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Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.
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Variaciones en el Número de Copia de ADN , Genómica , Humanos , Genómica/métodos , Metilación de ADN , Neoplasias/genética , MicroARNs/genética , Femenino , Biomarcadores de Tumor/genética , Glioma/genética , Glioma/patología , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , MultiómicaRESUMEN
BACKGROUND: Vestibular migraine (VM) and Menière's disease (MD) are two common causes of recurrent spontaneous vertigo. Using history, video-nystagmography and audiovestibular tests, we developed machine learning models to separate these two disorders. METHODS: We recruited patients with VM or MD from a neurology outpatient facility. One hundred features from six "feature subsets": history, acute video-nystagmography and four laboratory tests (video head impulse test, vestibular-evoked myogenic potentials, caloric testing and audiogram) were used. We applied ten machine learning algorithms to develop classification models. Modelling was performed using three "tiers" of data availability to simulate three clinical settings. "Tier 1" used all available data to simulate the neuro-otology clinic, "Tier 2" used only history, audiogram and caloric test data, representing the general neurology clinic, and "Tier 3" used history alone as occurs in primary care. Model performance was evaluated using tenfold cross-validation. RESULTS: Data from 160 patients with VM and 114 with MD were used for model development. All models effectively separated the two disorders for all three tiers, with accuracies of 85.77-97.81%. The best performing algorithms (AdaBoost and Random Forest) yielded accuracies of 97.81% (95% CI 95.24-99.60), 94.53% (91.09-99.52%) and 92.34% (92.28-96.76%) for tiers 1, 2 and 3. The best feature subset combination was history, acute video-nystagmography, video head impulse test and caloric testing, and the best single feature subset was history. CONCLUSIONS: Machine learning models can accurately differentiate between VM and MD and are promising tools to assist diagnosis by medical practitioners with diverse levels of expertise and resources.
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Aprendizaje Automático , Enfermedad de Meniere , Trastornos Migrañosos , Vértigo , Humanos , Femenino , Masculino , Persona de Mediana Edad , Trastornos Migrañosos/diagnóstico , Trastornos Migrañosos/fisiopatología , Vértigo/diagnóstico , Vértigo/fisiopatología , Adulto , Enfermedad de Meniere/diagnóstico , Enfermedad de Meniere/fisiopatología , Diagnóstico Diferencial , Anciano , RecurrenciaRESUMEN
Results of the preliminary measurements of indoor radon, thoron and progeny concentrations showed very high values of thoron concentrations in the eastern coastal region of Odisha, India. Therefore, measurements of thoron and its progeny concentrations were extended to a larger number of houses in this area for the assessment of the radiation dose received by the public. The measured values of thoron concentrations were used for the calculation of annual effective doses. The estimated values of the annual effective dose due to thoron exposure were observed in the range of 0.2-14.7 mSv. The estimated radiation doses responsible for thoron exposure were observed considerably high in the region. The results obtained are compared with those obtained in other studies performed so far in the study area and a review of different studies involving different measurement techniques is presented in the paper. The results of this study support the preliminary studies showing high values of thoron levels in the study area.
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Contaminantes Radiactivos del Aire , Contaminación del Aire Interior , Monitoreo de Radiación , Radón , Contaminantes Radiactivos del Aire/análisis , Radiación de Fondo , Contaminación del Aire Interior/análisis , Hijas del Radón/análisis , Monitoreo de Radiación/métodos , Vivienda , Radón/análisis , India , Dosis de RadiaciónRESUMEN
Background and Aims: Laparoscopic cholecystectomy (LC) is a widely accepted surgical procedure associated with postoperative pain. This study was done to compare peripheral nerve stimulator (PNS)-guided serratus anterior plane block (SAP) and transversus abdominis plane (TAP) block for postoperative analgesia for patients undergoing LC. Methods: Following approval from the ethical committee, 70 patients for LC were randomly assigned to Group S: SAP block and Group T: TAP block. The blocks were performed under PNS guidance, and 20 ml of 0.375% ropivacaine was administered. The severity of pain was measured using a visual analogue scale (VAS). The study's primary objective was the evaluation of the postoperative VAS score. The time of the first dose of rescue analgesia and total tramadol consumption for 24 h postoperatively were secondary objectives. All the statistical calculation was done using statistical analyses for Social Sciences for Windows version 23.0 (IBM Corp, NY, USA). Results: Lower VAS score was seen in patients of TAP block at rest as well as movement at 6 h (P = 0.001), 12 h (P = 0.001) and 18 h (P = 0.001) postoperatively compared with SAP. The TAP group showed a significantly increased time of first rescue analgesic compared to the SAP group (7.97 ± 0.51 vs. 5.89 ± 1.45, P = 0.001). Tramadol usage was significantly higher in the SAP group than in the TAP group (128.9 ± 36.22 vs. 72.43 ± 44.80, P = 0.001). Conclusion: TAP block guided by the PNS improves postoperative pain with less tramadol consumption and during the postoperative period without significant complications.
