Factors associated with poor outcomes among hospitalized patients with COVID-19: Experience from a MERS-CoV referral hospital

Effectiveness of COVID-19 vaccines against ICU admission during Omicron surge in Saudi Arabia: a nationwide retrospective cohort study

INTRODUCTION

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused significant economic damage and forced a slew of limitations to be placed by regulatory bodies worldwide. As the SARS-CoV-2 virus continuously mutates over time, it's crucial to understand how well the vaccines are effective against a new variant.

OBJECTIVES

To measure COVID-19 vaccine effectiveness against ICU admission with the Omicron variant in Saudi Arabia regions.

METHODS AND MATERIALS

A retrospective cohort study was conducted of vaccinated and non-vaccinated individuals who tested positive during Omicron dominant period (Jan 1, 2020- Jun 11, 2022). We used a Cox proportional hazards model based on calendar time to assess the vaccine's effectiveness while controlling for age and gender.

RESULTS

A total of 14103 individuals who were divided into fully vaccinated included 8388 (59.5%) individuals, partially vaccinated included 1851 (13.5%) individuals, and un-vaccinated included 3864 (27.4%) individuals. Higher age was associated with a higher risk of ICU admission (HR = 1.03, 95% CI: 1.02, 1.04). Three doses are associated with a lower risk of ICU admission compared to the single dose (HR = 0.09, 95% CI: 0.04, 0.20). By studying the distribution of Omicron infection among different regions, Al-Madinah Al-Monawarah had the highest proportion at 60.23 per 100,000 population (95% CI: 57.05, 63.53). In contrast, Al-jouf had the lowest proportion at 4.51 per 100,000 population (95%CI: 2.891, 6.713). The vaccination status was significantly different in different regions, as the highest proportion of fully vaccinated participants inhabited in Tabouk region, with 71.8% of its cases. Out of all regions, Najran had the highest proportion of ICU admission among Omicron cases with 20% (95% CI: 9.94%, 34.22%). While the lowest rates existed in Riyadh with 0.86% (95%CI: 0.61%, 1.17%).

CONCLUSION

We found that a booster significantly enhanced protection against severe COVID-19. The partially vaccinated and unvaccinated participants were at significantly higher risk of ICU admission when compared to the fully vaccinated participants. Furthermore, in future, it is worth investigating the effectiveness of a booster when other potential factors (e.g., region, comorbidities, etc.) are included, particularly among future variants of COVID-19.

Prevalence of secondary infections and association with mortality rates of hospitalized COVID-19 patients

BACKGROUND

ICU and other patients hospitalized with corona-virus disease 2019 (COVID-19) are more susceptible to secondary infections. Undetected secondary infections tend to have a severe clinical impact, associated with prolonged hospitalization and higher rates of inpatient mortality.

OBJECTIVES

Estimate the prevalence of secondary infections, determine the frequency of microbial species detected at different body sites, and measure the association between secondary infections and outcomes among hospitalized COVID-19 patients.

DESIGN

Cross-sectional analytical study.

SETTING

Tertiary care center in Riyadh PATIENTS AND METHODS: Data were collected through retrospective chart review of hospitalized COVID-19 patients >18 years old from March 2020 until May 2022 at King Saud University Medical City (27 months). Rates of secondary infections among hospitalized COVID-19 patients were described and data on clinical outcomes (intensive care admission, invasive management procedures and mortality) was collected.

MAIN OUTCOME MEASURES

Features and rates of infection and mortality.

SAMPLE SIZE

260 RESULTS: In total, 24.2% of the study population had secondary infections. However, only 68.8% of patients had secondary infection testing, from which 35.2% had a confirmed secondary infection. These patients had a significantly higher prevalence of diabetes mellitus (P<.0001) and cardiovascular diseases (P=.001). The odds of ICU admissions (63.3%) among secondarily infected patients was 8.4 times higher compared to patients with only COVID-19 infection (17.3%). Secondarily infected patients were more likely to receive invasive procedures (OR=5.068) and had a longer duration of hospital stay compared to COVID-19 only patients. Overall mortality was 16.2%, with a predominantly higher proportion among those secondarily infected (47.6% vs 6.1%) (OR=14.015). Bacteria were the most commonly isolated organisms, primarily from blood (23.3%), followed by fungal isolates, which were mostly detected in urine (17.2%). The most detected organism was Candida albicans (17.2%), followed by Escherichia coli (9.2%), Klebsiella pneumoniae (9.2%) and Pseudomonas aeruginosa (9.2%).

