Prediction of COVID-19 Mortality in the Intensive Care Unit Using Machine Learning.

Since its emergence, the COVID-19 pandemic still poses a major global health threat. In this setting, a number of useful machine learning applications have been explored to assist clinical decision-making, predict the severity of disease and admission to the intensive care unit, and also to estimate future demand for hospital beds, equipment, and staff. The present study examined demographic data, hematological and biochemical markers routinely measured in Covid-19 patients admitted to the intensive care unit (ICU) of a public tertiary hospital, in relation to the ICU outcome, during the second and third Covid-19 waves, from October 2020 until February 2022. In this dataset, we applied eight well-known classifiers of the caret package for machine learning of the R programming language, to evaluate their performance in forecasting ICU mortality. The best performance regarding area under the receiver operating characteristic curve (AUC-ROC) was observed with Random Forest (0.82), while k-nearest neighbors (k-NN) were the lowest performing machine learning algorithm (AUC-ROC: 0.59). However, in terms of sensitivity, XGB outperformed the other classifiers (max Sens: 0.7). The six most important predictors of mortality in the Random Forest model were serum urea, age, hemoglobin, C-reactive protein, platelets, and lymphocyte count.

A Narrative Review of Emerging Therapeutics for COVID-19.

The novel severe acute respiratory syndrome coronavirus 2, the causal agent of coronavirus disease 2019 (COVID-19), quickly spread around the world, resulting in the most aggressive pandemic experienced in more than 100 years. Research on targeted therapies and vaccines has been initiated on an unprecedented scale and speed but will take months and even years to come to fruition. Meanwhile, the efficacy of emerging therapeutics for use in treating COVID-19 is feverishly being investigated to identify the best available treatment options for dealing with the current wave of disease. This review of publications with a "treatment" tag through June 29, 2020 in the National Library of Medicine's LitCovid literature hub, provides frontline clinicians with a pragmatic summary of the current state of the rapidly evolving evidence supporting emerging candidate therapeutics for COVID-19. Two main categories of pharmaceutical therapeutics are showing promise: those with antiviral activity directly addressing infection and those that counteract the inflammatory cytokine storm induced by severe disease. Preliminary results suggest that other approaches such as convalescent plasma therapy and lung radiation therapy may have some efficacy. The current clinical evidence for potential treatments is preliminary-often small retrospective series or early results of randomized trials-and the science is evolving rapidly. The long-term results from large, well-designed randomized controlled trials will provide definitive evidence for therapeutic effectiveness and are likely months away. The trial landscape for promising therapies is described.

Antibiotic use during coronavirus disease 2019 intensive care unit shape multidrug resistance bacteriuria: A Swedish longitudinal prospective study.

Objectives: High frequency of antimicrobial prescription and the nature of prolonged illness in COVID-19 increases risk for complicated bacteriuria and antibiotic resistance. We investigated risk factors for bacteriuria in the ICU and the correlation between antibiotic treatment and persistent bacteria. Methods: We conducted a prospective longitudinal study with urine from indwelling catheters of 101 ICU patients from Uppsala University Hospital, Sweden. Samples were screened and isolates confirmed with MALDI-TOF and whole genome sequencing. Isolates were analyzed for AMR using broth microdilution. Clinical data were assessed for correlation with bacteriuria. Results: Length of stay linearly correlated with bacteriuria (R2 = 0.99, p ≤ 0.0001). 90% of patients received antibiotics, primarily the beta-lactams (76%) cefotaxime, piperacillin-tazobactam, and meropenem. We found high prevalence of Enterococcus (42%) being associated with increased cefotaxime prescription. Antibiotic-susceptible E. coli were found to cause bacteriuria despite concurrent antibiotic treatment when found in co-culture with Enterococcus. Conclusion: Longer stays in ICUs increase the risk for bacteriuria in a predictable manner. Likely, high use of cefotaxime drives Enterococcus prevalence, which in turn permit co-colonizing Gram-negative bacteria. Our results suggest biofilms in urinary catheters as a reservoir of pathogenic bacteria with the potential to develop and disseminate AMR.

Corticosteroids and Outcomes in Solid Organ Transplant Recipients Infected With Severe Acute Respiratory Syndrome Coronavirus 2.

