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Lauren H Sansing

Publications and source records attributed to Lauren H Sansing.

4 recordsLinked to original sources
PubMed2026

Cross-Platform Proteomics and Machine Learning Algorithms Nominate Plasma Biomarkers of Stroke Diagnosis.

BACKGROUND: Blood-based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross-platform proteomics to identify plasma biomarkers differentiating major stroke diagnostic groups. METHODS: We conducted a case-control study using 2 biorepositories. Plasma was collected in the emergency department from adults with suspected stroke before therapeutic intervention. Differentially enriched proteins were identified across acute ischemic stroke, intracerebral hemorrhage, transient ischemic attack, and stroke mimics using SomaScan discovery proteomics (Grady). Differentially enriched proteins were nominated using pairwise and multigroup comparisons and adjusted for clinical covariates. Protein panels were created using least absolute shrinkage and selection operator logistic regression. Internal validation used repeated nested cross-validation (rCV) and targeted mass spectrometry (MS), while external validation used data-independent acquisition  mass spectrometry in an independent cohort (Yale). RESULTS: We included 100 subjects (40 with acute ischemic stroke, 20 with intracerebral hemorrhage, 20 with transient ischemic attack, 20 with stroke mimics) in discovery and 80 subjects (20 per group) in external validation cohorts. SomaScan quantified 7307 proteins, of which 61 differentiated stroke subtypes. We identified 7 protein classifiers for acute ischemic stroke (rCV-area under the curve, 0.82 [95% CI, 0.78-0.86]), 6 for intracerebral hemorrhage (rCV-area under the curve, 0.70 [95% CI, 0.64-0.76]), 8 for transient ischemic attack (rCV-area under the curve, 0.78 [95% CI, 0.73-0.84]), and 7 for stroke mimics (rCV-area under the curve, 0.81 [95% CI, 0.77-0.86]). Targeted proteomics internally validated 11 proteins, and data-independent acquisition-mass spectrometry externally validated 32 proteins, including VTN (vitronectin), PLG (plasminogen), and S100A9 as top stroke mimics, transient ischemic attack, and intracerebral hemorrhage classifiers. CONCLUSIONS: This study highlights plasma proteomics as a valuable tool for discovering protein biomarkers of stroke diagnosis. These findings support further validation in larger, multicenter cohorts to facilitate biomarker-guided stroke diagnosis in acute care.

Humans↗
PubMed2006

To close or not to close: PFO, sex and cerebrovascular events.

We report on 2 patients with cerebrovascular events associated with sexual activity and PFO who subsequently underwent endovascular patent foramen ovale (PFO) closure. The concurrence of sexual activity (a Valsalva equivalent) at symptom onset, together with supporting data, prior paradoxical embolus in 1 case, elevated D-dimer in another, supported paradoxical embolization as the most likely mechanism of the cerebrovascular events. These cases emphasize that clinicians evaluating patients for PFO closure should explicitly inquire about sexual activity at stroke onset.

Adult↗
PubMed2003

Edema after intracerebral hemorrhage: correlations with coagulation parameters and treatment.

OBJECT: Development of edema is known to contribute to poor outcome after spontaneous intracerebral hemorrhage (ICH). Recent research has identified thrombin as a key mediator in the development of edema in animal models; however, little has been published correlating the coagulation cascade and edema in humans. METHODS: In this retrospective clinical study of 80 patients with spontaneous supratentorial ICH, the authors sought to identify factors associated with edema development and outcome, including lesion imaging parameters, anticoagulant use, international normalized ratio and platelet count on hospital admission, and treatment with mannitol and steroid medications. A multivariate model was used to identify edema volume, use of mannitol, elevated blood glucose, and the presence of intraventricular hemorrhage as predictors of poor outcome at the time patients were discharged from the hospital. The authors developed a quadratic model for predicting edema volume against time by using a random coefficients model, and found that edema peaks between Days 5 and 6 after onset of ICH. The volume of the hemorrhage and the platelet count correlated significantly with edema volume within the first 24 hours post-ICH in the multiple regression analysis (p < 0.0001, r2 = 0.75). Edema growth during the first 5 days post-ICH also correlated with the platelet count, with an increasing platelet count associated with an increasing growth of edema (p = 0.0013). CONCLUSIONS: The authors propose that factors released from activated platelets at the site of hemorrhage, for example vascular endothelial growth factor, may interact with thrombin to increase vascular permeability and contribute to the development of edema.

Adrenal Cortex Hormones↗