A systematic review and meta-analysis of regional risk factors for critical outcomes of COVID-19 during early phase of the pandemic

Clinical-laboratory characteristics predictive of COVID-19 severity: a prospective hospital cohort, in Pernambuco, Northeast Brazil

OBJECTIVE

To describe the clinical-laboratory profile and analyze the factors associated with the severity of COVID-19.

METHODS

A prospective cohort study involving patients with COVID-19 admitted to a tertiary hospital in Recife, Brazil. All cases were confirmed by RT-PCR and classified according to severity criteria. A descriptive statistical analysis of the population's characteristics was conducted. Risk factors associated with the outcome of the case according to severity were analyzed by calculating the odds ratio (OR) using the general equation estimation (GEE) model.

RESULTS

Among the 75 cases included, 64% were female, and 62.7% were aged 65 years or older. The median length of stay was 9 days (6 - 14). Hypertension (65.3%) and Diabetes Mellitus (36%) were the most frequent comorbidities. Severe forms of COVID-19 constituted 41.3% of the sample. The factors associated with severity were a history of asthma (OR=4.58, 95%CI:1.13 - 18.7), report of anorexia (OR=1, 12, 95%CI:1.01-1.24), and laboratory changes that included elevated platelets (OR=1.00, 95% CI:1.00-1.01), elevated D'Dimer (OR=1, 26, 95% CI:1.04-1.52), elevated aspartate aminotransferase (OR=1.00, 95% CI:1.00-1.01), and gamma-glutamyl transferase (OR=1.22, IC95 %:0.98-1.51), hypernatremia (OR=1.31, 95%CI:1.12-1.52), and hyperkalemia (OR=1.21, 95% CI:1.04-1.41).

CONCLUSION

Multisystemic involvement with a tendency for thrombophilia, electrolyte disturbances, and hepatic aggression, reflected by laboratory changes, were factors associated with the severity of COVID-19.

Clinical outcomes and safety of remdesivir in hospitalized individuals with COVID-19, with or without severe renal impairment

BACKGROUND

The use of remdesivir in patients with coronavirus disease 2019 (COVID-19) and severe renal impairment has been approved; however, limited clinical data exist. Accordingly, we aimed to compare outcomes and adverse events associated with remdesivir in hospitalized patients with COVID-19, with and without severe renal impairment.

METHODS

Hospitalized patients with COVID-19 undergoing a 5-day remdesivir course at Taipei Veterans General Hospital from April 1 to July 31, 2022, were enrolled. Comparative analysis of outcomes and safety between patients with or without severe renal impairment (estimated glomerular filtration rate of < 30 mL/min per 1.73 m2) were conducted. Prognostic factors associated with 28-day mortality in patients with severe renal impairment were investigated using logistic regression analysis.

RESULTS

A total of 671 hospitalized patients, including 132 patients with severe renal impairment, who received a 5-day course of remdesivir were analyzed. The 28-day mortality was higher in patients with severe renal impairment than in patients without severe renal impairment (15.2% vs. 7.8%). The proportion of patients with acute kidney injury (AKI) and deteriorated liver function after completing remdesivir therapy was similar between the patients with and without severe renal impairment, and the recovery rate of AKI was similar in both groups. The sequential organ failure assessment score was an independent factor associated with 28-day mortality in patients with severe renal impairment.

CONCLUSIONS

Remdesivir was well-tolerated in hospitalized patients with COVID-19, regardless of renal function. Our findings support the recent recommendation to administer remdesivir in patients with severe renal impairment.

Type 1 interferon auto-antibodies are elevated in patients with decompensated liver cirrhosis

Patients with decompensated liver cirrhosis, in particular those classified as Childs-Pugh class C, are at increased risk of severe coronavirus disease-2019 (COVID-19) upon infection with severe acute respiratory coronavirus 2 (SARS-CoV-2). The biological mechanisms underlying this are unknown. We aimed to examine the levels of serum intrinsic antiviral proteins as well as alterations in the innate antiviral immune response in patients with decompensated liver cirrhosis. Serum from 53 SARS-CoV-2 unexposed and unvaccinated individuals, with decompensated liver cirrhosis undergoing assessment for liver transplantation, were screened using SARS-CoV-2 pseudoparticle and SARS-CoV-2 virus assays. The ability of serum to inhibit interferon (IFN) signalling was assessed using a cell-based reporter assay. Severity of liver disease was assessed using two clinical scoring systems, the Child-Pugh class and the MELD-Na score. In the presence of serum from SARS-CoV-2 unexposed patients with decompensated liver cirrhosis there was no association between SARS-CoV-2 pseudoparticle infection or live SARS-CoV-2 virus infection and severity of liver disease. Type I IFNs are a key component of the innate antiviral response. Serum from patients with decompensated liver cirrhosis contained elevated levels of auto-antibodies capable of binding IFN-α2b compared to healthy controls. High MELD-Na scores were associated with the ability of these auto-antibodies to neutralize type I IFN signalling by IFN-α2b but not IFN-β1a. Our results demonstrate that neutralizing auto-antibodies targeting IFN-α2b are increased in patients with high MELD-Na scores. The presence of neutralizing type I IFN-specific auto-antibodies may increase the likelihood of viral infections, including severe COVID-19, in patients with decompensated liver cirrhosis.

The impact of COVID-19 infection, the pandemic and its associated control measures on patients with Pompe disease

BACKGROUND

Patients with Pompe disease, a rare metabolic myopathy, were thought to be at increased risk of severe COVID-19 disease during the pandemic. In addition, the lockdown may have affected their regular treatment.

OBJECTIVE

To assess the perceived effect of COVID-19 infection and of the pandemic on the treatment, and physical and mental health of patients with Pompe disease.

