Hypoxia Conditioning for High-Altitude Pre-acclimatization

Purpose Main purposes of pre-acclimatization by hypoxia conditioning (HC) are the prevention of high-altitude illnesses and maintenance of aerobic exercise performance. However, robust evidence for those effects or evidence-based guidelines for exposure strategies, including recommendations to ensure safety, are largely lacking. Therefore, we summarize the current knowledge on the physiology of acclimatization to hypoxia and HC with the aim to derive implications for pre-acclimatization strategies before going on high-altitude treks and expeditions. Methods Based on the literature search and personal experience, core studies and important observations have been selected in order to present a balanced view on the current knowledge of high-altitude illnesses and the acclimatization process, specifically focusing on pre-acclimatization strategies by HC. Results and Conclusions It may be concluded that in certain cases even short periods (e.g., 7 h) of pre-acclimatization by HC are effective, but longer periods (e.g., > 60 h) are needed to elicit more robust effects. About 300 h of HC (intermittently applied) may be the optimal preparation for extreme altitude sojourns, although every additional hour spent in hypoxia may confer further benefits. The inclusion of hypobaric exposures (i.e., real altitude) in pre-acclimatization protocols could further increase their efficacy. The level of simulated altitude is progressively increased or individually adjusted ideally. HC should not be terminated earlier than 1–2 weeks before altitude sojourn. Medical monitoring of the pre-acclimatization program is strongly recommended.

Anesthesia Immutable Registry of Real-time Vital Signs and Waveforms using Blockchain

Healthcare has become one of the most important emerging application areas of blockchain technology.[1] Although the use of a cryptographic ledger within Anesthesia Information Management Systems (AIMS) remains uncertain. The need for a truly immutable anesthesia record is yet to be established, given that the current AIMS database systems have reliable audit capabilities. Adoption of AIMS has followed Roger's 1962 formulation of the theory of diffusion of innovation. Between 2018 and 2020, adoption was expected to be the 84% of U.S. academic anesthesiology departments.[2] Larger anesthesiology groups with large caseloads, urban settings, and government affiliated or academic institutions are more likely to adopt and implement AIMS solutions, due to the substantial amount of financial resources and dedicated staff to support both the implementation and maintenance that are required. As health care dollars become more scarce, this is the most frequently cited constraint in the adoption and implementation of AIMS.[3] We propose the use of a blockchain database for saving all incoming data from multiparametric monitors at the operating theatre. We present a proof of concept of the use of this technology for electronic anesthesia records even in the absence of an AIMS at site. In this paper we shall discuss its plausibility as well as its feasibility. The Electronic medical records (EMR) in AIMS might contain errors and artifacts that may (or may not) have to be dealt with. Making them immutable is a scary concept. The use of the blockchain for saving raw data directly from medical monitoring equipment and devices in the operating theatre has to be further investigated.

Impact of the SARS-CoV-2 pandemic and first lockdown on pregnancy monitoring in France: the COVIMATER cross-sectional study

Background In the context of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, consultations and pregnancy monitoring examinations had to be reorganised urgently. In addition, women themselves may have postponed or cancelled their medical monitoring for organisational reasons, for fear of contracting the disease caused by SARS-CoV-2 (COVID-19) or for other reasons of their own. Delayed care can have deleterious consequences for both the mother and the child. Our objective was therefore to study the impact of the SARS-CoV-2 pandemic and the first lockdown in France on voluntary changes by pregnant women in the medical monitoring of their pregnancy and the associated factors. Methods A cross-sectional study was conducted in July 2020 using a web-questionnaire completed by 500 adult (> 18 years old) pregnant women during the first French lockdown (March–May 2020). A robust variance Poisson regression model was used to estimate adjusted prevalence ratios (aPRs). Results Almost one women of five (23.4%) reported having voluntarily postponed or foregone at least one consultation or pregnancy check-up during the lockdown. Women who were professionally inactive (aPR = 1.98, CI95%[1.24–3.16]), who had experienced serious disputes or violence during the lockdown (1.47, [1.00–2.16]), who felt they received little or no support (1.71, [1.07–2.71]), and those who changed health professionals during the lockdown (1.57, [1.04–2.36]) were all more likely to have voluntarily changed their pregnancy monitoring. Higher level of worry about the pandemic was associated with a lower probability of voluntarily changing pregnancy monitoring (0.66, [0.46–0.96]). Conclusions Our results can guide prevention and support policies for pregnant women in the current and future pandemics.

Traumatic Brain Injury and Risk of Dementia and Alzheimer’s Disease: A Systematic Review and Meta-Analysis

Introduction: Previous studies have investigated the potential role of traumatic brain injury (TBI) in subsequent development of dementia and Alzheimer’s disease (AD) but reported inconsistent results. We aim to determine the association between TBI and subsequent occurrence of dementia and AD. Methods: We performed a systematic search in PubMed and Web of Science for studies that quantitatively investigated the association between TBI and risk of dementia and AD and were published on or before September 21, 2021. A random-effect model was used to combine the estimates. Results: Twenty-five eligible articles were included in this meta-analysis. The results suggested that TBI was associated with an increased risk of dementia (pooled odds ratio [OR] = 1.81, 95% confidence interval [CI] = 1.53 - 2.14). However, no association was observed between TBI and Alzheimer’s disease (pooled OR = 1.02, 95% CI = 0.91 - 1.15). In the subgroup analysis, TBI with loss of consciousness was not associated with risk of dementia (pooled OR = 0.96, 95% CI = 0.84 - 1.09). Besides, Asian ethnicity, male gender, and mean age of the participants less than 65 were associated with a higher risk of dementia. Conclusion: Our study suggests an increased risk of dementia among individuals with TBI, highlighting the need for more intensive medical monitoring and health education in individuals with TBI. Biological mechanisms linking TBI and the development of dementia are needed in future studies.

