The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases

Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts

The outbreak of the novel coronavirus (COVID-19) was declared to be a global emergency in January of 2020, and everyday life throughout the world was disrupted. Among many questions about COVID-19 that remain unanswered, it is of interest for society to identify whether there is any significant difference in daily case counts between males and females. The daily case count sequences are correlated due to the nature of a contagious disease, and contain a nonlinear trend owing to several unexpected events, such as vaccinations and the appearance of the delta variant. It is possible that these unexpected events have changed the dynamical system that generates data. The classic t-test is not appropriate to analyze such correlated data with a nonconstant trend. This study applies a simultaneous confidence band approach in an attempt to overcome these difficulties; that is, a simultaneous confidence band for the trend of an autoregressive moving-average time series is constructed using B-spline estimation. The proposed method is applied to the daily case count data of seniors of both genders (at least 60 years old) in the State of Ohio from April 1, 2020 to March 31, 2022, and the result shows that there is a significant difference at the 95% confidence level between the two gender case counts adjusted for the population sizes.

Relation of COVID-19 with liver diseases and their impact on healthcare systems: The Portuguese case

BACKGROUND

The impact caused by the coronavirus disease 2019 (COVID-19) on the Portuguese population has been addressed in areas such as clinical manifestations, frequent comorbidities, and alterations in consumption habits. However, comorbidities like liver conditions and changes concerning the Portuguese population's access to healthcare-related services have received less attention.

AIM

To (1) Review the impact of COVID-19 on the healthcare system; (2) examine the relationship between liver diseases and COVID-19 in infected individuals; and (3) investigate the situation in the Portuguese population concerning these topics.

METHODS

For our purposes, we conducted a literature review using specific keywords.

RESULTS

COVID-19 is frequently associated with liver damage. However, liver injury in COVID-19 individuals is a multifactor-mediated effect. Therefore, it remains unclear whether changes in liver laboratory tests are associated with a worse prognosis in Portuguese individuals with COVID-19.

CONCLUSION

COVID-19 has impacted healthcare systems in Portugal and other countries; the combination of COVID-19 with liver injury is common. Previous liver damage may represent a risk factor that worsens the prognosis in individuals with COVID-19.

Risk factors for SARS-CoV-2 related mortality and hospitalization before vaccination: A meta-analysis

The literature remains scarce regarding the varying point estimates of risk factors for COVID-19 associated mortality and hospitalization. This meta-analysis investigates risk factors for mortality and hospitalization, estimates individual risk factor contribution, and determines drivers of published estimate variances. We conducted a systematic review and meta-analysis of COVID-19 related mortality and hospitalization risk factors using PRISMA guidelines. Random effects models estimated pooled risks and meta-regression analyses estimated the impact of geographic region and study type. Studies conducted in North America and Europe were more likely to have lower effect sizes of mortality attributed to chronic kidney disease (OR: 0.21, 95% CI: 0.09-0.52 and OR: 0.25, 95% CI: 0.10-0.63, respectively). Retrospective studies were more likely to have decreased effect sizes of mortality attributed to chronic heart failure compared to prospective studies (OR: 0.65, 95% CI: 0.44-0.95). Studies from Europe and Asia (OR: 0.42, 95% CI: 0.30-0.57 and OR: 0.49, 95% CI: 0.28-0.84, respectively) and retrospective studies (OR: 0.58, 95% CI: 0.47-0.73) reported lower hospitalization risk attributed to male sex. Significant geographic population-based variation was observed in published comorbidity related mortality risks while male sex had less of an impact on hospitalization among European and Asian populations or in retrospective studies.

Impact of COVID-19 Pandemic on In-Hospital Mortality in Patients Without SARS-CoV-2 Infection in an Internal Medicine Ward of a Tertiary Care Hospital in Portugal

INTRODUCTION

Despite the emergence of a new worldwide cause of death related to COVID-19, several studies have hypothesized that the international mortality rate attributed to non-COVID-19 causes was significantly higher during the COVID pandemic, questioning whether this excess in mortality is related only to COVID-19 or to the difficulties that the healthcare systems faced during the pandemic. Therefore, understanding the impact of the COVID-19 pandemic on the prognosis of patients without severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a major unmet need as this was overshadowed by the overwhelming number of patients with SARS-CoV-2.

METHODS

This is a retrospective, cross-sectional, observational study in the internal medicine non-COVID-19 wards of a tertiary care hospital in Portugal. A total of 2021 patients without SARS-CoV-2 infection admitted between March and May of 2019 and 2020 were included. For each patient, we collected information regarding demographic characteristics, emergency department admission information, hospitalization information, date of discharge or death, health comorbidities, and current medication.