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High concentrations of potentially toxic elements (PTEs) in potable water can cause severe human health disorders. Present study examined the fitness of groundwater for drinking purpose based on the occurrence of nine PTEs in a heavy pilgrim and tourist influx region of the Garhwal Himalaya, India. The concentrations of analyzed PTEs in groundwater were observed in the order of Zn > Mn > As > Al > Cu > Cr > Se > Pb > Cd. Apart from Mn and As, other PTEs were within the corresponding guideline values. Spatial maps were produced to visualize the distribution of the PTEs in the area. Estimated water pollution indices and non-carcinogenic risk indicated that the investigated groundwater is safe for drinking purpose, as the hazard index was < 1 for all the water samples. Assessment of the cancer risk of Cr, As, Cd, and Pb also indicated low health risks associated with groundwater use, as the values were within the acceptable range of ≤ 1 × 10-6 to 1 × 10-4. Multivariate statistical analyses were used to describe the various possible geogenic and anthropogenic sources of the PTEs in the groundwater resources although the contamination levels of the PTEs were found to pose no serious health risk. However, the present study recommends to stop the discharge of untreated wastewater and also to establish cost-effective as well as efficient water treatment facility nearby the study area. Present work's findings are vital as they may protect the health of the massive population from contaminated water consumption. Moreover, it can help the researchers, governing authorities and water supplying agencies to take prompt and appropriate decisions for water security.
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Agua Subterránea , Metales Pesados , Contaminantes Químicos del Agua , Humanos , Metales Pesados/toxicidad , Metales Pesados/análisis , Monitoreo del Ambiente , Cadmio/análisis , Plomo/análisis , Medición de Riesgo , India , Contaminantes Químicos del Agua/análisisRESUMEN
Humans receive a significant portion (Ë50%) of the total dose attributed to all the natural radiation sources from indoor radon (222Rn), thoron (220Rn), and their progeny. While progeny contributes an overwhelming part to the dose, in most surveys, only radon gas is measured because of the simplicity of measurement. Progeny concentration is usually estimated by multiplying gas concentration with an assumed factor, called the equilibrium factor, and taken from literature. Recently, results of the measurements of equilibrium factors for 222Rn and 220Rn were reported from various parts of the globe. In India, many such studies have been conducted in the current decade. The studies show a wide variation of equilibrium factors which suggests that they depend on environmental factors and measurement conditions. Therefore, they should be determined site specifically if accurate site-specific dose estimation is targeted. This paper summarizes concepts, definitions, and methods to determine equilibrium factors and reviews literature about reported equilibrium factors worldwide, focusing on data reported from India.
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Contaminantes Radiactivos del Aire , Contaminación del Aire Interior , Monitoreo de Radiación , Radón , Humanos , Contaminantes Radiactivos del Aire/análisis , Contaminación del Aire Interior/análisis , Monitoreo de Radiación/métodos , Radón/análisis , India , Vivienda , Hijas del Radón/análisisRESUMEN
Due to the increasing interest of people in the stock and financial market, the sentiment analysis of news and texts related to the sector is of utmost importance. This helps the potential investors in deciding what company to invest in and what are their long-term benefits. However, it is challenging to analyze the sentiments of texts related to the financial domain, given the enormous amount of information available. The existing approaches are unable to capture complex attributes of language such as word usage, including semantics and syntax throughout the context, and polysemy in the context. Further, these approaches failed to interpret the models' predictability, which is obscure to humans. Models' interpretability to justify the predictions has remained largely unexplored and has become important to engender users' trust in the predictions by providing insight into the model prediction. Accordingly, in this paper, we present an explainable hybrid word representation that first augments the data to address the class imbalance issue and then integrates three embeddings to involve polysemy in context, semantics, and syntax in a context. We then fed our proposed word representation to a convolutional neural network (CNN) with attention to capture the sentiment. The experimental results show that our model outperforms several baselines of both classic classifiers and combinations of various word embedding models in the sentiment analysis of financial news. The experimental results also show that the proposed model outperforms several baselines of word embeddings and contextual embeddings when they are separately fed to a neural network model. Further, we show the explainability of the proposed method by presenting the visualization results to explain the reason for a prediction in the sentiment analysis of financial news.