Objective: To examine outcomes in organ transplant and nontransplant patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during the initial 22 months of the pandemic. Patients and Methods: We used Optum electronic health records to compare outcomes between an adult transplant group and a propensity-matched nontransplant group that tested positive for SARS-CoV-2 from February 1, 2020, to December 15, 2021. Baseline characteristics, hospitalization, intensive care unit admission, mechanical ventilation, renal replacement therapy, inpatient, and 90-day mortality were compared between the transplant and nontransplant groups and among specific transplant recipients. Cox proportional analysis was used to examine hospitalization and mortality by organ transplant, medical therapy, sex, and the period of the pandemic. Results: We identified 876,959 patients with SARS-CoV-2 infection, of whom 3548 were organ transplant recipients. The transplant recipients had a higher risk of hospitalization (30.6% vs 25%, respectively; P<.001), greater use of mechanical ventilation (7.8% vs 5.6%, respectively; P<.001), and increased inpatient mortality (6.7% vs 4.7%, respectively; P<.001) compared with the nontransplant patients. The initiation of mechanical ventilation was significantly more frequent in the transplant group. After adjustment for baseline characteristics and comorbidities, the transplant group had a higher risk of hospitalization (odds ratio, 1.38; 95% confidence interval, 1.19-1.59), without a difference in mortality. In the transplant group, lung transplant recipients had the highest inpatient mortality (11.6%). Conclusion: Among patients with SARS-CoV-2 infection, the transplant recipients were at a higher risk of hospitalization and inpatient mortality; however, mortality was mainly driven by advanced age and comorbidities rather than by transplant status or immunosuppressive medications. Lung transplant recipients had the greatest inpatient and 90-day mortality.

Airways management in SARS-COV-2 acute respiratory failure: A prospective observational multi-center study.

Objective: Few studies have reported the implications and adverse events of performing endotracheal intubation for critically ill COVID-19 patients admitted to intensive care units. The aim of the present study was to determine the adverse events related to tracheal intubation in COVID-19 patients, defined as the onset of hemodynamic instability, severe hypoxemia, and cardiac arrest. Setting: Tertiary care medical hospitals, dual-centre study performed in Northern Italy from November 2020 to May 2021. Patients: Adult patients with positive SARS-CoV-2 PCR test, admitted for respiratory failure and need of advanced invasive airways management. Interventions: Endotracheal Intubation Adverse Events. Main variables of interests: The primary endpoint was to determine the occurrence of at least 1 of the following events within 30 minutes from the start of the intubation procedure and to describe the types of major adverse peri-intubation events: severe hypoxemia defined as an oxygen saturation as measured by pulse-oximetry <80%; hemodynamic instability defined as a SBP 65 mmHg recoded at least once or SBP < 90 mmHg for 30 minutes, a new requirement or increase of vasopressors, fluid bolus >15 mL/kg to maintain the target blood pressure; cardiac arrest. Results: Among 142 patients, 73.94% experienced at least one major adverse peri-intubation event. The predominant event was cardiovascular instability, observed in 65.49% of all patients undergoing emergency intubation, followed by severe hypoxemia (43.54%). 2.82% of the patients had a cardiac arrest. Conclusion: In this study of intubation practices in critically ill patients with COVID-19, major adverse peri-intubation events were frequent. Clinical Trial registration: www.clinicaltrials.gov identifier: NCT04909476.

Objetivo: Pocos estudios han informado las implicaciones y los eventos adversos de realizar una intubación endotraqueal para pacientes críticos con COVID-19 ingresados ​​en unidades de cuidados intensivos. El objetivo del presente estudio fue determinar los eventos adversos relacionados con la intubación traqueal en pacientes con COVID-19, definidos como la aparición de inestabilidad hemodinámica, hipoxemia severa y paro cardíaco. Ámbito: Hospitales médicos de atención terciaria, estudio de doble centro realizado en el norte de Italia desde noviembre de 2020 hasta mayo de 2021. Pacientes: Pacientes adultos con prueba PCR SARS-CoV-2 positiva, ingresados por insuficiencia respiratoria y necesidad de manejo avanzado de vías aéreas invasivas. Intervenciones: Eventos adversos de la intubación endotraqueal. Principales variables de interés: El punto final primario fue determinar la ocurrencia de al menos 1 de los siguientes eventos dentro de los 30 minutos posteriores al inicio del procedimiento de intubación y describir los tipos de eventos adversos periintubación mayores. : hipoxemia severa definida como una saturación de oxígeno medida por pulsioximetría <80%; inestabilidad hemodinámica definida como PAS 65 mmHg registrada al menos una vez o PAS < 90 mmHg durante 30 minutos, nuevo requerimiento o aumento de vasopresores, bolo de líquidos > 15 mL/kg para mantener la presión arterial objetivo; paro cardiaco. Resultados: Entre 142 pacientes, el 73,94% experimentó al menos un evento periintubación adverso importante. El evento predominante fue la inestabilidad cardiovascular, observada en el 65,49% de todos los pacientes sometidos a intubación de urgencia, seguido de la hipoxemia severa (43,54%). El 2,82% de los pacientes tuvo un paro cardíaco. Conclusión: En este estudio de prácticas de intubación en pacientes críticos con COVID-19, los eventos adversos periintubación mayores fueron frecuentes. Registro de ensayos clínicos: www.clinicaltrials.gov identificador: NCT04909476.