METHODS

Patients with Pompe disease over 16 years of age participated in an international, cross-sectional, online survey (September 20, 2022-November 7, 2022). The questionnaire, available in eight languages, consisted of 89 questions divided into 3 parts: (A) severity of Pompe disease, (B) COVID-19 precautions and infection(s) and (C) effects of the COVID-19 pandemic.

RESULTS

Among 342 respondents, originating from 25 different countries, 47.6% experienced one or more COVID-19 infections. While most recovered within 4 weeks (69.7%) and only eight patients needed to be admitted to the hospital, 42.2% of patients experienced an impact of the infection on their overall condition, respiratory status and/or mobility status. More severely affected patients took more stringent control measures. The pandemic additionally caused interruptions in medical care in many patients (56.0%) and 17.2% of patients experienced interruptions of enzyme replacement therapy. The pandemic also affected many patients' disease severity (27.7%), mental health (55.4%) and feeling of loneliness (43.4%).

CONCLUSION

COVID-19 infection(s) and the pandemic affected the treatment, physical health and mental health of patients with Pompe disease, emphasizing the importance of continued patient centered care during a difficult time such as the COVID-19 pandemic.

Machine learning-driven development of a disease risk score for COVID-19 hospitalization and mortality: a Swedish and Norwegian register-based study

Aims

To develop a disease risk score for COVID-19-related hospitalization and mortality in Sweden and externally validate it in Norway.

Method

We employed linked data from the national health registries of Sweden and Norway to conduct our study. We focused on individuals in Sweden with confirmed SARS-CoV-2 infection through RT-PCR testing up to August 2022 as our study cohort. Within this group, we identified hospitalized cases as those who were admitted to the hospital within 14 days of testing positive for SARS-CoV-2 and matched them with five controls from the same cohort who were not hospitalized due to SARS-CoV-2. Additionally, we identified individuals who died within 30 days after being hospitalized for COVID-19. To develop our disease risk scores, we considered various factors, including demographics, infectious, somatic, and mental health conditions, recorded diagnoses, and pharmacological treatments. We also conducted age-specific analyses and assessed model performance through 5-fold cross-validation. Finally, we performed external validation using data from the Norwegian population with COVID-19 up to December 2021.

Results

During the study period, a total of 124,560 individuals in Sweden were hospitalized, and 15,877 individuals died within 30 days following COVID-19 hospitalization. Disease risk scores for both hospitalization and mortality demonstrated predictive capabilities with ROC-AUC values of 0.70 and 0.72, respectively, across the entire study period. Notably, these scores exhibited a positive correlation with the likelihood of hospitalization or death. In the external validation using data from the Norwegian COVID-19 population (consisting of 53,744 individuals), the disease risk score predicted hospitalization with an AUC of 0.47 and death with an AUC of 0.74.

Conclusion

The disease risk score showed moderately good performance to predict COVID-19-related mortality but performed poorly in predicting hospitalization when externally validated.

Determinants of SARS-CoV-2 nasopharyngeal testing in a rural community sample susceptible of first infection: the CHRIS COVID-19 study

To characterize COVID-19 epidemiology, numerous population-based studies have been undertaken to model the risk of SARS-CoV-2 infection. Less is known about what may drive the probability to undergo testing. Understanding how much testing is driven by contextual or individual conditions is important to delineate the role of individual behavior and to shape public health interventions and resource allocation. In the Val Venosta/Vinschgau district (South Tyrol, Italy), we conducted a population-representative longitudinal study on 697 individuals susceptible to first infection who completed 4,512 repeated online questionnaires at four-week intervals between September 2020 and May 2021. Mixed-effects logistic regression models were fitted to investigate associations of self-reported SARS-CoV-2 testing with individual characteristics (social, demographic, and biological) and contextual determinants. Testing was associated with month of reporting, reflecting the timing of both the pandemic intensity and public health interventions, COVID-19-related symptoms (odds ratio, OR:8.26; 95% confidence interval, CI:6.04-11.31), contacts with infected individuals within home (OR:7.47, 95%CI:3.81-14.62) or outside home (OR:9.87, 95%CI:5.78-16.85), and being retired (OR:0.50, 95%CI:0.34-0.73). Symptoms and next within- and outside-home contacts were the leading determinants of swab testing predisposition in the most acute phase of the pandemics. Testing was not associated with age, sex, education, comorbidities, or lifestyle factors. In the study area, contextual determinants reflecting the course of the pandemic were predominant compared to individual sociodemographic characteristics in explaining the SARS-CoV-2 probability of testing. Decision makers should evaluate whether the intended target groups were correctly prioritized by the testing campaign.

Validity of prognostic models of critical COVID-19 is variable. A systematic review with external validation

OBJECTIVES

To identify prognostic models which estimate the risk of critical COVID-19 in hospitalized patients and to assess their validation properties.

STUDY DESIGN AND SETTING

We conducted a systematic review in Medline (up to January 2021) of studies developing or updating a model that estimated the risk of critical COVID-19, defined as death, admission to intensive care unit, and/or use of mechanical ventilation during admission. Models were validated in two datasets with different backgrounds (HM [private Spanish hospital network], n = 1,753, and ICS [public Catalan health system], n = 1,104), by assessing discrimination (area under the curve [AUC]) and calibration (plots).

RESULTS

We validated 18 prognostic models. Discrimination was good in nine of them (AUCs ≥ 80%) and higher in those predicting mortality (AUCs 65%-87%) than those predicting intensive care unit admission or a composite outcome (AUCs 53%-78%). Calibration was poor in all models providing outcome's probabilities and good in four models providing a point-based score. These four models used mortality as outcome and included age, oxygen saturation, and C-reactive protein among their predictors.

