidualization marker) by ELISA.

Results
Overall, proliferation assays revealed a significant increase in eSC numbers following LPS treatment compared to vehicle: 0 ng/ml vs. 25 ng/ml (p = 0.014), 0 ng/ml vs. 50 ng/ml (p < 0.0001), 0 ng/ml vs. 250 ng/ml (p = 0.0017). By contrast, decidualization assays revealed a significant decrease in IGFBP1 concentrations in LPS-treated conditions compared to vehicle: 0 ng/ml vs. 10 ng/ml (p = 0.0078), 0 ng/ml vs. 25 ng/ml (p = 0.0078).

Conclusion
LPS has opposing effects on eSC proliferation and decidualization. An increase in proliferation following LPS exposure supports the increased eSC density reported in the endometrium during CE and may promote endometrial polyp formation in confirmed CE cases. The decreased decidualization following LPS may contribute to the infertility observed in CE. Further research is needed to elucidate the potential mechanisms underlying these altered eSC phenotypes.

Defining the effects of chronic endometritis on the endometrium through menstrual effluent

Background: Rotator cuff repairs often fail due to insufficient biologic healing at the tendon-bone interface (enthesis). Patch augmentation has emerged as a promising strategy that promotes cellular infiltration, organized collagen deposition, and matrix remodeling. The objective of this review is to comprehensively evaluate the histologic and biochemical effects of scaffold augmentation, to compare the effectiveness of different augmentation materials, and to analyze commercially available implants with histologic evaluation in animals and human studies.

Methods: A PRISMA-guided search of PubMed, Scopus, and Embase through May 2025 identified forty-two eligible studies. Inclusion criteria were histologic and biochemical outcomes following rotator cuff repair with patch augmentation. Studies limited to biomechanical or imaging outcomes, in vitro or cadaveric models, reviews, editorials, technical notes were excluded. 

Results: Dermal matrix patches accelerated early neovascularization and collagen synthesis but often led to incomplete fibrocartilage formation and persistent type III collagen. ECM-derived patches showed progressive collagen alignment but were associated with inflammation. Synthetic polymers were successful at generating dense type 1 collagen with variable immune responses. Biologically augmented scaffolds demonstrated the highest collagen density and minimal macrophage infiltration. Demineralized bone matrix (DBM) achieved mature collagen crimp and fibrocartilage integration by eight weeks with low inflammation.

Among commercial products, REGENETEN, ArthroFLEX, and Dynagraft II demonstrated the most complete scaffold resorption and tendon-like remodeling. Conexa and Zimmer patches showed consistent integration, and Permacol and BioEnthesis exhibited limited improvements.

Conclusion: Patch augmentation enhanced healing following rotator cuff repair. Biologically augmented and DBM scaffolds yielded the most favorable histologic outcomes, followed by ECM-derived and synthetic patches. Dermal matrix patches showed strong early effects but lacked long-term integration. However, no definitive conclusions can be made due to the lack of high-quality human trials. These findings may guide scaffold selection and inform future design aimed at improving tendon-bone healing and reducing re-tear rates.

Rotator Cuff Patch Augmentation: Histologic Outcomes and Comparative Performance of Commercial Implants

Background
Industrial pollution has introduced toxic heavy metals—such as lead, mercury, and cadmium—into the environment, contributing to oxidative stress, DNA damage, and systemic health disorders. Marginalized and low-income communities of color are disproportionately affected due to proximity to industrial sites and legacy pollutants. Melanin, a biopolymer produced by melanocytes, is known for its protective role against ultraviolet radiation and oxidative damage. Emerging studies suggest that melanin may also function in heavy metal detoxification through binding and subsequent excretion via skin desquamation. However, the potential for melanin saturation and its consequences in chronically exposed individuals remain unclear.

Methods
A preliminary scoping review was conducted using PubMed with the search terms “melanin” and “heavy metal detoxification.” Fourteen peer-reviewed articles were identified and reviewed, with supplemental articles included via backward citation tracking and grey literature reviews. Articles were assessed for evidence of melanin-metal interactions, particularly the chelation capacity of eumelanin and pheomelanin. Emphasis was placed on mechanistic studies and environmental context, including disproportionate exposure among racially and socioeconomically marginalized communities.

