Factors impacting the adoption of big data in healthcare: A systematic literature review

BACKGROUND

The term "big data" refers to the vast volume, variety, and velocity of data generated from various sources-e.g., sensors, social media, and online platforms. Big data adoption within healthcare poses an intriguing possibility for improving patients' health, increasing operational efficiency, and enabling data-driven decision-making. Despite considerable interest in the adoption of big data in healthcare, empirical research assessing the factors impacting the adoption process is lacking. Therefore, this review aimed to investigate the literature using a systematic approach to explore the factors that affect big data adoption in healthcare.

METHODS

A systematic literature review was conducted. The methodical and thorough process of discovering, assessing, and synthesizing relevant studies provided a full review of the available data. Several databases were used for the information search. Most of the articles retrieved from the search came from popular medical research databases, such as Scopus, Taylor & Francis, ScienceDirect, Emerald Insights, PubMed, Springer, IEEE, MDPI, Google Scholar, ProQuest Central, ProQuest Public Health Database, and MEDLINE.

RESULTS AND CONCLUSION

The results of the systematic literature review indicated that several theoretical frameworks (including the technology acceptance model; the technology, organization, and environment framework; the interactive communication technology adoption model; diffusion of innovation theory; dynamic capabilities theory; and the absorptive capability framework) can be used to analyze and understand technology acceptance in healthcare. It is vital to consider the safety of electronic health records during the use of big data. Furthermore, several elements were found to determine technological acceptance, including environmental, technological, organizational, political, and regulatory factors.

Acute-on-Chronic Liver Failure: Causes, Clinical Parameters, and Predictors of Mortality

Objectives This study aimed to identify the causes, clinical characteristics, and 28-day in-hospital mortality predictors in patients with acute-on-chronic liver failure (ACLF). Methods A cross-sectional study enrolled sixty-four patients aged 18-70 years with acute-on-chronic liver failure. The study was conducted at the Gastroenterology Department, Lahore General Hospital. The study classified ACLF according to the criteria of the European Association for the Study of the Liver - Chronic Liver Failure (EASL-CLIF). Patients were followed for 28 days for mortality outcomes. The outcomes between Survivor and Non-survivor groups were compared using the Chi-Square/Fisher's Exact Test for categorical variables and the Mann-Whitney U test for continuous variables. Results In this study, age and duration of chronic liver disease were not significantly different between survivors and non-survivors. The etiology of liver disease and ACLF causes had no impact on 28-day mortality. Non-survivors had lower mean arterial pressure, and higher mortality was linked with lower Glasgow Coma Scale scores, upper gastrointestinal bleeding, and Grade IV hepatic encephalopathy. Significant differences in bilirubin, serum creatinine, urea, and C-reactive protein levels were observed at 28 days. Survival rates were highest with single organ failure (35.94%) and decreased with multiple organ failures. The overall survival rate was 51.56%. Predictive validity for mortality was assessed using the Area Under the Curve (AUC), with Child-Turcotte-Pugh (CTP) at 0.679, Model for End-Stage Liver Disease (MELD) at 0.819, and Chronic Liver Failure-Sequential Organ Failure Assessment (CLIF-SOFA) at 0.771. Conclusion This study concludes that in acute-on-chronic liver failure, factors like age, gender, and disease etiology do not significantly predict 28-day mortality. Key mortality indicators include clinical parameters such as lower Glasgow Coma Scale scores, hepatic encephalopathy Grade IV, and laboratory findings like elevated bilirubin and serum creatinine. The MELD score is the most compelling prognostic tool.