CONCLUSION

The validity of models predicting critical COVID-19 by using only routinely collected predictors is variable. Four models showed good discrimination and calibration when externally validated and are recommended for their use.

Post-COVID symptom profiles and duration in a global convalescent COVID-19 observational cohort: Correlations with demographics, medical history, acute COVID-19 severity and global region

Background

Post-COVID conditions are characterised by persistent symptoms that negatively impact quality of life after SARS-CoV-2 diagnosis. While post-COVID risk factors and symptoms have been extensively described in localised regions, especially in the global north, post-COVID conditions remain poorly understood globally. The global, observational cohort study HVTN 405/HPTN 1901 characterises the convalescent course of SARS-CoV-2 infection among adults in North and South America and Africa.

Methods

We categorised the cohort by infection severity (asymptomatic, symptomatic, no oxygen requirement (NOR), non-invasive oxygen requirement (NIOR), invasive oxygen requirement (IOR)). We applied a regression model to assess correlations of demographics, co-morbidities, disease severity, and concomitant medications with COVID-19 symptom persistence and duration across global regions.

Results

We enrolled 759 participants from Botswana, Malawi, South Africa, Zambia, Zimbabwe, Peru, and the USA a median of 51 (interquartile range (IQR) = 35-66) days post-diagnosis, from May 2020 to March 2021. 53.8% were female, 69.8% were 18-55 years old (median (md) = 44 years old, IQR = 33-58). Comorbidities included obesity (42.8%), hypertension (24%), diabetes (14%), human immunodeficiency virus (HIV) infection (11.6%) and lung disease (7.5%). 76.2% were symptomatic (NOR = 47.4%; NIOR = 22.9%; IOR = 5.8%). Median COVID-19 duration among symptomatic participants was 20 days (IQR = 11-35); 43.4% reported symptoms after COVID-19 resolution, 33.6% reported symptoms ≥30 days, 9.9% reported symptoms ≥60 days. Symptom duration correlated with disease severity (P < 0.001, NIOR vs NOR; P = 0.003, IOR vs NOR), lung disease (P = 0.001), race (P < 0.05, non-Hispanic Black vs White), and global region (P < 0.001). Prolonged viral shedding correlated with persistent abdominal pain (odds ratio (OR) = 5.51, P < 0.05) and persistent diarrhoea (OR = 6.64, P < 0.01).

Conclusions

Post-COVID duration varied with infection severity, race, lung disease, and region. Better understanding post-COVID conditions, including regionally-diverse symptom profiles, may improve clinical assessment and management globally.

Registration

Clinicaltrials.gov (#NCT04403880).

Development and external validation of prediction models for critical outcomes of unvaccinated COVID-19 patients based on demographics, medical conditions and dental status

Background

Multiple prediction models were developed for critical outcomes of COVID-19. However, prediction models using predictors which can be easily obtained in clinical practice and on dental status are scarce.

Aim

The study aimed to develop and externally validate prediction models for critical outcomes of COVID-19 for unvaccinated adult patients in hospital settings based on demographics, medical conditions, and dental status.

Methods

A total of 285 and 352 patients from two hospitals in the Netherlands were retrospectively included as derivation and validation cohorts. Demographics, medical conditions, and dental status were considered potential predictors. The critical outcomes (death and ICU admission) were considered endpoints. Logistic regression analyses were used to develop two models: for death alone and for critical outcomes. The performance and clinical values of the models were determined in both cohorts.

Results

Age, number of teeth, chronic kidney disease, hypertension, diabetes, and chronic obstructive pulmonary diseases were the significant independent predictors. The models showed good to excellent calibration with observed: expected (O:E) ratios of 0.98 (95%CI: 0.76 to 1.25) and 1.00 (95%CI: 0.80 to 1.24), and discrimination with shrunken area under the curve (AUC) values of 0.85 and 0.79, based on the derivation cohort. In the validation cohort, the models showed good to excellent discrimination with AUC values of 0.85 (95%CI: 0.80 to 0.90) and 0.78 (95%CI: 0.73 to 0.83), but an overestimation in calibration with O:E ratios of 0.65 (95%CI: 0.49 to 0.85) and 0.67 (95%CI: 0.52 to 0.84).

Conclusion

The performance of the models was acceptable in both derivation and validation cohorts. Number of teeth was an additive important predictor of critical outcomes of COVID-19. It is an easy-to-apply tool in hospitals for risk stratification of COVID-19 prognosis.

Adaptive immune response to BNT162b2 mRNA vaccine in immunocompromised adolescent patients

Protective immunity against COVID-19 is orchestrated by an intricate network of innate and adaptive anti-viral immune responses. Several vaccines have been rapidly developed to combat the destructive effects of COVID-19, which initiate an immunological cascade that results in the generation of neutralizing antibodies and effector T cells towards the SARS-CoV-2 spike protein. Developing optimal vaccine-induced anti-SARS- CoV-2 protective immunity depends on a fully competent immune response. Some evidence was gathered on the effects of vaccination outcomes in immunocompromised adult individuals. Nonetheless, protective immunity elicited by the Pfizer Biontech BNT162b2 vaccine in immunocompromised adolescents received less attention and was mainly focused on the antibody response and their neutralization potential. The overall immune response, including T-cell activities, was largely understudied. In this study, we characterized the immune response of vaccinated immunocompromised adolescents. We found that immunocompromised adolescents, which may fail to elicit a humoral response and develop antibodies, may still develop cellular T-cell immunity towards SARS-CoV-2 infections. Furthermore, most immunocompromised adolescents due to genetic disorders or drugs (Kidney and liver transplantation) still develop either humoral, cellular or both arms of immunity towards SARS-CoV-2 infections. We also demonstrate that most patients could mount a cellular or humoral response even after six months post 2nd vaccination. The findings that adolescents immunocompromised patients respond to some extent to vaccination are promising. Finally, they question the necessity for additional vaccination boosting regimens for this population who are not at high risk for severe disease, without further testing of their post-vaccination immune status.