The use of the monoclonal antibody Erenumab in patients with chronic migraine in real clinical experience

Patients with chronic migraine are characterized by frequent severe headache attacks, polypharmacy (painkillers), insufficient effect of preventive therapy, and a decrease in the quality of life. The aim of a prospective open-label study was the evaluation of the efficacy and tolerance of Erenumab (Irinex) in the treatment of patients with chronic migraine in real clinical practice.Material and methods. 48 patients with chronic migraine were clinically and neurologically examined (35.5 [19; 56]; diagnosis was established according to the criteria of ICHD classification and diagnosis of migraine. Medical monitoring period was 3 months. Clinical and neurological testing and subcutaneous administration of Erenumab (Irinex) 70 mg were performed once a month during the whole period.Results. Safety, good tolerance and an obvious significant clinical effect were noted when using Erenumab (Irinex) 70 mg. It led to a significant improvement in clinical score and the course of chronic migraine, the effectiveness of rapid relief of symptoms and significant reduction in the need for painkillers in most patients. The best results were found after 3 months of therapy.

Data mining technologies in a distributed medical information system

Proposed a method for solving the problem of identifying hidden relationships in hard-to-structure data that have an implicit character is considered using information mining. Proposed decision trees, the effectiveness of which is illustrated by a specific example. The use of OLAP analysis systems on data presented using in the form of a real or virtual hypercube’s information is an effective tool for the effectiveness of the management for medical monitoring

SIMpLE: A Mobile Cloud-Based System for Health Monitoring of People with ALS

Adopting telemonitoring services during the pandemic for people affected by chronic disease is fundamental to ensure access to health care services avoiding the risk of COVID-19 infection. Among chronic diseases, Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, is a progressive neurodegenerative disease of adulthood, caused by the loss of spinal, bulbar and cortical motor neurons, which leads to paralysis of the voluntary muscles and, also, involves respiratory ones. Therefore, remote monitoring and teleconsulting are essential services for ALS patients with limited mobility, as the disease progresses, and for those living far from ALS centres and hospitals. In addition, the COVID 19 pandemic has increased the need to remotely provide the best care to patients, avoiding infection during ALS centre visits. The paper illustrates an innovative, secure medical monitoring and teleconsultation mobile cloud-based system for disabled people, such as those with ALS (Amyotrophic Lateral Sclerosis). The design aims to remotely monitor biosignals, such as ECG (electrocardiographic) and EMG (electromyographic) signals of ALS patients in order to prevent complications related to the pathology.

An Internet of Medical Things-Based Model for Real-Time Monitoring and Averting Stroke Sensors

In recent years, neurological diseases have become a standout amongst all the other diseases and are the most important reasons for mortality and morbidity all over the world. The current study’s aim is to conduct a pilot study for testing the prototype of the designed glove-wearable technology that could detect and analyze the heart rate and EEG for better management and avoiding stroke consequences. The qualitative, clinical experimental method of assessment was explored by incorporating use of an IoT-based real-time assessing medical glove that was designed using heart rate-based and EEG-based sensors. We conducted structured interviews with 90 patients, and the results of the interviews were analyzed by using the Barthel index and were grouped accordingly. Overall, the proportion of patients who followed proper daily heart rate recording behavior went from 46.9% in the first month of the trial to 78.2% after 3–10 months of the interventions. Meanwhile, the percentage of individuals having an irregular heart rate fell from 19.5% in the first month of the trial to 9.1% after 3–10 months of intervention research. In T5, we found that delta relative power decreased by 12.1% and 5.8% compared with baseline at 3 and at 6 months and an average increase was 24.3 ± 0.08. Beta-1 remained relatively steady, while theta relative power grew by 7% and alpha relative power increased by 31%. The T1 hemisphere had greater mean values of delta and theta relative power than the T5 hemisphere. For alpha ( p < 0.05) and beta relative power, the opposite pattern was seen. The distinction was statistically significant for delta ( p < 0.001), alpha ( p < 0.01), and beta-1 ( p < 0.05) among T1 and T5 patient groups. In conclusion, our single center-based study found that such IoT-based real-time medical monitoring devices significantly reduce the complexity of real-time monitoring and data acquisition processes for a healthcare provider and thus provide better healthcare management. The emergence of significant risks and controlling mechanisms can be improved by boosting the awareness. Furthermore, it identifies the high-risk factors besides facilitating the prevention of strokes. The EEG-based brain-computer interface has a promising future in upcoming years to avert DALY.