Influence of Intraoperative Hemodynamic Parameters on Outcome in Simultaneous Pancreas–Kidney Transplant Recipient

Objectives: Adequate organ perfusion, as well as appropriate blood pressure levels at the time of unclamping, is crucial for early and long-term graft function and outcome in simultaneous pancreas–kidney transplantation (SPKT). However, the optimal intraoperative mean arterial pressure (MAP) level has not well been defined. Methods: From a prospectively collected database, the medical data of 105 patients undergoing SPKT at our center were retrospectively analyzed. A receiver operating characteristic (ROC) analysis was preliminarily performed for optimal cut-off value for MAP at reperfusion, to predict early pancreatic graft function. Due to these results, we divided the patients according to their MAP values at reperfusion into 91 mmHg (n = 58 patients) groups. Clinicopathological characteristics and outcomes, as well as early graft function and long-term survival, were retrospectively analyzed. Results: Donor and recipient characteristics were comparable between both groups. Rates of postoperative complications were significantly higher in the 91 mmHg group (vascular thrombosis of the pancreas: 7 (14%) versus 2 (3%); p = 0.03; pancreatitis/intraabdominal abscess: 10 (21%) versus 4 (7%); p = 0.03; renal delayed graft function (DGF): 11 (23%) versus 5 (9%); p = 0.03; postreperfusion urine output: 106 ± 50 mL versus 195 ± 45 mL; p = 0.04). There were no significant differences in intraoperative volume repletion, central venous pressure (CVP), use of vasoactive inotropic agents, and the metabolic outcome. Five-year pancreas graft survival was significantly higher in the >91 mmHg group (>91 mmHg: 82% versus 91 mmHg at the time point of reperfusion was associated with a reduced rate of postoperative complications, enhancing and recovering long-term graft function and outcome and thus increasing long-term survival in SPKT recipients

Quantifying the Impact of Chronic Ischemic Injury on Clinical Outcomes in Acute Stroke With Machine Learning.

Acute stroke is often superimposed on chronic damage from previous cerebrovascular events. This background will inevitably modulate the impact of acute injury on clinical outcomes to an extent that will depend on the precise anatomical pattern of damage. Previous attempts to quantify such modulation have employed only reductive models that ignore anatomical detail. The combination of automated image processing, large-scale data, and machine learning now enables us to quantify the impact of this with high-dimensional multivariate models sensitive to individual variations in the detailed anatomical pattern. We introduce and validate a new automated chronic lesion segmentation routine for use with non-contrast CT brain scans, combining non-parametric outlier-detection score, Zeta, with an unsupervised 3-dimensional maximum-flow, minimum-cut algorithm. The routine was then applied to a dataset of 1,704 stroke patient scans, obtained at their presentation to a hyper-acute stroke unit (St George's Hospital, London, UK), and used to train a support vector machine (SVM) model to predict between low (0-2) and high (3-6) pre-admission and discharge modified Rankin Scale (mRS) scores, quantifying performance by the area under the receiver operating curve (AUROC). In this single center retrospective observational study, our SVM models were able to differentiate between low (0-2) and high (3-6) pre-admission and discharge mRS scores with an AUROC of 0.77 (95% confidence interval of 0.74-0.79), and 0.76 (0.74-0.78), respectively. The chronic lesion segmentation routine achieved a mean (standard deviation) sensitivity, specificity and Dice similarity coefficient of 0.746 (0.069), 0.999 (0.001), and 0.717 (0.091), respectively. We have demonstrated that machine learning models capable of capturing the high-dimensional features of chronic injuries are able to stratify patients-at the time of presentation-by pre-admission and discharge mRS scores. Our fully automated chronic stroke lesion segmentation routine simplifies this process, and utilizes routinely collected CT head scans, thereby facilitating future large-scale studies to develop supportive clinical decision tools

Prognostic value of cortically induced motor evoked activity by TMS in chronic stroke: caveats from a very revealing single clinical case

