Umbilical Coiling Index as a Marker of Perinatal Outcome: An Analytical Study

Objectives. To measure umbilical coiling index (UCI) postnatally and to study the association of normocoiling, hypocoiling and hypercoiling to maternal and perinatal outcome. Method(s). One thousand antenatal women who went into labour were studied and umbilical coiling index calculated at the time of delivery. UCI was determined by dividing the total number of coils by the total umbilical cord length in centimeters. Its association with various maternal and perinatal risk factors were noted. The statistical tests were the Chi-square test and assessed with SPSS version 13.0 software and statistically analyzed. P value of less than 0.05 was regarded as statistically significant. Results. The mean umbilical coiling index was found to be 0.24 ± 0.09. Hypocoiling (<0.12) was found to be significantly associated with hypertensive disorders, abruptio placentae, preterm labour, oligohydramnios, and fetal heart rate abnormalities. Hypercoiling (>0.36) was found to be associated with diabetes mellitus, polyhydramnios, cesarean delivery, congenital anomalies, and respiratory distress of the newborn. Conclusion. Abnormal umbilical coiling index is associated with several antenatal and perinatal adverse features

Study on Relaparotomy in Coimbatore Medical College and Hospital

INTRODUCTION: The term RELAPAROTOMY (RL) refers to operations performed within 60 days in association with the initial surgery, for complications arising following primary surgery whereas the term ―early RL‖ refers to laparotomy performed for the original disease within 21 days of the first operation. These urgent Relaparotomy are also called as final choice operation. OBJECTIVES: To find out, common indications for performing Relaparotomy, outcomes of Relaparotomies, factors influencing the associated mortality rate in Coimbatore Medical College Hospital. METHODS: 30 patients who underwent relaparotomy for complications arising due to initial laparotomy were included in the study. Demographic features and initial diagnoses of the patients, the reasons for their initial surgery and their postoperative complications and outcome of relaparotomy were analyzed. RESULTS: The average patient age was 52.2 years and the male:female ratio was 25:5. Relaparotomy was performed for the following complications: leakage of an intestinal repair or anastomosis (n = 7, 23%); persistent intraabdominal infection (n = 7, 23%), burst abdomen (n = 6, 20%), enterocutaneous fistula (n = 3, 10%), persistent intraabdominal abscess (n = 2, 7%), stomal complications (n = 2, 7%), post-operative hemorrhage (n = 2, 7%) and persistent intestinal gangrene (n = 1, 3%). A mortality rate of 20% (n = 6) was attributed mainly to infections (n = 22, 73%). The average interval between the first laparotomy and relaparotomy was 12.3 days, and the average hospital stay was 25.8 days. CONCLUSIONS: According to our study, the reasons for Relaparotomy (RL) are many. Anastomotic leak and persistent intra abdominal infection are major reason for relaparotomy, and these are associated with high mortality. The reduction of high RL rates, and subsequent high mortality rates, mainly depends on the success of the first operation

The Study and Efficacy of Conventional Machine Learning Strategies for Predicting Cardiovascular Disease

Regarding medical science, cardiovascular disease is the main cause of death. Testing patient samples for cardiac disease can save lives and lower mortality rates. During a subsequent visit, the right remedies should be outlined and prescribed. One of the most important factors in preemptive cardiac disease diagnosis is accuracy. Based on this factor, many research approaches were examined and compared. According to the analysis of these approaches, new procedures appear to be more advanced and reliable in detecting cardiac illness. A notation of the methods and their underlying themes and precision levels will be discussed. This paper surveys many models that use these methods and methodologies and evaluates their performance. Models created utilizing supervised learning methods, such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN), Decision Trees (DT), Random Forest (RF), and Logistic Regression Units, are highly valued by researchers. For benchmark datasets like the Cleveland or Kaggle, the methodologies are derived from data mining, machine learning, deep learning, and other related techniques and technologies. The accuracy of the provided methods is graphically demonstrated

Border Alert System for Fishermen Using GPS System

The livelihood of fishermen is such that he crosses the country border unknowingly and poses threats to them by being killed or captured. The sea borders between countries are not easily identifiable which is the main reason behind this problem. ldquoBorder alert system for fisherman using GPSrdquo describes about a system which helps the fishermen by notifying the country border. Global Positioning System (GPS) and Global system for mobile communication (GSM) are used for this purpose. Here GPS receiver is used to find the current location of the fishing boat. Using GPS, present latitude and longitude values are sent to microcontroller unit. Later the controller unit identifies the current location by comparing the present latitude and longitudinal values with the predefined value. After the comparison, border alert system aware the fishermen that they are about to reach the nautical border. The region is divided into normal zone and warning zone. When the boat is in normal area, the LCD displays normal zone. Thus they can make it clear that the boat is in normal area. In case if it moves further and reaches the warning zone, the LCD displays warning zone

Clinical skill learning for tomorrow’s doctors - a step towards better obstetric care

