Our Experience in the Surgical Management of Arterio-Venous Malformations of the head and neck

Introduction

Vascular anomalies comprise a diverse group of abnormalities in blood vessel morphogenesis that usually occur prenatally. Arterio-venous malformations (AVMs) are rare congenital vascular lesions accounting for 1.5% of all vascular anomalies, with 50% of them occur in the oral and maxillo-facial regions. Treatment of large, complex vascular lesions is a serious challenge for patients and surgeons because it can cause disfigurement and massive haemorrhage, which may be spontaneous or the result of surgical intervention. Our study aimed to demonstrate surgical management of massive AVMs of the head and neck.

Method

This retrospective study shows the treatment outcomes of 28 patients with massive maxillo-facial vascular malformations, who presented to our department for treatment from 1 January 2015 to 31 July 2022.

Results

Twenty-eight patients with a mean age of 17.32 ± 12.21 years (women: 15, men: 13) were enrolled in the study. Diagnosis included extra cranial AVMs of the head and neck region. Treatment modalities, in isolation or combination, included angioembolisation procedure, sclerotherapy, and surgery.

Conclusion

Management of AVMs is challenging owing to the replacement of normal tissue by the diseased ones and the high rate of recurrence. Hence, multi-modal approaches are needed for the effective restoration of tissues.

Frequency of Hyponatremia in Adults with Acute Bacterial Meningitis

Bacterial meningitis is a life-threatening disease. Bacterial meningitis patients are prone to develop acute hyponatremia. In the central nervous system infection hyponatremia could be due to the Syndrome of Inappropriate Anti Diuretic Hormone secretion. The frequency of hyponatremia in adults with acute bacterial meningitis patients was seen in this study. This cross-sectional study was conducted in the Internal Medicine Department of Mymensingh Medical College Hospital, Mymensingh, Bangladesh from February 2016 to July 2016. A total of 50 patients were enrolled in this study by purposive sampling. Among 50 acute bacterial meningitis patients, 33 (66%) were diagnosed as hyponatremic state. The mean serum sodium level of 33 hyponatremic bacterial meningitis cases was 130.66±2.95 mmol/L. Most of the cases (78.79%) were mild hyponatremic state (130 mmol/L-135 mmol/L) whereas 18.18% were revealed as moderate hyponatremia (125 mmol/L-129 mmol/L). Only 3.03% of cases were presented as severe cases (≤124 mmol/L). The result revealed that a large number of patients with acute bacterial meningitis were suffering from hyponatremia and in the majority of cases were mildly hyponatremic.

Post-hospitalization Short Versus Long Steroid Taper Strategies in Patients With Acute Severe Ulcerative Colitis: A Comparison of Clinical Outcomes

Background

Ulcerative colitis (UC) is a chronic inflammatory colon disease characterized by relapsing flares and remission episodes. However, the optimal steroid tapering strategy in patients hospitalized for acute severe UC (ASUC) remains relatively unknown. We aim to examine the clinical outcomes in patients hospitalized for ASUC regarding variable prednisone taper regimens upon discharge.

Methods

We retrospectively reviewed all adult patients admitted to our facility with ASUC between 2000 and 2022. Patients were divided into 2 groups based on the duration of steroid taper on discharge (< 6 and > 6 weeks). Patients who had colectomy at index admission were excluded from the analysis. The primary outcome was rehospitalization for ASUC within 6 months of index admission. Secondary outcomes included the need for colectomy, worsening endoscopic disease extent and/or severity during the follow-up period (6 months), and a composite outcome as a surrogate of worsening disease (defined as a combination of all products above). Two-sample t-tests and Pearson's chi-square tests were used to compare the means of continuous and categorical variables, respectively. Multivariate logistic regression analysis was performed to identify independent predictors for rehospitalization with ASUC.

Results

A total of 215 patients (short steroid taper = 91 and long steroid taper = 124) were analyzed. A higher number of patients in the long steroid taper group had a longer disease duration since diagnosis and moderate-severe endoscopic disease activity (63.8 vs. 25.6 months, p < 0.0001, 46.8% vs. 23.1%, P = ≤ .05, respectively). Both groups had similar disease extent, prior biologic therapy, and the need for inpatient rescue therapy. At the 6-month follow-up, rates of rehospitalization with a flare of UC were comparable between the 2 groups (68.3% vs. 68.5%, P = .723). On univariate and multivariate logistic regression, escalation of steroid dose within four weeks of discharge (aOR 6.09, 95% CI: 1.82-20.3, P  = .003) was noted to be the only independent predictor for rehospitalization with ASUC.

Conclusions

This is the first study comparing clinical outcomes between post-discharge steroid tapering regimens in hospitalized patients for ASUC. Both examined steroid taper regimens upon discharge showed comparable clinical results. Hence, we suggest a short steroid taper as a standard post-hospitalization strategy in patients following ASUC encounters. It is likely to enhance patient tolerability and reduce steroid-related adverse effects without adversely affecting outcomes.

Age, Gender, and Liver Enzyme Impact Hospital Stay in COVID-19 Minority Patient with Cancer in the USA: Does Race Matters in the Pandemic?

Patients with cancer are known to have a poor prognosis when infected with SARS-CoV-2 infection. We aimed in this study to assess health outcomes in COVID-19 patients with different cancers in comparison to non-cancer COVID-19 patients from different centers in the United States (US). We evaluated medical records of 1,943 COVID-19 Cancer patients from 3 hospitals admitted between December 2019 to October 2021 and compared them with non-cancer COVID-19 patients. Among 1,943 hospitalized COVID-19 patients, 18.7% (n=364) have an active or previous history of cancer. Among these 364 cancer patients, 222 were African Americans (61.7%) and 121 were Caucasians (33.2%). Cancer patients had significantly longer hospitalization compared to controls (8.24 vs 6.7 days). Overall, Lung cancer is associated with high mortality. Patients with a previous history of cancer were more prone to death (p=0.04) than active cancer patients. In univariate and multivariate analyses, predictors of death among cancer patients were male sex, older age, presence of dyspnea, elevated troponin, elevated AST (0.001) and ALT (0.05), low albumin (p=0.04) and mechanical ventilation (p=0.001). Patients with a previous history of cancer were more prone to death when compared to active cancer COVID-19 patients. Early recognition of cancer COVID-19 patients' death-associated risk factors can help determine appropriate treatment and management plans for better prognosis and outcome.

Optimizing multimodal feature selection using binary reinforced cuckoo search algorithm for improved classification performance

Background

Feature selection is a vital process in data mining and machine learning approaches by determining which characteristics, out of the available features, are most appropriate for categorization or knowledge representation. However, the challenging task is finding a chosen subset of elements from a given set of features to represent or extract knowledge from raw data. The number of features selected should be appropriately limited and substantial to prevent results from deviating from accuracy. When it comes to the computational time cost, feature selection is crucial. A feature selection model is put out in this study to address the feature selection issue concerning multimodal.

Methods

In this work, a novel optimization algorithm inspired by cuckoo birds' behavior is the Binary Reinforced Cuckoo Search Algorithm (BRCSA). In addition, we applied the proposed BRCSA-based classification approach for multimodal feature selection. The proposed method aims to select the most relevant features from multiple modalities to improve the model's classification performance. The BRCSA algorithm is used to optimize the feature selection process, and a binary encoding scheme is employed to represent the selected features.

Results

The experiments are conducted on several benchmark datasets, and the results are compared with other state-of-the-art feature selection methods to evaluate the effectiveness of the proposed method. The experimental results demonstrate that the proposed BRCSA-based approach outperforms other methods in terms of classification accuracy, indicating its potential applicability in real-world applications. In specific on accuracy of classification (average), the proposed algorithm outperforms the existing methods such as DGUFS with 32%, MBOICO with 24%, MBOLF with 29%, WOASAT 22%, BGSA with 28%, HGSA 39%, FS-BGSK 37%, FS-pBGSK 42%, and BSSA 40%.

Transcriptome Changes and Metabolic Outcomes After Bariatric Surgery in Adults With Obesity and Type 2 Diabetes

Context

Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery.

Objective

We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome.

Methods

We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction.

Results

Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (SKT4, SIRT1, and TNF superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery.

Conclusion

The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.

Impact of Genetic Variations on Thromboembolic Risk in Saudis with Sickle Cell Disease

BACKGROUND

Sickle cell disease (SCD) is a Mendelian disease characterized by multigenic phenotypes. Previous reports indicated a higher rate of thromboembolic events (TEEs) in SCD patients. A number of candidate polymorphisms in certain genes (e.g., FVL, PRT, and MTHFR) were previously reported as risk factors for TEEs in different clinical conditions. This study aimed to genotype these genes and other loci predicted to underlie TEEs in SCD patients.