CONCLUSION

Secondary infections were prevalent among hospitalized COVID-19 patients. Secondarily infected patients had longer hospital stay, higher odds of ICU admission, mortality, and invasive procedures.

LIMITATION

Single-center study, retrospective design and small sample size.

CONFLICT OF INTEREST

None.

Trends in the morbidity and mortality of coronavirus disease 2019 in different ethnic groups and gender in a large Brazilian city

As the coronavirus disease 2019 (COVID-19) outbreak spread, evidence has emerged that gender and race would bear a disproportionate impact on the morbimortality of COVID-19. Here, we conducted a retrospective observational study using the TabNet/Departamento de informática do sistema único de saúde platform of the city of São Paulo. COVID-19 records from March 2020 through December 2021 were included, and we evaluated the temporal trends of confirmed cases and case fatality rate by gender and ethnicity. Statistical analysis was performed using the R-software and BioEstat-software, considering p < 0.05 significant. From March/2020 to December/2021, 1 315 160 COVID-19 confirmed cases were recorded (57.1% females), and 2973 deaths were due to COVID-19. Males presented higher median mortality (0.44% vs. 0.23%; p < 0.05) and intensive care unit (ICU) admission rates (0.34% vs. 0.20%; p < 0.05). Men were also associated with a higher risk of death (risk ratio [RR] = 1.28; p < 0.05) and a higher chance of requiring ICU care (RR = 1.29; p < 0.05). Black ethnicity was associated with a higher risk of death (RR = 1.19; p < 0.05). White patients were more likely to require ICU admission (RR = 1.13; p < 0.05), whereas Browns were associated with a protective effect (RR = 0.86; p < 0.05). Furthermore, men presented a higher chance of death than women across the three major ethnic groups: Whites (RR = 1.33; p < 0.05), Blacks (RR = 1.24; p < 0.05), and Browns (RR = 1.35; p < 0.05). In this study of COVID-19 in São Paulo, men were associated with worse outcomes, including in the three major ethnicities in the population. Blacks exhibited a higher risk of death, Whites were more likely to require intensive care, and Browns were at protection from ICU hospitalization.

Ethical uncertainty and COVID-19: exploring the lived experiences of senior physicians at a major medical centre

Given the wide-reaching and detrimental impact of COVID-19, its strain on healthcare resources, and the urgent need for-sometimes forced-public health interventions, thorough examination of the ethical issues brought to light by the pandemic is especially warranted. This paper aims to identify some of the complex moral dilemmas faced by senior physicians at a major medical centre in Saudi Arabia, in an effort to gain a better understanding of how they navigated ethical uncertainty during a time of crisis. This qualitative study uses a semistructured interview approach and reports the findings of 16 interviews. The study finds that participants were motivated by a profession-based moral obligation to provide care during the toughest and most uncertain times of the pandemic. Although participants described significant moral dilemmas during their practice, very few identified challenges as ethical in nature, and in turn, none sought formal ethics support. Rather, participants took on the burden of resolving ethical challenges themselves-whenever possible-rationalising oft fraught decisions by likening their experiences to wartime action or by minimising attention to the moral. In capturing these accounts, this paper ultimately contemplates what moral lessons can, and must be, learnt from this experience.

Deep Learning-Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs

Accurate estimation of mortality and time to death at admission for COVID-19 patients is important and several deep learning models have been created for this task. However, there are currently no prognostic models which use end-to-end deep learning to predict time to event for admitted COVID-19 patients using chest radiographs and clinical data. We retrospectively implemented a new artificial intelligence model combining DeepSurv (a multiple-perceptron implementation of the Cox proportional hazards model) and a convolutional neural network (CNN) using 1356 COVID-19 inpatients. For comparison, we also prepared DeepSurv only with clinical data, DeepSurv only with images (CNNSurv), and Cox proportional hazards models. Clinical data and chest radiographs at admission were used to estimate patient outcome (death or discharge) and duration to the outcome. The Harrel's concordance index (c-index) of the DeepSurv with CNN model was 0.82 (0.75-0.88) and this was significantly higher than the DeepSurv only with clinical data model (c-index = 0.77 (0.69-0.84), p = 0.011), CNNSurv (c-index = 0.70 (0.63-0.79), p = 0.001), and the Cox proportional hazards model (c-index = 0.71 (0.63-0.79), p = 0.001). These results suggest that the time-to-event prognosis model became more accurate when chest radiographs and clinical data were used together.