Correlates of Coronavirus Disease 2019 Inpatient Mortality at a Southern California Community Hospital With a Predominantly Hispanic/Latino Adult Population

Background

Studies of inpatient coronavirus disease 2019 (COVID-19) mortality risk factors have mainly used data from academic medical centers or large multihospital databases and have not examined populations with large proportions of Hispanic/Latino patients. In a retrospective cohort study of 4881 consecutive adult COVID-19 hospitalizations at a single community hospital in Los Angeles County with a majority Hispanic/Latino population, we evaluated factors associated with mortality.

Methods

Data on demographic characteristics, comorbidities, laboratory and clinical results, and COVID-19 therapeutics were abstracted from the electronic medical record. Cox proportional hazards regression modeled statistically significant, independently associated predictors of hospital mortality.

Results

Age ≥65 years (hazard ratio [HR] = 2.66; 95% confidence interval [CI] = 1.90-3.72), male sex (HR = 1.31; 95% CI = 1.07-1.60), renal disease (HR = 1.52; 95% CI = 1.18-1.95), cardiovascular disease (HR = 1.45; 95% CI = 1.18-1.78), neurological disease (HR = 1.84; 95% CI = 1.41-2.39), D-dimer ≥500 ng/mL (HR = 2.07; 95% CI = 1.43-3.0), and pulse oxygen level <88% (HR = 1.39; 95% CI = 1.13-1.71) were independently associated with increased mortality. Patient household with (1) multiple COVID-19 cases and (2) Asian, Black, or Hispanic compared with White non-Hispanic race/ethnicity were associated with reduced mortality. In hypoxic COVID-19 inpatients, remdesivir, tocilizumab, and convalescent plasma were associated with reduced mortality, and corticosteroid use was associated with increased mortality.

Conclusions

We corroborate several previously identified mortality risk factors and find evidence that the combination of factors associated with mortality differ between populations.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Neurological Presentations in Patients with COVID-19 in Cytokine Storm

BACKGROUND

Coronavirus disease 2019 (COVID-19) infection causes a wide variety of neurological disorders by affecting both central and peripheral nervous systems. The cytokine storm (CS) has been blamed for the development of severe neurological disorders in COVID-19. However, the relationship between COVID-19 CS and neurological manifestations has not been adequately studied. Thus, we aimed to investigate the neurological presentations in patients with COVID-19 CS.

METHODS

The study population consisted of hospitalized moderate-to-severe COVID-19 patients. It was divided into two groups CS (36 patients, 29.3%) and non-CS (87 patients, 70.7%) based on significant clinical symptoms, elevated inflammatory marker levels, radiological findings, and interleukin-6 levels (IL-6).

RESULTS

The three most common neurological symptoms in the CS group were altered level of consciousness, headache, and unsteadiness. Altered level of consciousness was higher in the CS group (69.4%) than the non-CS group (25.3%) (p:0.001). The frequency of headache was comparable in both groups (p:0.186). The number of patients requiring intensive care unit and intubation was higher in the CS group (p:0.005 and p:0.001). The mortality rate in the CS group (38.9%) was higher than the non-CS group (8.0%) (p:0.001). IL-6, CRP, ferritin, neutrophil-lymphocyte ratio, procalcitonin, and D-dimer levels were higher in the CS group (for all p:0.001) while lymphocyte count was lower (p:0.003).

CONCLUSION

The most common neurological presentation in patients with CS was altered level of consciousness. The presence of CS was an independent risk factor for high mortality.

Cross-Clade Memory Immunity in Adults Following SARS-CoV-1 Infection in 2003

IMPORTANCE

Knowledge of the longevity and breath of immune response to coronavirus infection is crucial for the development of next-generation vaccines to control the COVID-19 pandemic.

OBJECTIVES

To determine the profile of SARS-CoV-2 antibodies among persons infected with the closely related virus, SARS-CoV-1, in 2003 (SARS03 survivors) and to characterize their antibody response soon after the first and second doses of COVID-19 vaccines.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study examined SARS-CoV-2 antibodies among SARS03 survivors compared with sex- and age-matched infection-naive controls. Participants received the COVID-19 vaccines between March 1 and September 30, 2021.

INTERVENTIONS

One of the 2 COVID-19 vaccines (inactivated [CoronaVac] or messenger RNA [BNT162b2]) available in Hong Kong. Two doses were given according to the recommended schedule. The vaccine type administered was known to both participants and observers.

MAIN OUTCOMES AND MEASURES

SARS-CoV-2 antibodies were measured prevaccination, 7 days after the first dose, and 14 days after the second dose.

