Characteristics of traumatic out-of-hospital cardiac arrest patients presenting to major centers in Karachi, Pakistan-A longitudinal cohort study

Background: Trauma is the leading cause of death for adults under 44 years of age. Survival after traumatic out-of-hospital cardiac arrest (OHCA) has been reported to be poor, and its epidemiology is not well defined. A few studies have reported better survival in response to pre-hospital life-saving interventions. Currently, no published data on traumatic cardiac arrests in the field exist from low- and lower middle-income countries. We aimed to explore the epidemiology and outcomes of traumatic OHCA patients from Karachi, Pakistan. We conducted a longitudinal cohort study at emergency departments (ED) of five major public and private hospitals of the city from January to April 2013. Data was collected on all adult patients (age 18 years or more) presenting to the hospitals directly from field with cardiac arrest and history of trauma using a structured questionnaire. Patients with do-not-resuscitate status and those referred from other hospitals were excluded.Results: During 3 months, a total of 187 patients were enrolled with mean age of 35.1 years. About 95% were men, and 68.4% had a penetrating injury. Even though half of the patients had a witnessed arrest, none received a bystander cardiopulmonary resuscitation (CPR). 83.4% were brought to the hospital in an ambulance, with median response and scene times of 3 and 2 min respectively; however, only 3 received any pre-hospital life-support interventions. One hundred eighty-one patients (96.7%) were pronounced dead on arrival to the ED, and of the remaining 6 patients, 4 received CPR in the EDs. Overall survival at the end of ED stay was 0%. Patients who received life-support interventions survived for longer time, though not clinically significant, as compared to those who did not (45 min vs. 35 min, p = 0.02).Conclusion: There was no survival after a traumatic OHCA in Karachi, Pakistan. Even though ambulances reached the scene in a very short time, pre-hospital interventions were largely absent. There is a strong need to strengthen our pre-hospital care system but most importantly train the general public to deal with emergencies and be able to provide timely bystander CPR

Attitude of Medical Students Towards Psychiatry in a Tertiary Care Hospital

Background: Dearth of psychiatrist specialists is evident worldwide. Awareness of undergraduate students towards mental illness has an important role in affecting the quality of care the patient receives and in choosing  psychiatry as a career . Decision to specialize in psychiatry based on many factors, however attitude of undergraduates towards career choice play most important role in this aspect. Objective: This study aims to explore attitude and towards psychiatry among medical undergraduates in tertiary care hospital and factors influencing this decision. Methodology: It was Descriptive cross sectional study done at Nishtar medical University, tertiary care hospital of Multan Pakistan from July to December 2019. The total 384 students from first to final year were enrolled by non probability convenient sampling technique. Participation was voluntary and ensured that response would be kept anonymous. ATP-30 (Attitude towards Psychiatry)   a 30 item self- administered questionnaire was used to measure the attitude of medical students. Data collected on a pre defined questionnaire was analyzed using SPSS version 23. Results pertaining to rates were reported as frequencies and percentages. Result: 47.4% of study respondents were male and 52.6 % were female. 52.3% of our study respondents strongly agree that psychiatry was respected branch of medicine and 56.7% strongly agree that psychiatry should be an important part of medical curriculum. 19.4% of study respondents consider it in the list of the carrier choice while majority didn’t think that it should be in their career list options. Conclusion: Majority of students shows positive attitude. Mostly found it as respected and essential field of medicine. However insufficient knowledge and awareness can also be observed in responses pertaining to available treatment and advancement in the field. There is a need to revise the curriculum and clinical rotation schedule to raise interest of students  regarding  mental health issues of their community and ease their decision in choosing it as a career. Keywords: Attitude, Undergraduate medical students, Psychiatry, Multan, Pakistan DOI: 10.7176/JMPB/63-06 Publication date: January 31st 202

Estimation of the burden of out-of-hospital traumatic cardiac arrest in Karachi, Pakistan, using a cross-sectional capture-recapture analysis

Background: The burden of trauma-related-out-of-hospital cardiac arrest (OHCA) in developing countries like Pakistan remains largely unexplored due to a lack of organized pre-hospital systems. In order to estimate the burden, we used a two-sample capture-recapture method which has been used in several domains to estimate difficult-to-count populations.Methods: We obtained 3-month data from two sources: Records of two major EMS (emergency medical services) systems and five major hospitals providing coverage to the city\u27s population. All adults with traumatic OHCA were included. Information on variables such as name, age, gender, date and time of arrest, cause of arrest, and destination hospital were obtained for these cases and data were compared to obtain a matched sample. Utilizing an equation and different levels of restrictive criteria, estimates were obtained for burden.Results: The EMS records reported 788 and hospital records reported 344 cases of traumatic OHCA. The capture-recapture analysis estimated the annual traumatic OHCA incidence as 45.7/100,000 (95% CI: 44.2 to 47.3). Estimation of the burden from individual hospital or EMS records underestimated and calculated only 14.6% and 33.9% of the total burden, respectively. Most of the traumatic arrest victims had gunshot wound (GSW) (65.2%) followed by road traffic injuries (RTI) (20.8%).Conclusion: The actual burden of traumatic OHCA in Pakistan is larger than the burden reported by either the hospitals or EMS services alone. Most of the cases occurred due to GSW and RTI. A multipronged approach is required to manage the problem; from prevention to developing organized trauma care systems and training lay responders in pre-hospital trauma care is vital