RESULTS

Data from 1013 patients in 2019 and 1008 patients in 2020 was analyzed. The patients' demographic characteristics, health comorbidities, and current medications were distributed in similar patterns in the two studied periods. There was a statistically significant difference in the in-hospital mortality in patients without SARS-CoV-2 infection between 2019 and 2020 (12% vs 17%, p-value < 0.001) and in admission severity in hospitalized patients without SARS-CoV-2 infection between 2019 and 2020 (0.9 vs 0.6, p-value < 0.001).

CONCLUSION

Our work showed a statistically significant increase in in-hospital mortality during the COVID-19 pandemic in patients without SARS-CoV-2 infection, which was not apparently explained by differences in the characteristics of hospitalized patients. As this is one of the first works describing the silent impact of the COVID-19 pandemic in Portugal, we believe it holds an important value in the provision of bases for building up future health policies in case of new COVID-19 outbreaks or other medical emergencies.

Methodological Considerations on COVID-19 Mortality in Cancer Patients: A Systematic Review and Meta-Analysis

BACKGROUND

Patients with cancer are at risk for severe COVID-19. Previous studies examining mortality in cancer patients with COVID-19 have produced inconclusive results. Several published meta-analyses have aimed to estimate this association; however, because of methodological limitations in study selection and data aggregation, these studies do not reliably estimate the independent association between cancer and COVID-19 mortality. We conducted this systematic review and meta-analysis to determine whether cancer is an independent risk factor for COVID-19 mortality.

METHODS

A literature search was performed in PubMed to identify studies that compared COVID-19 mortality in adult patients with and without cancer. Selection criteria included polymerase chain reaction-confirmed COVID-19, multivariate adjustment and/or matching for mortality risk estimates, and inclusion of hospitalized noncancer controls. Adjusted odds ratios and/or hazard ratios for mortality based on cancer status were extracted. Odds ratio and hazard ratio estimates were pooled using a random effects model.

RESULTS

The analysis included 42 studies comprising 129 840 patients: 8612 cancer patients and 121 228 noncancer patients. Of these studies, 18 showed a null difference in survival between cancer and noncancer patients with COVID-19, and 24 studies showed statistically significantly worse survival in cancer patients with COVID-19. Meta-analysis revealed an increased risk of mortality in patients with cancer compared with noncancer patients with COVID-19 (odds ratio = 1.93, 95% confidence interval = 1.55 to 2.41; hazard ratio = 1.54, 95% confidence interval = 1.29 to 1.84).

CONCLUSION

We conclude that cancer is an independent risk factor for mortality in unvaccinated patients admitted for or diagnosed with COVID-19 during hospitalization.

COVID-19 in Portugal: a retrospective review of paediatric cases, hospital and PICU admissions in the first pandemic year

BACKGROUND

COVID-19 is considered by WHO a pandemic with public health emergency repercussions. Children often develop a mild disease with good prognosis and the recognition of children at risk is essential to successfully manage paediatric COVID-19. Quality epidemiological surveillance data are required to characterise and assess the pandemic.

METHODS

Data on all reported paediatric COVID-19 cases, in Portugal, were retrospectively assessed from a fully anonymised dataset provided by the Directorate General for Health (DGS). Paediatric hospital admission results were obtained from the DGS vaccine recommendations and paediatric intensive care unit (PICU) admission results from the EPICENTRE.PT group. Reported cases and PICU admissions from March 2020 to February 2021 and hospital admissions between March and December 2020 were analysed.

RESULTS

92 051 COVID-19 cases were studied, 50.5% males, average age of 10.1 years, corresponding to 5.4% of children in Portugal. The most common symptoms were cough and fever, whereas gastrointestinal symptoms were infrequent. The most common comorbidity was asthma. A high rate of missing surveillance data was noticed, on presentation of disease and comorbidity variables, which warrants a cautious interpretation of results. Hospital admission was required in 0.93% of cases and PICU on 3.48 per 10 000 cases. PICU admission for Multisystem Inflammatory Syndrome in Children (MIS-C) was more frequent in children with no comorbidities and males, severe COVID-19 was rarer and occurred mainly in females and infants. Case fatality rate and mortality rates were low, 1.8 per 100 000 cases and 1.2 per 1 000 000 cases, respectively.

CONCLUSIONS

The overall reported case incidence was 5.4 per 100 children and adolescents and <1% of cases required hospital admission. MIS-C was more frequent in patients with no comorbidities and males. Mortality and case fatality rates were low. Geographic adapted strategies, and information systems to facilitate surveillance are required to improve surveillance data quality.

COVID‐19 mortality and its predictors in the elderly: A systematic review

Background and Aims

Older people have higher rates of comorbidities and may experience more severe inflammatory responses; therefore, are at higher risk of death. Herein, we aimed to systematically review the mortality in coronavirus disease 2019 (COVID‐19) patients and its predictors in this age group.