Results
Experimental studies suggest that melanin binds various heavy metals—including lead, chromium, and arsenic—potentially reducing systemic toxicity. Eumelanin demonstrates higher metal-binding capacity than pheomelanin. Excretion via skin shedding may contribute to detoxification, though prolonged exposure could exceed melanin’s capacity, particularly in individuals with darker skin tones. Saturated melanin may lead to dermal bioaccumulation, localized oxidative stress, and chronic inflammation. Neuromelanin studies further support this metal-binding hypothesis, though translational human data are limited. Environmental racism and systemic inequities exacerbate exposure risks in communities of color, amplifying potential health burdens.

Conclusion
Melanin may play a dual role in detoxifying and accumulating heavy metals in the body. While protective at baseline, chronic exposure may shift melanin’s function toward a reservoir of toxicity, especially in individuals with greater melanin content and in communities facing environmental injustice. These findings underscore the need for further empirical research on melanin-metal interactions in humans and highlight the importance of addressing environmental and structural determinants of health in mitigating toxic exposures.


Melanin-Metal Interactions: A Double-Edged Shield in Environmental Toxicity and Health Disparities

Background
Dupilumab is a monoclonal antibody used to treat inflammatory skin diseases such as atopic dermatitis (AD) but does not treat collagen vascular diseases (CVD). Some studies suggest an association between AD and CVD, however, there is currently no literature presenting co-occurrent dermatomyositis (DM) with AD and its management with dupilumab. We present a unique case of severe AD with DM overlap unmasked by dupilumab.

Case Presentation
A 78-year-old woman presented with pruritic rashes on the forearms, upper sternum, and back. On physical examination she had scaly, pruritic plaques with violaceous erythema in shawl-like distribution, ragged cuticles, and widely distributed eczematous patches. Biopsy demonstrated spongiotic and interface epidermal change and dermal inflammation with eosinophils consistent with AD. She was treated with dupilumab and drastically improved, however, one year later still had pruritic areas on her scalp and neck and had overtly ragged cuticles. A repeat biopsy showed spongiosis and vacuolar interface dermatitis without eosinophils. The patient’s clinical and dermatopathological findings indicated dermatomyositis, and methotrexate was added to dupilumab for treatment. After two months of methotrexate, her symptoms improved.

Discussion
One possible explanation for our patient’s remarkable clinical response to dupilumab is that AD was exacerbating the inflammatory processes of DM. Some studies suggest an association between AD and CVD, implying a shared autoimmune mechanism. It is critical to consider the whole picture regarding a patient’s condition, including history and changes in dermatopathology, while also considering co-occurrent skin pathologies based on patient presentation and response to treatment.


Dupilumab unmasks histopathologic diagnosis of dermatomyositis in a patient with severe atopic dermatitis and dermatomyositis overlap

Background:
Due to the pandemic, virtual nursing is further utilized and shown to improve patient experiences, communication, and patient adherence. This study uses Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) top-box scores after its implementation across multiple U.S. healthcare centers to study patient experience.
Objective:
This study aims to assess the impact of virtual nursing on patient experience across multiple healthcare centers.
Methods:
HCAHPS top-box scores of patient experience were collected from 2020-2021, pre-implementation period of 2023-2024, and post-implementation of virtual nursing. Center A-C had virtual nursing implementation while D center had no implementation. Scores were categorized by hospital units (PCU, Med-Surg). The primary outcomes include scores for "Communication with Doctors," "Communication with Nurses," and "Rate the Hospital 0-10."
Results:
There was a significant increase in top-box scores for each category from 2020-2024. Healthcare center A had significant improvements in the ICU unit with scores improving for: nursing (+4.27%), doctor (+10.23%), and hospital (+5.22%) scores. Healthcare center B experienced declines after implementation. Healthcare Center C showed mixed results, with significant increases in doctor (+27.05%) and hospital (+18.23%) scores but a decline in nursing (-7.71%). The variability in scores indicates differences in the effectiveness of implementing virtual nursing. 
Conclusion:
Overall, virtual nursing implementation had a positive impact on patient experience. The variability between top-box scores convey the need for further research on its utility. Further studies can explore the institutional barriers of implementing virtual nursing and the long term impacts on healthcare.

