Designing a comprehensive minimum dataset for patients with COVID-19 in Iranian hospital information systems

BACKGROUND

The Minimum Data Set (MDS) plays a vital role in data exchange, collection and quality improvement. In the context of the COVID-19 pandemic, there is a need for a tailored MDS that aligns with the specific information needs of the Iranian community and integrates seamlessly into the country's Hospital Information Systems (HIS).

OBJECTIVE

The study aimed to develop a comprehensive MDS for COVID-19 patients in Iran, with objectives to identify essential data elements and integrate the MDS into HIS, enhancing data exchange and supporting decision-making.

METHOD

This study employed a comparative-descriptive approach to design COVID-19 patient data elements based on World Health Organisation and Centers for Disease Control and Prevention guidelines. The Delphi technique involved 35 experts in two rounds for checklist refinement. The finalised MDS consisted of 9 main terms and 80 sub-terms, analysed using descriptive statistics and IBM SPSS software.

RESULTS

Of 35 experts involved with the study, 69% were male and 31% female, and Health Information Management experts were the majority (34%). The refined MDS for COVID-19 in Iran comprises 50 data elements, while 30 elements were excluded. The MDS includes 8 main terms and 80 sub-terms, with unanimous approval for identity, underlying disease, and treatment sections.

CONCLUSION

The customised MDS for COVID-19 patients in Iran addresses data collection challenges and supports effective disease prevention and management. By providing comprehensive and reliable information, the MDS enhances healthcare quality, facilitates timely access to medical records, and fosters integrated health services.

Mobile Learning Among University Students: Adoption and Application of M-Learning

The successful implementation of mobile learning is mainly impacted by learners’ attitudes to accepting and applying mobile learning systems. In the current study, an m-learning application was developed and implemented for university students, and their perspective toward the adoption and application of m-learning was investigated. This cross-sectional study was carried out in 2020. The participants were 114 university students at Abadan University of Medical Sciences. Data were collected by means of a valid questionnaire containing 42 questions in 13 subscales in addition to an open-ended question about the positive and negative aspects of the m-learning application. There was a significant relationship between acceptance and major (P=0.001), mobile usage (P=0.035), and familiarity with m-learning (P<0.001). The total mean of m-learning application acceptance was 3.95±0.32, which shows a good level. Self-efficacy, perceived ease of use, and user interface were, respectively, the most influencing factors; mobile device limitation and governmental support were the least influencing factors. “Direct communication with the teacher/instructor” and “Internet disconnection during video teaching” were among the positive and negative aspects of applying the m-learning application, respectively. The m-learning application was well adopted among the students. Mobile device limitations are a reason for the student's concerns. “Usability features” can be a point for covering mobile device limitations.

Evaluation of the effect of sofosbuvir and daclatasvir in hospitalized COVID-19 patients: a randomized double-blind clinical trial (DISCOVER)

Background

The combination of sofosbuvir and daclatasvir has shown preliminary efficacy for hospitalized patients with COVID-19 in four open-label studies with small sample sizes. This larger trial aimed to assess if the addition of sofosbuvir/daclatasvir to standard care improved clinical outcomes in hospitalized patients with COVID-19.

Methods

This was a placebo-controlled, double-blind, randomized clinical trial in adults hospitalized with COVID-19 at 19 hospitals in Iran. Patients were randomized to oral sofosbuvir/daclatasvir 400/60 mg once-daily or placebo in addition to standard of care. Patients were included if they had positive PCR or diagnostic chest CT, O₂ saturation <95% and compatible symptoms. The primary outcome was hospital discharge within 10 days of randomization. Secondary outcomes included mortality and time to clinical events. The trial is registered on the Iran Registry of Clinical Trials under IRCT20200624047908N1.