Methods

We searched PubMed, Web of Science, and Science Direct using relevant keywords. Retrieved records underwent a two‐step screening process consisting of title/abstract and full‐text screenings to identify the eligible studies.

Results

Summarizing findings of 35 studies demonstrated that older patients have higher mortality rates compared to the younger population. A review of articles revealed that increasing age, body mass index, a male gender, dementia, impairment or dependency in daily activities, presence of consolidations on chest X‐ray, hypoxemic respiratory failure, and lower oxygen saturation at admission were risk factors for death. High d‐dimer levels, 25‐hydroxy vitamin D serum deficiencies, high C‐reactive protein (≥5 mg/L) levels plus any other abnormalities of lymphocyte, higher blood urea nitrogen or lactate dehydrogenase, and higher platelet count were predictors of poor prognosis and mortality in the elderly. Studies have also shown that previous treatment with renin–angiotensin–aldosterone system inhibitors, pharmacological treatments of respiratory disorders, antibiotics, corticosteroids, vitamin K antagonist, antihistamines, azithromycin, Itolizumab (an anti‐CD6 monoclonal antibody) in combination with other antivirals reduces COVID‐19 worsening and mortality. Vaccination against seasonal influenza might also reduce COVID‐19 mortality.

Conclusion

Overall, a critical consideration is necessary for the care and management of COVID‐19 in the aged population considering the drastic contrasts in manifestation and prognosis compared to other age groups. Mortality from COVID‐19 is independently associated with the patient's age. Elderly patients with COVID‐19 are more vulnerable to poor outcomes. Thus, strict preventive measures, timely diagnosis, and aggressive therapeutic/nontherapeutic care are of great importance to reduce acute respiratory distress syndrome and severe complications in older people.

COVID-19 mortality and its predictors in the elderly: A systematic review

BACKGROUND AND AIMS

Older people have higher rates of comorbidities and may experience more severe inflammatory responses; therefore, are at higher risk of death. Herein, we aimed to systematically review the mortality in coronavirus disease 2019 (COVID-19) patients and its predictors in this age group.

METHODS

We searched PubMed, Web of Science, and Science Direct using relevant keywords. Retrieved records underwent a two-step screening process consisting of title/abstract and full-text screenings to identify the eligible studies.

RESULTS

Summarizing findings of 35 studies demonstrated that older patients have higher mortality rates compared to the younger population. A review of articles revealed that increasing age, body mass index, a male gender, dementia, impairment or dependency in daily activities, presence of consolidations on chest X-ray, hypoxemic respiratory failure, and lower oxygen saturation at admission were risk factors for death. High d-dimer levels, 25-hydroxy vitamin D serum deficiencies, high C-reactive protein (≥5 mg/L) levels plus any other abnormalities of lymphocyte, higher blood urea nitrogen or lactate dehydrogenase, and higher platelet count were predictors of poor prognosis and mortality in the elderly. Studies have also shown that previous treatment with renin-angiotensin-aldosterone system inhibitors, pharmacological treatments of respiratory disorders, antibiotics, corticosteroids, vitamin K antagonist, antihistamines, azithromycin, Itolizumab (an anti-CD6 monoclonal antibody) in combination with other antivirals reduces COVID-19 worsening and mortality. Vaccination against seasonal influenza might also reduce COVID-19 mortality.

CONCLUSION

Overall, a critical consideration is necessary for the care and management of COVID-19 in the aged population considering the drastic contrasts in manifestation and prognosis compared to other age groups. Mortality from COVID-19 is independently associated with the patient's age. Elderly patients with COVID-19 are more vulnerable to poor outcomes. Thus, strict preventive measures, timely diagnosis, and aggressive therapeutic/nontherapeutic care are of great importance to reduce acute respiratory distress syndrome and severe complications in older people.

A proposed fractional dynamic system and Monte Carlo-based back analysis for simulating the spreading profile of COVID-19

This paper presents a dynamic system for estimating the spreading profile of COVID-19 in Thailand, taking into account the effects of vaccination and social distancing. For this purpose, a compartmental network is built in which the population is divided into nine mutually exclusive nodes, including susceptible, insusceptible, exposed, infected, vaccinated, recovered, quarantined, hospitalized, and dead. The weight of edges denotes the interaction between the nodes, modeled by a series of conversion rates. Next, the compartmental network and corresponding rates are incorporated into a system of fractional partial differential equations to define the model governing the problem concerned. The fractional degree corresponding to each compartment is considered the node weight in the proposed network. Next, a Monte Carlo-based optimization method is proposed to fit the fractional compartmental network to the actual COVID-19 data of Thailand collected from the World Health Organization. Further, a sensitivity analysis is conducted on the node weights, i.e., fractional orders, to reveal their effect on the accuracy of the fit and model predictions. The results show that the flexibility of the model to adapt to the observed data is markedly improved by lowering the order of the differential equations from unity to a fractional order. The final results show that, assuming the current pandemic situation, the number of infected, recovered, and dead cases in Thailand will, respectively, reach 4300, 4.5 × 10 6 , and 36,000 by the end of 2021.