The Implications of Virtual Nursing on Patient Experience and Satisfaction: A Multicenter Quality Improvement Analysis

Background
Gap years before medical school have become an increasingly popular opportunity for students to gain research, clinical, and other experience, leading to diverse medical school cohorts where students have varying lengths of time since last engaging in formal education. This underscores the need for medical schools to adapt curriculum designs to accommodate these diverse learner backgrounds. One way to approach this adaptation involves reevaluating how student performance is assessed in the preclerkship phase. McGovern Medical School utilizes a hybrid preclerkship grading system in which the first semester is graded on a pass/fail basis, and the second through fourth semesters are graded on a tiered basis (i.e. honors, high pass). This study explores how students’ perceptions on this grading system differs based on their educational backgrounds, and how these perceptions can inform broader discussions on preclerkship grading practices across medical schools nationwide.

Methods
Following exemption by the UTHealth Houston Center for Protection of Human Subjects Institutional Review Board, an online survey was distributed to third- and fourth-year students at McGovern Medical School. “Traditional” students were defined as those who matriculated without taking gap years; “non-traditional” students took one or more gap years before medical school. The survey included Likert-scale and free-response questions assessing perceptions of the hybrid system’s effectiveness and overall student satisfaction.

Results
71 medical students completed the survey, including 37 non-traditional students and 34 traditional students. No statistically significant differences in perceptions of the pass/fail and tiered grading components were observed between traditional and non-traditional students (p > 0.05). Overall, 88.9% of students agree that one semester of pass-fail grading offers sufficient time to adjust to the rigor of medical school. Furthermore, correlation analysis revealed a moderately positive association between students who felt pass/fail grading gave them adequate time to adjust and those who felt tiered grading later on increased motivation (Spearman’s rho = .62, p < .01). 

Conclusion
This study found no significant differences in perceptions of the preclerkship hybrid grading system between traditional and non-traditional students at McGovern Medical School, suggesting that the combination of an initial pass/fail semester followed by tiered grading is broadly acceptable across diverse educational backgrounds. As many U.S. medical schools continue to use tiered preclerkship grading, these results support the idea that integrating a pass/fail transition period may help students adjust to medical school regardless of their prior educational pathway, while preserving the motivational benefits of tiered grading. 


Comparing the Perceptions of Traditional and Non-Traditional Medical Students on a Hybrid Preclerkship Grading System

Disparities in Septicemia-related Mortality in the Black and White American Populations, 2000–2020

Co-authors:
Zachary Lebowitz, Berk Madendere, Rutgers New Jersey Medical School
Yazan Abboud, UCLA Medical School

Background and Aims: Racial disparities are a persistent determinant of health outcomes in the United States. Septicemia is a leading cause of death, yet long-term trends in race-specific mortality remain underexplored. This study analyzed racial disparities in septicemia-related mortality among non-Hispanic Black and non-Hispanic White adults from 2000–2020, stratified by age and sex.
Methods: Age-adjusted mortality rates (per 100,000, standardized to the 2000 U.S. population) were obtained from the CDC’s National Center for Health Statistics. Two age groups were assessed: younger adults (<55 years) and older adults (≥55 years). Joinpoint regression estimated annual percentage change (APC) and average APC (AAPC). Coincidence and parallelism tests evaluated differences by race and sex (α = 0.05).
Results: From 2000–2020, 764,504 septicemia-related deaths were recorded: 80.3% in Whites and 17.3% in Blacks. Mortality declined in both groups overall and among older adults, but more sharply in Blacks (AAPC: -2.36 vs. -0.48 overall; -2.46 vs. -0.68 in ≥55 years, Black vs. White, respectively). Among younger adults, mortality increased in Whites but declined in Blacks (AAPC: +1.38 vs. -1.16). Patterns were consistent across sexes: in younger adults, mortality rose in White males (+1.24) and females (+1.38) but declined in Black males (-1.45) and females (-1.16). Despite steeper declines, septicemia-related mortality remained higher in Blacks across all age and sex categories.
Conclusions: Between 2000 and 2020, septicemia mortality declined overall but diverged by race and age. Younger White adults experienced rising mortality, whereas Black adults saw sustained declines. Nonetheless, mortality remained disproportionately higher among Blacks across subgroups. These findings highlight persistent inequities and call for further research into underlying causes and targeted interventions.


