Sympathetic-transduction in untreated hypertension.

Transduction of muscle sympathetic nerve activity (MSNA) into vascular tone varies with age and sex. Older normotensive men have reduced sympathetic transduction so that a given level of MSNA causes less arteriole vasoconstriction. Whether sympathetic transduction is altered in hypertension (HTN) is not known. We investigated whether sympathetic transduction is impaired in untreated hypertensive men compared to normotensive controls. Eight untreated hypertensive men and 10 normotensive men (age 50 ± 15 years vs. 45 ± 12 years (mean ± SD); p = 0.19, body mass index (BMI) 24.7 ± 2.7 kg/m2 vs. 26.0 ± 4.2 kg/m2; p = 0.21) were recruited. MSNA was recorded from the peroneal nerve using microneurography; beat-to-beat blood pressure (BP; Finapres) and heart rate (ECG) were recorded simultaneously at rest for 10 min. Sympathetic-transduction was quantified using a previously described method. The relationship between MSNA burst area and subsequent diastolic BP was measured for each participant with the slope of the regression indicating sympathetic transduction. MSNA was higher in the hypertensive group compared to normotensives (73 ± 17 bursts/100 heartbeats vs. 49 ± 19 bursts/100 heart bursts; p = 0.007). Sympathetic-transduction was lower in the hypertensive versus normotensive group (0.04%/mmHg/s vs. 0.11%/mmHg/s, respectively; R = 0.622; p = 0.006). In summary, hypertensive men had lower sympathetic transduction compared to normotensive individuals suggesting that higher levels of MSNA are needed to cause the same level of vasoconstrictor tone.

Artificial intelligence outperforms human students in conducting neurosurgical audits.

OBJECTIVES: Neurosurgical audits are an important part of improving the safety, efficiency and quality of care but require considerable resources, time, and funding. To that end, the advent of the Artificial Intelligence-based algorithms offered a novel, more economically viable solution. The aim of the study was to evaluate whether the algorithm can indeed outperform humans in that task. PATIENTS & METHODS: Forty-six human students were invited to inspect the clinical notes of 45 medical outliers on a neurosurgical ward. The aim of the task was to produce a report containing a quantitative analysis of the scale of the problem (e.g. time to discharge) and a qualitative list of suggestions on how to improve the patient flow, quality of care, and healthcare costs. The Artificial Intelligence-based Frideswide algorithm (FwA) was used to analyse the same dataset. RESULTS: The FwA produced 44 recommendations whilst human students reported an average of 3.89. The mean time to deliver the final report was 5.80 s for the FwA and 10.21 days for humans. The mean relative error for factual inaccuracy for humans was 14.75 % for total waiting times and 81.06 % for times between investigations. The report produced by the FwA was entirely factually correct. 13 out of 46 students submitted an unfinished audit, 3 out of 46 made an overdue submission. Thematic analysis revealed numerous internal contradictions of the recommendations given by human students. CONCLUSION: The AI-based algorithm can produce significantly more recommendations in shorter time. The audits conducted by the AI are more factually accurate (0 % error rate) and logically consistent (no thematic contradictions). This study shows that the algorithm can produce reliable neurosurgical audits for a fraction of the resources required to conduct it by human means.

Cerebral Blood Flow Response to Simulated Hypovolemia in Essential Hypertension: A Magnetic Resonance Imaging Study.

Hypertension is associated with raised cerebral vascular resistance and cerebrovascular remodeling. It is currently unclear whether the cerebral circulation can maintain cerebral blood flow (CBF) during reductions in cardiac output (CO) in hypertensive patients thereby avoiding hypoperfusion of the brain. We hypothesized that hypertension would impair the ability to effectively regulate CBF during simulated hypovolemia. In the present study, 39 participants (13 normotensive, 13 controlled, and 13 uncontrolled hypertensives; mean age±SD, 55±10 years) underwent lower body negative pressure (LBNP) at -20, -40, and -50 mmHg to decrease central blood volume. Phase-contrast MR angiography was used to measure flow in the basilar and internal carotid arteries, as well as the ascending aorta. CBF and CO decreased during LBNP (P<0.0001). Heart rate increased during LBNP, reaching significance at -50 mmHg (P<0.0001). There was no change in mean arterial pressure during LBNP (P=0.3). All participants showed similar reductions in CBF (P=0.3, between groups) and CO (P=0.7, between groups) during LBNP. There was no difference in resting CBF between the groups (P=0.36). In summary, during reductions in CO induced by hypovolemic stress, mean arterial pressure is maintained but CBF declines indicating that CBF is dependent on CO in middle-aged normotensive and hypertensive volunteers. Hypertension is not associated with impairments in the CBF response to reduced CO.

Diagnostic accuracy of frontotemporal dementia. An artificial intelligence-powered study of symptoms, imaging and clinical judgement.

PURPOSE: Frontotemporal dementia (FTD) is a neurodegenerative disorder associated with a poor prognosis and a substantial reduction in quality of life. The rate of misdiagnosis of FTD is very high, with patients often waiting for years without a firm diagnosis. This study investigates the current state of the misdiagnosis of FTD using a novel artificial intelligence-based algorithm. PATIENTS & METHODS: An artificial intelligence algorithm has been developed to retrospectively analyse the patient journeys of 47 individuals diagnosed with FTD (age range 52-80). The algorithm analysed the efficiency of patient pathways by utilizing a reward signal of ‒1 to +1 to assess the symptoms, imaging techniques, and clinical judgement in both behavioural and language variants of the disease. RESULTS: On average, every patient was subjected to 4.93 investigations, of which 67.4% were radiological scans. From first presentation it took on average 939 days for a firm diagnosis. The mean time between appointments was 204 days, and the average patient had their diagnosis altered 7.37 times during their journey. The algorithm proposed improvements by evaluating the interventions that resulted in a decreased reward signal to both the individual and the population as a whole. CONCLUSIONS: The study proves that the algorithm can efficiently guide clinical practice and improve the accuracy of the diagnosis of FTD whilst making the process of auditing faster and more economically viable.

Incidental Follow-up Imaging of Previous Ventricular Tuberculosis and Pneumoencephalography in a 57-year-old man.

We present a rare case of follow-up by neuroimaging in a 57-year-old man with a previous pneumoencephalography to evaluate ventricular tuberculosis (TB). Magnetic resonance imaging (MRI) of the whole head was performed at 3T using T1-weighted magnetization-prepared rapid gradient echo (T1-MPRAGE). A full quantitative sensory testing battery on the forearm was also performed, alongside a brief clinical examination. All test results were normal with the exception of the T1-MPRAGE which showed enlarged ventricles and a cyst-like focal changes, mistaken for a sign of old ischaemic infarct. The change, however, is consistent with the insertion of a cannula for the pneumoencephalogram. This is the first follow-up report with neuroimaging presented nearly 40 years after the diagnosis of ventricular TB.