Multimorbidity Profile of COVID-19 Deaths in Portugal during 2020

BACKGROUND

COVID-19 is caused by SARS-CoV-2 infection and has reached pandemic proportions. Since then, several clinical characteristics have been associated with poor outcomes. This study aimed to describe the morbidity profile of COVID-19 deaths in Portugal.

METHODS

A study was performed including deaths certificated in Portugal with "COVID-19" (ICD-10: U07.1 or U07.2) coded as the underlying cause of death from the National e-Death Certificates Information System between 16 March and 31 December 2020. Comorbidities were derived from ICD-10 codes using the Charlson and Elixhauser indexes. The resident Portuguese population estimates for 2020 were used.

RESULTS

The study included 6701 deaths (death rate: 65.1 deaths/100,000 inhabitants), predominantly males (72.1). The male-to-female mortality ratio was 1.1. The male-to-female mortality rate ratio was 1.2; however, within age groups, it varied 5.0-11.4-fold. COVID-19 deaths in Portugal during 2020 occurred mainly in individuals aged 80 years or older, predominantly in public healthcare institutions. Uncomplicated hypertension, uncomplicated diabetes mellitus, congestive heart failure, renal failure, cardiac arrhythmias, dementia, and cerebrovascular disease were observed among COVID-19 deceased patients, with prevalences higher than 10%. A high prevalence of zero morbidities was registered using both the Elixhauser and Charlson comorbidities lists (above 40.2%). Nevertheless, high multimorbidity was also identified at the time of COVID-19 death (about 36.5%). Higher multimorbidity levels were observed in men, increasing with age up to 80 years old. Zero-morbidity prevalence and high multimorbidity prevalences varied throughout the year 2020, seemingly more elevated in the mortality waves' peaks, suggesting variation according to the degree of disease incidence at a given period.

CONCLUSIONS

This study provides detailed sociodemographic and clinical information on all certificated deaths from COVID-19 in Portugal during 2020, showing complex and extreme levels of morbidity (zero-morbidity vs. high multimorbidity) dynamics during the first year of the pandemic in Portugal.

Heat-related mortality amplified during the COVID-19 pandemic

Excess mortality not directly related to the virus has been shown to have increased during the COVID-19 pandemic. However, changes in heat-related mortality during the pandemic have not been addressed in detail. Here, we performed an observational study crossing daily mortality data collected in Portugal (SICO/DGS) with high-resolution temperature series (ERA5/ECMWF), characterizing their relation in the pre-pandemic, and how it aggravated during 2020. The combined result of COVID-19 and extreme temperatures caused the largest annual mortality burden in recent decades (~ 12 000 excess deaths [~ 11% above baseline]). COVID-19 caused the largest fraction of excess mortality during March to May (62%) and from October onwards (85%). During summer, its direct impact was residual, and deaths not reported as COVID-19 dominated excess mortality (553 versus 3 968). A prolonged hot spell led mortality to the upper tertile, reaching its peak in mid-July (+ 45% deaths/day). The lethality ratio (+ 14 deaths per cumulated ºC) was higher than that observed in recent heatwaves. We used a statistical model to estimate expected deaths due to cold/heat, indicating an amplification of at least 50% in heat-related deaths during 2020 compared to pre-pandemic years. Our findings suggest mortality during 2020 has been indirectly amplified by the COVID-19 pandemic, due to the disruption of healthcare systems and fear of population in attending healthcare facilities (expressed in emergency room admissions decreases). While lockdown measures and healthcare systems reorganization prevented deaths directly related to the virus, a significant burden due to other causes represents a strong secondary impact. This was particularly relevant during summer hot spells, when the lethality ratio reached magnitudes not experienced since the 2003 heatwaves. This severe amplification of heat-related mortality during 2020 stresses the need to resume normal healthcare services and public health awareness.

Effect of cancer on outcome of COVID-19 patients: a systematic review and meta-analysis of studies of unvaccinated patients

Background:

Since the beginning of the SARS-CoV-2 pandemic, cancer patients affected by COVID-19 have been reported to experience poor prognosis; however, a detailed quantification of the effect of cancer on outcome of unvaccinated COVID-19 patients has not been performed.

Methods:

To carry out a systematic review of the studies comparing the outcome of unvaccinated COVID-19 patients with and without cancer, a search string was devised which was used to identify relevant publications in PubMed up to December 31, 2020. We selected three outcomes: mortality, access to ICU, and COVID-19 severity or hospitalization. We considered results for all cancers combined as well as for specific cancers. We conducted random-effects meta-analyses of the results, overall and after stratification by region. We also performed sensitivity analyses according to quality score and assessed publication bias.

