An analytical study of standard propofol- sufentanil target controlled infusion protocols for total intravenous anaesthesia requirements in an Indian population using bispectral index monitoring

Background: Target controlled infusion (TCI) is an automated and regulated total intravenous anaesthesia delivering device. On the basis of western pharmacokinetic and pharmacodynamic models it delivers a calculated dosage of intravenous anaesthetic drugs to achieve an ideal anaesthetic plane. The depth of anaesthesia is judged by monitors such as bispectral index (BIS) monitors which gives a rough estimate whether the TCI is delivering more or less.Methods: This analytical study was carried out on 100 patients between 20 to 60 years of age in a teaching hospital. Simultaneous BIS monitoring and TCI were set on these patients. If BIS values went below 45 the target concentration was decreased by 0.5μg/ml and if it was more than Injection propofol was supplemented manually and the changes were collected and analyzed.Results: On analyses and comparison of the data with a western study it was found that the duration of surgery was similar in both studies. With the help of “t” test based on normal distribution it was found that group having BIS 60 was more statistically significant in the Indian population.Conclusions: Depth of anaesthesia was assessed with neurological monitor, BIS, at the time of administration of Target controlled infusion (TCI) and data acquired was compared with data from a western study. The two groups had similar anaesthetic depth levels with the same infusion protocols of Target controlled infusion (TCI)

Exhaled nitric oxide atopy, and spirometry in asthma and rhinitis patients in India

  INTRODUCTION: Asthma is a chronic airway inflammatory disorder. Nitric oxide (NO) is non-invasively measured in exhaled breath (FeNO). The aim of the study was to investigate the anthropometric and physiologic factors that influence FeNO measurements. Also, to evaluate FeNO correlation with spirometry and inflammatory markers in asthma and rhinitis. MATERIAL AND METHODS: The study was a prospective analysis of asthma (BA) and rhinitis (AR) in patients enrolled from outpatient clinics between 2011 and 2015. Healthy controls (HC) were enrolled from the community. All subjects underwent baseline spirometry with reversibility, FeNO measurements, skin prick tests, and blood sampling for absolute eosinophil counts and serum total IgE levels. RESULTS: Of 528 enrolled participants, 215 were BA, 248 were BA-AR and 65 were HC. The mean FeNO was higher in atopic versus nonatopic subjects (34.14 vs. 25.99; p < 0.001); asthmatics versus non-asthmatics (30.46 vs. 12.91; p < 0.001), and in participants with BA-AR, compared to those without BA-AR (32.56 vs. 30.46; p < 0.001). The odds ratio for FeNO in the study population showed a significant positive association with male gender, absolute eosinophil count (AEC), breathlessness, duration of symptoms, family history and atopy. In examining the diagnostic accuracy of FeNO for asthma, the AUC for FeNO value is 0.833 (95% confidence interval [CI], 0.717–0.901), with cut-off levels to screen for asthma being 19.45 at 71.2% sensitivity and 81.8% specificity (p < 0.001). The Positive Predictive Value 96.84% (95% CI: 94.43–98.23) and Negative Predictive Value 30% (95% CI: 23.78–37.05) for asthma prediction with FeNO. CONCLUSION: The study highlights the importance of estimation of anthropometric parameters and dyspnea assessment in the evaluation of FeNO levels. Also, the presence of atopy may influence the results in the interpretation of FeNO readings. Moreover, the study have demonstrated that spirometry and FeNO have no significant correlation, which further lays emphasis on them as being different physiological parameters of asthma.  

Improvement in Semantic Address Matching using Natural Language Processing

Address matching is an important task for many businesses especially delivery and take out companies which help them to take out a certain address from their data warehouse. Existing solution uses similarity of strings, and edit distance algorithms to find out the similar addresses from the address database, but these algorithms could not work effectively with redundant, unstructured, or incomplete address data. This paper discuss semantic Address matching technique, by which we can find out a particular address from a list of possible addresses. We have also reviewed existing practices and their shortcoming. Semantic address matching is an essentially NLP task in the field of deep learning. Through this technique We have the ability to triumph the drawbacks of existing methods like redundant or abbreviated data problems. The solution uses the OCR on invoices to extract the address and create the data pool of addresses. Then this data is fed to the algorithm BM-25 for scoring the best matching entries. Then to observe the best result, this will pass through BERT for giving the best possible result from the similar queries. Our investigation exhibits that our methodology enormously improves both accuracy and review of cutting-edge technology existing techniques.Comment: 5 pages, 7 tables, 2021 2nd International Conference for Emerging Technology (INCET

