Background Digital health is well-positioned in low and middle-income countries (LMICs) to revolutionize health care due, in part, to increasing mobile phone access and internet connectivity. This paper evaluates the underlying factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Objective The objective of this study is to identify the current digital health projects and studies being carried out in Pakistan, as well as the key stakeholders involved in these initiatives. We aim to follow a mixed-methods strategy and to evaluate these projects and studies through a strengths, weaknesses, opportunities, and threats (SWOT) analysis to identify the internal and external factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Methods This study aims to evaluate digital health projects carried out in the last 5 years in Pakistan with mixed methods. The qualitative and quantitative data obtained from field surveys were categorized according to the World Health Organization’s (WHO) recommended building blocks for health systems research, and the data were analyzed using a SWOT analysis strategy. Results Of the digital health projects carried out in the last 5 years in Pakistan, 51 are studied. Of these projects, 46% (23/51) used technology for conducting research, 30% (15/51) used technology for implementation, and 12% (6/51) used technology for app development. The health domains targeted were general health (23/51, 46%), immunization (13/51, 26%), and diagnostics (5/51, 10%). Smartphones and devices were used in 55% (28/51) of the interventions, and 59% (30/51) of projects included plans for scaling up. Artificial intelligence (AI) or machine learning (ML) was used in 31% (16/51) of projects, and 74% (38/51) of interventions were being evaluated. The barriers faced by developers during the implementation phase included the populations’ inability to use the technology or mobile phones in 21% (11/51) of projects, costs in 16% (8/51) of projects, and privacy concerns in 12% (6/51) of projects. Conclusions We conclude that while digital health has a promising future in Pakistan, it is still in its infancy at the time of this study. However, due to the coronavirus disease 2019 (COVID-19) pandemic, there is an increase in demand for digital health and implementation of health outcomes following global social distancing protocols, especially in LMICs. Hence, there is a need for active involvement by public and private organizations to regulate, mobilize, and expand the digital health sector for the improvement of health care systems in countries.

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Background: Postoperative arrhythmias are a known complication after surgical repair for congenital heart disease (CHD). This study aimed to identify and discuss the prevalence, diagnosis, and management of common rhythm disturbances seen in the immediate postoperative period after surgery for CHD in the pediatric population at a tertiary care hospital in Pakistan. Methods: A retrospective study was conducted at a tertiary care hospital in Pakistan between January 2014 and December 2018. All pediatric (<18 years old) patients admitted to the intensive care unit and undergoing continuous electrocardiographic monitoring after surgery for CHD were included in this study. Data pertaining to the incidence, diagnosis, and management of postoperative arrhythmias were collected. Results: Amongst 812 children who underwent surgery for CHD, 185 (22.8%) developed arrhythmias. Junctional ectopic tachycardia (JET) was the most common arrhythmia, observed in 120 patients (64.9%), followed by complete heart block (CHB) in 33 patients (17.8%). The highest incidence of early postoperative arrhythmia was seen in patients with atrioventricular septal defects (64.3%) and transposition of the great arteries (36.4%). Patients were managed according to the Pediatric Advanced Life Support guidelines. JET resolved successfully within 24 hours in 92% of patients, while 16 (48%) patients with CHB required a permanent pacemaker. Conclusions: More than one in five pediatric patients suffered from early postoperative arrhythmias in our setting. Further research exploring predictive factors and the development of better management protocols of patients with CHB are essential for reducing the morbidity and mortality associated with postoperative arrhythmia.

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Examination cheating activities like whispering, head movements, hand movements, or hand contact are extensively involved, and the rectitude and worthiness of fair and unbiased examination are prohibited by such cheating activities. The aim of this research is to develop a model to supervise or control unethical activities in real-time examinations. Exam supervision is fallible due to limited human abilities and capacity to handle students in examination centers, and these errors can be reduced with the help of the Automatic Invigilation System. This work presents an automated system for exams invigilation using deep learning approaches i.e., Faster Regional Convolution Neural Network (RCNN). Faster RCNN is an object detection algorithm that is implemented to detect the suspicious activities of students during examinations based on their head movements, and for student identification, MTCNN (Multi-task Cascaded Convolutional Neural Networks) is used for face detection and recognition. The training accuracy of the proposed model is 99.5% and the testing accuracy is 98.5%. The model is fully efficient in detecting and monitoring more than 100 students in one frame during examinations. Different real-time scenarios are considered to evaluate the performance of the Automatic Invigilation System. The proposed invigilation model can be implemented in colleges, universities, and schools to detect and monitor student suspicious activities. Hopefully, through the implementation of the proposed invigilation system, we can prevent and solve the problem of cheating because it is unethical.

Introduction Since most hip fractures are treated surgically, it is imperative to find an optimum fracture-to-surgery time to decrease the potential complications and enhance postoperative outcomes. In comparison to the vast plethora of literature available on surgical delay and its implications on mortality, very little, if any, research is available on the impact of delayed surgery on postoperative ICU admission. The primary objective of our study is to examine the factors influencing post-surgical ICU admission in order to work on preventive strategies to reduce the potential associated morbidity. Material and methods Investigators did a nested case control study in a university hospital. A case was defined as a patient who had postoperative ICU admission while controls were patients who did not have postoperative ICU admission after hip fracture surgery. The primary outcome variable was postoperative ICU admission. The exposure variable was defined as the time to surgery which was categorized into two categories; early and late; the early surgery included patients who were operated within ≤ 48 h and the late included patients who had their surgery >48 h. Information on potential confounders including age, type of the procedure and comorbidities were also obtained. Result reported in-line with STROCSS criteria. Results A total cohort of 1084 hip fracture surgeries were performed from January 2010 to December 2018. After screening for eligibility criteria, 911 patients were eligible for the final simple logistic regression analysis (48 cases and 863 controls). Our exposure variable i.e. time from admission to surgery showed no difference between cases and controls. The odds of being treated with Hemiarthroplasty among cases admitted in ICU was 2.42 times as compared to controls (aOR = 2.42; 95% C.I. 1.21–4.86). Conclusion Our study did not find an association between surgical delay and post-operative ICU admission after accounting for other covariates and potential confounders.

Anti-N-methyl-D-aspartate-receptor (NMDA-R) encephalitis is a new autoimmune, often paraneoplastic disorder that presents with complex neuropsychiatric symptoms. It was first described in 2007 by Dalmau et al. Our patient presented with headache, behavioral changes and then seizures with hallucinations. She was initially misdiagnosed to have schizophrenia and was prescribed antipsychotics. She deteriorated and developed further seizures with hypoventilation and choreoathetosis. Her blood investigations were positive for mycoplasma IGM. Her CSF studies showed high white cell counts, predominantly lymphocytes, and high anti-NMDA-R titre. Her brain MRI scans showed high tbl2 and FLAIR intensities in the grey and white matter of the left cerebellar hemisphere suggestive of acute disseminated encephalomyelitis. She responded to treatment with antibiotics, multiple antiepileptics, steroids and needed five sessions of plasmapheresis. There was no underlying malignancy on repeated scanning of the abdomen. She needed around one year for full recovery with intensive rehabilitation. The objective of this paper was to highlight the occurrence of this fairly new, challenging, easily missed, not-so-rare form of encephalitis often occurring in the absence of fever.