Results:

For all cancer combined, the pooled odds ratio (OR) for mortality was 2.32 (95% confidence interval [CI] 1.82–2.94, I² for heterogeneity 90.1%, 24 studies), that for ICU admission was 2.39 (95% CI 1.90–3.02, I² 0.0%, 5 studies), that for disease severity or hospitalization was 2.08 (95% CI 1.60–2.72, I² 92.1%, 15 studies). The pooled mortality OR for hematologic neoplasms was 2.14 (95% CI 1.87–2.44, I² 20.8%, 8 studies). Data were insufficient to perform a meta-analysis for other cancers. In the mortality meta-analysis for all cancers, the pooled OR was higher for studies conducted in Asia than studies conducted in Europe or North America. There was no evidence of publication bias.

Conclusions:

Our meta-analysis indicates a twofold increased risk of adverse outcomes (mortality, ICU admission, and severity of COVID-19) in unvaccinated COVID-19 patients with cancer compared to COVID-19 patients without cancer. These results should be compared with studies conducted in vaccinated patients; nonetheless, they argue for special effort to prevent SARS-CoV-2 infection in patients with cancer.

Funding:

No external funding was obtained.

Mathematical indices for the influence of risk factors on the lethality of a disease

We develop a theoretical model to measure the relative relevance of different pathologies of the lethality of a disease in society. This approach allows a ranking of diseases to be determined, which can assist in establishing priorities for vaccination campaigns or prevention strategies. Among all possible measurements, we identify three families of rules that satisfy a combination of relevant properties: neutrality, irrelevance, and one of three composition concepts. One of these families includes, for instance, the Shapley value of the associated cooperative game. The other two families also include simple and intuitive indices. As an illustration, we measure the relative relevance of several pathologies in lethality due to COVID-19.

COVID-19 surveillance data quality issues: a national consecutive case series

OBJECTIVES

High-quality data are crucial for guiding decision-making and practising evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese epidemiological surveillance dataset, our study aims to assess COVID-19 data quality issues and suggest possible solutions.

SETTINGS

On 27 April 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On 4 August, an updated dataset (DGSAugust) was also obtained.

PARTICIPANTS

All COVID-19-confirmed cases notified through the medical component of National System for Epidemiological Surveillance until end of June.

PRIMARY AND SECONDARY OUTCOME MEASURES

Data completeness and consistency.

RESULTS

DGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (eg, 4075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (eg, the variable 'underlying conditions' had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily.

CONCLUSIONS

Important quality issues of the Portuguese COVID-19 surveillance datasets were described. These issues can limit surveillance data usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed-for example, simplification of data entry processes, constant monitoring of data, and increased training and awareness of healthcare providers-as low data quality may lead to a deficient pandemic control.

Impact of Asthma on Severity and Outcomes in COVID-19

BACKGROUND

We conducted this systematic review to evaluate whether asthma increases the risk of severe disease and adverse outcomes among subjects with COVID-19.

METHODS

We queried the PubMed and Embase databases for studies indexed through December 2020. We included studies providing data on severe disease, hospitalization, ICU care, need for mechanical ventilation, or mortality among subjects with COVID-19 with and without asthma. We calculated the relative risk for each reported outcome of interest and used random effects modeling to summarize the data.

RESULTS

We retrieved 1,832 citations, and included 90 studies, in our review. Most publications reported data retrieved from electronic records of retrospective subject cohorts. Only 25 studies were judged to be of high quality. Subjects with asthma and COVID-19 had a marginally higher risk of hospitalization (summary relative risk 1.13, 95% CI 1.03-1.24) but not for severe disease (summary relative risk 1.17, 95% CI 0.62-2.20), ICU admission (summary relative risk 1.13, 95% CI 0.96-1.32), mechanical ventilation (summary relative risk 1.05, 95% CI 0.85-1.29), or mortality (summary relative risk 0.92, 95% CI 0.82-1.04) as compared to subjects with COVID-19 without asthma.

CONCLUSIONS

Comorbid asthma increases risk of COVID-19-related hospitalization but not severe disease or other adverse outcomes in subjects with COVID-19.

Diabetes, hypertension, body mass index, smoking and COVID-19-related mortality: a systematic review and meta-analysis of observational studies

OBJECTIVES

We conducted a systematic literature review and meta-analysis of observational studies to investigate the association between diabetes, hypertension, body mass index (BMI) or smoking with the risk of death in patients with COVID-19 and to estimate the proportion of deaths attributable to these conditions.

METHODS

Relevant observational studies were identified by searches in the PubMed, Cochrane library and Embase databases through 14 November 2020. Random-effects models were used to estimate summary relative risks (SRRs) and 95% CIs. Certainty of evidence was assessed using the Cochrane methods and the Grading of Recommendations, Assessment, Development and Evaluations framework.