Artificial intelligence-based model for COVID-19 prognosis incorporating chest radiographs and clinical data; a retrospective model development and validation study

OBJECTIVES

The purpose of this study was to develop an artificial intelligence-based model to prognosticate COVID-19 patients at admission by combining clinical data and chest radiographs.

METHODS

This retrospective study used the Stony Brook University COVID-19 dataset of 1384 inpatients. After exclusions, 1356 patients were randomly divided into training (1083) and test datasets (273). We implemented three artificial intelligence models, which classified mortality, ICU admission, or ventilation risk. Each model had three submodels with different inputs: clinical data, chest radiographs, and both. We showed the importance of the variables using SHapley Additive exPlanations (SHAP) values.

RESULTS

The mortality prediction model was best overall with area under the curve, sensitivity, specificity, and accuracy of 0.79 (0.72-0.86), 0.74 (0.68-0.79), 0.77 (0.61-0.88), and 0.74 (0.69-0.79) for the clinical data-based model; 0.77 (0.69-0.85), 0.67 (0.61-0.73), 0.81 (0.67-0.92), 0.70 (0.64-0.75) for the image-based model, and 0.86 (0.81-0.91), 0.76 (0.70-0.81), 0.77 (0.61-0.88), 0.76 (0.70-0.81) for the mixed model. The mixed model had the best performance (p value < 0.05). The radiographs ranked fourth for prognostication overall, and first of the inpatient tests assessed.

CONCLUSIONS

These results suggest that prognosis models become more accurate if AI-derived chest radiograph features and clinical data are used together.

ADVANCES IN KNOWLEDGE

This AI model evaluates chest radiographs together with clinical data in order to classify patients as having high or low mortality risk. This work shows that chest radiographs taken at admission have significant COVID-19 prognostic information compared to clinical data other than age and sex.

Rapid systematic review of respiratory rate as a vital sign of clinical deterioration in COVID-19

OBJECTIVES

This meta-analysis aimed to establish a clinical evidence base for respiratory rate (RR) as a single predictor of early-onset COVID-19. The review also looked to determine the practical implementation of mobile respiratory rate measuring devices where information was available.

METHODS

We focused on domestic settings with older adults. Relevant studies were identified through MEDLINE, Embase, and CENTRAL databases. A snowballing method was also used. Articles published from the beginning of the COVID-19 pandemic (2019) until Feb 2022 were selected. Databases were searched for terms related to COVID-19 and respiratory rate measurements in domestic patients.

RESULTS

A total of 2,889 articles were screened for relevant content, of which 60 full-text publications were included. We compared the Odds Ratios and statistically significant results of both vital signs.

CONCLUSION

Multinational studies across dozens of countries have shown respiratory rate to have predictive accuracy in detecting COVID-19 deterioration. However, considerable variability is present in the data, making it harder to be sure about the effects. There is no meaningful difference in data quality in terms of variability (95% CI intervals) between vital signs as predictors of decline in COVID-19 patients. Contextual and economic factors will likely determine the choice of measurement used.

COVID-19 vaccine had a significant positive impact on patients with SARS-COV-2 during the third (Omicron) wave in Saudi Arabia

INTRODUCTION

The third (Omicron) wave had caused significant increase in the number of COVID-19 cases around the globe. The severity of the disease dependeds on the extent of the vaccination status.

METHODS

This is a retrospective study of infected COVID-19 patients during the third (Omicron) wave in a hospital in Saudi Arabia.

RESULTS

A total of 400 patients were included with 220 (55 %) males and 180 (45 %) females, and a mean age (+/- SD) of 36.34 + 16.47 years. The most common presenting symptoms were: sore throat 159 (39.8 %), cough 158 (39.5 %), fever 132 (33 %), headache 122 (30.5 %), and muscle ache 124 (31%). There was no difference in underlying conditions, signs and symptoms between males and females apart from the occurrence of sore throat with an OR of 2.014 (95 % CI: 1.103-3.677, P = 0.023) and need of hospitalization OR 2.457 (95 % CI: 1.168-5.167, P value =.018) in a binary logistic regression comparison. The need for hospitalization was inversely related to the number of COVID-19 vaccination doses. The rate of admission was 8 (72.7 %), 34 (12 %), 4 (5.4 %) for one, two, and three doses of COVID-19 vaccine, respectively (P < 0.0001). Of all the patients, 14 (3.5 %) and 8 (2 %) required intensive care (ICU) admission and mechanical ventilation, respectively. The median Ct-value of SARS-CoV-2 was higher in those who had 2 or 3 doses compared to those who had one dose of the COVID-19 vaccine, but the difference did not reach statistical significance. None of the included patients died during the study period.