Comparison of the Efficacy of Two-Week Vonoprazan Versus Lansoprazole-Based Quadruple Sequential Antibiotic Therapy in Eradicating Helicobacter pylori Infection: A Non-randomized Clinical Trial

AIM

The prevalence of Helicobacter pylori is escalating in developing countries, exacerbated by unjustified antibiotic usage, which leads to increased resistance. This trend has been notably amplified since the COVID-19 pandemic. Consequently, the effectiveness of existing eradication regimens has been compromised. This study aimed to compare the efficacy of two weeks of vonoprazan-based quadruple sequential therapy and lansoprazole-based quadruple sequential therapy in treating H. pylori infection.  Methods: A non-randomized clinical trial was conducted over 18 months at the Department of Gastroenterology, Lahore General Hospital, Lahore, Pakistan. It included patients presenting with dyspepsia, as defined by the Rome IV criteria, and who tested positive on the urea breath test. Patients were divided into two groups, i.e., Group A and Group B. Group A patients received lansoprazole 30 mg + amoxicillin + tinidazole + tab. colloidal bismuth subcitrate for the first seven days, followed by lansoprazole + levofloxacin + azithromycin + colloidal bismuth subcitrate. Group B patients received vonoprazan + amoxicillin + tinidazole + colloidal bismuth subcitrate for the first seven days, followed by vonoprazan + levofloxacin + azithromycin + colloidal bismuth subcitrate. Both regimes continued for 14 days. Four weeks after 14 days of the treatment, an early morning urea breath test was conducted to evaluate the efficacy of the treatment. Patients were scheduled for follow-up visits at seven and 14 days post-treatment initiation to record adverse events and assess compliance with the treatment regimen. Patients who lost the follow-up and remained non-compliant to the medications were excluded from the final data analysis as per standard protocols of the per-protocol analysis.  Results: A total of 252 patients were included. In Group A and Group B, 6/126 (4.76%) and 8/126 (6.35%) of the patients were lost to follow-up, respectively. The non-compliance rate in Group A was 5/126 (3.97%), compared to Group B with 3/126 (2.38%). Finally, the per-protocol analysis of the results included 115 patients in each group. Baseline characteristics, including demographics, lifestyle, and clinical factors, were comparable between groups with p-values of 0.138 for age, 0.356 for gender, 0.126 for BMI, 0.495 for residence, 0.500 for water source, 0.866 for meal habit, 0.863 for smoking, 0.188 for nonsteroidal anti-inflammatory drug (NSAID) use, 0.145 for proton pump inhibitor (PPI) use, 0.213 for antibiotics, and 0.456 for treatment history. Both treatments effectively eradicated H. pylori, as determined by a negative urea breath test at four weeks post-treatment, with Group B showing a higher eradication rate of 96.5% compared to 92.2% in Group A, although the difference was not statistically significant (p = 0.153). There was no difference in adverse effects in both treatment groups (p-value > 0.05).  Conclusion: The study found that while the vonoprazan-based regime exhibited a slightly higher eradication rate of H. pylori compared to lansoprazole, the difference was not statistically significant. It was concluded that both regimens demonstrated comparable efficacy and similar profiles of adverse effects in treating H. pylori infection.

Dengue hemorrhagic fever: a growing global menace

Dengue virus is an arthropod-borne virus, transmitted by Aedes aegypti among humans. In this review, we discussed the epidemiology of dengue hemorrhagic fever (DHF) as well as the disease's natural history, cycles of transmission, clinical diagnosis, aetiology, prevention, therapy, and management. A systematic literature search was done by databases such as PubMed and Google Scholar using search terms, 'dengue fever', 'symptoms and causes of dengue fever', 'dengue virus transmission', and 'strategies to control dengue'. We reviewed relevant literature to identify hazards related to DHF and the most recent recommendations for its management and prevention. Clinical signs and symptoms of dengue infection range from mild dengue fever (DF) to potentially lethal conditions like DHF or dengue shock syndrome (DSS). Acute-onset high fever, muscle and joint pain, myalgia, a rash on the skin, hemorrhagic episodes, and circulatory shock are among the most common symptoms. An early diagnosis is vital to lower mortality. As dengue virus infections are self-limiting, but in tropical and subtropical areas, dengue infection has become a public health concern. Hence, developing and executing long-term control policies that can reduce the global burden of DHF is a major issue for public health specialists everywhere.