RESULTS

Eighteen SARS03 adult survivors (15 women and 3 men; median age, 46.5 [IQR, 40.0-54.3] years) underwent prevaccination serologic examination. The vast majority retained a detectable level of antibodies that cross-reacted with SARS-CoV-2 (16 of 18 [88.9%] with nucleocapsid protein antibodies and 17 of 18 [94.4%] with receptor-binding domain of spike protein antibodies); a substantial proportion (11 of 18 [61.1%]) had detectable cross-neutralizing antibodies. Twelve SARS03 adult survivors (10 women and 2 men) underwent postvaccination serologic examination. At 7 days after the first dose of vaccine, SARS03 survivors mounted significantly higher levels of neutralizing antibodies compared with controls (median inhibition: 89.5% [IQR, 77.1%-93.7%] vs 13.9% [IQR, 11.8%-16.1%] for BNT162b2; 64.9% [IQR, 60.8%-69.5%] vs 13.4% [IQR, 9.5%-16.8%] for CoronaVac; P < .001 for both). At 14 days after the second dose, SARS03 survivors generated a broader antibody response with significantly higher levels of neutralizing antibodies against variants of concern compared with controls (eg, median inhibition against Omicron variant, 52.1% [IQR, 35.8%-66.0%] vs 14.7% [IQR, 2.5%-20.7%]; P < .001).

CONCLUSIONS AND RELEVANCE

The findings of this prospective cohort study suggest that infection with SARS-CoV-1 was associated with detectable levels of antibodies that cross-react and cross-neutralize SARS-CoV-2, which belongs to a distinct clade under the same subgenus Sarbecovirus. These findings support the development of broadly protective vaccines to cover sarbecoviruses that caused 2 devastating zoonotic outbreaks in humans over the last 2 decades.

Characteristics of hospitalised COVID-19 patients during the first two pandemic waves, Gauteng

Background

Gauteng province (GP) was one of the most affected provinces in the country during the first two pandemic waves in South Africa. We aimed to describe the characteristics of coronavirus disease 2019 (COVID-19) patients admitted in one of the largest quaternary hospitals in GP during the first two waves.

Objectives

Study objectives were to determine factors associated with hospital admission during the second wave and to describe factors associated with in-hospital COVID-19 mortality.

Method

Data from a national hospital-based surveillance system of COVID-19 hospitalisations were used. Multivariable logistic regression models were conducted to compare patients hospitalised during wave 1 and wave 2, and to determine factors associated with in-hospital mortality.

Results

The case fatality ratio was the highest (39.95%) during wave 2. Factors associated with hospitalisation included age groups 40–59 years (adjusted odds ratio [aOR]: 2.14, 95% confidence interval [CI]: 1.08–4.27), 60–79 years (aOR: 2.49, 95% CI: 1.23–5.02) and ≥ 80 years (aOR: 3.39, 95% CI: 1.35–8.49). Factors associated with in–hospital mortality included age groups 60–79 years (aOR: 2.55, 95% CI: 1.11–5.84) and ≥ 80 years (aOR: 5.66, 95% CI: 2.12–15.08); male sex (aOR: 1.56, 95% CI: 1.22–1.99); presence of an underlying comorbidity (aOR: 1.76, 95% CI: 1.37–2.26), as well as being admitted during post–wave 2 (aOR: 2.42, 95% CI: 1.33–4.42).

Conclusion

Compared to the recent omicron-driven pandemic waves characterised by lower admission rates and less disease severity among younger patients, COVID-19 in-hospital mortality during the earlier waves was associated with older age, being male and having an underlying comorbidity.

Contribution

This study showed how an active surveillance system can contribute towards identifying changes in disease trends.

Clinical presentation of COVID-19 at the time of testing and factors associated with pre-symptomatic cases in Cameroon

OBJECTIVES

To describe the clinical features at time of testing and explore factors associated with SARS-CoV-2 infection and pre-symptomatic cases in Cameroon.

METHODS

Data was collected on people in Cameroon who participated in COVID-19 testing by real-time reverse transcriptase-polymerase chain reaction between 1 March and 5 October 2020. After descriptive analysis, multivariate logistic regression was used to identify factors associated with SARS-CoV-2 infection and pre-symptomatic cases.

RESULTS

Of 85 206 test participants, 14 863 (17.4%) were infected with SARS-CoV-2. The median age for cases was 38.4 years (interquartile range 29.6-49.4); 6.1% were aged <19 years, and 6.3% were ≥65 years. Of these cases, 46.5% had at least one symptom/sign with a median time from illness onset to testing of 6 days (interquartile range 3-9). Cough (64.2%), headache (46.5%), fatigue/malaise (46.0%), shortness of breath (30.6%) and myalgia/arthralgia (25.6%) were the most commonly observed symptoms/signs. Pre-symptomatic SARS-CoV-2 infection was associated with age <50 years, being male and absence of comorbidities.

CONCLUSION

This study provides a comprehensive summary of the early clinical profile of SARS-CoV-2 infection during the first wave of COVID-19 in Cameroon, which was dominated by pre-symptomatic illness. These findings would be helpful for SARS-CoV-2 surveillance and control at a regional level.

Age-specific associations between underlying health conditions and hospitalisation, death and in-hospital death among confirmed COVID-19 cases: a multi-country study based on surveillance data, June to December 2020

Background

Underlying conditions are risk factors for severe COVID-19 outcomes but evidence is limited about how risks differ with age.

Aim

We sought to estimate age-specific associations between underlying conditions and hospitalisation, death and in-hospital death among COVID-19 cases.

Methods

We analysed case-based COVID-19 data submitted to The European Surveillance System between 2 June and 13 December 2020 by nine European countries. Eleven underlying conditions among cases with only one condition and the number of underlying conditions among multimorbid cases were used as exposures. Adjusted odds ratios (aOR) were estimated using 39 different age-adjusted and age-interaction multivariable logistic regression models, with marginal means from the latter used to estimate probabilities of severe outcome for each condition–age group combination.

Results

Cancer, cardiac disorder, diabetes, immunodeficiency, kidney, liver and lung disease, neurological disorders and obesity were associated with elevated risk (aOR: 1.5–5.6) of hospitalisation and death, after controlling for age, sex, reporting period and country. As age increased, age-specific aOR were lower and predicted probabilities higher. However, for some conditions, predicted probabilities were at least as high in younger individuals with the condition as in older cases without it. In multimorbid patients, the aOR for severe disease increased with number of conditions for all outcomes and in all age groups.