Spectrum of interstitial lung disease at a tertiary care centre in India

Introduction: The available data on the epidemiology of interstitial lung disease (ILD) from India is sparse. Hence, the present study was undertaken with the aim to analyse the demographic profile and clinical, radiological and pathological characteristics along with physiological parameters of various subgroups of ILD patients.Material and methods: We retrospectively studied 289 patients diagnosed with ILD during the years 2001–2013 at one of the respiratory units of Vallabhbhai Patel Chest Institute.Results: Mean age at presentation was 44.24 years; females comprised 54.68% of the patients. Prior to presentation at our centre, 14.84% patients had been treated with antituberculous therapy due to misdiagnosis of tuberculosis. In the pool of ILDs analysed, sarcoidosis (37.3%) was found to be the most common subgroup, followed by IPF (27.6%) and NSIP (25.6%). Cough (92.97%) was the most common presenting symptom; exertional dyspnoea was found in 79.2% of patients. Digital clubbing was commonest in IPF, found in 30% of patients. Significant desaturation on six-minute walk test was most frequenty seen (50%) in NSIP patients. The most common pattern on chest roentgenogram was reticular/reticulo-nodular pattern (80.2%) and on HRCT — interstitial fibrosis (49.9%). Mean of predicted total lung capacity (TLC) was 64.3%, the lowest being in the IPF group (58.88%). Mean of predicted DLCO was 50.56%, the lowest being in the IPF group (42.75%). The overall diagnostic yield of bronchoscopic biopsy was 83.04%, the highest yield being among sarcoidosis patients (96.29%).Conclusions: We found sarcoidosis, IPF and NSIP to be the most common ILDs in northern India. ILDs are still frequently misdiagnosed as TB, and increased awareness, education and diagnostic facilities are required to diagnose ILDs at an early stage.Wstęp: Istnieje stosunkowo mało informacji dotyczących epidemiologii śródmiąższowych chorób płuc (ILD) w Indiach. Aktualna praca została podjęta w celu oceny danych demograficznych, kliniczno-patologicznych i fizjologicznych różnych typów chorób śródmiąższowych.Materiał i metody: Badaniem retrospektywnym objęto 289 pacjentów, u których rozpoznano ILD w latach 2001–2013 w jednym z oddziałów Vallabhbhai Patel Chest Institute (Indie, Delhi).Wyniki: Średni wiek chorych w chwili rozpoznania wynosił 44,4 roku, kobiety stanowiły 54,68% ogółu chorych. Z powodu mylnego rozpoznania gruźlicy 14,84% chorych było uprzednio leczonych przeciwprątkowo. Sarkoidozę rozpoznano u 37% chorych, a IPF i NSIP odpowiednio w przypadku 27,6 i 25,6% chorych. Najczęściej zgłaszanymi objawami były kaszel (92,97%) i duszność wysiłkowa (79,2%) a palce pałeczkowate stwierdzono u 30% chorych na IPF. Znamienny spadek utlenowania krwi w 6-minutowym teście chodu najczęściej obserwowano u chorych na NSIP (50%). Zmiany guzkowo-siateczkowe w obrazie radiologicznym uwidoczniono u 80,2% chorych, a śródmiąższowe włóknienie w badaniu HRCT wykryto u 49,9% chorych. Średnia wartość zdolności dyfuzyjnej płuc (DLCO) wynosiła 50,56% wartości należnej i była najbardziej upośledzona w grupie chorych na IPF (42,75%). Wartość diagnostyczna biopsji wykonanej podczas bronchoskopii wynosiła 83,04% i dotyczyła szczególnie chorych na sarkoidozę (96,29%).Wnioski: Autorzy pracy stwierdzili, że w północnych Indiach najczęstszymi chorobami śródmiąższowymi są: sarkoidoza, IPF i NSIP. Śródmiąższowe choroby płuc są w Indiach często rozpoznawane błędnie jako gruźlica, dlatego konieczne jest szkolenie personelu i stworzenie ułatwień diagnostycznych, aby były one trafnie rozpoznane we wczesnym stadium

Effect of obesity and metabolic syndrome on severity, quality of life, sleep quality and inflammatory markers in patients of asthma in India