METHODOLOGY

A multi-center genome-wide association study (GWAS) involving Saudi SCD adult patients with a history of TEEs (n = 65) and control patients without TEE history (n = 285) was performed. Genotyping used the 10× Affymetrix Axiom array, which includes 683,030 markers. Fisher's exact test was used to generate p-values of TEE associations with each single-nucleotide polymorphism (SNP). The haplotype analysis software tool version 1.05, designed by the University of Göttingen, Germany, was used to identify the common inherited haplotypes.

RESULTS

No association was identified between the targeted single-nucleotide polymorphism rs1801133 in MTHFR and TEEs in SCD (p = 0.79). The allele frequency of rs6025 in FVL and rs1799963 in PRT in our cohort was extremely low (<0.01); thus, both variants were excluded from the analysis as no meaningful comparison was possible. In contrast, the GWAS analysis showed novel genome-wide associations (p < 5 × 10-8) with seven signals; five of them were located on Chr 11 (rs35390334, rs331532, rs317777, rs147062602, and rs372091), one SNP on Chr 20 (rs139341092), and another on Chr 9 (rs76076035). The other 34 SNPs located on known genes were also detected at a signal threshold of p < 5 × 10-6. Seven of the identified variants are located in olfactory receptor family 51 genes (OR51B5, OR51V1, OR51A1P, and OR51E2), and five variants were related to family 52 genes (OR52A5, OR52K1, OR52K2, and OR52T1P). The previously reported association between rs5006884-A in OR51B5 and fetal hemoglobin (HbF) levels was confirmed in our study, which showed significantly lower levels of HbF (p = 0.002) and less allele frequency (p = 0.003) in the TEE cases than in the controls. The assessment of the haplotype inheritance pattern involved the top ten significant markers with no LD (rs353988334, rs317777, rs14788626882, rs49188823, rs139349992, rs76076035, rs73395847, rs1368823, rs8888834548, and rs1455957). A haplotype analysis revealed significant associations between two haplotypes (a risk, TT-AA-del-AA-ins-CT-TT-CC-CC-AA, and a reverse protective, CC-GG-ins-GG-del-TT-CC-TT-GG-GG) and TEEs in SCD (p = 0.024, OR = 6.16, CI = 1.34-28.24, and p = 0.019, OR = 0.33, CI = 0.13-0.85, respectively).

CONCLUSIONS

Seven markers showed novel genome-wide associations; two of them were exonic variants (rs317777 in OLFM5P and rs147062602 in OR51B5), and less significant associations (p < 5 × 10-6) were identified for 34 other variants in known genes with TEEs in SCD. Moreover, two 10-SNP common haplotypes were determined with contradictory effects. Further replication of these findings is needed.

Deep residual-dense network based on bidirectional recurrent neural network for atrial fibrillation detection

Atrial fibrillation easily leads to stroke, cerebral infarction and other complications, which will seriously harm the life and health of patients. Traditional deep learning methods have weak anti-interference and generalization ability. Therefore, we propose a new-fashioned deep residual-dense network via bidirectional recurrent neural network (RNN) model for atrial fibrillation detection. The combination of one-dimensional dense residual network and bidirectional RNN for atrial fibrillation detection simplifies the tedious feature extraction steps, and constructs the end-to-end neural network to achieve atrial fibrillation detection through data feature learning. Meanwhile, the attention mechanism is utilized to fuse the different features and extract the high-value information. The accuracy of the experimental results is 97.72%, the sensitivity and specificity are 93.09% and 98.71%, respectively compared with other methods.

Transcriptomic and Proteomic Analysis Reveals the Potential Role of RBMS1 in Adipogenesis and Adipocyte Metabolism

Adipocytes play a critical role in maintaining a healthy systemic metabolism by storing and releasing energy in the form of fat and helping to regulate glucose and lipid levels in the body. Adipogenesis is the process through which pre-adipocytes are differentiated into mature adipocytes. It is a complex process involving various transcription factors and signaling pathways. The dysregulation of adipogenesis has been implicated in the development of obesity and metabolic disorders. Therefore, understanding the mechanisms that regulate adipogenesis and the factors that contribute to its dysregulation may provide insights into the prevention and treatment of these conditions. RNA-binding motif single-stranded interacting protein 1 (RBMS1) is a protein that binds to RNA and plays a critical role in various cellular processes such as alternative splicing, mRNA stability, and translation. RBMS1 polymorphism has been shown to be associated with obesity and type 2 diabetes, but the role of RBMS1 in adipose metabolism and adipogenesis is not known. We show that RBMS1 is highly expressed during the early phase of the differentiation of the murine adipocyte cell line 3T3-L1 and is significantly upregulated in the adipose tissue depots and adipocytes of high-fat-fed mice, implying a possible role in adipogenesis and adipose metabolism. Knockdown of RBMS1 in pre-adipocytes impacted the differentiation process and reduced the expression of some of the key adipogenic markers. Transcriptomic and proteomic analysis indicated that RBMS1 depletion affected the expression of several genes involved in major metabolic processes, including carbohydrate and lipid metabolism. Our findings imply that RBMS1 plays an important role in adipocyte metabolism and may offer novel therapeutic opportunity for metabolic disorders such as obesity and type 2 diabetes.

Whole genome transcriptomic reveals heat stroke molecular signatures in humans

An evolutionary heat shock response (HSR) protects most living species, including humans, from heat-induced macromolecular damage. However, its role in the pathogenesis of heat stroke is unknown. We examined the whole genome transcriptome in peripheral blood mononuclear cells of a cohort of subjects exposed to the same high environmental heat conditions, who developed heat stroke (n = 19) versus those who did not (n = 19). Patients with heat stroke had a mean rectal temperature at admission of 41.7 ± 0.8°C, and eight were in deep coma (Glasgow Coma Score = 3). The transcriptome showed that genes involved in more than half of the entire chaperome were differentially expressed relative to heat stress control. These include the heat shock protein, cochaperone, and chaperonin genes, indicating a robust HSR. Differentially expressed genes also encoded proteins related to unfolded protein response, DNA repair, energy metabolism, oxidative stress, and immunity. The analysis predicted perturbations of the proteome network and energy production. Cooling therapy attenuated these alterations without complete restoration of homeostasis. We validated the significantly expressed genes by a real-time polymerase chain reaction. The findings reveal the molecular signature of heat stroke. They also suggested that a powerful HSR may not be sufficient to protect against heat injury. The overwhelming proteotoxicity and energy failure could play a pathogenic role. KEY POINTS: Most living species, including humans, have inherent heat stress response (HSR) that shields them against heat-induced macromolecular damage. The role of the HSR in subjects exposed to environmental heat who progressed to heat stroke versus those that did not is unknown. Our findings suggest that heat stroke induces a broad and robust HSR of nearly half of the total heat shock proteins, cochaperones, and chaperonin genes. Heat stroke patients exhibited inhibition of genes involved in energy production, including oxidative phosphorylation and ATP production. Significant enrichment of neurodegenerative pathways, including amyloid processing signalling, the Huntington's and Parkinson's disease signalling suggestive of brain proteotoxicity was noted. The data suggests that more than a powerful HSR may be required to protect against heat stroke. Overwhelming proteotoxicity and energy failure might contribute to its pathogenesis.

Identification of novel interacts partners of ADAR1 enzyme mediating the oncogenic process in aggressive breast cancer

Triple-negative breast cancer (TNBC) subtype is characterized by aggressive clinical behavior and poor prognosis patient outcomes. Here, we show that ADAR1 is more abundantly expressed in infiltrating breast cancer (BC) tumors than in benign tumors. Further, ADAR1 protein expression is higher in aggressive BC cells (MDA-MB-231). Moreover, we identify a novel interacting partners proteins list with ADAR1 in MDA-MB-231, using immunoprecipitation assay and mass spectrometry. Using iLoop, a protein-protein interaction prediction server based on structural features, five proteins with high iloop scores were discovered: Histone H2A.V, Kynureninase (KYNU), 40S ribosomal protein SA, Complement C4-A, and Nebulin (ranged between 0.6 and 0.8). In silico analysis showed that invasive ductal carcinomas had the highest level of KYNU gene expression than the other classifications (p < 0.0001). Moreover, KYNU mRNA expression was shown to be considerably higher in TNBC patients (p < 0.0001) and associated with poor patient outcomes with a high-risk value. Importantly, we found an interaction between ADAR1 and KYNU in the more aggressive BC cells. Altogether, these results propose a new ADAR-KYNU interaction as potential therapeutic targeted therapy in aggressive BC.