Repurposing of drugs for combined treatment of COVID-19 cytokine storm using machine learning.

Severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) induced cytokine storm is the major cause of COVID­19 related deaths. Patients have been treated with drugs that work by inhibiting a specific protein partly responsible for the cytokines production. This approach provided very limited success, since there are multiple proteins involved in the complex cell signaling disease mechanisms. We targeted five proteins: Angiotensin II receptor type 1 (AT1R), A disintegrin and metalloprotease 17 (ADAM17), Nuclear Factor­Kappa B (NF­κB), Janus kinase 1 (JAK1) and Signal Transducer and Activator of Transcription 3 (STAT3), which are involved in the SARS­CoV­2 induced cytokine storm pathway. We developed machine learning (ML) models for these five proteins, using known active inhibitors. After developing the model for each of these proteins, FDA-approved drugs were screened to find novel therapeutics for COVID­19. We identified twenty drugs that are active for four proteins with predicted scores greater than 0.8 and eight drugs active for all five proteins with predicted scores over 0.85. Mitomycin C is the most active drug across all five proteins with an average prediction score of 0.886. For further validation of these results, we used the PyRx software to conduct protein-ligand docking experiments and calculated the binding affinity. The docking results support findings by the ML model. This research study predicted that several drugs can target multiple proteins simultaneously in cytokine storm-related pathway. These may be useful drugs to treat patients because these therapies can fight cytokine storm caused by the virus at multiple points of inhibition, leading to synergistically effective treatments.

Impact of angiotensin receptor blocker as antihypertensive in assessing mortality in patients of COVID-19: A single tertiary care center study.

BACKGROUND: The angiotensin-converting enzyme 2 (ACE2) receptor, a membrane receptor present in the respiratory system, the gastrointestinal tracts, the heart, and the kidney is the entry point for SARS-CoV-2 to enter human cells. Concerns were raised about the influence of using antihypertensive drugs like angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) in individuals with COVID-19 due to its tight relationship with the ACE2 receptor. The aim of this study was to investigate the impact of being on an Angiotensin Receptor Blockers (ARB) on mortality in patients consecutively diagnosed with COVID-19. MATERIAL AND METHODS: This is the retrospective observational study done in all patients consecutively diagnosed with COVID-19 from January 2021 to June 2021. All related patient information and clinical data was retrieved from the hospitals electronic medical record system. RESULTS: In this study, out of 500 patients, 51 died, having mean age of 66.92 ± 10.85 years. 144 (28.8%) patients were on angiotensin receptor blockers as antihypertensive treatment, 142 (28.4%) having other antihypertensive and 214 (42.8%) were not on any treatment. Out of 51 Death 7 (4.9) patients were on ARBs, 15 ± 10.6 were on other medication [OR 2.31 (0.94-6.22, P = 0.077) univariable; OR 2.57 (1.00-7.23, P = 0.058) multivariable] and 29 ± 13.6 had no treatment at all [OR 3.07 (1.38-7.80, P = 0.010) univariable; OR 3.36 (1.41-9.08, P = 0.010) multivariable]. CONCLUSION: Use of ARB medications for the hypertensive patients who acquire COVID-19 infection has shown protective effects of such medications on COVID-19 disease severity in the term of mortality and the mortality rate among hypertensive patients on COVID-19 with ARBs/ACE inhibitors showed significant differences as compared to other antihypertensives.

A Multimodal Approach to Training COVID-19 Processes Across Four Intensive Care Units.