Conclusion

While supporting age-based vaccine roll-out, our findings could inform a more nuanced, age- and condition-specific approach to vaccine prioritisation. This is relevant as countries consider vaccination of younger people, boosters and dosing intervals in response to vaccine escape variants.

A Machine Learning Model for Predicting Hospitalization in Patients with Respiratory Symptoms during the COVID-19 Pandemic

A machine learning approach is a useful tool for risk-stratifying patients with respiratory symptoms during the COVID-19 pandemic, as it is still evolving. We aimed to verify the predictive capacity of a gradient boosting decision trees (XGboost) algorithm to select the most important predictors including clinical and demographic parameters in patients who sought medical support due to respiratory signs and symptoms (RAPID RISK COVID-19). A total of 7336 patients were enrolled in the study, including 6596 patients that did not require hospitalization and 740 that required hospitalization. We identified that patients with respiratory signs and symptoms, in particular, lower oxyhemoglobin saturation by pulse oximetry (SpO₂) and higher respiratory rate, fever, higher heart rate, and lower levels of blood pressure, associated with age, male sex, and the underlying conditions of diabetes mellitus and hypertension, required hospitalization more often. The predictive model yielded a ROC curve with an area under the curve (AUC) of 0.9181 (95% CI, 0.9001 to 0.9361). In conclusion, our model had a high discriminatory value which enabled the identification of a clinical and demographic profile predictive, preventive, and personalized of COVID-19 severity symptoms.

Severity and prognostic factors of SARS-CoV-2-induced pneumonia: The value of clinical and laboratory biomarkers and the A-DROP score

Introduction

Numerous clinical and laboratory scores that include C-reactive protein (CRP), D-dimer, ferritin, lactate dehydrogenase (LDH), interleukin 6 (IL-6), procalcitonin (PCT), blood urea nitrogen (BUN), creatinine levels and oxygenation (PaO₂ and SaO₂) have been used for the prognosis of COVID-19. In addition, composite scores have been developed for the assessment of general state and risk in community-acquired pneumonia (CAP) that may be applied for COVID-19 as well. In this study, we assessed severity and potential prognostic risk factors for unfavorable outcome among hospitalized COVID-19 patients. We also applied the A-DROP general scoring system used in CAP to COVID-19.

Patients and methods

Altogether 233 patients admitted to our center with COVID-19 were included in the study. Clinical status, several laboratory biomarkers described above, indicators of oxygenation were determined at hospital admission. We also applied the A-DROP composite scoring system that includes Age (≥ 70 years in males and ≥ 75 years in females), Dehydration (BUN ≥ 7.5 mmol/l), Respiratory failure (SaO₂ ≤ 90% or PaO₂ ≤ 60 mmHg), Orientation disturbance (confusion) and low blood Pressure (systolic BP ≤ 90 mmHg) to COVID-19.

Results

At the time of admission, most patients had elevated CRP, LDH, ferritin, D-dimer, and IL-6 levels indicating multisystemic inflammatory syndrome (MIS). Altogether 49 patients (21.2%) required admission to ICU, 46 (19.7%) needed ventilation and 40 patients (17.2%) died. In the binary analysis, admission to ICU, the need for ventilation and death were all significantly associated with the duration of hospitalization, history of hypertension or obesity, confusion/dizziness, as well as higher absolute leukocyte and neutrophil and lower lymphocyte counts, elevated CRP, PCT, LDH, ferritin, IL-6, BUN, and creatinine levels, low PaO₂ and SaO₂ and higher A-DROP score at the time of admission (p < 0.05).

Conclusion

Numerous laboratory biomarkers in addition to obesity, dizziness at the time of admission and the history of hypertension may predict the need for ICU admission and ventilation, as well as mortality in COVID-19. Moreover, A-DROP may be a suitable scoring system for the assessment of general health and disease outcome in COVID-19.

Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units

Purpose: To identify clinical phenotypes and biomarkers for best mortality prediction considering age, symptoms and comorbidities in COVID-19 patients with chronic neurological diseases in intensive care units (ICUs). Subjects and Methods: Data included 1252 COVID-19 patients admitted to ICUs in Cuba between January and August 2021. A k-means algorithm based on unsupervised learning was used to identify clinical patterns related to symptoms, comorbidities and age. The Stable Sparse Classifiers procedure (SSC) was employed for predicting mortality. The classification performance was assessed using the area under the receiver operating curve (AUC). Results: Six phenotypes using a modified v-fold cross validation for the k-means algorithm were identified: phenotype class 1, mean age 72.3 years (ys)-hypertension and coronary artery disease, alongside typical COVID-19 symptoms; class 2, mean age 63 ys-asthma, cough and fever; class 3, mean age 74.5 ys-hypertension, diabetes and cough; class 4, mean age 67.8 ys-hypertension and no symptoms; class 5, mean age 53 ys-cough and no comorbidities; class 6, mean age 60 ys-without symptoms or comorbidities. The chronic neurological disease (CND) percentage was distributed in the six phenotypes, predominantly in phenotypes of classes 3 (24.72%) and 4 (35,39%); χ² (5) 11.0129 p = 0.051134. The cerebrovascular disease was concentrated in classes 3 and 4; χ² (5) = 36.63, p = 0.000001. The mortality rate totaled 325 (25.79%), of which 56 (17.23%) had chronic neurological diseases. The highest in-hospital mortality rates were found in phenotypes 1 (37.22%) and 3 (33.98%). The SSC revealed that a neurological symptom (ageusia), together with two neurological diseases (cerebrovascular disease and Parkinson's disease), and in addition to ICU days, age and specific symptoms (fever, cough, dyspnea and chilliness) as well as particular comorbidities (hypertension, diabetes and asthma) indicated the best prediction performance (AUC = 0.67). Conclusions: The identification of clinical phenotypes and mortality biomarkers using practical variables and robust statistical methodologies make several noteworthy contributions to basic and experimental investigations for distinguishing the COVID-19 clinical spectrum and predicting mortality.