RNA- and ATAC-sequencing Reveals a Unique CD83+ Microglial Population Focally Depleted in Parkinson's Disease

All brain areas affected in Parkinson's disease (PD) show an abundance of microglia with an activated morphology together with increased expression of pro-inflammatory cytokines, suggesting that neuroinflammation may contribute to the neurodegenerative process in this common and incurable disorder. We applied a single nucleus RNA- and ATAC-sequencing approach using the 10x Genomics Chromium platform to postmortem PD samples to investigate microglial heterogeneity in PD. We created a multiomic dataset using substantia nigra (SN) tissues from 19 PD donors and 14 non-PD controls (NPCs), as well as three other brain regions from the PD donors which are differentially affected in this disease: the ventral tegmental area (VTA), substantia inominata (SI), and hypothalamus (HypoTs). We identified thirteen microglial subpopulations within these tissues as well as a perivascular macrophage and a monocyte population, of which we characterized the transcriptional and chromatin repertoires. Using this data, we investigated whether these microglial subpopulations have any association with PD and whether they have regional specificity. We uncovered several changes in microglial subpopulations in PD, which appear to parallel the magnitude of neurodegeneration across these four selected brain regions. Specifically, we identified that inflammatory microglia in PD are more prevalent in the SN and differentially express PD-associated markers. Our analysis revealed the depletion of a CD83 and HIF1A- expressing microglial subpopulation, specifically in the SN in PD, that has a unique chromatin signature compared to other microglial subpopulations. Interestingly, this microglial subpopulation has regional specificity to the brainstem in non-disease tissues. Furthermore, it is highly enriched for transcripts of proteins involved in antigen presentation and heat-shock proteins, and its depletion in the PD SN may have implications for neuronal vulnerability in disease.

Vulnerable newborn types: analysis of subnational, population-based birth cohorts for 541 285 live births in 23 countries, 2000-2021

OBJECTIVE

To examine prevalence of novel newborn types among 541 285 live births in 23 countries from 2000 to 2021.

DESIGN

Descriptive multi-country secondary data analysis.

SETTING

Subnational, population-based birth cohort studies (n = 45) in 23 low- and middle-income countries (LMICs) spanning 2000-2021.

POPULATION

Liveborn infants.

METHODS

Subnational, population-based studies with high-quality birth outcome data from LMICs were invited to join the Vulnerable Newborn Measurement Collaboration. We defined distinct newborn types using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], nonLBW) as ten types (using all three outcomes), six types (by excluding the birthweight categorisation), and four types (by collapsing the AGA and LGA categories). We defined small types as those with at least one classification of LBW, PT or SGA. We presented study characteristics, participant characteristics, data missingness, and prevalence of newborn types by region and study.

RESULTS

Among 541 285 live births, 476 939 (88.1%) had non-missing and plausible values for gestational age, birthweight and sex required to construct the newborn types. The median prevalences of ten types across studies were T+AGA+nonLBW (58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW (14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%), PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). The median prevalence of small types (six types, 37.6%) varied across studies and within regions and was higher in Southern Asia (52.4%) than in Sub-Saharan Africa (34.9%).

CONCLUSIONS

Further investigation is needed to describe the mortality risks associated with newborn types and understand the implications of this framework for local targeting of interventions to prevent adverse pregnancy outcomes in LMICs.

Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach

Knee osteoarthritis is a challenging problem affecting many adults around the world. There are currently no medications that cure knee osteoarthritis. The only way to control the progression of knee osteoarthritis is early detection. Currently, X-ray imaging is a central technique used for the prediction of osteoarthritis. However, the manual X-ray technique is prone to errors due to the lack of expertise of radiologists. Recent studies have described the use of automated systems based on machine learning for the effective prediction of osteoarthritis from X-ray images. However, most of these techniques still need to achieve higher predictive accuracy to detect osteoarthritis at an early stage. This paper suggests a method with higher predictive accuracy that can be employed in the real world for the early detection of knee osteoarthritis. In this paper, we suggest the use of transfer learning models based on sequential convolutional neural networks (CNNs), Visual Geometry Group 16 (VGG-16), and Residual Neural Network 50 (ResNet-50) for the early detection of osteoarthritis from knee X-ray images. In our analysis, we found that all the suggested models achieved a higher level of predictive accuracy, greater than 90%, in detecting osteoarthritis. However, the best-performing model was the pretrained VGG-16 model, which achieved a training accuracy of 99% and a testing accuracy of 92%.

Quantitative proteomics analysis of COVID-19 patients: Fetuin-A and tetranectin as potential modulators of innate immune responses

Treatment of severe cases of coronavirus disease 2019 (COVID-19) is extremely important to minimize death and end-organ damage. Here we performed a proteomic analysis of plasma samples from mild, moderate and severe COVID-19 patients. Analysis revealed differentially expressed proteins and different therapeutic potential targets related to innate immune responses such as fetuin-A, tetranectin (TN) and paraoxonase-1 (PON1). Furthermore, protein changes in plasma showed dysregulation of complement and coagulation cascades in COVID-19 patients compared to healthy controls. In conclusion, our proteomics data suggested fetuin-A and TN as potential targets that might be used for diagnosis as well as signatures for a better understanding of the pathogenesis of COVID-19 disease.

IoMT with Deep CNN: AI-Based Intelligent Support System for Pandemic Diseases

The Internet of Medical Things (IoMT) is an extended version of the Internet of Things (IoT). It mainly concentrates on the integration of medical things for servicing needy people who cannot get medical services easily, especially rural area people and aged peoples living alone. The main objective of this work is to design a real time interactive system for providing medical services to the needy who do not have a sufficient medical infrastructure. With the help of this system, people will get medical services at their end with minimal medical infrastructure and less treatment cost. However, the designed system could be upgraded to address the family of SARs viruses, and for experimentation, we have taken COVID-19 as a test case. The proposed system comprises of many modules, such as the user interface, analytics, cloud, etc. The proposed user interface is designed for interactive data collection. At the initial stage, it collects preliminary medical information, such as the pulse oxygen rate and RT-PCR results. With the help of a pulse oximeter, they could get the pulse oxygen level. With the help of swap test kit, they could find COVID-19 positivity. That information is uploaded as preliminary information to the designed proposed system via the designed UI. If the system identifies the COVID positivity, it requests that the person upload X-ray/CT images for ranking the severity of the disease. The system is designed for multi-model data. Hence, it can deal with X-ray, CT images, and textual data (RT-PCR results). Once X-ray/CT images are collected via the designed UI, those images are forwarded to the designed AI module for analytics. The proposed AI system is designed for multi-disease classification. It classifies the patients affected with COVID-19 or pneumonia or any other viral infection. It also measures the intensity level of lung infection for providing suitable treatment to the patients. Numerous deep convolution neural network (DCNN) architectures are available for medical image classification. We used ResNet-50, ResNet-100, ResNet-101, VGG 16, and VGG 19 for better classification. From the experimentation, it observed that ResNet101 and VGG 19 outperform, with an accuracy of 97% for CT images. ResNet101 outperforms with an accuracy of 98% for X-ray images. For obtaining enhanced accuracy, we used a major voting classifier. It combines all the classifiers result and presents the majority voted one. It results in reduced classifier bias. Finally, the proposed system presents an automatic test summary report textually. It can be accessed via user-friendly graphical user interface (GUI). It results in a reduced report generation time and individual bias.

Management Outcome of Patients with Infected Sternotomy Wounds

Objective: to evaluate management outcomes of post-sternotomy wounds. Study Design: Retrospective longitudinal study. Place and Duration of Study: Department of Plastic Surgery, Shifa International Hospital, Islamabad Pakistan, from Jan 2020 to Dec 2021. Methodology: We reviewed 35 patients who had developed sternal wound infections post-cardiothoracic surgery. Outcomes of the study were measured using the SF-36 Quality of Life questionnaire. Results: Our patients presented with either Pairolero Type-II 11(31.4%) or Type-III 19(54.2%) sternal wound infection. Preoperatively patients scored 296.667±69.40 in physical functional, 100.00±30.51 in limitations due to physical health, 16.67±37.90 in role limitation due to emotional problems, energy/fatigue scored 43.53±23.70, emotional well-being 163.33±23.54, social functioning as 11.40±11.66, pain score 31.25±19.90 and general health 131.67±35.31. The improvement in scores was noted in all domains postoperatively. Physical functioning mean scored as 790.00±48.07, role limitations due to physical health scored as310.34±67.32, role limitations due to emotional problems scored as 266.67±47.94, energy/fatigue 284.67±18.71, emotional well being 448.67±18.71, social functioning 185.83±12.60, pain score 164.17±22.01 and general health 316.67±34.95. Thirty-four (97.1%) out of 35 patients recovered well postoperative, with a maximum follow-up of 4 years and a minimum follow-up of 1 year. One patient expired on the sixth day of muscle flap coverage of the wound due to cardiac arrest. Conclusion: A positive prognosis can be obtained by this treatment protocol.