In Silico Analysis: Genome-Wide Identification, Characterization and Evolutionary Adaptations of Bone Morphogenetic Protein (BMP) Gene Family in Homo sapiens

We systematically analyzed BMP gene family in H. sapiens to elucidate genetic structure, phylogenetic relationships, adaptive evolution and tissue-specific expression pattern. Total of 13 BMPs genes were identified in the H. sapiens genome. Bone morphogenetic proteins (BMPs) are composed of a variable number of exons ranging from 2 to 21. They exhibit a molecular weight ranging from 31,081.81 to 82,899.61 Da. These proteins possess hydrophilic characteristics, display thermostability, and exhibit a pH range from acidic to basic. We identified four segmental and two tandem duplication events in BMP gene family of H. sapiens. All of the vertebrate species that were studied show the presence of BMPs 1, 2, 3, 4, 5, 6, 7, 8A, and 15, however only Homo sapiens demonstrated the presence of BMP9 and BMP11. The pathway and process enrichment analysis of BMPs genes showed that these were considerably enriched in positive regulation of pathway-restricted SMAD protein phosphorylation (92%) and cartilage development (77%) biological processes. These genes exhibited positive selection signals that were shown to be conserved across vertebrate lineages. The results showed that BMP2/3/5/6/8a/15 proteins underwent adaptive selection at many amino acid locations and increased positive selection was detected in TGF-β propeptide and TGF-β super family domains which were involved in dorso-ventral patterning, limb bud development. More over the expression pattern of BMP genes revealed that BMP1 and BMP5; BMP4 and BMP6 exhibited substantially identical expression patterns in all tissues while BMP10, BMP15, and BMP3 showed tissue-specific expression.

Lung Tumor Image Segmentation from Computer Tomography Images Using MobileNetV2 and Transfer Learning

BACKGROUND

Lung cancer is one of the most fatal cancers worldwide, and malignant tumors are characterized by the growth of abnormal cells in the tissues of lungs. Usually, symptoms of lung cancer do not appear until it is already at an advanced stage. The proper segmentation of cancerous lesions in CT images is the primary method of detection towards achieving a completely automated diagnostic system.

METHOD

In this work, we developed an improved hybrid neural network via the fusion of two architectures, MobileNetV2 and UNET, for the semantic segmentation of malignant lung tumors from CT images. The transfer learning technique was employed and the pre-trained MobileNetV2 was utilized as an encoder of a conventional UNET model for feature extraction. The proposed network is an efficient segmentation approach that performs lightweight filtering to reduce computation and pointwise convolution for building more features. Skip connections were established with the Relu activation function for improving model convergence to connect the encoder layers of MobileNetv2 to decoder layers in UNET that allow the concatenation of feature maps with different resolutions from the encoder to decoder. Furthermore, the model was trained and fine-tuned on the training dataset acquired from the Medical Segmentation Decathlon (MSD) 2018 Challenge.

RESULTS

The proposed network was tested and evaluated on 25% of the dataset obtained from the MSD, and it achieved a dice score of 0.8793, recall of 0.8602 and precision of 0.93. It is pertinent to mention that our technique outperforms the current available networks, which have several phases of training and testing.

Chemistry and Pharmacology of Fluorinated Drugs Approved by the FDA (2016-2022)