CONCLUSION

Omicron variant symptoms among infected patients are generally milder compared to other variants. Prior COVID-19 vaccination may limit disease severity and need for hospitalization.

Comparison of Hospital Readmission and Mortality between COVID-19 and Pneumonia Patients

Coronavirus disease 2019 (COVID-19) survivors can have lasting signs and symptoms, including various organ damage, indicating that COVID-19 can be a chronic illness. The current study aims to compare the 30-day hospital readmission and death rate of patients admitted to the hospital with COVID-19 and pneumonia due to other causes. A retrospective cohort study was conducted using data from the Saudi National Guard Health Affairs (NGHA). Records of patients admitted with COVID-19 between 1 March 202 and 31 December 2020 (n = 3597) and pneumonia during 2017 and 2019 (n = 6324) were retrieved and analyzed. We compared the likelihood of 30-day hospital readmission, intensive care unit (ICU) admission, and death between the two groups. Compared with the control group, COVID-19 patients had higher odds of 30-day readmission (odds ratio 1.90, 95% confidence interval 1.61–2.24), higher risk of ICU transfer (hazard ratio 1.85, 95% confidence interval 1.65–2.07), more extended hospital stay (7 vs. 4 days), but less risk of death (hazard ratio 0.18, 95% confidence interval 0.14–0.24). The findings that hospital readmission was higher in COVID-19 recovered patients than in other pneumonia patients inform the current discussion about readmission and death in COVID-19 patients.

Carbapenem use correlates with percentage of patients with COVID-19 in intensive care units

BACKGROUND

The first wave of COVID-19 pandemic may have significantly impacted antimicrobial consumption in hospitals. The objective of this study was to assess the evolution of carbapenem consumption and describe the implemented measures during the first year of the COVID-19 pandemic.

METHODS

We calculated carbapenem consumption for all the hospital and for intensive care units (ICU) for three periods: baseline (before COVID-19 cases, January 2019-February 2020), and the period of COVID-19 cases as a pre-intervention (March-August 2020) and a post-intervention phase (September 2020-December 2021).

RESULTS

During the study period, the percentage of admitted COVID-19 patients increased in the months of April-August of 2020 (pre-intervention period) from 5 to 26% of total admitted patients. The consumption of carbapenems (DDD/1000 patient days) increased from a mean of 67.1 at baseline to 142.9 pre-intervention. In ICUS, there was an increase in the mean from 125.7 to 240.8 DDD/1000 patient days. After interventions, the DDD/1000 patient days decreased by 49.5% overall the hospital and by 36% in ICUs. For the post-intervention period, there was a correlation between COVID-19 cases and carbapenem usage in the ICU but not the overall hospital.

CONCLUSION

An increase in the antimicrobial consumption during the first wave of COVID-19 pandemic was noticed, especially in the ICU. Antimicrobial stewardship programs are essential to reduce consumption rate.

Predictors of Poor Outcome among Critically Ill COVID-19 Patients: A Nationally Representative Sample of the Saudi Arabian Population

The outbreak and continuing impact of COVID-19 have significantly increased the rates of hospitalization and admissions to intensive care units (ICU). This study evaluates clinical outcomes in critically ill patients and investigates variables tied to poor prognosis. A secondary database analysis was conducted to investigate the predictors of poor outcome among critically ill COVID-19 patients in Saudi Arabia. Multivariable logistic regression analysis was used to assess the association between various demographic characteristics, comorbidities, and COVID-19 symptoms and patients’ poor prognosis, as a composite outcome. A total of 2257 critically ill patients were identified (male (71.8%), and elderly (37.3%)). The mortality rate was 50.0%, and the composite poor outcome was 68.4%. The predictors of poor outcome were being elderly (OR = 4.79, 95%CI 3.19−7.18), obesity (OR = 1.43, 95%CI 1.1−1.87), having a severe or critical case at admission (OR = 6.46, 95%CI 2.34−17.8; OR = 22.3, 95%CI 11.0−45, respectively), and some signs and symptoms of COVID-19 such as shortness of breath, feeling fatigued or headache, respiratory rate ≥ 30/min, PaO2/FiO2 ratio < 300, and altered consciousness. In conclusion, identifying high-risk populations that are expected to have a poor prognosis based on their criteria upon admission helps policymakers and practitioners better triage patients when faced with limited healthcare resources.

