Trends of Hospitalizations and In-Hospital Outcomes for Traumatic Cardiac Injury in United States.

Introduction: Traumatic cardiac injury (TCI) poses a significant risk of morbidity and mortality, yet there is a lack of population-based outcomes data for these patients. Methods: The authors examined national yearly trends, demographics, and in-hospital outcomes of TCI using the National Inpatient Sample from 2007 to 2014. We focused on adult patients with a primary discharge diagnosis of TCI, categorizing them into blunt (BTCI) and penetrating (PTCI) cardiac injury. Results: A total of 11,510 cases of TCI were identified, with 7,155 (62.2%) classified as BTCI and 4,355 (37.8%) as PTCI. BTCI was predominantly caused by motor vehicle collisions (66.7%), while PTCI was mostly caused by piercing injuries (67.4%). The overall mortality rate was 11.3%, significantly higher in PTCI compared to BTCI (20.3% vs. 5.9%, χ2(1, N = 11,185) = 94.9, p <0.001). Additionally, 21.5% required blood transfusion, 19.6% developed hemopericardium, and 15.9% suffered from respiratory failure. Procedures such as heart and pericardial repair were more common in PTCI patients. Length of hospitalization and cost of care were also significantly higher for PTCI patients, W(1, N = 11,015) = 88.9, p <0.001). Conclusions: Patients with PTCI experienced higher mortality rates than those with BTCI. Within the PTCI group, young men from minority racial groups and low-income households had poorer outcomes. This highlights the need for early and specialized attention from emergency and cardiothoracic providers for patients in these demographic groups.

Autonomous Tool for Monitoring Multi-Morbidity Health Conditions in UAE and India.

Multi-morbidity is the presence of two or more long-term health conditions, including defined physical or mental health conditions, such as diabetes or schizophrenia. One of the regular and critical health cases is an elderly person with a multi-morbid health condition and special complications who lives alone. These patients are typically not familiar with advanced Information and Communications Technology (ICT), but they are comfortable using smart devices such as wearable watches and mobile phones. The use of ICT improves medical quality, promotes patient security and data security, lowers operational and administrative costs, and gives the people in charge to make informed decisions. Additionally, the use of ICT in healthcare practices greatly reduces human errors, enhances clinical outcomes, ramps up care coordination, boosts practice efficiencies, and helps in collecting data over time. The proposed research concept provides a natural technique to implement preventive health care innovative solutions since several health sensors are embedded in devices that autonomously monitor the patients' health conditions in real-time. This enhances the elder's limited ability to predict and respond to critical health situations. Autonomous monitoring can alert doctors and patients themselves of unexpected health conditions. Real-time monitoring, modeling, and predicting health conditions can trigger swift responses by doctors and health officials in case of emergencies. This study will use data science to stimulate discoveries and breakthroughs in the United Arab Emirates (UAE) and India, which will then be reproduced in other world areas to create major gains in health for people, communities, and populations.

Legal and social consequences of substance use: Results from a nationwide study in Bangladesh.

Substance use is a major public health concern and its consequences can destroy someone's life. This study aimed to explore the legal and social consequences of substance use in Bangladesh. We conducted a nationwide descriptive cross-sectional study among relapse cases of substance use from January to December 2018. We visited 138 drug rehabilitation centers countrywide and were able to recruit 939 relapse cases, from where 28 cases were excluded due to incomplete data. Finally, data from 911 cases were analyzed. The majority (89.3%) of the study participants were 19-45 years old. Most commonly used drugs were amphetamine (76.1%), cannabis (75.0%), alcohol (54.3%), cough sirup (54.2%), heroin (47.0%) and sleeping pills (21.6%). Almost half (49.5%) of the substance users were arrested for drug use and among arrested cases, 52.1% were sent to jail. About 75% of the substance users experienced a lack of family interaction, 70% experienced destroyed family relationships, and 71.4% faced social stigma. Our study also found 60% of the participants were bullied, 50% were deprived or unwilling to have social interactions. Moreover, 13.8% of the participants left home, while 8% got divorced. Our data represented the significant impact of substance use on the legal aspect and social life of individuals. However, with a multi-dimensional treatment, rehabilitation, and social intervention approach, it is not impossible to overcome. Therefore, we believe it is imperative to focus on social awareness and to create a robust platform for health promotion and improve quality of life.

Shonjibon cash and counselling: a community-based cluster randomised controlled trial to measure the effectiveness of unconditional cash transfers and mobile behaviour change communications to reduce child undernutrition in rural Bangladesh.