Fluorine is characterized by high electronegativity and small atomic size, which provide this molecule with the unique property of augmenting the potency, selectivity, metabolic stability, and pharmacokinetics of drugs. Fluorine (F) substitution has been extensively explored in drug research as a means of improving biological activity and enhancing chemical or metabolic stability. Selective F substitution onto a therapeutic or diagnostic drug candidate can enhance several pharmacokinetic and physicochemical properties such as metabolic stability and membrane permeation. The increased binding ability of fluorinated drug target proteins has also been reported in some cases. An emerging line of research on F substitution has been addressed by using 18F as a radiolabel tracer atom in the extremely sensitive methodology of positron emission tomography (PET) imaging. This review aims to report on the fluorinated drugs approved by the US Food and Drug Administration (FDA) from 2016 to 2022. It cites selected examples from a variety of therapeutic and diagnostic drugs. FDA-approved drugs in this period have a variety of heterocyclic cores, including pyrrole, pyrazole, imidazole, triazole, pyridine, pyridone, pyridazine, pyrazine, pyrimidine, triazine, purine, indole, benzimidazole, isoquinoline, and quinoline appended with either F-18 or F-19. Some fluorinated oligonucleotides were also authorized by the FDA between 2019 and 2022.

Impact of Environmental Risk Factors on Mitochondrial Dysfunction, Neuroinflammation, Protein Misfolding, and Oxidative Stress in the Etiopathogenesis of Parkinson's Disease

As a prevalent progressive neurodegenerative disorder, Parkinson's disease (PD) is characterized by the neuropathological hallmark of the loss of nigrostriatal dopaminergic (DAergic) innervation and the appearance of Lewy bodies with aggregated α-synuclein. Although several familial forms of PD have been reported to be associated with several gene variants, most cases in nature are sporadic, triggered by a complex interplay of genetic and environmental risk factors. Numerous epidemiological studies during the past two decades have shown positive associations between PD and several environmental factors, including exposure to neurotoxic pesticides/herbicides and heavy metals as well as traumatic brain injury. Other environmental factors that have been implicated as potential risk factors for PD include industrial chemicals, wood pulp mills, farming, well-water consumption, and rural residence. In this review, we summarize the environmental toxicology of PD with the focus on the elaboration of chemical toxicity and the underlying pathogenic mechanisms associated with exposure to several neurotoxic chemicals, specifically 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), rotenone, paraquat (PQ), dichloro-diphenyl-trichloroethane (DDT), dieldrin, manganese (Mn), and vanadium (V). Our overview of the current findings from cellular, animal, and human studies of PD provides information for possible intervention strategies aimed at halting the initiation and exacerbation of environmentally linked PD.

Effect of gasotransmitters treatment on expression of hypertension, vascular and cardiac remodeling and hypertensive nephropathy genes in left ventricular hypertrophy

BACKGROUND

Cardiac and renal dysfunction are often co-morbid pathologies leading to worsening prognosis resulting in difficulty in therapy of left ventricular hypertrophy (LVH). The aim of the current study was to determine the changes in expression of human ortholog genes of hypertension, vascular and cardiac remodeling and hypertensive nephropathy phenotypes under normal, disease and upon treatment with gasotransmitter including H₂S (hydrogen sulphide), NO (nitric oxide) and combined (H₂S + NO).

METHODS

A total of 72 Wistar Kyoto rats (with equivalent male and female animals) were recruited in the present study where LVH rat models were treated with H₂S and NO individually as well as with both combined. Cardiac and renal physical indices were recorded and relative gene expression were quantified.

RESULTS

Both cardiac and renal physical indices were significantly modified with individual as well as combined H₂S + NO treatment in control and LVH rats. Expression analysis revealed, hypertension, vascular remodeling genes ACE, TNFα and IGF1, mRNAs to be significantly higher (P ≤ 0.05) in the myocardia and renal tissues of LVH rats, while individual and combined H₂S + NO treatment resulted in lowering the gene expression to normal/near to normal levels. The cardiac remodeling genes MYH7, TGFβ, SMAD4 and BRG1 expression were significantly up-regulated (P ≤ 0.05) in the myocardia of LVH where the combined H₂S + NO treatment resulted in normal/near to normal expression more effectively as compared to individual treatments. In addition individual as well as combined H₂S and NO treatment significantly decreased PKD1 expression in renal tissue, which was up-regulated in LVH rats (P ≤ 0.05).