Outcomes of Vaginoplasty Using Pudendal Thigh Flap in a Tertiary Care Hospital

Objective: To evaluate the outcomes following vaginoplasty by pudendal thigh flap. Study Design: Retrospective longitudinal study. Place and Duration of the Study: Plastic surgery Department, Shifa International Hospital, Islamabad Pakistan, from Jan 2010 to Dec 2021. Methodology: Vaginal reconstruction was done using bilateral pudendal thigh flap in 20 patients with vaginal defects during eleven years, 2010-2021. Results: All patients were adults with an age range from 18 to 41 years. Five were married, and 15 were unmarried patients at the time of surgery. Out of the 20 patients, 10(50%) were diagnosed with Mayer Rokitansky Kuster Hauser syndrome, 9(45%) with isolated vaginal atresia and 1(5%) with s/p resection angiosarcoma. The mean vaginal length was 9.0±0.46cm, one year post-operatively. Two patients (10%) developed necrosis of the distal part of the unilateral flap followed by infection, which was managed conservatively, and the other was managed with the McIndoe technique. One patient developed a cutaneous fistula which was excised. All flaps survived completely in the rest of the 19(95%) patients. Conclusion: Vaginoplasty using pudendal thigh flap was a safe and reliable method for vaginal reconstruction and showed adequate functional and aesthetic results.

Job scheduling problem in fog-cloud-based environment using reinforced social spider optimization

Fog computing is an emerging research domain to provide computational services such as data transmission, application processing and storage mechanism. Fog computing consists of a set of fog server machines used to communicate with the mobile user in the edge network. Fog is introduced in cloud computing to meet data and communication needs for Internet of Things (IoT) devices. However, the vital challenges in this system are job scheduling, which is solved by examining the makespan, minimizing energy depletion and proper resource allocation. In this paper, we introduced a reinforced strategy Dynamic Opposition Learning based Social Spider Optimization (DOLSSO) Algorithm to enhance individual superiority and schedule workflow in Fog computing. The extensive experiments were conducted using the FogSim simulator to generate the dataset and an energy-efficient open-source tool utilized to model and simulate resource management in fog computing. The performance of the formulated model is ratified using two test cases. The proposed algorithm attained the optimized schedule with minimized cost function concerning the CPU processing period and assigned memory. Our simulation outcomes show the efficacy of the introduced technique in handling job scheduling issues, and the results are contrasted with five existing metaheuristic techniques. The results show that the proposed method achieves 10% - 15% better CPU utilization and 5%-10% less energy consumption than the other techniques.

Impact of pre-existing vascular disease on clinical outcomes in patients with non-ST-segment myocardial infarction: a nationwide cohort study

Aims

Little is known about the outcomes and processes of care of patients with non ST-segment myocardial infarction (NSTEMI) who present with “polyvascular” disease.

Methods

We analysed 287,279 NSTEMI patients using the Myocardial Infarction National Audit Project (MINAP) registry. Clinical characteristics and outcomes were analysed according to history of affected vascular bed; coronary artery disease (CAD), cerebrovascular disease (CeVD) and peripheral vascular disease (PVD), with comparison to a historically disease-free control group; comprising 167,947 patients (59%). Further analyses compared cumulative number of affected beds with our control.

Results

After adjusting for demographics and management, vascular bed disease was associated with increased likelihood of MACE (CAD OR: 1.06, 95% CI: 1.01–1.12, P=0.02) (CeVD OR: 1.19, 95% CI: 1.12–1.27, P&lt;0.001) (PVD OR: 1.22, 95% CI: 1.13–1.33, P&lt;0.001) and in-hospital mortality (CeVD OR: 1.24, 95% CI: 1.16–1.32, P&lt;0.001) (PVD OR: 1.33, 95% CI: 1.21–1.46, P&lt;0.001). Patients with no vascular disease were less likely to be discharged on statins (PVD 88%, CeVD 86%, CAD 90% and control 78%), and those with moderate (EF 30–49%) or severe left ventricular systolic dysfunction (LVSD) (EF&lt;30%) were less likely to be discharged on ACE inhibitors (CAD 82%, CeVD 77%, PVD 77%, control 74%). Patients with polyvascular disease were less likely to be discharged on DAPT (PVD 78%, CeVD 77%, CAD 80%, control 87%).

Conclusion

Polyvascular disease patients had a higher adjusted incidence of in-hospital mortality and MACE. Patients with no history of vascular disease were less likely to receive statins or ACE inhibitors/ARBs, but more likely to receive DAPT.

Funding Acknowledgement

Type of funding sources: None.

Vascular access in complex high-risk but indicated percutaneous coronary interventions (CHiP) types, trends, and outcomes

Background

Radial access improves the safety of PCI; however, its role in Complex, High-risk but indicated Percutaneous coronary interventions (CHiP) remains poorly studied.

Objectives

To examine CHiP types, clinical and procedural characteristics and clinical outcomes according to vascular access.

Methods

Data was obtained from the British Cardiovascular Intervention Society. We compared the baseline characteristics of 125,662 CHiP procedures performed electively between 2006 and 2017 stratified by access site. Multivariate regression analyses was used to investigate the access site specific odds for in-hospital death, bleeding, and major cardiovascular and cerebral events (MACCE).

Results

Overall, 61,825 CHiP procedures (49.2%) were performed via transradial access (TRA) and 63,837 (50.8%) via trans-femoral access (TFA). TRA use increased over time (14.6% in 2006 to 78.4% in 2017). The patients who had PCI through TRA were older (Median age: TRA, 71.2 vs TFA, 70.2 years). Cardiovascular risks were more prevalent in the TRA than TFA (stroke: 5.3 vs 4.3%; hypertension: 67.4 vs 64.3%; peripheral vascular disease: 7.2 vs 6.7%; smoking: 9.6 vs 8.9% respectively; p&lt;0.001 for all). TRA patients had higher rates of multi-vessel PCI than TFA (two or more vessel PCI: 27.2 vs 24.2% respectively; p&lt;0.001) and longer lesions (median stent length: 24mm vs 23mm). TFA group had higher rates of diabetes (26.6 vs 25.8%), previous myocardial infarction (44.2 vs 40.2%), previous PCI (38.7 vs 37.1%), heart failure (10.3 vs 9.3%), respectively (p&lt;0.001 for all) suggesting operators' tendency to choose TFA in patients with greater cardiometabolic burden. TRA adoption was more prevalent in most CHiP types (elderly (54%), chronic renal failure (55.7%), poor LV function (51.4%), left main PCI (51.2%), treatment for severe vascular calcifications (53.1%)). Following adjustment for differences in clinical and procedural characteristics, TFA was independently associated with increased odds for mortality (aOR: 1.4 (1.1–1.8), p=0.004), bleeding (aOR: 2.9 (2.4–3.5), p&lt;0.001), and MACCE (aOR: 1.2 (1.1–1.3), p&lt;0.001).

Conclusion

Over the 12 years, TRA has become the predominant access site used in CHiP PCI and is associated with significantly lower mortality, major bleeding and MACCE odds than TFA. Addressing the cardiometabolic burden-treatment paradox by preferentially selecting TRA as the baseline cardiovascular burden increases may potentially improve CHiP clinical outcomes.

Funding Acknowledgement

Type of funding sources: Private company. Main funding source(s): An unrestricted educational grant from Abbott supports Warkaa Shamkhani's salary. However, the company had no role in the study design, manuscript preparation, or access to the manuscript's contents before submission. The authors are solely responsible for this study design and conduct and all analysis, drafting, and editing of the manuscript and its final content.

Chest X ray and cough sample based deep learning framework for accurate diagnosis of COVID-19

All witnessed the terrible effects of the COVID-19 pandemic on the health and work lives of the population across the world. It is hard to diagnose all infected people in real time since the conventional medical diagnosis of COVID-19 patients takes a couple of days for accurate diagnosis results. In this paper, a novel learning framework is proposed for the early diagnosis of COVID-19 patients using hybrid deep fusion learning models. The proposed framework performs early classification of patients based on collected samples of chest X-ray images and Coswara cough (sound) samples of possibly infected people. The captured cough samples are pre-processed using speech signal processing techniques and Mel frequency cepstral coefficient features are extracted using deep convolutional neural networks. Finally, the proposed system fuses extracted features to provide 98.70% and 82.7% based on Chest-X ray images and cough (audio) samples for early diagnosis using the weighted sum-rule fusion method.

A review of deep learning applications in human genomics using next-generation sequencing data

Genomics is advancing towards data-driven science. Through the advent of high-throughput data generating technologies in human genomics, we are overwhelmed with the heap of genomic data. To extract knowledge and pattern out of this genomic data, artificial intelligence especially deep learning methods has been instrumental. In the current review, we address development and application of deep learning methods/models in different subarea of human genomics. We assessed over- and under-charted area of genomics by deep learning techniques. Deep learning algorithms underlying the genomic tools have been discussed briefly in later part of this review. Finally, we discussed briefly about the late application of deep learning tools in genomic. Conclusively, this review is timely for biotechnology or genomic scientists in order to guide them why, when and how to use deep learning methods to analyse human genomic data.