Orthopaedic, trauma surgery, and Covid-2019 pandemic: clinical panorama and future prospective in Europe

Purpose

This study investigated the impact of the Covid-19 pandemic in Europe on consultations, surgeries, and traumas in the field of orthopaedic and trauma surgery. Strategies to resume the clinical activities were also discussed.

Methods

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the 2020 PRISMA statement. All the comparative studies reporting data on the impact of Covid-19 in the field of orthopaedic and trauma surgery in Europe were accessed. Only comparative clinical studies which investigated the year 2020 versus 2019 were eligible.

Results

57 clinical investigations were included in the present study. Eight studies reported a reduction of the orthopaedic consultations, which decreased between 20.9 and 90.1%. Seven studies reported the number of emergency and trauma consultations, which were decreased between 37.7 and 74.2%. Fifteen studies reported information with regard to the reasons for orthopaedic and trauma admissions. The number of polytraumas decreased between 5.6 and 77.1%, fractures between 3.9 and 63.1%. Traffic accidents admissions dropped by up to 88.9%, and sports-related injuries dropped in a range of 59.3% to 100%. The overall reduction of the surgical interventions ranged from 5.4 to 88.8%.

Conclusion

The overall trend of consultations, surgeries, and rate of traumas and fragility fractures appear to decrease during the 2020 European COVID pandemic compared to the pre-pandemic era. Given the heterogeneities in the clinical evidence, results from the present study should be considered carefully.

Level of evidence

Level IV, systematic review.

Post-COVID-19 syndrome: assessment of short- and long-term post-recovery symptoms in recovered cases in Saudi Arabia

Introduction

Recent studies investigated the endurance of symptoms and occurrence of complications three months after SARS-CoV-2 infection. This study aims to examine the prevalence, variation, and severity of continual symptoms in the post‐COVID-19 using a single-center questionnaire.

Methods

The questionnaire was distributed among population in Saudi Arabia who recovered from COVID‐19 between April 1, 2020 and December 31, 2021.

Results

A total of 744 participants completed the questionnaire, 318 (42.8%) recovered less than 3 months, 75 (10.1%) recovered 3–6 months, while 351 (47.2%) recovered more than 6 months. About half of the participants 353 (47.5%) had incessant symptoms and of those patients, more than half had two or more symptoms. Common symptoms included fatigue 189 (25.4%), headache 118 (15.9%), and myalgia 63 (8.5%). Of the participants, 189 (21.4%) experienced continual symptoms including anxiety in 98 (13.2%) and depression in 70 (9.5%).

Conclusion

The current study showed a high proportion of individuals with long-COVID-19 symptoms. Thus, proper assessment of the individuals in the post-recovery period can guide the patients to the relevant clinics for rehabilitation. Moreover, there is a great importance to decrease COVID-19 infection, populations should be targeted to boost vaccine efficiency.

Clinical Presentation and Outcome of Hospitalized Patients With COVID-19 in the First and Second Waves in Saudi Arabia

Introduction

The world had witnessed the occurrence of multiple waves of the SARS-CoV-2. Data comparing the clinical characteristics and outcomes of hospitalized patients in Saudi Arabia during the first and second waves are lacking. This study compares the characteristics and the outcomes of patients in these 2 waves.

Methods

This is a retrospective case series of hospitalized patients with confirmed SARS-CoV-2. We compared epidemiological, demographic, laboratory, and clinical data.

Results

The study included hospitalized patients admitted up to February 28, 2021 as the first wave and those admitted from March 1, 2021 as the second wave. There were 378 patients in the first wave and 241 patients in the second wave. Patients in the first wave were significantly younger (mean age and SD of 47.5 ± 20 vs 55.3 ± 18.2 years; p <0.001). In relation to symptoms, shortness of breath, wheezes, myalgia, tachypnea, and respiratory distress were significantly more common in the second wave than the first wave. On the other hand, sore throat was more common in the first wave than the second wave. Patients in the second wave had higher mean values of lymphocytes count, platelet counts, and ALT than those in the first wave. Patients in the first wave were more likely to receive antibiotics and antiviral therapy and had higher death rate (16.2% vs 8.4%; p = 0.001).

Conclusion

The study showed that patients in the second wave were younger and had a lower rate of death than the first wave.