Maternal mortality in a tertiary care hospital: a 3-year retrospective study

Background: Systematic review to determine the epidemiological aspects and causes of maternal mortality there by exploring possibility of intervention and implementing Evidence-based health policies and programmes to prevent future maternal death. Aims and objectives of the study were to calculate the maternal mortality rate in our hospital, to assess the epidemiological aspects of maternal mortality, to assess the type of delay and causes of maternal mortality and to suggest ways to reduce the MMR.Methods: This is a 3-year retrospective study from January 2017 to December 2019 that will be conducted in the department of obstetrics and gynaecology, The Apollo medical college and District hospital, Chittoor a tertiary care teaching hospital situated in the southernmost part of Andhra Pradesh state in India. It gets a large number of referrals from PHCs, CHCs, and maternity homes as well as from hospitals across Chittoor district. Epidemiological data will be collected from the hospital register. Maternal mortality ratio, epidemiological factors and causes affecting maternal mortality are assessed.Results: MMR in present study was 66 per 1,00,000 live births. Women in the age group of 20 to 30 years (85.72%), illiteracy (57.16%) and low socioeconomic status (100%) were risk factors for maternal mortality. Obstetric haemorrhage (57.16%) is most common cause whereas type 1 and type 2 delays are most common contributing factors for maternal mortality.Conclusions: Early identification and management of pregnancy complication, strengthening of existing Emergency obstetric care (EmOC) facilities, easy transport and appropriate referral linkages are keys to reduce maternal mortality to further extent

Phase transitions in A<SUB>4</SUB>Li(HSO<SUB>4</SUB>)<SUB>3</SUB>(SO<SUB>4</SUB>); A = Rb, K: single crystal X-ray diffraction studies

The crystal structure of ferroelastic Rb4Li(HSO4)3(SO4) has been determined at two temperatures, which indicates a structural phase transition, tetragonal P43 with a = 7.629(1) &#197;,c = 29.497(2) &#197; at 293 K and monoclinic P21 witha = 7.583(3) &#197;,b = 29.230(19) &#197;,c = 7.536(5) &#197;,&#946; = 90.14(1)&#176; at 90 K. The crystal structure of K4Li(HSO4)3(SO4)4 has also been determined at two temperatures, tetragonalP41 witha = 7.405(1) &#197;,c = 28.712(6) &#197; at 293 K and tetragonalP41 with a = 7.371(5) &#197;,c = 28.522(5) &#197; at 100 K. The overall coordination features in both the structures have been analysed in terms of bond valence sum calculations

Incidence and risk factors associated with ectopic pregnancy: a prospective study

Background: Increased incidence of ectopic pregnancy and its impact on women’s fertility in recent years need significant attention.Methods: A two years prospective study from January 2018 to December 2019 conducted to determine incidence, association of risk factors with ectopic pregnancy and find the most common risk factor of ectopic pregnancy in department of obstetrics and Gynaecology, a tertiary care Hospital in Pune.Results: During the study period 100 patients were diagnosed to have ectopic pregnancy. Incidence was 5.29 per 1000 births. Majority were in the age group of 20-24 years (42%), multiparous (59%) and belong to low socioeconomic state (62%). In majority of the patients (22%) no risk factors was found. Among the patients who had risk factors, the main risk factors for ectopic pregnancy were history of history of pelvic inflammatory disease (20%), previous tubal/abdominal surgery (12%), history of Infertility (10%), previous termination of pregnancy (10%), contraception with mirena IUS or IUCD in situ (8%) and a history of prior ectopic pregnancy (4%).Conclusions: In majority (78%) of patients risk factors for ectopic pregnancy was present and pelvic inflammatory disease was found to be a major risk factor for ectopic pregnancy

Study of serum cobalamin level in vegetarian v/s nonvegetarian geriatric individuals