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Semántica , Análisis de Sentimientos , Humanos , Lenguaje , Redes Neurales de la Computación , Procesamiento de Lenguaje NaturalRESUMEN
This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations. We accomplish this goal by a simple yet effective self-supervised approach coupled with the U-Net discriminator. The proposed method extends the ability of the standard discriminators to learn not only the global data representations via classification (real/fake) but also learn semantic and structural information through pseudo labels created using the self-supervised task. The proposed method empowers the generator to create meaningful masks by forcing it to learn informative per-pixel and global image feedback from the discriminator. Our experiments demonstrate that our proposed method significantly outperforms the state-of-the-art methods on the standard benchmark datasets.
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Transfusion of blood and blood products has many adverse effects and should be done only if patient benefits outweigh the associated risks. Current understanding of blood transfusion has improved dramatically, revolutionising the care of surgical, trauma, obstetric and critically ill patients. Most guidelines advise a restrictive approach for stable patients with non-haemorrhagic anaemia for red blood cell transfusion. The rationale for red blood cell transfusion has historically been to improve oxygen transport capacity and consumption-related parameters in anaemic patients. Current understanding casts serious doubts about the true potential of red blood cell transfusions to improve these factors. There may not be any benefit from blood transfusion beyond a haemoglobin threshold of 7 g/dL. In fact, liberal transfusion may be associated with higher complications. Guideline-based transfusion policy should be adopted for the administration of all blood products including fresh frozen plasma, platelet concentrates and cryoprecipitate etc. This should be integrated with clinical judgement.
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Human body exposure to various toxic and non-toxic heavy metals in groundwater is a significant health concern, especially in developing countries. The present study was planned and carried out to appraise the potential health risks of eight heavy metals (Mn, Co, Cu, As, Se, Cd, Hg, and Pb) in different water sources of the Mansa and Muktsar districts of Punjab. The measurements of heavy metals were performed using the inductively coupled plasma mass spectrometry (ICPMS) technique. The health (carcinogenic and non-carcinogenic) risks and doses (ingestion and dermal) associated with exposure to heavy metals in water were estimated from the measured concentrations using USEPA guidelines. The average concentrations of heavy metals were observed in the order of Mn (13.93) > Cu (13.12) > Se (4.14) > As (3.28) > Hg (3.27) > Pb (1.29) > Co (0.20) > Cd (0.10) µg L-1. The results show that the Hg, Pb, As, and Se concentrations are above the guideline values of the World Health Organization (WHO) in 10.34%, 3.45%, 6.90%, and 6.90% locations, respectively. The high values of these heavy metals may be due to geogenic anthropogenic activities. The hazard quotients (non-carcinogenic risk) for ingestion and dermal exposures were observed in the range of 0.32-3.79 and 8.05 × 10-6-1.34 × 10-4, respectively. On the other hand, the carcinogenic health risks due to ingestion and dermal exposure were observed to be 0.02-0.38 and 6.67 × 10-8-1.15 × 10-6, respectively. The results of this study will be helpful to the drinking water supplying agencies, water resource development authorities, etc.
