In the previous article, the author demonstrated the close relationship between bloodletting practices in medieval Europe and acupuncture in Traditional Chinese Medicine. This study aimed to explore how acupuncture-based treatment was applied in medieval Europe. The author hypothesizes that the physical stimulation of acupuncture points associated with bloodletting was one of the main methods of pain management at that time. The study examined the indications for phlebotomy as depicted in the original illustration from Practica Medicinalis written by the 15th-century Archbishop of Prague, Sigismundus Albicus, supplemented by two other European medieval medical manuscripts. A total of 76 distinct symptoms (corresponding to 25 bloodletting acupuncture points) from the Practica Medicinalis illustration were assembled into four groups: 1) Pain and inflammation symptoms; 2) Symptoms commonly associated with pain and inflammation; 3) General symptoms affecting various organs and functions; and 4) Conditions unrelated to pain or inflammation. Among the 76 symptoms and 25 acupuncture points, only nine symptoms and a single bloodletting point were not associated with the treatment of pain or inflammation. This suggests that acupuncture-based therapy was an effective method for managing pain and inflammation in the Middle Ages and that such treatment could still be valuable from a modern clinical perspective.
- MeSH
- akupunkturní body * MeSH
- akupunkturní terapie * dějiny MeSH
- bolest dějiny MeSH
- dějiny středověku MeSH
- lidé MeSH
- management bolesti * dějiny metody MeSH
- zánět * dějiny terapie MeSH
- Check Tag
- dějiny středověku MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- historické články MeSH
- Geografické názvy
- Evropa MeSH
BACKGROUND: An in-depth study of neurological symptoms and complications of influenza in elderly patients. This population group is more susceptible to complications of the disease and these complications are more likely to end in death. METHODS: A retrospective analysis of patient data was performed. All patients aged 65 years and older were included in the study. The study period was from the 1st of January , 2018 to 31st of December, 2021. All symptoms and complications of influenza were analyzed. Especially neurological and general symptoms were analyzed. Data were extracted from the complete medical records of the patients. RESULTS: The most common symptoms of influenza in the elderly were fever in 218 cases (83.52%), cough in 189 patients (72.41%), general weakness in 182 (69.73%) and fatigue in 166 patients (63.6%). Myalgias were experienced by 106 patients (40.61%) and arthralgias by 101 patients (38.7%). Headache occurred in only 21 patients (8.06%). Encephalopathy was observed in 7 elderly patients (2.68%) during hospitalization. Influenza encephalitis was noted in 2 cases. CONCLUSION: The most common neurological symptoms of influenza in more than half of the elderly are general weakness and increased fatigue. Myalgias are common, headache less often. Nausea is not uncommon. Of the complications, encephalopathy is the most common. Cases of influenza encephalitis have also been reported. We have not encountered a stroke. Concerning other complications, bacterial pneumonia was the most common.
- MeSH
- bolesti hlavy etiologie epidemiologie MeSH
- chřipka lidská * komplikace epidemiologie MeSH
- horečka etiologie MeSH
- kašel etiologie MeSH
- lidé MeSH
- myalgie etiologie epidemiologie MeSH
- nemoci nervového systému epidemiologie etiologie MeSH
- retrospektivní studie MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- svalová slabost etiologie epidemiologie MeSH
- únava etiologie epidemiologie MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVES: Patients are the most common source of violence against EMS personnel. This study aims at elucidating specific clinical features in patients with mental alteration and aggressive behaviour increasing risk of violence. MATERIAL AND METHODS: This consecutive cross-sectional retrospective study analysed consecutive patients treated for prespecified list of primary diagnoses by one EMS provider in the Czech Republic between 1 January 2021 and 31 December 2023. The effect of individual features of medical history and present symptoms on the occurrence of violence, need for the Police assistance and use of restraints was evaluated, using linear regression model. RESULTS: 410 patients were evaluated. Verbal and brachial violence was present in 21.5 and 12.9 %, respectively. Police assistance was needed in 48.3 %, restraints were used in 4.6 %. The most significant predictor for violence, need for Police or restraints was agitation (OR 7.02, CI 4.14 - 11.90; OR 2.60, CI 1.60 - 4.24, OR 11.02, CI 3.49 - 34.80 respectively). Other predictors of violence included history of acute psychotic attacks and psychotic disorders, or outpatient psychiatry care. Among other predictors for Police assistance was presence of delusions, paranoia and history of outpatient psychiatry care. CONCLUSION: Prehospital care for patients with mental status alteration and aggressive behaviour is complex. Some clinical features seem to increase the risk of violence. Future research in the evaluation of agitated and violent patients is warranted to find strategies of risk mitigation for EMS personnel.