Clinical features of COVID-19 for integration of COVID-19 into influenza surveillance: A systematic review

Background

In November 2020, the World Health Organization (WHO) created interim guidance on how to integrate testing for SARS-CoV-2 into existing influenza surveillance systems. Influenza-like illness (ILI) and severe acute respiratory illness (SARI) case definitions have been used to specify the case definition of COVID-19 for surveillance purposes. This review aims to assess whether the common clinical features of COVID-19 have changed to the point that the criteria used to identify both COVID-19 and influenza in surveillance programs needs to be altered.

Methods

A systematic review of reviews following PRISMA-P guidelines was conducted using the "COVID-19 evidence review" database from August 19, 2020, to August 19, 2021. Reviews providing pooled estimates of the prevalence of clinical features of COVID-19 within the general population, diagnosed by polymerase chain reaction or rapid diagnostic test, were included. These were critically appraised and sensitivity analysis was undertaken to examine potential causes of bias.

Results

Fourteen reviews were identified, including three on adults only and three on children only. For all reviews, combined fever (median prevalence = 73.0%, IQR = 58.3-78.7) and cough (45.1%, IQR = 28.9-54.0) were the most common features. These were followed by loss of taste or smell (45.1%, IQR = 28.9-54.0), hypoxemia (33%, one review), fatigue (26.4%, IQR = 9.0-39.4) and expectoration (23.9%, IQR = 23.3-25.5). Fever and cough continued to be the most prevalent features for adults and children, with subsequent symptoms being similar for adults only. However, the pattern differed for children, with headache (34.3%, IQR = 18-50.7) and nasal congestion (20%, one review) being the third and fourth commonest symptoms.

Conclusions

The prevalent features found in this recent review were the same as the ones identified at the beginning of the pandemic. Therefore, the current approach of using the ILI and SARI criteria which incorporate fever and cough will identify COVID-19 cases in addition to influenza. Interestingly, children may present with different features, as headaches and nasal congestion were more common in this group. Future research could examine this further and investigate whether symptomology changes with new variants of COVID-19.

Mathematical Modeling to Predict COVID-19 Infection and Vaccination Trends

Background: COVID-19 caused by the Severe Acute Respiratory Syndrome Coronavirus 2 placed the health systems around the entire world in a battle against the clock. While most of the existing studies aimed at forecasting the infections trends, our study focuses on vaccination trend(s). Material and methods: Based on these considerations, we used standard analyses and ARIMA modeling to predict possible scenarios in Romania, the second-lowest country regarding vaccinations from the entire European Union. Results: With approximately 16 million doses of vaccine against COVID-19 administered, 7,791,250 individuals had completed the vaccination scheme. From the total, 5,058,908 choose Pfizer−BioNTech, 399,327 Moderna, 419,037 AstraZeneca, and 1,913,978 Johnson & Johnson. With a cumulative 2147 local and 17,542 general adverse reactions, the most numerous were reported in recipients of Pfizer−BioNTech (1581 vs. 8451), followed by AstraZeneca (138 vs. 6033), Moderna (332 vs. 1936), and Johnson & Johnson (96 vs. 1122). On three distinct occasions have been reported >50,000 individuals who received the first or second dose of a vaccine and >30,000 of a booster dose in a single day. Due to high reactogenicity in case of AZD1222, and time of launching between the Pfizer−BioNTech and Moderna vaccine could be explained differences in terms doses administered. Furthermore, ARIMA(1,1,0), ARIMA(1,1,1), ARIMA(0,2,0), ARIMA(2,1,0), ARIMA(1,2,2), ARI-MA(2,2,2), ARIMA(0,2,2), ARIMA(2,2,2), ARIMA(1,1,2), ARIMA(2,2,2), ARIMA(2,1,1), ARIMA(2,2,1), and ARIMA (2,0,2) for all twelve months and in total fitted the best models. These were regarded according to the lowest MAPE, p-value (p < 0.05, p < 0.01, and p < 0.001) and through the Ljung−Box test (p < 0.05, p < 0.01, and p < 0.001) for autocorrelations. Conclusions: Statistical modeling and mathematical analyses are suitable not only for forecasting the infection trends but the course of a vaccination rate as well.

Burnout Syndrome in a Military Tertiary Hospital Staff during the COVID-19 Contingency

(1) Background: Burnout syndrome (BOS) is defined as a psychological state of physical and mental fatigue associated with work. The COVID-19 pandemic greatly impacted the physical and mental wellbeing of health professionals. The objective of this work was to determine the impact on personnel, monitoring the frequency of BOS throughout the pandemic. (2) Methods: The Maslach Burnout Inventory (MBI) was self-applied in four periods of the pandemic according to sociodemographic and employment characteristics. In this study, all hospital personnel were included; the association of BOS with sex, age, type of participant (civilian or military), military rank and profession was analyzed. (3) Results: The frequency of BOS was 2.4% (start of the pandemic), 7.9% (peak of the first wave), 3.7% (end of the first wave) and 3.6% (peak of the third wave). Emotional exhaustion (EE) was the most affected factor, and the groups most affected were men under 30 years of age, civilians, chiefs and doctors, especially undergraduate medical doctors and specialty resident doctors, and nursing personnel were less affected. (4) Conclusions: The low BOS levels show that the containment measures and military training implemented by the hospital authorities were effective, although the chief personnel were more affected in the first wave. It is probable that this combination allowed the containment of BOS, which was not observed in civilians.