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Agua Subterránea , Mercurio , Metales Pesados , Contaminantes Químicos del Agua , Humanos , Monitoreo del Ambiente/métodos , Cadmio/análisis , Plomo/análisis , Metales Pesados/análisis , Mercurio/análisis , Agua Subterránea/química , Agua/análisis , India , Medición de Riesgo , Contaminantes Químicos del Agua/análisisRESUMEN
The occurrence of heavy metals (HMs) in drinking water has been a critical water quality concern for a long time and can compromise its aesthetic value to the larger extent. Chronic exposure of human beings to these toxic and non-toxic HMs through water ingestion can result in significant health risks. To assess these associated health risks, the present study was planned, designed and carried out for analyses of nine HMs namely, Al, Cr, Mn, Co, Ni, Cu, Zn, Cd and Pb in the potable water samples collected from different sources located across the Mandakini valley of Garhwal Himalaya, India using Inductively Coupled Plasma Mass Spectrometry. The measured values of Al, Cr, Mn, Co, Ni, Cu, Zn, Cd and Pb were found in the range of BDL-27.4 µg l-1, 0.26-4.5 µg l-1, BDL-139 µg l-1, 0.02-0.9 µg l-1, 0.4-5.5 µg l-1, 0.07-9.2 µg l-1, BDL-4164 µg l-1, BDL-0.8 µg l-1, and BDL-11.2 µg l-1, respectively. The observed values of analyzed HMs except Zn and Pb were found below the reference values prescribed by the WHO, USEPA and BIS. In addition, Zn concentration exceeded its maximum permissible limit (4000 µg l-1) recommended by WHO for infants at one station only. The observed indices show that there are no health risks from HMs contamination via drinking water in the region. Moreover, the estimated hazard quotients for children and adults also revealed no potential health risks. The results of present study will be useful as baseline data for state and national regulatory agencies.
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Agua Potable , Metales Pesados , Adulto , Niño , Lactante , Humanos , Cadmio , Plomo , Metales Pesados/toxicidad , IndiaRESUMEN
Context: The context of the study is to compare and find better muscle relaxant between rocuronium and vecuronium for intubation and maintenance under general anesthesia in patients undergoing laparoscopic cholecystectomy. Aims: The aim of the study is to measure intubating condition, hemodynamic changes during intubation and also during maintenance of general anesthesia and to record complications, if any. Settings and Design: A prospective clinical study conducted in the Department of Anesthesiology in tertiary care center. Materials and Methods: A total of 100 patients of the American Society of Anesthesiologists Classes Grade I and II were planned for laparoscopic cholecystectomy were divided into two groups of 50 each. The subjects in the control and study group were put under anesthesia using injection propofol 2.0 mg.kg-1 along with injection vecuronium 0.10 mg.kg-1 and injection propofol 2.0 mg.kg-1 along with injection rocuronium 0.60 mg.kg-1, respectively. Hemodynamic monitoring and oxygen saturation (SPO2) were recorded at various intervals. Statistical Analysis Used: All the collected data were imported into Microsoft Excel, and the statistical analysis was done by using SPSS 25.0 version. Results: The mean heart rate before and after carboperitoneum at different time intervals and before and after extubation was significantly lower in vecuronium group. The mean systolic blood pressure and mean arterial pressure at 1 and 5 minutes after extubation were significantly more among vecuronium group. Conclusions: Rocuronium is reasonably cardiostable, produces excellent intubation conditions, has a shorter duration of action, and shows minimal cumulative effect.
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This paper reviews different types of conversational agents used in health care for chronic conditions, examining their underlying communication technology, evaluation measures, and AI methods. A systematic search was performed in February 2021 on PubMed Medline, EMBASE, PsycINFO, CINAHL, Web of Science, and ACM Digital Library. Studies were included if they focused on consumers, caregivers, or healthcare professionals in the prevention, treatment, or rehabilitation of chronic diseases, involved conversational agents, and tested the system with human users. The search retrieved 1087 articles. Twenty-six studies met the inclusion criteria. Out of 26 conversational agents (CAs), 16 were chatbots, seven were embodied conversational agents (ECA), one was a conversational agent in a robot, and another was a relational agent. One agent was not specified. Based on this review, the overall acceptance of CAs by users for the self-management of their chronic conditions is promising. Users' feedback shows helpfulness, satisfaction, and ease of use in more than half of included studies. Although many users in the studies appear to feel more comfortable with CAs, there is still a lack of reliable and comparable evidence to determine the efficacy of AI-enabled CAs for chronic health conditions due to the insufficient reporting of technical implementation details.