- MeSH
- agrese * psychologie MeSH
- dospělí MeSH
- duševní poruchy epidemiologie terapie MeSH
- fyzické omezení statistika a číselné údaje MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- násilí statistika a číselné údaje psychologie MeSH
- policie MeSH
- průřezové studie MeSH
- retrospektivní studie MeSH
- senioři MeSH
- urgentní zdravotnické služby * statistika a číselné údaje MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
Objective.This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus, and posterior hippocampus over an extended period.Approach.Impedance was periodically sampled every 5-15 min over several months in five subjects with drug-resistant epilepsy using an investigational neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24 h impedance cycle throughout the multi-month recording.Main results.Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 d to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24 h impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures.Significance.Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.
- MeSH
- cizí tělesa * MeSH
- elektrická impedance MeSH
- hluboká mozková stimulace * metody MeSH
- implantované elektrody MeSH
- lidé MeSH
- mozek fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Loss of consciousness ranks among very common causes for emergency medical service actions and is common occurrence in the emergency department. Its differential diagnosis is very broad and includes many possible causes, not in the least an intoxication. The same applies to convulsive states. Clinical course of mushroom poisoning varies depending on the particular fungal species, with some of the species causing loss of consciousness. One typical representative of such species is panther cap (Amanita pantherina). This case report introduces panther cap poisoning, initially presenting in given patient as coma and protracted generalized convulsions. Complex treatment led to withdrawal of neurologic symptoms, circulatory and metabolic stabilisation and subsequent discharge without signs of permanent organ damage.
- MeSH
- Amanita * MeSH
- bezvědomí MeSH
- lidé MeSH
- otrava houbami * komplikace diagnóza terapie MeSH
- záchvaty chemicky indukované MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- kazuistiky MeSH
Objective.Long-term intracranial electroencephalography (iEEG) in freely behaving animals provides valuable electrophysiological information and when correlated with animal behavior is useful for investigating brain function.Approach.Here we develop and validate an automated iEEG-based sleep-wake classifier for canines using expert sleep labels derived from simultaneous video, accelerometry, scalp electroencephalography (EEG) and iEEG monitoring. The video, scalp EEG, and accelerometry recordings were manually scored by a board-certified sleep expert into sleep-wake state categories: awake, rapid-eye-movement (REM) sleep, and three non-REM sleep categories (NREM1, 2, 3). The expert labels were used to train, validate, and test a fully automated iEEG sleep-wake classifier in freely behaving canines.Main results. The iEEG-based classifier achieved an overall classification accuracy of 0.878 ± 0.055 and a Cohen's Kappa score of 0.786 ± 0.090. Subsequently, we used the automated iEEG-based classifier to investigate sleep over multiple weeks in freely behaving canines. The results show that the dogs spend a significant amount of the day sleeping, but the characteristics of daytime nap sleep differ from night-time sleep in three key characteristics: during the day, there are fewer NREM sleep cycles (10.81 ± 2.34 cycles per day vs. 22.39 ± 3.88 cycles per night;p< 0.001), shorter NREM cycle durations (13.83 ± 8.50 min per day vs. 15.09 ± 8.55 min per night;p< 0.001), and dogs spend a greater proportion of sleep time in NREM sleep and less time in REM sleep compared to night-time sleep (NREM 0.88 ± 0.09, REM 0.12 ± 0.09 per day vs. NREM 0.80 ± 0.08, REM 0.20 ± 0.08 per night;p< 0.001).Significance.These results support the feasibility and accuracy of automated iEEG sleep-wake classifiers for canine behavior investigations.
- MeSH
- bdění fyziologie MeSH
- elektroencefalografie metody MeSH
- elektrokortikografie MeSH
- psi MeSH
- spánek REM fyziologie MeSH
- spánek * fyziologie MeSH
- stadia spánku * fyziologie MeSH
- zvířata MeSH
- Check Tag
- psi MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
Objective.The current practices of designing neural networks rely heavily on subjective judgment and heuristic steps, often dictated by the level of expertise possessed by architecture designers. To alleviate these challenges and streamline the design process, we propose an automatic method, a novel approach to enhance the optimization of neural network architectures for processing intracranial electroencephalogram (iEEG) data.Approach.We present a genetic algorithm, which optimizes neural network architecture and signal pre-processing parameters for iEEG classification.Main results.Our method improved the macroF1 score of the state-of-the-art model in two independent datasets, from St. Anne's University Hospital (Brno, Czech Republic) and Mayo Clinic (Rochester, MN, USA), from 0.9076 to 0.9673 and from 0.9222 to 0.9400 respectively.Significance.By incorporating principles of evolutionary optimization, our approach reduces the reliance on human intuition and empirical guesswork in architecture design, thus promoting more efficient and effective neural network models. The proposed method achieved significantly improved results when compared to the state-of-the-art benchmark model (McNemar's test,p≪ 0.01). The results indicate that neural network architectures designed through machine-based optimization outperform those crafted using the subjective heuristic approach of a human expert. Furthermore, we show that well-designed data preprocessing significantly affects the models' performance.