Fungal conversion of chicken-feather waste into biofortified compost

Poultry industry is amongst highly developed industries of Pakistan, fulfilling the protein demand of rapidly increasing population. On the other hand, the untreated poultry waste is causing several health and environmental problems. The current study was designed to check the potential of keratinolytic fungal species for the conversion of chicken-feather waste into biofortified compost. For the purpose, three fungal species were isolated from soil samples. These strains were pure cultured and then characterized phenotypically and genotypically. BLAST searches of 18S rDNA nucleotide sequence of the fungal isolates revealed that the two fungal isolates belonged to genus Aspergillus and one belonged to genus Chrysosporium. Optimum temperature for Aspergillus flavus, Aspergillus niger and Chrysosporium queenslandicum was 29, 26 and 25 oC, respectively. A. flavus showed maximum (53%) feather degradation, A. niger degraded feather waste up to 37%, while C. queenslandicum showed 21% keratinolytic activity on chicken feathers at their respective temperature optima. The degradation potential of these fungal species showed their ability to form compost that has agro-industrial importance.

Distance Based Pattern Driven Mining for Outlier Detection in High Dimensional Big Dataset

Detection of outliers or anomalies is one of the vital issues in pattern-driven data mining. Outlier detection detects the inconsistent behavior of individual objects. It is an important sector in the data mining field with several different applications such as detecting credit card fraud, hacking discovery and discovering criminal activities. It is necessary to develop tools used to uncover the critical information established in the extensive data. This paper investigated a novel method for detecting cluster outliers in a multidimensional dataset, capable of identifying the clusters and outliers for datasets containing noise. The proposed method can detect the groups and outliers left by the clustering process, like instant irregular sets of clusters (C) and outliers (O), to boost the results. The results obtained after applying the algorithm to the dataset improved in terms of several parameters. For the comparative analysis, the accurate average value and the recall value parameters are computed. The accurate average value is 74.05% of the existing COID algorithm, and our proposed algorithm has 77.21%. The average recall value is 81.19% and 89.51% of the existing and proposed algorithm, which shows that the proposed work efficiency is better than the existing COID algorithm.

Evaluation of Speech Intelligibility And Factors Influencing Its Outcome in Patients with Tongue Reconstruction Using Radial Forearm Free Flap

Objective: To study the speech outcomes in patients undergoing tongue reconstruction after tumour resection in terms of intelligibility and to examine the factors influencing the outcome. Study Design: Prospective observational study. Place and Duration of Study: Department of Plastic Surgery, Shifa International Hospital, Islamabad, Jan 2015 to Jan 2020. Methodology: A total of 109 patients diagnosed with tongue cancer meeting the inclusion criteria were included in the study. All the participants underwent tumor resection followed by adjuvant radiotherapy (unless refused by the patients). Patients were followed for six months and then underwent speech evaluation via the Functional Intra-oral Glasgow Scale score and Likert scale. Results: Thirty (27.5%) patients could be clearly understood at all the times, while 27 (24.8%) and 42 (38.5%) required some and frequent repetition, respectively. Nine (8.3%) patients could only be understood by close relations and one patient was completely unintelligible. Advancing age (p=0.01), male gender (p=0.01), tumour stage (p=0.004), presence of comorbidities (p=0.004) and degree of resection (p=0.004) had a significant statistical relationship with speech outcome. Addiction (p=0.32), adjuvant radiotherapy (p=0.97) and the development of complications (p=0.59) had no effect on speech. Conclusion: The provision of a mobile reconstructed tongue gives speech intelligibility in a majority of the patients however, the degree of speech recovery is directly dependent on advanced age, disease stage, the presence of comorbidities and degree of resection.

AI-enabled radiologist in the loop: novel AI-based framework to augment radiologist performance for COVID-19 chest CT medical image annotation and classification from pneumonia

A SARS-CoV-2 virus-specific reverse transcriptase-polymerase chain reaction (RT-PCR) test is usually used to diagnose COVID-19. However, this test requires up to 2 days for completion. Moreover, to avoid false-negative outcomes, serial testing may be essential. The availability of RT-PCR test kits is currently limited, highlighting the need for alternative approaches for the precise and rapid diagnosis of COVID-19. Patients suspected to be infected with SARS-CoV-2 can be assessed using chest CT scan images. However, CT images alone cannot be used for ruling out SARS-CoV-2 infection because individual patients may exhibit normal radiological results in the primary phases of the disease. A machine learning (ML)-based recognition and segmentation system was developed to spontaneously discover and compute infection areas in CT scans of COVID-19 patients. The computable assessment exhibited suitable performance for automatic infection region allocation. The ML models developed were suitable for the direct detection of COVID-19 (+). ML was confirmed to be a complementary diagnostic technique for diagnosing COVID-19(+) by forefront medical specialists. The complete manual delineation of COVID-19 often requires up to 225.5 min; however, the proposed RILML method decreases the delineation time to 7 min after four iterations of model updating.

Prevalence of intestinal nematodes infection in school children of urban areas of district Lower Dir, Pakistan

Abstract Intestinal parasitism is the main cause of disease all over the world and described as a significant community health problem. The current study intended to find out the occurrence and identification of hazard factors linked with IPIs among 4-12 years aged shool-age children residing in Lower Dir district, Pakistan during 2019 - 2020. A cross-sectional school-based study was conducted using a pre-arranged pre-tested survey. Anthropometric data and stool collection were done to obtain the findings. The direct wet mount preparation in saline/iodine/methods was used for stool examination. Data were investigated using the GraphPad Prism 5. A total of 400 children studied (mean age of 8.6±3.6 years) the total incidence rate for the intestinal parasitic disease was established to be 71.75%. Of the 400 children studied, the overall prevalence rate for intestinal parasitic infections was found to 71.75% Ascaris lumbricoides (33.1%), Trichuris trichiura (1.04%), E. vermicularis (1.39%), Hookworm (19.86%) were identified in children living in the study area. We concluded that there is a mass scale campaigns were required to generate alertness about health and sanitation in children and the need for the development of effective poverty control programs because deworming (killing of worm with drugs) alone is not adequate to control parasitic infections.

Chemical stability of naloxone products beyond their labeled expiration dates

OBJECTIVE

The purpose of this study was to evaluate the chemical stability of previously dispensed, expired naloxone products.

SETTING

When properly stored, certain products maintain stable, defined as within compendia acceptability, beyond their manufacturer's expiration date. Stockpiling life-saving medications such as the opioid overdose reversing agent naloxone nasal spray (NNS) or injection (NIJ) is of utmost importance to ensure public health emergency preparedness and response. Design/interventions/methods: After each naloxone product was stored at room temperature for several months (6-19) past their labeled expiration date, the level of active therapeutic content and the presence of degradation impurity, 2,29'-bisnaloxone, were evaluated via chromatographic separation with waters higher performance liquid chromatography integrated using the Waters X-Select CSHC-18. The effluent was detected at 229 nm.

MAIN OUTCOME MEASURE

Active naloxone presence and the presence of degradation impurity, 2,29'-bisnaloxone, were evaluated.

RESULTS

The mean potency of naloxone in both NNS and NIJ, up to 10 and 19 months post-expiration, respectively, is within the 90-110 percent United States Pharmacopeia acceptance limit (NNS: 102.8 ± 2.6 percent and NIJ: 106.0 ± 1.3 percent). No impurity was detected in any chromatogram of the expired products.

CONCLUSION

In summary, since both NNS and NIJ were found to be chemically stable beyond 10 months of the expiration date, shelf-life extension of climate controlled, commercially available naloxone products should be further investigated as a potential cost savings measure for national strategic stockpiles, emergency medical services, hospitals, and public responders.

Genetic variations and phylogenetic relationship of genus Uromastyx from Punjab Pakistan

During the present study, specimens were collected from selected sites of Cholistan desert and Kalabagh Game Reserve, Punjab province, Pakistan. Each captured specimen was tagged with voucher number and morphometric measurements were taken. The average snout to vent length was 172.559±1.40 mm and average weight was 92.1±1.30 g. The DNA of Uromastyx hardwickii was amplified and sequenced using 16S rRNA primer set. The obtained DNA sequence has shown reliable and clear species identification. After trimming ambiguous bases, the obtained 16S rRNA fragment was 520 bp while 16S rRNA fragments aligned with closely matched sequence from NCBI comprised of 510 bp. Closely matched sequences of genus Uromastyx were retrieved from NCBI in blast searches. Neighbour-joining tree of genus Uromastyx was constructed based on p-distance using MEGA X. The mean intraspecific variation was 0.095±0.01 while intraspecific variation was ranging from 0-1%. Similarly, interspecific variation of Uromastyx hardwikii with Saara asmussi, Uromastyx alfredschmidti, Uromastyx geyri, Uromastyx thomasi, Uromastyx alfredschmidti was 0-12%, 0-19%, 0-19%, 0-20%, 12-19% respectively. The newly produced DNA was submitted to NCBI and accession number was obtained (MW052563.1). Results of current study provided information about the molecular and morphological identification of Genus Uromastyx. In our recommendation, comprehensive molecular based identification of Pakistan's reptiles is required to report any new or subspecies from country.