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Inteligencia Artificial , Comunicación , Enfermedad Crónica , Atención a la Salud , Humanos , Tecnología de la InformaciónRESUMEN
Background: Facial area is one of the most frequently injured area of the body, accounting for 23-97% of all facial fractures. Treatments under general anesthesia as those for maxillofacial fractures or infections is a highly complicated and a major challenging task in trismus associated patients. The main culprit in trismus is the increase muscle tone of masticatory muscles which are supplied via the mandibular nerve, blocking which could help increase the mouth opening thus, changing the whole of airway management. Material and Method: A prospective study was done on 50 patients of ASA grade I-II with unilateral mandibular fracture with trismus posted for maxillofacial surgery. Mandibular nerve block was given via extraoral approach with 5 ml of 0.5% bupivacaine using peripheral nerve stimulator to determine the difference in Pre block and Post block mouth opening and the VAS score at 2, 5, 10, 15, 20, 25, and 30 minutes. Results: The Interincisor distance measured Pre block was 1.20 ± 0.32 mm and was significantly increased after 5 mins onwards from the block (P < 0.005). The VAS score determined Pre block was 5.14 ± 1.37 which significantly decreased just 2 minutes after the application of block (P < 0.005). Conclusion: Mandibular nerve block decreases the pain and will aid in the decision making by an anesthetist regarding airway management as it helps in increasing the inter incisor distance significantly. Moreover, given the feasibility and effectiveness of the block it could be included in standard of care protocol for mandibular fracture patients.
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Introduction: to evaluate the effects of intravenous (IV) dexmedetomidine as a pre-medication on clinical profile of bupivacaine spinal anaesthesia in lower abdominal surgeries. Methods: this prospective randomized double blind study was done on 60 patients with ASA grade I/II undergoing lower abdominal surgeries under bupivacaine spinal anaesthesia. They were allocated to group-1 and group-2. Group-1 (control group) received normal saline and group-2 (study group) received IV dexmedetomidine 1 µg/kg over 10 min as premedication. Five minutes after premedication, subarachnoid block (SAB) was given with 3 ml of 0.5% hyperbaric bupivacaine following which sensory and motor blockade, hemodynamic changes, sedation, and complications of the surgery were recorded and this data was analyzed statistically using χ2 test, corrected χ2 test, Fisher´s exact test, and test of proportion (Z-test). Results: the results of the present study showed that in group-2 there was significant decrease in the onset of sensory block, higher level of sensory blockade achieved, less time required to attain highest level of anaesthesia, prolonged time required for 2 dermatomal regression, prolonged duration of sensory blockade, prolonged duration of analgesia, decrease in onset of motor blockade, no significant increase in duration of motor blockade, there was overall hemodynamic stability except for few cases of bradycardia responding to atropine and hypotension responding to mephentramine, adequate and acceptable intraoperative sedation, and significantly less incidence of shivering in perioperative period. Conclusion: IV infusion of dexmedetomidine 1 µg/kg body weight prior to SAB can be recommended to achieve better sensory blockade and adequate hemodynamic stability and sedation.
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Anestesia Raquidea , Dexmedetomidina , Anestesia Raquidea/métodos , Anestésicos Locales , Bupivacaína , Dexmedetomidina/farmacología , Dexmedetomidina/uso terapéutico , Humanos , Estudios ProspectivosRESUMEN
Introduction: Severe preeclampsia can lead to various complications including increased intracranial pressure (ICP) which can be catastrophic but difficult to detect because of variable nonspecific symptoms. Ultrasonography has been used as noninvasive measure to monitor optic nerve sheath diameter (ONSD) as a marker of raised ICP. Effect of MgSO4 on ICP can modify the management approach, need for additional monitoring, targeting hemodynamic goals, timing of delivery, and choice of anesthesia. We evaluated the effect of MgSO4 on raised ICP in severely preeclamptic patients using ultrasound-guided ONSD as a surrogate marker of ICP. Methodology: This prospective observational study was conducted after ethical committee approval and written informed consent from patients. Ultrasound-guided ONSD was measured and compared in 47 severe preeclamptic patients before and at 1 h, 4 h, 12 h, and 24 h after starting MgSO4 therapy. The analysis of data was done by one-way analysis of variance using Statistical Package for the Social Science. Results: Mean ONSD was 5.56 ± 0.30 mm in our study group. ONSD above 5.8 mm was seen in 17 (36.17%) patients and was considered as marker of raised ICP. There was a significant decrease in ONSD after 4 h of administration of MgSO4. No significant correlation was observed between mean arterial pressure, serum magnesium level, and ONSD. Conclusion: Ultrasound-guided ONSD measurement can be used as a quick, noninvasive bedside tool in severe preeclamptic patient on MgSO4 treatment as marker of ICP which help us in determining clinical severity, therapeutic response, and to decide further course of management.