Results

Between July and October 2020, 1083 patients were randomized to either the sofosbuvir/daclatasvir arm (n = 541) or the placebo arm (n = 542). No significant difference was observed in the primary outcome of hospital discharge within 10 days, which was achieved by 415/541 (77%) in the sofosbuvir/daclatasvir arm and 411/542 (76%) in the placebo arm [risk ratio (RR) 1.01, 95% CI 0.95–1.08, P = 0.734]. In-hospital mortality was 60/541 (11%) in the sofosbuvir/daclatasvir arm versus 55/542 (10%) in the placebo arm (RR 1.09, 95% CI 0.77–1.54, P = 0.615). No differences were observed in time to hospital discharge or time to in-hospital mortality.

Conclusions

We observed no significant effect of sofosbuvir/daclatasvir versus placebo on hospital discharge or survival in hospitalized COVID-19 patients.

Evaluation of Hepatic, Renal and Cardiac Diagnostic Markers in Patients With Severe COVID-19

SARS-CoV-2 that causes Coronavirus disease 2019 (COVID-19) was first known in Wuhan, China, in December 2019. The aim of this study was to evaluate the level of common hepatic, renal, and cardiac diagnostic markers in hospitals in patients with severe COVID 19. In this study, 259 patients with symptoms of severe COVID-19 and a positive RT-PCR assay of nasopharyngeal samples were enrolled. Inclusion criteria are positive for COVID-19 patients at the diagnosis of an infectious disease physician. Diagnostic markers of liver, kidney, and heart were evaluated by age and gender. In this study, 48.3% of patients severe with COVID-19 were male, and 51.7% were female. The mean of markers such as LDH, Direct Bilirubin, SGOT, SGPT, D-dimer was higher than normal, which was observed in men more than women. The mean of CK-MB also was higher than normal, which was observed in women more than men. The highest mean of markers was seen in the older ages. The mean of BUN was observed in the age range of 55-64 years and above 65 years above normal. But the mean of CPK, creatinine, potassium and alkaline phosphatase were normal. The results of the present study showed an increase in the level of some of the most important diagnostic markers of hepatic, renal, and cardiac in patients with COVID 19. This increase was greater in some markers, including SGOT, SGPT, Direct bilirubin, LDH, D-dimer, in men than in women, and more in older patients.

Efficacy of naproxen in the management of patients hospitalized with COVID-19 infection: A randomized, double-blind, placebo-controlled, clinical trial

BACKGROUND AND AIMS

The current study was done to examine the efficacy of naproxen in the management of patients with COVID-19 infection.

METHODS

This randomized, double-blind, placebo-controlled, clinical trial was done on hospitalized adult patients with confirmed COVID-19 infection. Patients were randomly assigned to receive either naproxen (two capsules per day each containing 500 mg naproxen sodium) or placebo (containing starch) for five days along with the routine treatment that was nationally recommended for COVID-19 infection. Clinical symptoms of COVID-19 infection, the time to clinical improvement, blood pressure, laboratory parameters, and death due to COVID-19 infection were considered as the outcome variables in the present study.

RESULTS

Treatment with naproxen improved cough and shortness of breath in COVID-19 patients; such that, compared with placebo, naproxen intake was associated with 2.90 (95% CI: 1.10-7.66) and 2.82 (95% CI: 1.05-7.55) times more improvement in cough and shortness of breath, respectively. In addition, naproxen administration resulted in a significant increase in mean corpuscular volume (MCV) and had a preventive effect on the reduction of systolic blood pressure in COVID-19 patients.

CONCLUSION

Treatment with naproxen can improve cough and shortness of breath in COVID-19-infected patients. Further studies are required to confirm our findings.

Performance evaluation of selected machine learning algorithms for COVID-19 prediction using routine clinical data: With versus Without CT scan features

BACKGROUND

Given coronavirus disease (COVID-19's) unknown nature, diagnosis, and treatment is very complex up to the present time. Thus, it is essential to have a framework for an early prediction of the disease. In this regard, machines learning (ML) could be crucial to extract concealed patterns from mining of huge raw datasets then it establishes high-quality predictive models. At this juncture, we aimed to apply different ML techniques to develop clinical predictive models and select the best performance of them.