CONCLUSIONS

The reduction in hemodynamic parameters and cardiac indices as well as alteration in gene expression on treatment of LVH rat model indicates important therapeutic potential of combined treatment with H₂S + NO gasotransmitters in hypertension and cardiac hypertrophy when present as co-morbidity with renal complications.

Mechanistic Interplay Between Autophagy and Apoptotic Signaling in Endosulfan-Induced Dopaminergic Neurotoxicity: Relevance to the Adverse Outcome Pathway in Pesticide Neurotoxicity

Chronic exposure to pesticides is implicated in the etiopathogenesis of Parkinson's disease (PD). Previously, we showed that dieldrin induces dopaminergic neurotoxicity by activating a cascade of apoptotic signaling pathways in experimental models of PD. Here, we systematically investigated endosulfan's effect on the interplay between apoptosis and autophagy in dopaminergic neuronal cell models of PD. Exposing N27 dopaminergic neuronal cells to endosulfan rapidly induced autophagy, indicated by an increased number of autophagosomes and LC3-II accumulation. Prolonged endosulfan exposure (>9 h) triggered apoptotic signaling, including caspase-2 and -3 activation and protein kinase C delta (PKCδ) proteolytic activation, ultimately leading to cell death, thus demonstrating that autophagy precedes apoptosis during endosulfan neurotoxicity. Furthermore, inhibiting autophagy with wortmannin, a phosphoinositide 3-kinase inhibitor, potentiated endosulfan-induced apoptosis, suggesting that autophagy is an early protective response against endosulfan. Additionally, Beclin-1, a major regulator of autophagy, was cleaved during the initiation of apoptotic cell death, and the cleavage was predominantly mediated by caspase-2. Also, caspase-2 and caspase-3 inhibitors effectively blocked endosulfan-induced apoptotic cell death. CRISPR/Cas9-based stable knockdown of PKCδ significantly attenuated endosulfan-induced caspase-3 activation, indicating that the kinase serves as a regulatory switch for apoptosis. Additional studies in primary mesencephalic neuronal cultures confirmed endosulfan's effect on autophagy and neuronal degeneration. Collectively, our results demonstrate that a functional interplay between autophagy and apoptosis dictate pesticide-induced neurodegenerative processes in dopaminergic neuronal cells. Our study provides insight into cell death mechanisms in environmentally linked neurodegenerative diseases.

Engineering-out hazards: digitising the management working safety in confined spaces

Purpose

This paper aims to report upon the further development of a hybrid application programming interface (API) plug-in to building information modelling (BIM) entitled confined spaces safety monitoring system “CoSMoS”. Originally designed to engineer-out environmental hazards associated with working in a building’s confined spaces (during the construction phase of a building’s life-cycle), this second generation version is expanded upon to use archival records to proactively learn from data generated within a sensor network during the building’s operations and maintenance (O&M) phase of asset management (AM).

Design/methodology/approach

An applied research methodological approach adopted used a two-phase process. In phase one, a conceptual model was created to provide a “blueprint map” to integrate BIM, sensor-based networks and data analytics (DA) into one integral system. A literature review provided the basis for the conceptual model’s further development. In phase two, the conceptual model was transposed into the prototype’s development environment as a proof of concept using primary data accrued from a large educational building.

Findings

An amalgamation of BIM, historical sensor data accrued and the application of DA demonstrate that CoSMoS provides an opportunity for the facilities management (FM) team to monitor pertinent environmental conditions and human behaviour within buildings that may impact upon occupant/worker safety. Although working in confined spaces is used to demonstrate the inherent potential of CoSMoS, the system could readily be expanded to analyse sensor-based network’s historical data of other areas of building performance, maintenance and safety.

Originality/value

This novel prototype has automated safety applications for FM during the asset lifecycle and maintenance phase of a building’s O&M phase of AM. Future work is proposed in several key areas, namely, develop instantaneous indicators of current safety performance within a building; and develop lead indicators of future safety performance of buildings.