RESULTS

A total of 186 studies representing 210 447 deaths among 1 304 587 patients with COVID-19 were included in this analysis. The SRR for death in patients with COVID-19 was 1.54 (95% CI 1.44 to 1.64, I2=92%, n=145, low certainty) for diabetes and 1.42 (95% CI 1.30 to 1.54, I2=90%, n=127, low certainty) for hypertension compared with patients without each of these comorbidities. Regarding obesity, the SSR was 1.45 (95% CI 1.31 to 1.61, I2=91%, n=54, high certainty) for patients with BMI ≥30 kg/m2 compared with those with BMI <30 kg/m2 and 1.12 (95% CI 1.07 to 1.17, I2=68%, n=25) per 5 kg/m2 increase in BMI. There was evidence of a J-shaped non-linear dose-response relationship between BMI and mortality from COVID-19, with the nadir of the curve at a BMI of around 22-24, and a 1.5-2-fold increase in COVID-19 mortality with extreme obesity (BMI of 40-45). The SRR was 1.28 (95% CI 1.17 to 1.40, I2=74%, n=28, low certainty) for ever, 1.29 (95% CI 1.03 to 1.62, I2=84%, n=19) for current and 1.25 (95% CI 1.11 to 1.42, I2=75%, n=14) for former smokers compared with never smokers. The absolute risk of COVID-19 death was increased by 14%, 11%, 12% and 7% for diabetes, hypertension, obesity and smoking, respectively. The proportion of deaths attributable to diabetes, hypertension, obesity and smoking was 8%, 7%, 11% and 2%, respectively.

CONCLUSION

Our findings suggest that diabetes, hypertension, obesity and smoking were associated with higher COVID-19 mortality, contributing to nearly 30% of COVID-19 deaths.

TRIAL REGISTRATION NUMBER

CRD42020218115.

Update of the recommendations of the Sociedade Portuguesa de Cuidados Intensivos and the Infection and Sepsis Group for the approach to COVID-19 in Intensive Care Medicine

INTRODUCTION

The Sociedade Portuguesa de Cuidados Intensivos and the Infection and Sepsis Group have previously issued health service and management recommendations for critically ill patients with COVID-19. Due to the evolution of knowledge, the panel of experts was again convened to review the current evidence and issue updated recommendations.

METHODS

A national panel of experts who declared that they had no conflicts of interest regarding the development of the recommendations was assembled. Operational questions were developed based on the PICO methodology, and a rapid systematic review was conducted by consulting different bibliographic sources. The panel determined the direction and strength of the recommendations using two Delphi rounds, conducted in accordance with the principles of the GRADE system. A strong recommendation received the wording "is recommended", and a weak recommendation was written as "is suggested."

RESULTS

A total of 48 recommendations and 30 suggestions were issued, covering the following topics: diagnosis of SARS-CoV-2 infection, coinfection and superinfection; criteria for admission, cure and suspension of isolation; organization of services; personal protective equipment; and respiratory support and other specific therapies (antivirals, immunomodulators and anticoagulation).

CONCLUSION

These recommendations, specifically oriented to the Portuguese reality but that may also apply to Portuguese-speaking African countries and East Timor, aim to support health professionals in the management of critically ill patients with COVID-19. They will be continuously reviewed to reflect the progress of our understanding and the treatment of this pathology.

Outcomes among patients with COVID-19 and asthma: A systematic review and meta-analysis

Background: It remains unclear if asthma is a risk factor associated with worse outcomes among patients with coronavirus disease 2019 (COVID-19). Methods: We performed a comprehensive database search for studies published from January 1, 2019, to October 2, 2020. We included studies that evaluated outcomes among patients with COVID-19 and underlying asthma. Outcomes of interest included the need for hospitalization, length of hospitalization, intensive care unit (ICU) admission, and death. The meta-analysis was conducted by using random-effects methodology. Results: A total of 389 studies were identified through data base searches. After abstract and full-text screening, 16 observational studies with 92,275 patients were included in the analysis. Of the 16 studies, 15 were retrospective and 1 was a prospective cohort study. The average age was 39.6 years, with 48% female patients. Six of the studies included pediatric patients, and one of these studies only evaluated pediatric patients. One study only evaluated pregnant patients. Among patients with COVID-19, the presence of asthma was not associated with any significant increase in risk of hospitalization (odds ratio [OR] 1.46 [95% confidence interval {CI}, 0.29-7.28]), length of hospitalization (1.59 days [-0.55 to 3.74]), ICU admission (OR 1.65 [95% CI, 0.56-4.17]), or death (OR 0.73 [95% CI, 0.38-1.40]). The overall risk of bias of the included studies was high. Conclusion: Among the patients with COVID-19, asthma did not seem to significantly increase the risk of hospitalization, length of hospitalization, ICU admission, or death.