Disparities in Septicemia-related Mortality in the Black and White American Populations, 2000–2020

Background: Cancer survivors frequently experience coexisting chronic diseases that extend beyond their primary diagnosis. This study aimed to identify independent predictors of self-reported cancer history using multivariable models incorporating chronic conditions, biomarkers, and body composition metrics in a nationally representative U.S. population.

Methods: Data were obtained from the National Health and Nutrition Examination Survey, covering adults aged ≥18 years from 1999 to 2018. Cancer history was determined by self-report. Candidate predictors included chronic health conditions (e.g., anemia, emphysema, bronchitis, liver disease, thyroid disorder, arthritis), body composition metrics derived from dual-energy X-ray absorptiometry such as appendicular lean mass index and additional variables including waist circumference, smoking status and systolic blood pressure. Multivariable survey-weighted logistic regression was used to identify predictors of cancer history, adjusting for age, sex, education, marital status, and income. Variables significant in univariable models were entered into a final multivariable model. Performance was evaluated using the area under the curve, and multicollinearity was assessed using variance inflation factors.

Results: Among 55,021 adults included in the dataset, 5,166 participants reported cancer history. In weighted descriptive analysis, individuals with cancer history had significantly higher prevalence of multiple chronic conditions, including emphysema, bronchitis, anemia, and arthritis.

In the final multivariable survey-weighted logistic regression model, adjusted for age, sex, education, marital status, and income, several conditions emerged as independent predictors of cancer history. Anemia (OR = 1.78), liver disease (OR = 1.76), emphysema (OR = 1.55), bronchitis (OR = 1.47), thyroid disorder (OR = 1.42), and arthritis (OR = 1.32) were all associated with increased odds of cancer history. Current smoking (OR = 1.35) and larger waist circumference (OR = 1.01 per cm) also remained significant. In contrast, higher appendicular lean mass index was associated with lower odds of cancer history (OR = 0.83), indicating a potential protective role of skeletal muscle mass. The final model demonstrated moderate discriminatory power with an area under the ROC curve of approximately 0.79.


Conclusion: A history of cancer is independently associated with a broad range of chronic conditions and unfavorable changes in body composition. Conditions such as anemia, emphysema, and low lean muscle mass were among the strongest predictors, reflecting a lasting systemic burden among cancer survivors. These findings underscore the need for comprehensive survivorship care that includes regular screening for chronic disease, monitoring of musculoskeletal health, and targeted management of modifiable risk factors. Longitudinal studies are warranted to explore causal relationships and evaluate interventions to improve long-term outcomes in this growing population.

Identifying Predictors of Cancer History Using Multivariable Models of Chronic Disease and Body Composition: Findings from NHANES 1999–2018


Preeclampsia (PE) is a pregnancy-specific hypertensive disorder arising after 20 weeks of gestation and remains a major cause of maternal and neonatal morbidity. It originates from abnormal trophoblast invasion and inadequate spiral artery remodeling, leading to placental ischemia, endothelial dysfunction, and excessive mitochondrial reactive oxygen species (mitoROS). These events drive trophoblast injury, impaired angiogenesis, and systemic oxidative stress that not only compromise fetal development but also confer a two to four higher lifetime risk of cardiovascular disease and heart failure in 
affected women.

Conventional antioxidants have shown limited success, underscoring the need for targeted interventions. Mitochondria-directed therapeutics such as JP4-039, a nitroxide that scavenges mitoROS and stabilizes mitochondrial membrane potential, offer promise in restoring endothelial and placental health. We propose a placenta-targeted delivery systemusing CGKRK-engineered extracellular vesicles (EVs) loaded with JP4-039 to reduce oxidative injury, enhance vascular remodeling, and mitigate both acute placental dysfunction and long-term maternal cardiovascular risk in Preeclampsia.

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