Background: Vegetarianism is found in all geographic areas, they may have lower B-12 levels than nonvegetarian; problem could be graver in elderly. This study intended to recognise geriatric individuals with B-12 deficiency so as to save them from anaemia, dementia & neuropsychiatric disturbances by timely recommendations for supplementation.Methods: Current study was conducted on 200 healthy attendants divided in to two groups- A comprised of 100 vegetarian and B of 100 nonvegetarian geriatric individuals (> 60yrs.), they had no previous chronic disease and an attempt was made to exclude diabetes mellitus, hypertension, chronic gastritis, hypoplastic & aplastic anaemia. Those with history of alcohol intake, PPI therapy & regular vitamin supplementation were excluded. Complete clinical examination and routine blood tests were done. Serum cobalamin level was determined by ACCU-BIND ELISA Microwells method.Results: Total of 58 vegetarians were found to be B-12 deficient compared to 42 normal (>350pg/ml) this was statistically significant. Out of 100 nonvegetarian 48 were deficient while 52 had normal levels this too was statistically significant. On comparing the vegetarians and non vegetarian groups significant result was obtained (p <0.01). When different age groups were statistically compared insignificant result was obtained, same was true for gender distribution. Statistically significant result was obtained on comparing vegetarian Vs nonvegetarian group.Conclusions: Irrespective of the dietary habit B-12 deficiency is prevalent in elderly, as 58% of vegetarian & 48% of nonvegetarian were found B-12 deficient, detailed dietary analysis revealed that majority of them consumed nonvegetarian food only occasionally. No significant effect of increasing age & gender was found on B-12 levels in either group. Every elderly vegetarian or non vegetarian irrespective of gender should get their B-12 levels checked & if found low should receive B-12 supplement.

Trends of Research studies on Gridhrasi

Gridhrasi is a pain dominating Vata Vyadhi and is surge in incidence is alarming. A large group of patients with this condition suffer from limited or restricted daily routine activities and is posing burden on socioeconomic life of an individual. This disease is being studied routinely in postgraduate departments, this article attempts to assess the trends and pattern of research studies conducted till date on the subject and also to highlight the unexplored areas to bring out the best possible solution for this malady. Number of studies are targeted on assessing the therapeutical potential of a modality or a drug and least number of studies are targeted on the studying the disease pathology

Classification of Mild Cognitive Impairment with Deep Transfer Learning Approach using CWT based Scalogram Images

Mild Cognitive Impairment (MCI) is a condition that can occur as a person gets older, and faces problems like recognition, memory, and language skills. Early detection of MCI is crucial, as it can progress to more severe conditions like Alzheimer's disease. This study proposes a method to use Scalogram images, obtained by applying Continuous Wavelet Transform (CWT) to EEG signals and pre-trained models like ResNet50, VGG16, InceptionV3, Inception_ResNetV2 through transfer learning to classify MCI and Healthy Control (HC). Fine-tuning of the models is also used to improve the results, and various performance metrics are employed for classification. The study concludes that Inception_ResNetV2 transfer learning yielded good results, while ResNet50 and InceptionV3 transfer learning with fine-tuning resulted in higher accuracy using a low learning rate

Search for an Instability on a Quenched-Liquid Interface

We searched for signs of an instability on the interface between the two phases of a binary-liquid mixture, isobutyric acid and water, after the mixture was quenched further into the two-phase region. Such an instability would be the liquid-liquid analog of the Mullins-Sekerka instability seen in quenched alloys. Never is any dramatic growth observed, but under conditions of small dimensionless quench depth (theta\u3c1.5×10−3), the intensity of light scattered from the interface grows for small values of the momentum transfer k

Artificial Neural Network based Cancer Cell Classification

This paper addresses the system which achieves auto-segmentation and cell characterization for prediction of percentage of carcinoma (cancerous) cells in the given image with high accuracy. The system has been designed and developed for analysis of medical pathological images based on hybridization of syntactic and statistical approaches, using Artificial Neural Network as a classifier tool (ANN) [2]. This system performs segmentation and classification as is done in human vision system [1] [9] [10] [12], which recognize objects; perceives depth; identifies different textures, curved surfaces, or a surface inclination by texture information and brightness. In this paper, an attempt has been made to present an approach for soft tissue characterization utilizing texture-primitive features and segmentation with Artificial Neural Network (ANN) classifier tool. The present approach directly combines second, third, and fourth steps into one algorithm. This is a semi-supervised approach in which supervision is involved only at the level of defining structure of Artificial Neural Network; afterwards, algorithm itself scans the whole image and performs the segmentation and classification in unsupervised mode. Finally, algorithm was applied to selected pathological images for segmentation and classification. Results were in agreement with those with manual segmentation and were clinically correlated [18] [21]. Keywords: Grey scale images, Histogram equalization, Gausian filtering, Haris corner detector, Threshold, Seed point, Region growing segmentation, Tamura texture feature extraction, Artificial Neural Network(ANN), Artificial Neuron, Synapses, Weights, Activation function, Learning function, Classification matrix