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Coronavirus disease-19 (COVID-19) is a very dangerous infectious disease for the entire world in the current scenario. Coronavirus spreads from one person to another person very rapidly. It spreads exponentially throughout the globe. Everyone should be cautious to avoid the spreading of this novel disease. In this paper, a fuzzy rule-based approach using priority-based method is proposed for the management of hospital beds for COVID-19 infected patients in the worst-case scenario where the number of hospital beds is very less as compared to the number of COVID-19 infected patients. This approach mainly attempts to minimize the number of hospital beds as well as emergency beds requirement for the treatment of COVID-19 infected patients to handle such a critical situation. In this work, higher priority has given to severe COVID-19 infected patients as compared to mild COVID-19 infected patients to handle this critical situation so that the survival probability of the COVID-19 infected patients can be increased. The proposed method is compared with first-come first-serve (FCFS)-based method to analyze the practical problems that arise during the assignment of hospital beds and emergency beds for the treatment of COVID-19 patients. The simulation of this work is carried out using MATLAB R2015b.
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BACKGROUND AND AIMS: The pain following total abdominal hysterectomy (TAH), a very commonly performed gynaecological surgery, is usually taken care of by various opioids, non-opioids, regional and peripheral nerve blocks. Erector spinae plane block (ESPB) under ultrasound guidance is a relatively new approach for postoperative analgesia in thoracic and abdominal surgeries. Ultrasound availability and expertise to use it is a limitation at times. The primary aim of this study was to determine the analgesic efficacy of ESPB using peripheral nerve stimulation (PNS) technique in patients undergoing TAH. METHODS: A total of 60 American Society of Anesthesiologists physical status I and II female patients were posted for abdominal hysterectomy after obtaining ethical committee clearance in a tertiary care centre. Group I (n = 30) received spinal anaesthesia, whereas Group II (n = 30) received ESPB under peripheral nerve stimulator (PNS) guidance with 20 mL of 0.375% ropivacaine before spinal anaesthesia. Post-operative pain intensity reported using the Visual Analogue Scale (VAS) was considered as the primary outcome. The haemodynamic variables, total duration before the first rescue analgesia, total consumption of tramadol, level of satisfaction regarding analgesia and any complications were considered as secondary outcomes. The data were recorded in an excel sheet, and analysis was performed using the Statistical Package for the Social Sciences version 23.0. RESULTS: VAS score was significantly lower (P < 0.001) in Group II at 0, 1, 2, 3, 4, 6, 12, 18 and 24 h post-operatively. The total dose of rescue analgesia was significantly reduced in the ESPB group. CONCLUSION: PNS-guided ESPB is effective in relieving pain in patients undergoing TAH.
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Vertigo is a sensation of movement that results from disorders of the inner ear balance organs and their central connections, with aetiologies that are often benign and sometimes serious. An individual who develops vertigo can be effectively treated only after a correct diagnosis of the underlying vestibular disorder is reached. Recent advances in artificial intelligence promise novel strategies for the diagnosis and treatment of patients with this common symptom. Human analysts may experience difficulties manually extracting patterns from large clinical datasets. Machine learning techniques can be used to visualize, understand, and classify clinical data to create a computerized, faster, and more accurate evaluation of vertiginous disorders. Practitioners can also use them as a teaching tool to gain knowledge and valuable insights from medical data. This paper provides a review of the literatures from 1999 to 2021 using various feature extraction and machine learning techniques to diagnose vertigo disorders. This paper aims to provide a better understanding of the work done thus far and to provide future directions for research into the use of machine learning in vertigo diagnosis.