Septic Shock Due to Tuberculosis in Down Syndrome

Both Immune dysfunction and deficiency, are known in Down syndrome. Tuberculosis commonly presents as insidious illness and septicemic shock is its rare presentation, mostly in immunocompromized patients. We report a 16 year old boy with Down syndrome presenting with septicemic shock due to tuberculosis.     

Drug dependence in adolescents 1978–2003: A clinical-based observation from north India

Objective  To study the demographic and clinical profile of adolescent subjects (≤18 yr) presenting to a state-funded drug deaddiction centre in north India. Methods  Data on demographic and clinical features were extracted from available case notes of adolescent patients who presented to the centre during 1978–2003 (n=85). Results  Many adolescents came from nuclear family (63.5%), of urban background (83.5%), and were school dropouts (54.1%). Mean age-at-first-use of the primary substance was 14.8 yr and mean age at first presentation was 17 yr. The commonest used primary class of substance was opioids (76.2%) and the commonest used opioid was heroin (36.5%). More than half of the subjects (54.2%) were also nicotine dependent at the time of presentation. The most common reason for starting the use of drugs was curiosity (78.8%). About one-fifth (21.2%) of the subjects indulged in high-risk behaviour such as having sexual intercourse with multiple sexual partners. Nearly half of the subjects had positive family history of either drug dependence (40.2%) or psychiatric disorder (5.5%). Conclusion  The results suggest that the development of substance dependence in children and adolescents is a combination of familial and social vulnerability factors, including the drug culture of the social milieu.     

Localized hippocampus measures are associated with Alzheimer pathology and cognition independent of total hippocampal volume

Hippocampal injury in the Alzheimer's disease (AD) pathological process is region-specific and magnetic resonance imaging (MRI)-based measures of localized hippocampus (HP) atrophy are known to detect region-specific changes associated with clinical AD, but it is unclear whether these measures provide information that is independent of that already provided by measures of total HP volume. Therefore, this study assessed the strength of association between localized HP atrophy measures and AD-related measures including cerebrospinal fluid (CSF) amyloid beta and tau concentrations, and cognitive performance, in statistical models that also included total HP volume as a covariate. A computational technique termed localized components analysis (LoCA) was used to identify 7 independent patterns of HP atrophy among 390 semiautomatically delineated HP from baseline magnetic resonance imaging of participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among cognitively normal participants, multiple measures of localized HP atrophy were significantly associated with CSF amyloid concentration, while total HP volume was not. In addition, among all participants, localized HP atrophy measures and total HP volume were both independently and additively associated with CSF tau concentration, performance on numerous neuropsychological tests, and discrimination between normal, mild cognitive impairment (MCI), and AD clinical diagnostic groups. Together, these results suggest that regional measures of hippocampal atrophy provided by localized components analysis may be more sensitive than total HP volume to the effects of AD pathology burden among cognitively normal individuals and may provide information about HP regions whose deficits may have especially profound cognitive consequences throughout the AD clinical course.     

A clinico-epidemiological study of rescuer burns

Rescuer burn is a relatively newer terminology introduced to define the burns sustained by a person attempting to rescue a primary burn victim. Few studies have been published thus far on this peculiar type of burns. Due to the general neglect of the rescuer burns victim and discontinuation of treatment in most cases, once the primary victim dies, the rescuer often ends up in badly infected wounds and has a delayed return to work. A prospective study was conducted at the B J Medical College and Civil Hospital, Ahmedabad from January 2009 to December 2012 on the rescuer burns patients treated in its burns and plastic surgery department. 3074 patients of burns received treatment during the period of study. Of these, 48 patients gave the history of sustaining burns while trying to rescue a burns victim. Male to female ratio of rescuers was approximately 7:1. It was significantly higher as compared to the ratio of 1:0.8 of females to male burn victims observed at our centre (p ≤ 0.01). Average age of the rescuers was higher in males as compared to females but the difference was not significant (p ≥ 0.05). Of the 45 cases of female primary burns victims, male rescuer was husband of the primary victim in 41/45 cases (91.1%), mother was rescuer in three cases (6.6% cases) and sister was rescuer in one case. Though multiple people came to rescue a burns victim, in all cases, it was seen that it was the first rescuer who sustained burns himself or herself. None of the rescuers had any knowledge of the techniques and precautions to be taken while performing a rescue operation irrespective of their education status, indirectly pointing to the lack of any teaching on burns rescue in the school education curriculum.     

The bedside insertion of inferior vena cava filters using ultrasound guidance

Since the introduction of inferior vena cava (IVC) filters more than 30 years ago, there has been a steady improvement in the design, ease, and safety of the delivery systems. Today, all of the commonly used filters can be placed via a peripheral vein by using standard percutaneous Seldinger technique. However, this typically requires fluoroscopy, intravenous contrast agents, radiation exposure, and transport of the patient to the interventional or operating suite. In the multiply injured trauma or critically-ill intensive care unit patient, often requiring inotropic and ventilator support, transport to these facilities can be hazardous. In addition, these patients frequently have a combination of neurospinal and long bone injuries, which require skeletal immobilization, thus further complicating transportation. Advancing technology with portable duplex ultrasound and improved deep abdominal duplex imaging has allowed for routine diagnostic evaluation of the IVC, renal veins, and surrounding visceral structures. This degree of accuracy has allowed numerous centers to gain experience with ultrasonic imaging of the IVC and insertion site after a filter has been placed. A logical progression has evolved to the point in which, today, duplex ultrasound can be used to guide the insertion of IVC filters. The following describes, in detail, a technique for the percutaneous placement of an IVC filter at the bedside using only duplex ultrasound guidance. The article also briefly compares and contrasts this technique with an alternate technique using intravascular ultrasound. Vena caval interruption can be safely performed under ultrasound guidance in a monitored, intensive care unit environment. In selected intensive care unit or multiply injured trauma patients, this will reduce the risk, complexity and cost of transport for these critically ill patients. Duplex-guided IVC filter placement also reduces procedural costs compared to an operating room or interventional suite, and eliminates intravenous contrast material exposure.     

Machine learning–based heart disease prediction system for Indian population: An exploratory study done in South India

BackgroundIn India, huge mortality occurs due to cardiovascular diseases (CVDs) as these diseases are not diagnosed in early stages. Machine learning (ML) algorithms can be used to build efficient and economical prediction system for early diagnosis of CVDs in India.MethodsA total of 1670 anonymized medical records were collected from a tertiary hospital in South India. Seventy percent of the collected data were used to train the prediction system. Five state-of-the-art ML algorithms (k-Nearest Neighbours, Naïve Bayes, Logistic Regression, AdaBoost and Random Forest [RF]) were applied using Python programming language to develop the prediction system. The performance was evaluated over remaining 30% of data. The prediction system was later deployed in the cloud for easy accessibility via Internet.ResultsML effectively predicted the risk of heart disease. The best performing (RF) prediction system correctly classified 470 out of 501 medical records thus attaining a diagnostic accuracy of 93.8%. Sensitivity and specificity were observed to be 92.8% and 94.6%, respectively. The prediction system attained positive predictive value of 94% and negative predictive value of 93.6%. The prediction model developed in this study can be accessed at http://das.southeastasia.cloudapp.azure.com/predict/ConclusionsML-based prediction system developed in this study performs well in early diagnosis of CVDs and can be accessed via Internet. This study offers promising results suggesting potential use of ML-based heart disease prediction system as a screening tool to diagnose heart diseases in primary healthcare centres in India, which would otherwise get undetected.