MATERIALS AND METHODS

The dataset of Ayatollah Talleghani hospital, COVID-19 focal center affiliated to Abadan University of Medical Sciences have been taken into consideration. The dataset used in this study consists of 501 case records with two classes (COVID-19 and non COVID-19) and 32 columns for the diagnostic features. ML algorithms such as Naïve Bayesian, Bayesian Net, random forest (RF), multilayer perceptron, K-star, C4.5, and support vector machine were developed. Then, the recital of selected ML models was assessed by the comparison of some performance indices such as accuracy, sensitivity, specificity, precision, F-score, and receiver operating characteristic (ROC).

RESULTS

The experimental results indicate that RF algorithm with the accuracy of 92.42%, specificity of 75.70%, precision of 92.30%, sensitivity of 92.40%, F-measure of 92.00%, and ROC of 97.15% has the best capability for COVID-19 diagnosis and screening.

CONCLUSION

The empirical results reveal that RF model yielded higher performance as compared to other six classification models. It is promising to the implementation of RF model in the health-care settings to increase the accuracy and speed of disease diagnosis for primary prevention, screening, surveillance, and early treatment.

The impact of sofosbuvir/daclatasvir or ribavirin in patients with severe COVID-19

OBJECTIVES

Sofosbuvir and daclatasvir are direct-acting antivirals highly effective against hepatitis C virus. There is some in silico and in vitro evidence that suggests these agents may also be effective against SARS-CoV-2. This trial evaluated the effectiveness of sofosbuvir in combination with daclatasvir in treating patients with COVID-19.

METHODS

Patients with a positive nasopharyngeal swab for SARS-CoV-2 on RT-PCR or bilateral multi-lobar ground-glass opacity on their chest CT and signs of severe COVID-19 were included. Subjects were divided into two arms with one arm receiving ribavirin and the other receiving sofosbuvir/daclatasvir. All participants also received the recommended national standard treatment which, at that time, was lopinavir/ritonavir and single-dose hydroxychloroquine. The primary endpoint was time from starting the medication until discharge from hospital with secondary endpoints of duration of ICU stay and mortality.

RESULTS

Sixty-two subjects met the inclusion criteria, with 35 enrolled in the sofosbuvir/daclatasvir arm and 27 in the ribavirin arm. The median duration of stay was 5 days for the sofosbuvir/daclatasvir group and 9 days for the ribavirin group. The mortality in the sofosbuvir/daclatasvir group was 2/35 (6%) and 9/27 (33%) for the ribavirin group. The relative risk of death for patients treated with sofosbuvir/daclatasvir was 0.17 (95% CI 0.04-0.73, P = 0.02) and the number needed to treat for benefit was 3.6 (95% CI 2.1-12.1, P < 0.01).

CONCLUSIONS

Given these encouraging initial results, and the current lack of treatments proven to decrease mortality in COVID-19, further investigation in larger-scale trials seems warranted.

Developing Cardiac Electrophysiology Ontology: Moving Towards Data Harmonization and Integration

Introduction: Cardiac electrophysiology (EP) studies the electrical heart conduction system which is used for diagnosis and treatment of cardiac arrhythmias. In this context, a huge amount of data is generated, requiring efficient and effective access, interpretation, and data analysis from multiple sources in a unified view. To resolve this challenge, this essay presents an ontology to reconcile data heterogeneity problems in this domain.Material and Methods: The cardiac EP ontology was constructed according to the life cycle of ontology building. Structural, functional, and expert evaluation was performed to ensure its quality and usability.     Results: Cardiac EP ontology was developed using protégé environment and implemented in OWL editing tool. It presented a detailed hierarchical structure of the cardiac EP domain with around 324 instances describing cardiac EP-related concepts.Conclusion: Cardiac EP ontology provides an explicit formal description of the concepts, relationships, and properties associated with cardiac electrophysiology making seamless data integration between multiple heterogeneous databases. It also is a useful framework for knowledge representation in knowledge-based systems, as well as for explicit communication between experts in the EP domain.