The Risk of COVID-19 Related Hospitalsation, Intensive Care Unit Admission and Mortality in People With Underlying Asthma or COPD: A Systematic Review and Meta-Analysis

Background: Several underlying diseases have been associated with unfavorable COVID-19 related outcomes including asthma and Chronic Obstructive Pulmonary Disease (COPD), however few studies have reported risks that are adjusted for confounding variables. This study aimed to examine the adjusted risk of COVID-19 related hospitalsation, intensive care unit (ICU) admission, and mortality in patients with vs. without asthma or COPD. Methods: A systematic review of major databases was undertaken for studies published between 1/12/2019 and 19/4/2021. Studies reporting the adjusted (for one or more confounder) risks of either hospitalsation, ICU admission, or mortality in asthmatics or COPD patients (control group = no asthma or no COPD) were identified. Risk of bias was determined via the QUIPS tool. A random effect meta-analysis was undertaken. Findings: 37 studies were eligible for analysis, with a total of 1,678,992 participants. The pooled ORs of COVID-19 hospitalsation in subjects with asthma and COPD was 0.91 (95% CI 0.76-1.09) and 1.37 (95% CI 1.29-1.46), respectively. For ICU admission, OR in subjects with asthma and COPD was 0.89 (95% CI 0.74-1.07) and 1.22 (95% CI 1.04-1.42), respectively. For mortality, ORs were 0.88 (95% CI 0.77-1.01) and 1.25 (95% CI 1.08-1.34) for asthma and COPD, respectively. Further, the pooled risk of mortality as measured via Cox regression was 0.93 (95% CI 0.87-1.00) for asthma and 1.30 (95% CI 1.17-1.44) for COPD. All of these findings were of a moderate level of certainty. Interpretation: COPD was significantly associated with COVID-19 related hospital admission, ICU admission, and mortality. Asthma was not associated with negative COVID-19 related health outcomes. Individuals with COPD should take precautions to limit the risk of COVID-19 exposure to negate these potential outcomes. Limitations include differing population types and adjustment for differing cofounding variables. Practitioners should note these findings when dealing with patients with these comorbidities. Review Protocol Registration: https://www.crd.york.ac.uk/prospero/.

Risk Factors for Mortality in COVID-19 Hospitalized Patients in Piedmont, Italy: Results from the Multicenter, Regional, CORACLE Registry

BACKGROUND

CORACLE is a retrospective and prospective, regional multicenter registry, developed to evaluate risk factors for mortality in a cohort of patients admitted with SARS-CoV-2 infection within non-intensive wards.

METHODS

The primary objective was to estimate the role of several prognostic factors on hospital mortality in terms of adjusted Odds Ratios (aOR) with multivariable logistic regression models.

RESULTS

A total of 1538 patients were enrolled; 42% were female, and 58% were >70 years old. Deceased patients were 422 (27%), with a median age of 83 years (IQR (Inter Quartile Range) 76-87). Older age at admission (aOR 1.07 per year, 95%CI 1.06-1.09), diabetes (1.41, 1.02-1.94), cardiovascular disease (1.79, 1.31-2.44), immunosuppression (1.65, 1.04-2.62), estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m2 (3.53, 2.26-5.51), higher C-reactive protein values and a decreased PaO2/FiO2 ratio at admission were associated with a higher risk of hospital mortality. Amongst patients still alive on day 7, only hydroxychloroquine (HCQ) treatment was associated with reduced mortality (0.57, 0.36-0.90).

CONCLUSIONS

Several risk factors were associated with mortality in SARS-CoV-2 positive patients. Although HCQ seems to be the only factor significantly associated with reduced mortality, this result is in contrast with evidence from randomized studies. These results should be interpreted in light of the study limitations.

Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study

BACKGROUND

In the face of the current COVID-19 pandemic, the timely prediction of upcoming medical needs for infected individuals enables better and quicker care provision when necessary and management decisions within health care systems.

OBJECTIVE

This work aims to predict the medical needs (hospitalizations, intensive care unit admissions, and respiratory assistance) and survivability of individuals testing positive for SARS-CoV-2 infection in Portugal.

METHODS

A retrospective cohort of 38,545 infected individuals during 2020 was used. Predictions of medical needs were performed using state-of-the-art machine learning approaches at various stages of a patient's cycle, namely, at testing (prehospitalization), at posthospitalization, and during postintensive care. A thorough optimization of state-of-the-art predictors was undertaken to assess the ability to anticipate medical needs and infection outcomes using demographic and comorbidity variables, as well as dates associated with symptom onset, testing, and hospitalization.

RESULTS

For the target cohort, 75% of hospitalization needs could be identified at the time of testing for SARS-CoV-2 infection. Over 60% of respiratory needs could be identified at the time of hospitalization. Both predictions had >50% precision.