Coronavirus disease (COVID-19) required innovative training strategies for emergent aerosol generating procedures (AGPs) in intensive care units (ICUs). This manuscript summarizes institutional operationalization of COVID-specific training, standardized across four ICUs. An interdisciplinary team collaborated with the Simulator Program and OpenPediatrics refining logistics using process maps, walkthroughs and simulation. A multimodal approach to information dissemination, high-volume team training in modified resuscitation practices and technical skill acquisition included instructional videos, training superusers, small-group simulation using a flipped classroom approach with rapid cycle deliberate practice, interactive webinars, and cognitive aids. Institutional data on application of this model are presented. Success was founded in interdisciplinary collaboration, resource availability and institutional buy in.

Relationship of political ideology of US federal and state elected officials and key COVID pandemic outcomes following vaccine rollout to adults: April 2021-March 2022.

Background: Scant research, including in the United States, has quantified relationships between the political ideologies of elected representatives and COVID-19 outcomes among their constituents. Methods: We analyzed observational cross-sectional data on COVID-19 mortality rates (age-standardized) and stress on hospital intensive care unit (ICU) capacity for all 435 US Congressional Districts (CDs) in a period of adult vaccine availability (April 2021-March 2022). Political metrics comprised: (1) ideological scores based on each US Representative's and Senator's concurrent overall voting record and their specific COVID-19 votes, and (2) state trifectas (Governor, State House, and State Senate under the same political party control). Analyses controlled for CD social metrics, population density, vaccination rates, the prevalence of diabetes and obesity, and voter political lean. Findings: During the study period, the higher the exposure to conservatism across several political metrics, the higher the COVID-19 age-standardized mortality rates, even after taking into account the CD's social characteristics; similar patterns occurred for stress on hospital ICU capacity for Republican trifectas and US Senator political ideology scores. For example, in models mutually adjusting for CD political and social metrics and vaccination rates, Republican trifecta and conservative voter political lean independently remained significantly associated with an 11%-26% higher COVID-19 mortality rate. Interpretation: Associations between the political ideologies of US federal elected officials and state concentrations of political party power with population health warrant greater consideration in public health analyses and monitoring dashboards. Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Neutrophil to lymphocyte ratio and in-hospital mortality among patients with SARS-CoV-2: A retrospective study.

The goal of this study was to investigate in-hospital mortality in patients suffering from acute respiratory syndrome coronavirus 2 (SARS-CoV-2) relative to the neutrophil to lymphocyte ratio (NLR) and to determine if there are gender disparities in outcome. Between February 26 and September 8, 2020, patients having SARS-CoV-2 infection were enrolled in this retrospective cohort research, which was categorized by NLR levels ≥9 and < 9. In total, 6893 patients were involved included of whom6591 had NLR <9, and 302 had NLR ≥9. The age of most of the patients in the NLR<9 group was 50 years, on the other hand, the age of most of the NLR ≥9 group patients was between 50 and 70 years. The majority of patients in both groups were male 2211 (66.1%). The ICU admission time and mortality rate for the patients with NLR ≥9 was significantly higher compared to patients with NLR <9. Logistic regression's outcome indicated that NLR ≥9 (odds ratio (OR), 24.9; 95% confidence interval (CI): 15.5-40.0; p < 0.001), male sex (OR, 3.5; 95% CI: 2.0-5.9; p < 0.001) and haemoglobin (HB) (OR, 0.95; 95% CI; 0.94-0.96; p < 0.001) predicted in-hospital mortality significantly. Additionally, Cox proportional hazards analysis (B = 4.04, SE = 0.18, HR = 56.89, p < 0.001) and Kaplan-Meier survival probability plots also indicated that NLR>9 had a significant effect on mortality. NLR ≥9 is an independent predictor of mortality(in-hospital) among SARS-CoV-2 patients.

Cross-immunity against SARS-COV-2 variants of concern in naturally infected critically ill COVID-19 patients.

Critically ill patients infected with SARS-CoV-2 display adaptive immunity, but it is unknown if they develop cross-reactivity to variants of concern (VOCs). We profiled cross-immunity against SARS-CoV-2 VOCs in naturally infected, non-vaccinated, critically ill COVID-19 patients. Wave-1 patients (wild-type infection) were similar in demographics to Wave-3 patients (wild-type/alpha infection), but Wave-3 patients had higher illness severity. Wave-1 patients developed increasing neutralizing antibodies to all variants, as did patients during Wave-3. Wave-3 patients, when compared to Wave-1, developed more robust antibody responses, particularly for wild-type, alpha, beta and delta variants. Within Wave-3, neutralizing antibodies were significantly less to beta and gamma VOCs, as compared to wild-type, alpha and delta. Patients previously diagnosed with cancer or chronic obstructive pulmonary disease had significantly fewer neutralizing antibodies. Naturally infected ICU patients developed adaptive responses to all VOCs, with greater responses in those patients more likely to be infected with the alpha variant, versus wild-type.