A new color image encryption technique using DNA computing and Chaos-based substitution box

In many cases, images contain sensitive information and patterns that require secure processing to avoid risk. It can be accessed by unauthorized users who can illegally exploit them to threaten the safety of people’s life and property. Protecting the privacies of the images has quickly become one of the biggest obstacles that prevent further exploration of image data. In this paper, we propose a novel privacy-preserving scheme to protect sensitive information within images. The proposed approach combines deoxyribonucleic acid (DNA) sequencing code, Arnold transformation (AT), and a chaotic dynamical system to construct an initial S-box. Various tests have been conducted to validate the randomness of this newly constructed S-box. These tests include National Institute of Standards and Technology (NIST) analysis, histogram analysis (HA), nonlinearity analysis (NL), strict avalanche criterion (SAC), bit independence criterion (BIC), bit independence criterion strict avalanche criterion (BIC-SAC), bit independence criterion nonlinearity (BIC-NL), equiprobable input/output XOR distribution, and linear approximation probability (LP). The proposed scheme possesses higher security wit NL = 103.75, SAC ≈ 0.5 and LP = 0.1560. Other tests such as BIC-SAC and BIC-NL calculated values are 0.4960 and 112.35, respectively. The results show that the proposed scheme has a strong ability to resist many attacks. Furthermore, the achieved results are compared to existing state-of-the-art methods. The comparison results further demonstrate the effectiveness of the proposed algorithm

A robust deep learning approach for tomato plant leaf disease localization and classification

Tomato plants' disease detection and classification at the earliest stage can save the farmers from expensive crop sprays and can assist in increasing the food quantity. Although, extensive work has been presented by the researcher for the tomato plant disease classification, however, the timely localization and identification of various tomato leaf diseases is a complex job as a consequence of the huge similarity among the healthy and affected portion of plant leaves. Furthermore, the low contrast information between the background and foreground of the suspected sample has further complicated the plant leaf disease detection process. To deal with the aforementioned challenges, we have presented a robust deep learning (DL)-based approach namely ResNet-34-based Faster-RCNN for tomato plant leaf disease classification. The proposed method includes three basic steps. Firstly, we generate the annotations of the suspected images to specify the region of interest (RoI). In the next step, we have introduced ResNet-34 along with Convolutional Block Attention Module (CBAM) as a feature extractor module of Faster-RCNN to extract the deep key points. Finally, the calculated features are utilized for the Faster-RCNN model training to locate and categorize the numerous tomato plant leaf anomalies. We tested the presented work on an accessible standard database, the PlantVillage Kaggle dataset. More specifically, we have obtained the mAP and accuracy values of 0.981, and 99.97% respectively along with the test time of 0.23 s. Both qualitative and quantitative results confirm that the presented solution is robust to the detection of plant leaf disease and can replace the manual systems. Moreover, the proposed method shows a low-cost solution to tomato leaf disease classification which is robust to several image transformations like the variations in the size, color, and orientation of the leaf diseased portion. Furthermore, the framework can locate the affected plant leaves under the occurrence of blurring, noise, chrominance, and brightness variations. We have confirmed through the reported results that our approach is robust to several tomato leaf diseases classification under the varying image capturing conditions. In the future, we plan to extend our approach to apply it to other parts of plants as well

A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI images

A brain tumor is an abnormal growth in brain cells that causes damage to various blood vessels and nerves in the human body. An earlier and accurate diagnosis of the brain tumor is of foremost important to avoid future complications. Precise segmentation of brain tumors provides a basis for surgical planning and treatment to doctors. Manual detection using MRI images is computationally complex in cases where the survival of the patient is dependent on timely treatment, and the performance relies on domain expertise. Therefore, computerized detection of tumors is still a challenging task due to significant variations in their location and structure, i.e., irregular shapes and ambiguous boundaries. In this study, we propose a custom Mask Region-based Convolution neural network (Mask RCNN) with a densenet-41 backbone architecture that is trained via transfer learning for precise classification and segmentation of brain tumors. Our method is evaluated on two different benchmark datasets using various quantitative measures. Comparative results show that the custom Mask-RCNN can more precisely detect tumor locations using bounding boxes and return segmentation masks to provide exact tumor regions. Our proposed model achieved an accuracy of 96.3% and 98.34% for segmentation and classification respectively, demonstrating enhanced robustness compared to state-of-the-art approaches

Acaricidal and insecticidal effects of essential oils against ectoparasites of veterinary importance

Ectoparasitism in animals has become an issue of great concern that needs to be resolved to prevent huge economic losses occurring to livestock industry all over the world. Synthetic adrugs have been playing a major role in controlling ectoparasites, but their frequent and irrational use has resulted in drug resistance to routinely used chemicals and their residual effects on food and environment. Therefore, this approach of using chemical acaricides and insecticides is losing its popularity and effectiveness in controlling ectoparasites. So, the development of alternative approaches in ectoparasite management is currently required. Among alternative protocols, plants and their essential oils have played remarkable role in controlling different ectoparasites (ticks, flies, mites, lice) of veterinary importance. Essential oils have been proved to be cheaper, more effective and safer therapeautic agents against different ectoparasites of livestock importance