Discovery of a novel potentially transforming somatic mutation in CSF2RB gene in breast cancer

The colony stimulating factor 2 receptor subunit beta (CSF2RB) is the common signaling subunit of the cytokine receptors for IL-3, IL-5, and GM-CSF. Several studies have shown that spontaneous and random mutants of CSF2RB can lead to ligand independence in vitro. To date, no report(s) have been shown for the presence of potentially transforming and oncogenic CSF2RB mutation(s) clinically in cancer patients until the first reported case of a leukemia patient in 2016 harboring a germline-activating mutation (R461C). We combined exome sequencing, pathway analyses, and functional assays to identify novel somatic mutations in KAIMRC1 cells and breast tumor specimen. The patient's peripheral blood mononuclear cell (PBMC) exome served as a germline control in the identification of somatic mutations. Here, we report the discovery of a novel potentially transforming and oncogenic somatic mutation (S230I) in the CSF2RB gene of a breast cancer patient and the cell line, KAIMRC1 established from her breast tumor tissue. KAIMRC1 cells are immortalized and shown to survive and proliferate in ligand starvation condition. Immunoblot analysis showed that mutant CSF2RB signals through JAK2/STAT and PI3K/mTOR pathways in ligand starvation conditions. Screening a small molecule kinase inhibitor library revealed potent JAK2 inhibitors against KAIMRC1 cells. We, for the first time, identified a somatic, potentially transforming, and oncogenic CSF2RB mutation (S230I) in breast cancer patients that seem to be an actionable mutation leading to the development of new therapeutics for breast cancer.

SP5.1.7 What did we miss? A 5 - year retrospective cohort study calculating the endoscopy miss rate for UGI cancers in a Scottish district general hospital

Aims

Despite the widespread use of endoscopy, upper gastrointestinal (UGI) cancers still present at an advanced stage. As survival is closely linked to stage and time of diagnosis, failure to detect subtle precancerous changes at endoscopy may compound poor prognoses. This study calculates the miss rate of UGI cancer over a 5-year period at a district general hospital.

Methods

All patients diagnosed with UGI cancer between January 2015 - December 2019 were identified from a prospectively collected cancer registry. Electronic health records and Unisoft GI reporting tool were used to identify patient demographics and previous UGI endoscopies. ‘Missed cancers’ were defined as patients who had a normal endoscopy within 3 years of their cancer diagnosis.

Results

The median age at diagnosis was 72.2 years (age range 24 - 98, n = 408) with a male predominance of 2:1 (66.6% male vs 33.4% female) in keeping with UK statistics.

Within this 5 year study period, there were 22 missed cancers (5.4%, n = 408).

A year by year break down shows miss rate in 2015 of 3% ( 3,n=100), 2016 of 4.2% (5,n=120), 2017 5.5% (5,n=91), 2018 6.4% (6,n=94) and most recently in 2019 3.2% (3,n=94).

Conclusions

In 2014, a meta-analysis by S.Menon et al recorded a miss rate of 11.3%. More recently published UK studies report miss rates between 6% - 7.3%, more in keeping with our local rate of 5.4%. Further assessment is required to assess whether the 2017 BSG and AUGIS UGI endoscopy quality standard statement will improve this rate.

Association of quality indicators for acute myocardial infarction and mortality: feasibility and validation study using linked nationwide registry data

Background

Quality indicators (QIs) have been increasingly used as tools to assess and improve the quality of care for acute myocardial infarction (AMI). However, it is not known if it is feasible to use the 2020 iteration of international AMI QIs using routinely collected data and, if so, whether higher performance is associated with improved outcomes.

Objective

To investigate if routine data are available to measure care quality against the 2020 European Society of Cardiology (ESC) Association for Acute Cardiovascular Care (ACVC) QIs for AMI, investigate whether higher performance is associated with reduced mortality, and to report quality of care during the COVID-19 pandemic.

Methods

Cohort study of linked data from the AMI and percutaneous coronary intervention (PCI) registries in England and Wales with outcome data from the Civil Registration of Deaths Register between 2017 and 2020 (representing 236 743 patients from 186 hospitals). Baseline ischaemic risk was estimated using the Global Registry of Acute Coronary Events (GRACE) risk score. The likelihood of attainment for each QI based on GRACE risk was quantified using logistic regression and the association with mortality at 30 days, 6 months, 1 year and long-term (maximum 1243 days) was obtained from Cox proportional hazard models.

Results

Of 26 QIs, 17 (65.3%) could be directly measured using nationwide registry data and were each inversely associated with risk-adjusted 1-year and long-term mortality. At 30 days, the measured QIs with exception of early invasive coronary angiography for non-ST elevation myocardial infarction, were associated with improved survival, and the QIs that had the greatest magnitude for a reduction in mortality were the prescription of secondary prevention medications at discharge; hazard ratio 0.13 (95% CI 0.12–0.14) for statins, 0.16 (95% CI 0.15–0.18) for adequate P2Y12 inhibition, and 0.18 (95% CI 0.17–0.20) for dual antiplatelet therapy (Figure 1). The magnitude of association between the composite QI (CQI) and survival attenuated over time, with greater long-term survival gains observed for the high GRACE risk compared with low- and intermediate-risk (Figure 2). During the first UK lockdown there was an improvement in the attainment for 62.5% of the measured QIs compared with before the COVID-19 pandemic, with a higher attainment for the CQI (43.8% to 45.2%, odds ratio 1.06, 95% CI 1.02–1.10).

Conclusion

Care quality for AMI may be evaluated using routinely collected clinical data from the national registries, whereby higher performance is associated with reduced mortality. Such QIs will have a role in monitoring hospital care as demonstrated for COVID-19.

Funding Acknowledgement

Type of funding sources: None.

1016 The Impact Of COVID-19 On Prostate Cancer: Is This the Calm Before the Storm?

Aim

Cancer treatment targets were halted in the COVID-era due to a major re-organisation of services and coincided with a drop in prostate cancer (PCa) referrals, investigations, and diagnoses. This study measures the impact of the pandemic on a PCa diagnostic pathway in a major cancer centre.

Method

Data was collected during the onset of COVID-19 (March to June 2020) and the same months in 2019 for urgent suspected prostate cancer (USPC) referrals. All referrals, PSA tests, multiparametric MRI's of prostate (mpMRI-P), and TRUS-guided biopsy of the prostate (TBP) were recorded.

Results

USPC referrals reduced by 65% from a mean 315 referrals per month to 110 during the pandemic. During March-June 2019 a total of 10,404 PSA tests were conducted in the healthcare trust, which reduced by 39% during COVID-19. Multiparametric MRI of prostate was reduced by 45%. TRUS biopsies were down by 65%, from a mean of 31 to 11 biopsies per month, with only 3 biopsies being conducted in April 2020.

Conclusions

The reduction in PCa referrals and workload in our centre in the COVID-era has been significant. The uncertainty associated with such a drop in demand poses concerns for meeting future cancer targets when prostate cancer referrals return to baseline.

HDL associates with insulin resistance and beta-cell dysfunction in South Asian families at risk of type 2 diabetes

OBJECTIVE

Dyslipidemia precedes type 2 diabetes (T2D) and worsens with increasing glucose intolerance. First degree relatives of T2D patients have an increased risk to develop dyslipidemia and glucose intolerance. The aim of the present study was to assess the relation between the development of dyslipidemia and glucose intolerance in first-degree relatives of T2D patients.

RESEARCH DESIGN AND METHODS

Fasting lipoprotein profiles were determined by density gradient ultracentrifugation in T2D patients and their first-degree relatives (42 Caucasians and 33 South Asians), and in 29 normoglycemic controls from non-T2D families. Glucose tolerance, insulin sensitivity index (ISI) and insulin disposition index (DI) were assessed by an extended, frequently sampled oral glucose tolerance test (OGTT), and fractional insulin synthesis rate (FSR) was measured by ¹³C-leucine enrichment in urinary C-peptide during the OGTT.