Transient expression of antinuclear RNP-A antibodies in patients with acute COVID-19 infection.

Introduction: Viral infections have been implicated in the initiation of the autoimmune diseases. Recent reports suggest that a proportion of patients with COVID-19 develop severe disease with multiple organ injuries. We evaluated the relationship between COVID-19 severity, prevalence and persistence of antinuclear and other systemic and organ specific autoantibodies as well as SARS-CoV-2 infection specific anti-nucleocapsid (N) IgG antibodies and protective neutralizing antibody (Nab) levels. Methods: Samples from 119 COVID-19 patients categorized based on their level of care and 284 healthy subjects were tested for the presence and persistence of antinuclear and other systemic and organ specific autoantibodies as well as SARS-CoV-2 and neutralizing antibody levels. Results: The data shows significantly increased levels of anti RNP-A, anti-nucleocapsid and neutralizing antibody among patients receiving ICU care compared to non-ICU care. Furthermore, subjects receiving ICU care demonstrated significantly higher nucleocapsid IgG levels among the RNP-A positive cohort compared to RNP-A negative cohort. Notably, the expression of anti RNP-A antibodies is transient that reverts to non-reactive status between 20 and 60 days post symptom onset. Conclusions: COVID-19 patients in ICU care exhibit significantly higher levels of transient RNP-A autoantibodies, anti-nucleocapsid, and SARS-CoV-2 neutralizing antibodies compared to patients in non-ICU care.

Vitamin D status can affect COVID-19 outcomes also in pediatric population.

Background: vitamin D influences the immune system and the inflammatory response. It is known that vitamin D supplementation reduces the risk of acute respiratory tract infection. In the last two years, many researchers have investigated vitamin D's role in the pathophysiology of COVID-19 disease. Results: the findings obtained from clinical trials and systematic reviews highlight that most patients with COVID-19 have decreased vitamin D levels and low levels of vitamin D increase the risk of severe disease. This evidence seems to be also confirmed in the pediatric population. Conclusions: further studies (systematic review and meta-analysis) conducted on children are needed to confirm that vitamin D affects COVID-19 outcomes and to determine the effectiveness of supplementation and the appropriate dose, duration and mode of administration.

Associations Between Gastrointestinal Symptoms and COVID-19 Severity Outcomes Based on a Propensity Score-Weighted Analysis of a Nationwide Cohort.

Background and Aims: Gastrointestinal (GI) symptoms are well-recognized manifestations of coronavirus disease 2019 (COVID-19). Our primary objective was to evaluate the association between GI symptoms and COVID-19 severity. Methods: In this nationwide cohort of US veterans, we evaluated GI symptoms (nausea/vomiting/diarrhea) reported 30 days before and including the date of positive SARS-CoV-2 testing (March 1, 2020, to February 20, 2021). All patients had ≥1 year of prior baseline data and ≥60 days follow-up relative to the test date. We used propensity score (PS)-weighting to balance covariates in patients with vs without GI symptoms. The primary composite outcome was severe COVID-19, defined as hospital admission, intensive care unit admission, mechanical ventilation, or death within 60 days of positive testing. Results: Of 218,045 SARS-CoV-2 positive patients, 29,257 (13.4%) had GI symptoms. After PS weighting, all covariates were balanced. In the PS-weighted cohort, patients with vs without GI symptoms had severe COVID-19 more often (29.0% vs 17.1%; P < .001). When restricted to hospitalized patients (14.9%; n=32,430), patients with GI symptoms had similar frequencies of intensive care unit admission and mechanical ventilation compared with patients without symptoms. There was a significant age interaction; among hospitalized patients aged ≥70 years, lower COVID-19-associated mortality was observed in patients with vs without GI symptoms, even after accounting for COVID-19-specific medical treatments. Conclusion: In the largest integrated US health care system, SARS-CoV-2-positive patients with GI symptoms experienced severe COVID-19 outcomes more often than those without symptoms. Additional research on COVID-19-associated GI symptoms may inform preventive efforts and interventions to reduce severe COVID-19.