Introduction: The study aimed to compare the effect of obesity with and without metabolic syndrome on asthma severity, quality of life, sleep quality, sleep disordered breathing and inflammatory markers as compared to non-obese asthma patients. Material and methods: 60 asthma patients recruited for the study were divided equally into non-obese (NOA), obese without metabolic syndrome (OANMS) and obese with metabolic syndrome (OAMS) groups. Study cohorts were assessed for severity of asthma, quality of life and quality of sleep using questionnaires and inflammatory markers (FENO, hs-CRP, IL-5, IL-6 and leptin). Institutional ethical committee approved the study. Results: The results suggests OAMS patients may be a subtype of asthmatics having significantly severe asthma (p < 0.05), poor quality of life (p < 0.05), high risk of OSA (p < 0.05), decreased lung volumes (FRC) (p < 0.05), higher levels of inflammatory markers (leptin and IL-6) (p < 0.05), and high incidence of sleep disordered breathing (p < 0.05) in comparison to NOA and OANMS patients. Conclusions: The present study has shown that obese asthmatics especially with metabolic syndrome represent a subtype of asthmatic population. Hence, the treatment of metabolic syndrome may be necessary in addition to asthma to achieve optimal control.  INTRODUCTION: The study aimed to compare the effect of obesity with and without metabolic syndrome on asthma severity, quality of life, sleep quality, sleep disordered breathing and inflammatory markers as compared to non-obese asthma patients. MATERIAL AND METHODS: 60 asthma patients recruited for the study were divided equally into non-obese (NOA), obese without metabolic syndrome (OANMS) and obese with metabolic syndrome (OAMS) groups. Study cohorts were assessed for severity of asthma, quality of life and quality of sleep using questionnaires and inflammatory markers (FENO, hs-CRP, IL-5, IL-6 and leptin). Institutional ethical committee approved the study. RESULTS: The results suggests OAMS patients may be a subtype of asthmatics having significantly severe asthma (p < 0.05), poor quality of life (p  < 0.05), high risk of OSA (p < 0.05), decreased lung volumes (FRC) (p < 0.05), higher levels of inflammatory markers (leptin and IL-6) (p  < 0.05), and high incidence of sleep disordered breathing (p < 0.05) in comparison to NOA and OANMS patients. CONCLUSIONS: The present study has shown that obese asthmatics especially with metabolic syndrome represent a subtype of asthmatic population. Hence, the treatment of metabolic syndrome may be necessary in addition to asthma to achieve optimal control.

Review: Ethnopharmacology: Bridging Traditional Knowledge and Modern Science

Ethnopharmacology, derived from the Greek words "ethno" (people, nation, tribe) and "pharmacology" (study of drugs), examines how human societies utilize natural resources such as plants, fungi, animals, and minerals for medicinal purposes. This field bridges traditional herbal knowledge with modern pharmacological science, aiming to integrate ancient wisdom with contemporary research methods. Ethnopharmacology seeks to document conventional medicine practices, understand cultural uses of natural remedies, and identify potential pharmaceuticals from these sources. It emphasizes ethical use, fair rewards for communities, and integration with modern healthcare. With historical roots in Central and Eastern Europe and influences from Greek and Roman cultures, ethnopharmacology continues to explore the potential for improving global healthcare by linking traditional wisdom with modern science. This review offers a snapshot of the field\u27s achievements and future directions

Business Plan of Precious Pets

Precious Pets is a one stop shop for all the dog lovers and pet owners in India. It not only breeds and sells pedigree dogs in its facility but also provides all the related products and services under the same roof as well

Designing an Intelligent Parcel Management System using IoT & Machine Learning

Parcels delivery is a critical activity in railways. More importantly, each parcel must be thoroughly checked and sorted according to its destination address. We require an efficient and robust IoT system capable of doing all of these tasks with great precision and minimal human interaction. This paper discusses, We created a fully-fledged solution using IoT and machine learning to assist trains in performing this operation efficiently. In this study, we covered the product, which consists mostly of two phases. Scanning is the first step, followed by sorting. During the scanning process, the parcel will be passed through three scanners that will look for explosives, drugs, and any dangerous materials in the parcel and will trash it if any of the tests fail. When the scanning step is over, the parcel moves on to the sorting phase, where we use QR codes to retrieve the details of the parcels and sort them properly. The simulation of the system is done using the blender software. Our research shows that our procedure significantly improves accuracy as well as the assessment of cutting-edge technology and existing techniques.Comment: 6 pages, 6 figures, 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET

Edge Enhancement from Low-Light Image by Convolutional Neural Network and Sigmoid Function

Due to camera resolution or any lighting condition, captured image are generally over-exposed or under-exposed conditions. So, there is need of some enhancement techniques that improvise these artifacts from recorded pictures or images. So, the objective of image enhancement and adjustment techniques is to improve the quality and characteristics of an image. In general terms, the enhancement of image distorts the original numerical values of an image. Therefore, it is required to design such enhancement technique that do not compromise with the quality of the image. The optimization of the image extracts the characteristics of the image instead of restoring the degraded image. The improvement of the image involves the degraded image processing and the improvement of its visual aspect. A lot of research has been done to improve the image. Many research works have been done in this field. One among them is deep learning. Most of the existing contrast enhancement methods, adjust the tone curve to correct the contrast of an input image but doesn’t work efficiently due to limited amount of information contained in a single image. In this research, the CNN with edge adjustment is proposed. By applying CNN with Edge adjustment technique, the input low contrast images are capable to adapt according to high quality enhancement. The result analysis shows that the developed technique significantly advantages over existing methods