BACKGROUND: Undernutrition is strongly associated with poverty - levels of undernutrition are higher in poor countries than in better-off countries. Social protection especially cash transfer is increasingly recognized as an important strategy to accelerate progress in improving maternal and child nutrition. A critical method to improve nutrition knowledge and influence feeding practices is through behaviour change communication intervention. The Shonjibon Cash and Counselling study aims to assess the effectiveness of unconditional cash transfers combined with a mobile application on nutrition counselling and direct counselling through mobile phone in reducing the prevalence of stunting in children at 18 months. METHOD: The study is a longitudinal cluster randomised controlled trial, with two parallel groups, and cluster assignment by groups of villages. The cohort of mother-child dyads will be followed-up over the intervention period of approximately 24 months, starting from recruitment to 18 months of the child's age. The study will take place in north-central Bangladesh. The primary trial outcome will be the percentage of stunted children at 18 m as measured in follow up assessments starting from birth. The secondary trial outcomes will include differences between treatment arms in (1) Mean birthweight, percentage with low birthweight and small for gestational age (2) Mean child length-for age, weight for age and weight-for-length Z scores (3) Prevalence of child wasting (4) Percentage of women exclusively breastfeeding and mean duration of exclusive breastfeeding (5) Percentage of children consuming > 4 food groups (6) Mean child intake of energy, protein, carbohydrate, fat and micronutrients (7) Percentage of women at risk of inadequate nutrient intakes in all three trimesters (8) Maternal weight gain (9) Household food security (10) Number of events for child suffering from diarrhoea, acute respiratory illness and fever (11) Average costs of mobile phone BCC and cash transfer, and benefit-cost ratio for primary and secondary outcomes. DISCUSSION: The proposed trial will provide high-level evidence of the efficacy and cost-effectiveness of mobile phone nutrition behavior change communication, combined with unconditional cash transfers in reducing child undernutrition in rural Bangladesh. TRIAL REGISTRATION: The study has been registered in the Australian New Zealand Clinical Trials Registry ( ACTRN12618001975280 ).

Evaluation of Standard and Mobile Health-Supported Clinical Diagnostic Tools for Assessing Dehydration in Patients with Diarrhea in Rural Bangladesh.

Diarrhea remains a leading cause of morbidity and mortality in patients worldwide. The objective of this study was to determine the relative inter-rater reliability and usability of standard and Mobile health (mHealth)-supported World Health Organization (WHO) algorithms for dehydration assessment in patients with acute diarrhea in a rural, low-income country hospital. Two nurses blinded to each other's examinations assessed dehydration status on patients soon after hospital arrival using either the standard WHO algorithm printed on a laminated card or an mHealth-supported WHO algorithm downloaded onto a smartphone. The assignment of assessment tool was based on odd or even enrollment date. The inter-rater reliability for dehydration assessment between the two nurses was calculated using Cohen's K statistic for each study group. A total of 496 patients (< 5 years N = 349, > 5 years N = 147) were enrolled in the study; 132 (27%) had some or severe dehydration, and 364 (73%) had no dehydration on arrival. Cohen's K statistic demonstrated greater reliability for the mHealth-supported dehydration assessment (0.59) compared with the standard assessment (0.50) in the overall population (P < 0.0001), as well as in the pediatric (0.43 versus 0.37, P < 0.0001) and adult (0.79 versus 0.57, P < 0.0001) populations individually. This is the first study to show that mHealth can improve the reliability of nursing dehydration assessment in patients with acute diarrhea and the first to report on the reliability of the WHO algorithm in adult patients specifically. Future studies should focus on the impact of mHealth-supported dehydration assessment on patient-centered outcomes and examine its reliability in different settings worldwide.

Transitional appearance-based motion tracking for real-time breast self-examination supervision.

Despite much research and clinical trials, breast cancer still presents a serious threat of premature death to women. Early detection of the lumps in the breast is a key contributing factor to the successful treatment of this potentially fatal disease. Performing breast self-examination (BSE) in an accurate manner can assist a woman in detecting any abnormalities in her breasts, which may mark the onset of potential disease. This is also an essential tool used to enhance breast awareness. Using the hand, in a specific configuration, and palpating the entire breast in a certain movement pattern can optimise her feeling of the breast, In this paper we describe an intelligent automated algorithm for tracking the finger pads of a moving hand with the movement videos captured by a common web camera. The algorithm employs the principle of HCRA (hand configuration recognition algorithm) and its refinement through a simple but novel transitional appearance-based model. A novel hand motion recognition algorithm (HMRA) is developed to recognise the motion pattern. Desirable tracking and recognition results have been achieved and the robustness of this algorithm is demonstrated in this paper.

Hand motion segmentation against skin colour background in breast awareness applications.

Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.