Rehabilitation and Return-to-Work of Patients Acquiring COVID-19 in the Workplace: A Study Protocol for an Observational Cohort Study

Background

In 2020, the novel coronavirus disease (COVID-19) developed into a worldwide pandemic. The course of COVID-19 is diverse, non-specific, and variable: Affected persons suffer from physical, cognitive, and psychological acute and long-term consequences. The symptoms influence everyday life activities, as well as work ability in the short or long-term. Healthcare professionals are considered particularly vulnerable to COVID-19 compared to the general population. In Germany, COVID-19 is recognized as an occupational disease or a work-related accident under certain conditions. Disease-specific rehabilitation is recommended for patients following acute COVID-19 to recover physical and neuropsychological performance and to improve work ability. Currently, there are limited findings on the short-term or long-term impact of COVID-19 as a recognized occupational disease or work-related accident, as well as on rehabilitation programs and associated influencing factors. Thus, the present research project will investigate these questions.

Methods

For this observational cohort study, post-acute patients with COVID-19 as a recognized occupational disease or work-related accident according to the insurance regulations for COVID-19 will be recruited at the BG Hospital for Occupational Disease in Bad Reichenhall, Germany. All participants will complete a comprehensive multimodal and interdisciplinary inpatient rehabilitation program for a duration of at least 3 weeks, beginning after their acute COVID-19 infection and depending on their individual indication and severity of disease. Participants will complete medical, functional, motor, psychological, and cognitive measurements at four time points (at the beginning (T1) and end (T2) of inpatient rehabilitation; 6 (T3) and 12 (T4) months after the beginning of inpatient rehabilitation).

Discussion

The present research project will help to assess and describe long-term effects of COVID-19 as a recognized occupational disease or work-related accident on physical and neuropsychological health, as well as on everyday activities and work ability of affected insured persons. In addition, this study will investigate influencing factors on severity and course of COVID-19. Furthermore, we will examine rehabilitation needs, measures, occurring specifics, and the feasibility of the rehabilitation procedure and disease development in the patients. The results of the intended study will further advance common recommendations for targeted and tailored rehabilitation management and participation in inpatient rehabilitation.

Clinical Trial Registration

www.drks.de, identifier: DRKS00022928.

The role of admission electrocardiogram in predicting outcome in patients hospitalized for COVID-19

BACKGROUND

Abnormal electrocardiogram (ECG) has been associated with poor outcome in patients hospitalized for COVID-19. However, the independent association between admission ECG and the risk of a poor outcome remains to be established. Our aim was to determine if abnormal admission ECG predicts treatment at intensive care unit or in-hospital death within 30 days in patients hospitalized for COVID-19.

METHODS

We analyzed the propensity weighted association between abnormal admission ECG and outcome in patients hospitalized for COVID-19 (March to May 2020). All adult patients hospitalized for COVID-19 at the three centers of Sahlgrenska University Hospital (Gothenburg, Sweden) were eligible for inclusion (N = 439). Patients with available admission ECG within six hours from admission were included.

RESULTS

238 patients (age 62 ± 16 years, 74% male) were included. 103 patients had normal ECG and 135 patients had abnormal ECG. 99 patients were admitted to intensive care unit or died in-hospital within 30 days. Abnormal ECG was associated with increased risk of the outcome (odds ratio 2.11 [95% confidence interval 1.21-3.66]).

CONCLUSIONS

Abnormal admission ECG was associated with increased risk of treatment at intensive care unit or in-hospital death within 30 days; and could be considered a high-risk criterion in patients hospitalized for COVID-19.

COVID-19 vaccine acceptance among healthcare workers in the United Arab Emirates

Background

COVID-19 vaccine hesitancy among healthcare workers (HCWs) is a threat to any healthcare system. Vaccine hesitancy can increase infection risk among HCWs and patients, while also impacting the patients' decision to accept the vaccine. Our study assessed COVID-19 vaccine acceptance among HCWs in United Arab Emirates (UAE).

Methods

Using purposive sampling, UAE HCWs registered in the Abu Dhabi Department of Health (DOH) email database were invited to complete an online questionnaire, between November 2020 and February 2021, to understand COVID-19 vaccine acceptance and hesitancy, and trust in sources of information. Simple logistic regression was used to assess the associations between demographic factors with COVID-19 vaccine acceptance.

Results

Of the 2832 HCWs who participated in the study, 1963 (69.9%) were aged between 25 and 44 years and 1748 (61.7%) were females. Overall, 2525 (89.2%) of the HCW population said they would accept a COVID-19 vaccine. HCWs who were 55+ years of age, male, and physicians/surgeons were more likely to accept a COVID-19 vaccine (OR 3.1, 95% CI 1.5-6.2, p = 0.002; OR 1.8, 95% CI 1.3-2.4, p < 0.001; and OR 1.8, 95% CI 1.1-2.9; p = 0.01, respectively). The most reliable sources for COVID-19 vaccine information were the UAE government (91.6%), healthcare providers (86.8%), health officials (86.3%), and the World Health Organization (WHO; 81.1%).

Conclusions

COVID-19 vaccine acceptance was high among the UAE HCW population. Several factors were identified as significant determinants of vaccine acceptance. UAE healthcare authorities can utilize these findings to develop public health messaging campaigns for HCWs to best address COVID-19 vaccine concerns - particularly when the government is vaccinating its general population.