RESULTS

Of the first-degree relatives, 40, 16 and 19 had NGT, prediabetes and T2D, respectively. NGT family members had lower plasma HDL-cholesterol (HDLC) (1.34 ± 0.07 vs 1.58 ± 0.06 mmol/L; p = 0.015), HDL₂-C (0.41 ± 0.05 vs 0.57 ± 0.05 mmol/L; p = 0.021) and HDL₃-C (0.62 ± 0.03 vs 0.72 ± 0.02 mmol/L; p = 0.043) than controls. HDL₂-C levels tended to decrease with increasing glucose intolerance state. In South Asians, buoyant LDL-C levels decreased with increasing glucose intolerance state (p = 0.006). In South Asian families, HDL-C correlated with both ISI and DI (β 0.42; p = 0.04 and β 0.53; p = 0.01, respectively), whereas HDL₂-C and HDL₃-C levels correlated with DI (β 0.64; p = 0.002 and β 0.57; p = 0.005, respectively). HDL₂-C and plasma triglyceride correlated with FSR (β 0.48; p = 0.033 and β -0.50; p = 0.029, respectively).

CONCLUSIONS

Low HDL₂-C and HDL₃-C levels are present in NGT first-degree relatives of T2D patients, and HDL₂-C tend to decrease further with increasing glucose intolerance. In South Asian families HDL₂-C and HDL₃-C levels linked predominantly to deteriorating beta cell function.

Identification of CSF3R Mutations in B-Lineage Acute Lymphoblastic Leukemia Using Comprehensive Cancer Panel and Next-Generation Sequencing

B-lineage acute lymphocytic leukemia (B-ALL) is characterized by different genetic aberrations at a chromosomal and gene level which are very crucial for diagnosis, prognosis and risk assessment of the disease. However, there is still controversial arguments in regard to disease outcomes in specific genetic abnormalities, e.g., 9p-deletion. Moreover, in absence of cytogenetic abnormalities it is difficult to predict B-ALL progression. Here, we use the advantage of Next-generation sequencing (NGS) technology to study the mutation landscape of 12 patients with B-ALL using Comprehensive Cancer Panel (CCP) which covers the most common mutated cancer genes. Our results describe new mutations in CSF3R gene including S661N, S557G, and Q170X which might be associated with disease progression.

"Osteomyelitis of mandible"-a rare presentation of osteopetrosis

Osteopetrosis is a rare metabolic disease. Dental abnormalities may be attributed to the pathological changes in osteopetrosis. Patients with disease seem to be especially susceptible to osteomyelitis of mandible. A 9 yrs old girl presented with complaints of jaw swelling on left side with multiple discharging sinuses since last seven months. The radiograph of left mandible (oblique lateral view) showed periodontal involvement of associated molars with loss of lamina dura with small sequestrum with irregularity and erosions of the mandibular cortical margins. The patient was diagnosed as a case of osteopetrosis with superadded mandibular osteomyelitis.

Early Prediction of COVID-19 Ventilation Requirement and Mortality from Routinely Collected Baseline Chest Radiographs, Laboratory, and Clinical Data with Machine Learning

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China, in late 2019 and created a global pandemic that overwhelmed healthcare systems. COVID-19, as of July 3, 2021, yielded 182 million confirmed cases and 3.9 million deaths globally according to the World Health Organization. Several patients who were initially diagnosed with mild or moderate COVID-19 later deteriorated and were reclassified to severe disease type.

OBJECTIVE

The aim is to create a predictive model for COVID-19 ventilatory support and mortality early on from baseline (at the time of diagnosis) and routinely collected data of each patient (CXR, CBC, demographics, and patient history).

METHODS

Four common machine learning algorithms, three data balancing techniques, and feature selection are used to build and validate predictive models for COVID-19 mechanical requirement and mortality. Baseline CXR, CBC, demographic, and clinical data were retrospectively collected from April 2, 2020, till June 18, 2020, for 5739 patients with confirmed PCR COVID-19 at King Abdulaziz Medical City in Riyadh. However, of those patients, only 1508 and 1513 have met the inclusion criteria for ventilatory support and mortalilty endpoints, respectively.

RESULTS

In an independent test set, ventilation requirement predictive model with top 20 features selected with reliefF algorithm from baseline radiological, laboratory, and clinical data using support vector machines and random undersampling technique attained an AUC of 0.87 and a balanced accuracy of 0.81. For mortality endpoint, the top model yielded an AUC of 0.83 and a balanced accuracy of 0.80 using all features with balanced random forest. This indicates that with only routinely collected data our models can predict the outcome with good performance. The predictive ability of combined data consistently outperformed each data set individually for intubation and mortality. For the ventilator support, chest X-ray severity annotations alone performed better than comorbidity, complete blood count, age, or gender with an AUC of 0.85 and balanced accuracy of 0.79. For mortality, comorbidity alone achieved an AUC of 0.80 and a balanced accuracy of 0.72, which is higher than models that use either chest radiograph, laboratory, or demographic features only.

CONCLUSION

The experimental results demonstrate the practicality of the proposed COVID-19 predictive tool for hospital resource planning and patients' prioritization in the current COVID-19 pandemic crisis.

CP-BDHCA: Blockchain-based Confidentiality-Privacy preserving Big Data scheme for healthcare clouds and applications

Healthcare big data (HBD) allows medical stakeholders to analyze, access, retrieve personal and electronic health records (EHR) of patients. Mostly, the records are stored on healthcare cloud and application (HCA) servers, and thus, are subjected to end-user latency, extensive computations, single point failures, and security and privacy risks. A joint solution is required to address the issues of responsive analytics, coupled with high data ingestion in HBD and secure EHR access. Motivated from the research gaps, the paper proposes a scheme, that integrates blockchain (BC)-based confidentiality-privacy (CP) preserving scheme, CP-BDHCA, that operates in two phases. In the first phase, elliptic curve cryptographic (ECC)-based digital signature framework, HCA-ECC is proposed to establish a session key for secure communication among different healthcare entities. Then, in the second phase, a two-step authentication framework is proposed that integrates RivestShamirAdleman (RSA) and advanced encryption standard (AES), named as HCARSAE is proposed that safeguards the ecosystem against possible denial-of-service (DoS) and distributed DoS (DDoS) based attack vectors. CP-BDAHCA is compared against existing HCA cloud applications in terms of parameters like response time, average delay, transaction and signing costs, signing and verifying of mined blocks, and resistance to DoS and DDoS attacks. We consider 10 BC nodes and create a real-world customized dataset to be used with SEER dataset. The dataset has 30; 000 patient profiles, with 1000 clinical accounts. Based on the combined dataset the proposed scheme outperforms traditional schemes like AI4SAFE, TEE, Secret, and IIoTEED, with a lower response time. For example, the scheme has a very less response time of 300 ms in DDoS. The average signing cost of mined BC transactions is 3; 34 seconds, and for 205 transactions, has a signing delay of 1405 ms, with improved accuracy of 12% than conventional state-of-the-art approaches.

Interferon-induced transmembrane protein-3 genetic variant rs12252 is associated with COVID-19 mortality

Interferon-induced membrane proteins (IFITM) 3 gene variants are known risk factor for severe viral diseases. We examined whether IFITM3 variant may underlie the heterogeneous clinical outcomes of SARS-CoV-2 infection-induced COVID-19 in large Arab population. We genotyped 880 Saudi patients; 93.8% were PCR-confirmed SARS-CoV-2 infection, encompassing most COVID-19 phenotypes. Mortality at 90 days was 9.1%. IFITM3-SNP, rs12252-G allele was associated with hospital admission (OR = 1.65 [95% CI; 1.01-2.70], P = 0.04]) and mortality (OR = 2.2 [95% CI; 1.16-4.20], P = 0.01). Patients less than 60 years old had a lower survival probability if they harbor this allele (log-rank test P = 0.002). Plasma levels of IFNγ were significantly lower in a subset of patients with AG/GG genotypes than patients with AA genotype (P = 0.00016). Early identification of these individuals at higher risk of death may inform precision public health response.

Interspecific variations in external and internal egg quality among various captive avian species from Punjab, Pakistan

Present study was planned to determine variations in external and internal quality egg parameters of different avian species including ostrich Struthio camelus, ducks Anas platyrhynchos, chicken Gallus gallus, turkeys Meleagris gallopavo and grey francolin Francolinus pondicerinus. All the birds were kept under similar rearing conditions. A total of 150 eggs were collected for each species to record external features of these eggs. Statistically significant (p<0.05) variations were recorded in egg weight, egg length and egg width between ostrich, ducks, chicken, turkey and quail eggs. Significantly (p<0.05) higher egg weight, egg length and egg width was observed for ostrich eggs while the same was lowest for grey francolin eggs. Similarly, significantly (p<0.05) greater shape index and egg volume values were observed for ostrich eggs while lowest shape index values were recorded for turkey eggs and egg volume was lowest for grey francolin. Significantly, higher (p<0.05) values of egg density were noted for eggs of the quail and the same were lowest for ostrich eggs. Non-significant variations in egg density values were observed between eggs of the ducks, chicken, turkey and grey francolin. It has been concluded that the positive correlations between the internal and external egg quality traits indicated that the traits can be improved through selection.