Background: Female urethral catheterization is the most commonly performed procedure in obstetrics and gynecology, for the assessment of urinary output. Many times catheterization is done by junior colleagues with improper technique resulting in improper catheterization and urethral injury. It is a must to know skill for every graduating medical student to avoid devastating consequences of performing it poorly. The objectives of this study are to evaluate the effectiveness of four step method of skill learning of bladder catheterization in female patients by interns and demonstrate the competency in the proper insertion and removal of an indwelling urinary catheter and also the study aimed to determine the effectiveness of bladder simulator training for medical interns.Methods: A prospective, observational and skill imparting study done using a specially designed model, after ethical committee approval. 30 Interns were divided in to six groups of five each for skill learning. It was done with Kirkpatrik model using specially designed objective structured clinical examination forms and scoring sheets. Sample paired t test was used.Results: 80% of the interns could perform the skill with maximum scores.Conclusions: It is an innovative teaching learning method for incoming interns which will help them to improve knowledge and practice and finally reduce the risk of complications and injury.

Genetic impairment of succinate metabolism disrupts bioenergetic sensing in adrenal neuroendocrine cancer

Metabolic dysfunction mutations can impair energy sensing and cause cancer. Loss of function of the mitochondrial tricarboxylic acid (TCA) cycle enzyme subunit succinate dehydrogenase B (SDHB) results in various forms of cancer typified by pheochromocytoma (PC). Here we delineate a signaling cascade where the loss of SDHB induces the Warburg effect, triggers dysregulation of [Ca2+]i, and aberrantly activates calpain and protein kinase Cdk5, through conversion of its cofactor from p35 to p25. Consequently, aberrant Cdk5 initiates a phospho-signaling cascade where GSK3 inhibition inactivates energy sensing by AMP kinase through dephosphorylation of the AMP kinase γ subunit, PRKAG2. Overexpression of p25-GFP in mouse adrenal chromaffin cells also elicits this phosphorylation signaling and causes PC. A potent Cdk5 inhibitor, MRT3-007, reverses this phospho-cascade, invoking a senescence-like phenotype. This therapeutic approach halted tumor progression in vivo. Thus, we reveal an important mechanistic feature of metabolic sensing and demonstrate that its dysregulation underlies tumor progression in PC and likely other cancers

SEASONAL ASSESSMENT OF HYDROGRAPHIC VARIABLES AND PHYTOPLANKTON COMMUNITY IN THE ARABIAN SEA WATERS OF KERALA, SOUTHWEST COAST OF INDIA

The seasonal variation of the hydrographic variables and phytoplankton species in the Arabian Sea waters of the Kerala coast, Southern India was investigated during different seasons. The variables such as pH, temperature, salinity, turbidity and chlorophyll-a contents of water were found to be high during pre-monsoon season and the dissolved oxygen content was minimal. The concentration of nutrients viz., nitrate, phosphate, silicate varied independently. In the study a total of 53 species of phytoplankton were recorded. Their density was higher during the post-monsoon season than during other seasons and the diatoms were found to be the dominant species. The major phytoplankton in terms of frequency and abundance were the species namely, Biddulphia mobiliensis, Chaetoceros curvisetus, Licmophora abbreviata, Skeletonema costatum, Prorocentrum micans and Oscillatoria sp. They showed significant positive correlation with pH, temperature, salinity, nitrate, phosphate and chlorophyll-a contents, whereas turbidity, dissolved oxygen and silicate exhibited significant negative correlation. The Principal Component Analysis (PCA) developed two principal components with 84.74% of total variability in the water quality which separated pre- and post-monsoon periods from the monsoon season on axis I, and pre-monsoon and monsoon periods from post-monsoon on axis II

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Performance Evaluation of Built Environment in Local Climate Zones

The thermal performance of a building is significantly influenced by the climate around it. It is observed that the microclimate of an urban area is notably different from that of the surrounding regions. This difference is mainly due to the variations in anthropogenic heat, built morphology and surface characteristics. The Local Climate Zone (LCZ) system, effectively classifies the urban areas concerning these climatic variations. This study comprises two sections; the first section explores the climatic differences across LCZs and the impact of urban built morphology on microclimate. For this, three different LCZs – LCZ-2, LCZ-5 and LCZ-9 (high, medium and low density respectively) were modelled within the range of values prescribed in the LCZ system and an analytical study was carried out with the help of the CFD tool – ENVIMET. To understand the influence of urban morphology features on microclimate, LCZ-2, a representative LCZ was chosen and a parametric study of variations in morphology variables was carried out. It was observed that incidence angle, surface characteristics and H/W greatly influence the microclimate. The second section of the study explores the thermal performance of the built environment across the LCZs. A typical 3-bedroom residential building was considered and thermal performance evaluation of the same in three different local climatic conditions was carried out through field measurements. It was observed that heat flux in LCZ-5 (65.5 W/m2) is high compared to that of LCZ-2 (16.6 W/m2) and LCZ-9 (6.04 W/m2). The study points to the significance of location-specific building performance studies and design criteria