Background: We report the case of a chronic stroke patient (62 months after injury) showing total absence of motor activity evoked by transcranial magnetic stimulation (TMS) of spared regions of the left motor cortex, but near-to-complete recovery of motor abilities in the affected hand. Case presentation: Multimodal investigations included detailed TMS based motor mapping, motor evoked potentials (MEP), and Cortical Silent period (CSP) as well as functional magnetic resonance imaging (fMRI) of motor activity, MRI based lesion analysis and Diffusion Tensor Imaging (DTI) Tractography of corticospinal tract (CST). Anatomical analysis revealed a left hemisphere subinsular lesion interrupting the descending left CST at the level of the internal capsule. The absence of MEPs after intense TMS pulses to the ipsilesional M1, and the reversible suppression of ongoing electromyographic (EMG) activity (indexed by CSP) demonstrate a weak modulation of subcortical systems by the ipsilesional left frontal cortex, but an inability to induce efficient descending volleys from those cortical locations to right hand and forearm muscles. Functional MRI recordings under grasping and finger tapping patterns involving the affected hand showed slight signs of subcortical recruitment, as compared to the unaffected hand and hemisphere, as well as the expected cortical activations. Conclusions: The potential sources of motor voluntary activity for the affected hand in absence of MEPs are discussed. We conclude that multimodal analysis may contribute to a more accurate prognosis of stroke patients

Long-term functional outcome after stroke: the impact of MRI-detected lesion characteristics

The objective of this thesis was to gain a better understanding of the relationship between ischemic lesion characteristics and long-term functional outcome of stroke survivors. The relationship between volume and localization of the ischemic cerebral lesion and the long-term functional outcome of first-ever ischemic middle cerebral artery stroke survivors was studied. Volume and localization was obtained with conventional Magnetic Resonance Imaging (MRI) scans. Outcome was assessed at the levels of body functions, activities and participation according to the International Classification of Functioning, Disability and Health (ICF). (1) In a systematic review, we found that previous studies showed a strong relationship between lesion volume and short-term outcome. However, earlier studies investigated only short follow-up periods up till 3-6 months, although functional improvement still occurs after 6 months. Furthermore, it was not clear if lesion volume related to all different levels of functional outcome (ICF) . (2) In the second week after stroke a strong relationship between lesion volume and neurological deficits was found as well as moderate correlations between lesion volume and body functions and limitations in activities. (3) Moderate relationships between lesion volume and functional outcome and quality of life after one year poststroke were demonstrated. A clinical model with clinical variables only predicted outcome of Activities of Daily Living of the stroke survivor after one year with an accuracy of 77%. Adding neuro-imaging variables to the clinical model increased the accuracy to 83%, but this difference was not statistically significant. (4) Involvement of structures with a greater density of corticofugal fibres (internal capsule) was associated with poor recovery of hand motor function after 1-year poststroke. The probability of recovery of some or all of the hand function ranged from 51% for those patients in whom the motor cortex was affected, to only 13% for those patients in whom both motor cortex and internal capsule were affected. (5) Our study showed that hemispheric lesion side, level and volume were weak to moderate predictors of verbal memory. Performance on visual recognition could not be predicted by lesion characteristics. (6) Stroke volume is a reflection of damaged brain tissue. A larger infarction leads to more deterioration of body functions, more activity limitations and a lesser capacity to participate, as well as an impaired Quality of Life. The strength of correlation between lesion characteristics and functional outcome weakens after a longer follow-up period post stroke. (7) Besides to its volume, the location of the lesion is important, especially for the outcome of motor function of the upper paretic limb. Long-term poststroke, the effect of localization was seen for hand motor recovery as well as for long-term episodic memory disorders

Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?

Contains fulltext : 49251.pdf (publisher's version ) (Closed access)BACKGROUND AND PURPOSE: To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke. METHODS: Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in logistic regression analyses. Model 1 was derived on the basis of clinical variables; for model 2, neuroimaging variables were added to model 1. Independent variables were stroke severity (National Institutes of Health Stroke Scale), consciousness (Glasgow Coma Scale), urinary continence, demographic variables (age, gender, relationship, educational level), hospital of admission, and clinical instruments: sitting balance (trunk control test), motor functioning (Motricity Index), and ADL (Barthel Index). Neuroimaging variables, determined on conventional MRI scans, included: number of days to scanning, lesion volume, lesion localization (cortex/subcortex), hemisphere, and the presence of white matter lesions. ADL independency was defined as 19 and 20 points on Barthel Index. Differences in accuracy of prediction of ADL independence between models 1 and 2 were analyzed by comparing areas under the curve (AUC) in a receiver operating characteristic analysis. RESULTS: Model 1 contained as significant predictors: age and ADL (AUC 0.84), correctly predicting 77%. In model 2, number of days to scanning, hemisphere, and lesion volume were added to model 1, increasing the AUC from 0.84 to 0.87, accurately predicting 83% of the surviving patients. CONCLUSIONS: Clinical variables in the second week after stroke are good predictors for independency in ADL 1 year after stroke. Neuroimaging variables on conventional MRI scans do not have added value in long-term prediction of ADL