Latent class analysis: an innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the intensive care unit.

Objective: The aim of this study was to identify clinical and laboratory phenotype distribution patterns and their usefulness as prognostic markers in COVID-19 patients admitted to the intensive care unit (ICU) at Tygerberg Hospital, Cape Town. Methods and results: A latent class analysis (LCA) model was applied in a prospective, observational cohort study. Data from 343 COVID-19 patients were analysed. Two distinct phenotypes (1 and 2) were identified, comprising 68.46% and 31.54% of patients, respectively. The phenotype 2 patients were characterized by increased coagulopathy markers (D-dimer, median value 1.73 ng/L vs 0.94 ng/L; p < 0.001), end-organ dysfunction (creatinine, median value 79 µmol/L vs 69.5 µmol/L; p < 0.003), under-perfusion markers (lactate, median value 1.60 mmol/L vs 1.20 mmol/L; p < 0.001), abnormal cardiac function markers (median N-terminal pro-brain natriuretic peptide (NT-proBNP) 314 pg/ml vs 63.5 pg/ml; p < 0.001 and median high-sensitivity cardiac troponin (Hs-TropT) 39 ng/L vs 12 ng/L; p < 0.001), and acute inflammatory syndrome (median neutrophil-to-lymphocyte ratio 15.08 vs 8.68; p < 0.001 and median monocyte value 0.68 × 109/L vs 0.45 × 109/L; p < 0.001). Conclusion: The identification of COVID-19 phenotypes and sub-phenotypes in ICU patients could help as a prognostic marker in the day-to-day management of COVID-19 patients admitted to the ICU.

Machine learning and comorbidity network analysis for hospitalized patients with COVID-19 in a city in Southern Brazil.

The large amount of data generated during the COVID-19 pandemic requires advanced tools for the long-term prediction of risk factors associated with COVID-19 mortality with higher accuracy. Machine learning (ML) methods directly address this topic and are essential tools to guide public health interventions. Here, we used ML to investigate the importance of demographic and clinical variables on COVID-19 mortality. We also analyzed how comorbidity networks are structured according to age groups. We conducted a retrospective study of COVID-19 mortality with hospitalized patients from Londrina, Parana, Brazil, registered in the database for severe acute respiratory infections (SIVEP-Gripe), from January 2021 to February 2022. We tested four ML models to predict the COVID-19 outcome: Logistic Regression, Support Vector Machine, Random Forest, and XGBoost. We also constructed a comorbidity network to investigate the impact of co-occurring comorbidities on COVID-19 mortality. Our study comprised 8358 hospitalized patients, of whom 2792 (33.40%) died. The XGBoost model achieved excellent performance (ROC-AUC = 0.90). Both permutation method and SHAP values highlighted the importance of age, ventilatory support status, and intensive care unit admission as key features in predicting COVID-19 outcomes. The comorbidity networks for old deceased patients are denser than those for young patients. In addition, the co-occurrence of heart disease and diabetes may be the most important combination to predict COVID-19 mortality, regardless of age and sex. This work presents a valuable combination of machine learning and comorbidity network analysis to predict COVID-19 outcomes. Reliable evidence on this topic is crucial for guiding the post-pandemic response and assisting in COVID-19 care planning and provision.

Jordanian nurses' attitudes toward using electronic health records during COVID-19 pandemic.

Electronic health records (EHRs) have proven their effectiveness during the coronavirus disease (COVID-19) pandemic. However, successful implementation of EHRs requires assessing nurses' attitudes as they are considered the first line in providing direct care for patients. This study assessed Jordanian nurses' attitudes and examined factors that affect nurses' attitudes toward using EHRs. A cross-sectional, correlational design was used. A convenient sample of 130 nurses was recruited from three major public hospitals in Jordan. All Participants completed the Nurses' attitudes Towards Computerization (NATC) Questionnaire. The overall nurses' attitude was positive; the mean was 61.85 (SD = 10.97). Findings revealed no significant relationship between nurses' attitudes toward using EHRs and nurses' age, gender, education level, previous computer skills experience, years of work experience, and years of dealing with EHRs. However, the work unit was found to have a significant correlation with nurses' attitudes toward using EHRs. Therefore, nurse administrators should arrange for the conduct of educational workshops and continuous training programs considering the needs of the nurses.