- MeSH
- elektroencefalografie metody MeSH
- elektrokortikografie * MeSH
- lidé MeSH
- neuronové sítě (počítačové) * MeSH
- počítačové zpracování signálu MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Manual visual review, annotation and categorization of electroencephalography (EEG) is a time-consuming task that is often associated with human bias and requires trained electrophysiology experts with specific domain knowledge. This challenge is now compounded by development of measurement technologies and devices allowing large-scale heterogeneous, multi-channel recordings spanning multiple brain regions over days, weeks. Currently, supervised deep-learning techniques were shown to be an effective tool for analyzing big data sets, including EEG. However, the most significant caveat in training the supervised deep-learning models in a clinical research setting is the lack of adequate gold-standard annotations created by electrophysiology experts. Here, we propose a semi-supervised machine learning technique that utilizes deep-learning methods with a minimal amount of gold-standard labels. The method utilizes a temporal autoencoder for dimensionality reduction and a small number of the expert-provided gold-standard labels used for kernel density estimating (KDE) maps. We used data from electrophysiological intracranial EEG (iEEG) recordings acquired in two hospitals with different recording systems across 39 patients to validate the method. The method achieved iEEG classification (Pathologic vs. Normal vs. Artifacts) results with an area under the receiver operating characteristic (AUROC) scores of 0.862 ± 0.037, 0.879 ± 0.042, and area under the precision-recall curve (AUPRC) scores of 0.740 ± 0.740, 0.714 ± 0.042. This demonstrates that semi-supervised methods can provide acceptable results while requiring only 100 gold-standard data samples in each classification category. Subsequently, we deployed the technique to 12 novel patients in a pseudo-prospective framework for detecting Interictal epileptiform discharges (IEDs). We show that the proposed temporal autoencoder was able to generalize to novel patients while achieving AUROC of 0.877 ± 0.067 and AUPRC of 0.705 ± 0.154.
OBJECTIVE: Reporting epidemiological data on prehospital cardiac arrest in the Pilsen Region in 2022. Expression of cardiopulmonary resuscitation success using the Cerebral Performance Category (CPC) score. MATERIALS AND METHODS: The study looked at the survival rate of out-of-hospital sudden cardiac arrest in all patients in whom emergency medical services performed cardiopulmonary resuscitation (CPR). The study covered the period from 1 January 2022 to 31 December 2022. Both electronic and paper medical records were used to obtain data. All cases were evaluated according to Utstein-style guidelines. RESULTS: During the studied period, emergency response teams in the Pilsen Region carried out CPR in 499 cases. The incidence of prehospital CPR was 88.43 cases per 100,000 population. A total of 146 patients (29.26%) were referred to the hospital with spontaneous circulation, and results indicating survival with a good neurological outcome of CPC 1 or 2 were recorded in 48 cases (9.62%). The first monitored rhythm was shockable in 119 cases (23.85%). In this subgroup, ROSC was achieved in 71 cases (59.66%) and 61 of them (51.26%) were referred to hospital. In this study subgroup, a total of 36 patients (30.25%) achieved a good neurological outcome with a CPC score of 1 or 2. CONCLUSION: The study presented epidemiological data on OHCA and prehospital CPR in the Pilsen region in 2022. The data obtained shows a survival rate with good neurological outcome in 9.62% of cases.
PURPOSE: The aim of this study was to investigate whether the retinal nerve fibre layer (RNFL) in some segments of the optic nerve disc in pathological intraocular pressure is more damaged in eyes without antiglaucoma treatment. PATIENTS AND METHODS: The cohort consisted of 69 subjects (122 eyes), 32 males (6x one, 26x both eyes) aged 21 to 76 years and 37 females (4x one and 30x both eyes) aged 22 to 75 years, who were measured to have IOP greater than 21 mmHg (21-36) in routine ambulatory care. Measurements were performed using the Ocular Response Analyser, taking into account corneal hysteresis. RNFL thickness was measured using the Avanti RTVue XR and was assessed in 8 segments (1-IT, 2-TI, 3-TS, 4-ST, 5-SN, 6-NS, 7-NI, 8-IN). The visual field was examined with a fast threshold glaucoma program using the Medmont M700. The overall defect (OD) was evaluated. Pearson's correlation coefficient r was used to assess the dependence between the selected parameters. RESULTS: The largest peripapillary changes in RNFL were observed in segments 1, 4, 5 and 8. It should be emphasized that segments 1 and 4 have been temporarily shifted. Segments 5 and 8 then corresponded to the upper (at no. 12) and lower (at no. 6) sectors. CONCLUSION: The most important result of this study is the finding that the greatest changes in the RNFL layer were observed in pathological IOP at segment 5 (r=-0.3) and 8 (r=-0.28), at the point where the fibres of the magnocellular retinal ganglion cells enter the retina.
- Publikační typ
- časopisecké články MeSH