487 Reducing Intraoperative Fluoroscopic Radiation Exposure in Orthopaedic Theatres at A Trauma Centre

Introduction

Intraoperative fluoroscopic imaging in orthopaedic trauma surgery subject’s theatre staff and patients to increasing radiation exposure and its detrimental health effects. This audit cycle uses a target maximum for total number of intraoperative fluoroscopic images taken, as defined by recently published reference values, to reduce intraoperative radiation exposure.

Method

This is a two-phase audit cycle retrospectively reviewing all trauma operations over a 12-month period (456 cases) and a 10-month period (256 cases) after disseminating the target standards through posters and focused training. Audit standards describe target maximum total intraoperative images taken for 5 commonly performed procedures, applicable to 33% of total cases. Operative notes, total intraoperative image count and radiation dose report were reviewed through ORMIS and PACS.

Results

Audit standard compliance improved/remained at 100% in 4/5 of the investigated ‘common procedures’: from 2/5 procedures &lt;80% compliance and 1/5 procedures =100% compliance initially, to 0/5 procedures &lt;80% compliance and 2/5 procedures =100% compliance target upon re-audit. This translated to an improvement in mean radiation risk (DAP Gy.cm^2) in 3/4 common procedures (one exclusion due to dissimilar cohort characteristics).

Conclusions

This study demonstrates employing a target maximum total image count limit reduced radiation exposure in trauma theatres.

A Simplified Method for Compounding Lidocaine Topical Gel: A Demonstration of Quality Assurance to Prevent Errors in 503A Pharmacies

Quality assurance is a key element in the process of creating safe and effective preparations. Furthermore, the implementation of quality-assurance measures allows 503A pharmacies to ensure accurate, well-made preparations to their customers. When corrective and preventive measures are not implemented, the risk of errors is increased, like subtherapeutic or supratherapeutic compounded medications. The objective of this article was to demonstrate the importance of quality assurance through the development and validation of the compounding method, preparation characterization, training, implementation of a master formulation record, compounding protocol, and verification to prevent compounding errors. Two groups, comprising of 10 students, compounded lidocaine gel following the quality-assurance guidelines in accordance with United States Pharmacopeia Chapter <1163>. Following the trial, the preparations from both groups were tested to evaluate the content of lidocaine using high-performance liquid chromatography and an ultra-viscosity detector. The study results indicated that the newly developed, validated procedure produced a stable, uniform, highly reproducible (%Assay ± SD; 101.65% ± 1.04), and elegant (clear hydro-alcoholic gel) preparation with a high yield (~98.5%). There was no significant difference observed in the %Assay results obtained from the two groups (%Assay ±SD; P1: 98.76% ±1.01, and P2: 99.02% ±1.39, %Difference: 0.3). Overall, our findings suggest that the implementation of quality assurance could significantly reduce compounding errors and improve both preparation quality and patient safety.

Performance Analysis of IoT and Long-Range Radio-Based Sensor Node and Gateway Architecture for Solid Waste Management

Long-range radio (LoRa) communication is a widespread communication protocol that offers long range transmission and low data rates with minimum power consumption. In the context of solid waste management, only a low amount of data needs to be sent to the remote server. With this advantage, we proposed architecture for designing and developing a customized sensor node and gateway based on LoRa technology for realizing the filling level of the bins with minimal energy consumption. We evaluated the energy consumption of the proposed architecture by simulating it on the Framework for LoRa (FLoRa) simulation by varying distinct fundamental parameters of LoRa communication. This paper also provides the distinct evaluation metrics of the the long-range data rate, time on-air (ToA), LoRa sensitivity, link budget, and battery life of sensor node. Finally, the paper concludes with a real-time experimental setup, where we can receive the sensor data on the cloud server with a customized sensor node and gateway.

Taking a step down on the reconstruction ladder for head and neck reconstruction during the COVID-19 pandemic

Background

Most of the head and neck cancers are time-critical and need urgent surgical treatment. Our unit is one of the departments in the region, at the forefront in treating head and neck cancers in Pakistan. We have continued treating these patients in the COVID-19 pandemic with certain modified protocols. The objective of this study is to share our experience and approach towards head and neck reconstruction during the COVID-19 pandemic.

Results

There were a total of 31 patients, 20 (64.5%) were males and 11 (35.4%) patients were females. The mean age of patients was 52 years. Patients presented with different pathologies, i.e. Squamous cell carcinoma n = 26 (83.8%), mucoepidermoid carcinoma n = 2 (6.4%), adenoid cystic carcinoma n = 2 (6.4%) and mucormycosis n = 1 (3%). The reconstruction was done with loco-regional flaps like temporalis muscle flap n = 12 (38.7%), Pectoralis major myocutaneous flap n = 8 (25.8%), supraclavicular artery flap n = 10 (32.2%) and combination of fore-head, temporalis major and cheek rotation flaps n = 1 (3%). Defects involved different regions like maxilla n = 11 (35.4%), buccal mucosa n = 6 (19.3%), tongue with floor of mouth n = 6 (19.3%), mandible n = 4 (12.9%), parotid gland, mastoid n = 3 (9.6%) and combination of defects n = 1 (3%). Metal reconstruction plate was used in 3 (9.6%) patients with mandibular defects. All flaps survived, with the maximum follow-up of 8 months and minimum follow-up of 6 months.

Conclusion

Pedicled flaps are proving as the workhorse for head and neck reconstruction in unique global health crisis. Vigilant use of proper PPE and adherence to the ethical principles proves to be the only shield that will benefit patients, HCW and health system.

Particulate Emission Characteristics from Palm Fibre and Shell Combustion with Alumino-Silicate Based Additives

Malaysia is one of the largest palm oil producers in the world with a continuous increment in worldwide demand. The palm oil extraction process leaves palm fibre and shell (F&S) as waste. The palm F&S are biomass fuels that have been utilized in many palm oil mills to generate energy through the combustion process. The release of harmful particulates from the combustion process is the main concern in this research. A few studies had shown that the PM2.5 particulate matters cannot be filtered by the Air Pollution Control System (APCS); thus, it can pollute the environment. In this research, the utilization of additives inside biomass fuels is studied. The effect of additives towards the particulate size of the ashes and determination of the best additive are the two main objectives of this research. The proximate and ultimate analysis was done the determine the combustion profile of the samples. The Scanning Electron Microscopy (SEM) analysis was done to determine the size of particulates inside the ashes.

Verification and Validation of Digital Pathology (Whole Slide Imaging) for Primary Histopathological Diagnosis: All Wales Experience

Aims:

The study is aimed to verify Aperio AT2 scanner for reporting on the digital pathology platform (DP) and to validate the cohort of pathologists in the interpretation of DP for routine diagnostic histopathological services in Wales, United Kingdom.

Materials, Methods and Results:

This was a large multicenter study involving seven hospitals across Wales and unique with 22 (largest number) pathologists participating. 7491 slides from 3001 cases were scanned on Leica Aperio AT2 scanner and reported on digital workstations with Leica software of e-slide manager. A senior pathology fellow compared DP reports with authorized reports on glass slide (GS). A panel of expert pathologists reviewed the discrepant cases under multiheader microscope to establish ground truth. 2745 out of 3001 (91%) cases showed complete concordance between DP and GS reports. Two hundred and fifty-six cases showed discrepancies in diagnosis, of which 170 (5.6%) were deemed of no clinical significance by the review panel. There were 86 (2.9%) clinically significant discrepancies in the diagnosis between DP and GS. The concordance was raised to 97.1% after discounting clinically insignificant discrepancies. Ground truth lay with DP in 28 out of 86 clinically significant discrepancies and with GS in 58 cases. Sensitivity of DP was 98.07% (confidence interval [CI] 97.57–98.56%); for GS was 99.07% (CI 98.72–99.41%).

Conclusions:

We concluded that Leica Aperio AT2 scanner produces adequate quality of images for routine histopathologic diagnosis. Pathologists were able to diagnose in DP with good concordance as with GS.

Strengths and Limitations of this Study:

Strengths of this study – This was a prospective blind study. Different pathologists reported digital and glass arms at different times giving an ambience of real-time reporting. There was standardized use of software and hardware across Wales. A strong managerial support from efficiency through the technology group was a key factor for the implementation of the study.

Limitations:

This study did not include Cytopathology and in situ hybridization slides. Difficulty in achieving surgical pathology practise standardization across the whole country contributed to intra-observer variations.