CONCLUSIONS

The conducted study pinpoints the relevance of the proposed predictive models as good candidates to support medical decisions in the Portuguese population, including both monitoring and in-hospital care decisions. A clinical decision support system is further provided to this end.

Pervasive Intelligent Models to Predict the Outcome of COVID-19 Patients

Nowadays, there is an increasing need to understand the behavior of COVID-19. After the Directorate-General of Health of Portugal made available the infected patient’s data, it became possible to analyze it and gather some conclusions, obtaining a better understanding of the matter. In this context, the project developed—ioCOVID19—Intelligent Decision Support Platform aims to identify patterns and develop intelligent models to predict and support clinical decisions. This article explores which typologies are associated with different outcomes to help clinicians fight the virus with a decision support system. So, to achieve this purpose, classification algorithms were used, and one target was studied—Patients outcome, that is, to predict if the patient will die or recover. Regarding the obtained results, the model that stood out is composed of scenario s4 (composed of all comorbidities, symptoms, and age), the decision tree algorithm, and the oversampling sampling method. The obtained results by the studied metrics were (in order of importance): Sensitivity of 95.20%, Accuracy of 90.67%, and Specificity of 86.08%. The models were deployed as a service, and they are part of a clinical decision support system that is available for authorized users anywhere and anytime.

Prognostic Factors of COVID-19 Infection in Elderly Patients: A Multicenter Study

The outbreak of the COVID-19 pandemic is a substantial threat to the health of all populations worldwide, and old age is a robust risk factor for poor prognosis of COVID-19 infection. To reduce the fatality rate of COVID-19 infection, further understanding of elderly patients with COVID-19 is necessary. We aimed to investigate the prognostic factors in elderly patients with COVID-19. This was a multicenter and retrospective study. Overall, 340 elderly patients with COVID-19 were enrolled in 3 hospitals in Daegu, South Korea. Death and severe pneumonia requiring oxygen treatment were defined as poor clinical outcomes. Of the patients studied, 15% died and 35.2% were classified as having severe pneumonia. In binary logistic regression analysis, activities of daily living (ADL) impairment, fever during hospitalization, initial infiltration on chest radiograph, and initial increased C-reactive protein (CRP) were significantly associated with severe pneumonia (OR = 5.33, p < 0.001; OR = 3.2, p = 0.002; OR = 2.32, p = 0.044; and OR = 1.33, p < 0.001, respectively). ADL impairment, comorbidity, fever during hospitalization, and initial increased CRP were significantly associated with death (OR = 7.13, p < 0.001; OR = 3.28, p = 0.005; OR = 3.15, p = 0.032, and OR = 1.18, p < 0.001, respectively). ADL impairment, fever, and initial CRP were poor prognostic factors in elderly patients with COVID-19. Understanding these poor prognostic factors is necessary to control the disease in elderly patients.

Impact of SARS-CoV-2 on Male Reproductive Health: A Review of the Literature on Male Reproductive Involvement in COVID-19

Coronavirus Disease 2019 (COVID-19) has created a global pandemic. Global epidemiological results show that elderly men are susceptible to infection of COVID-19. The difference in the number of cases reported by gender increases progressively in favor of male subjects up to the age group ≥60-69 (66.6%) and ≥70-79 (66.1%). Through literature search and analysis, we also found that men are more susceptible to SARS-CoV-2 infection than women. In addition, men with COVID-19 have a higher mortality rate than women. Male represents 73% of deaths in China, 59% in South Korea, and 61.8% in the United States. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the pathogen of COVID-19, which is transmitted through respiratory droplets, direct and indirect contact. Genomic analysis has shown that SARS-CoV-2 is 79% identical to SARS-CoV, and both use angiotensin-converting enzyme 2 (ACE2) as the receptor for invading cells. In addition, Transmembrane serine protease 2 (TMPRSS2) can enhance ACE2-mediated virus entry. However, SARS-CoV-2 has a high affinity with human ACE2, and its consequences are more serious than other coronaviruses. ACE2 acts as a "gate" for viruses to invade cells and is closely related to the clinical manifestations of COVID-19. Studies have found that ACE2 and TMPRSS2 are expressed in the testis and male reproductive tract and are regulated by testosterone. Mature spermatozoon even has all the machinery required to bind SARS-CoV-2, and these considerations raise the possibility that spermatozoa could act as potential vectors of this highly infectious disease. This review summarizes the gender differences in the pathogenesis and clinical manifestations of COVID-19 and proposes the possible mechanism of orchitis caused by SARS-CoV-2 and the potential transmission route of the virus. In the context of the pandemic, these data will improve the understanding of the poor clinical outcomes in male patients with COVID-19 and the design of new strategies to prevent and treat SARS-CoV-2 infection.