Euthyroid Sick Syndrome as a Prognostic Indicator of COVID-19 Pulmonary Involvement,Associated With Poorer Disease Prognosis and Increased Mortality

ObjectiveThe prevalence of euthyroid sick syndrome (ESS) and its association with the prognosis of COVID-19 and mortality in patients with lung involvement in COVID-19 have not yet been elucidated.MethodsClinical and laboratory data of patients with COVID-19 with or without ESS were collected retrospectively and analyzed on admission. All subjects were admitted to the Department of Internal Diseases and Clinical Pharmacology at Bieganski Hospital between December 2020 and April 2021.ResultsIn total, 310 medical records of patients with COVID-19 were analyzed retrospectively. Among 215 enrolled patients, 82 cases of ESS were diagnosed. The patients with ESS had higher pro-inflammatory factor levels, longer hospitalizations, and a higher risk of requiring high-flow nasal oxygen therapy or intubation than the patients without ESS. The Kaplan-Meier curve indicated that the patients with ESS had a lower probability of survival when computed tomography showed ≤50% parenchymal involvement compared with that in patients without ESS. However, no differences in mortality were noted in those with more than 50% parenchymal involvement. The survival curve showed that ESS was associated with a higher risk of mortality during hospitalization.ConclusionESS is closely associated with a poor prognosis, including longer hospitalizations, more frequent intubation, transfer to the intensive care unit, and a higher mortality rate in patients with COVID-19. ESS is a potential prognostic predictor of survival, regardless of lung involvement in COVID-19.     

C-reactive protein as an early predictor of COVID-19 severity

BackgroundData for predicting severity of patients with COVID-19 infection are sparse and still under investigation. We retrospectively studied whether the admission serum C-reactive protein level (CRP) can serve as nearly predictor of disease severity during COVID-19 infection in comparison with other hematologic and inflammatory markers.MethodsWe included all consecutive patients who were admitted in Cheikh Khalifa International University Hospital, Casablanca, Morocco, between February to April 2020, with a confirmed diagnosis of COVID-19 infection using SARS-CoV-2 viral nucleic acid via RT-PCR. The complete blood count and serum CRP level were routinely measured on admission. All clinical and laboratory data of patients were collected and analyzed. The classification of the disease severity was in accordance with the clinical classification of the WHO interim guidance, and the management of patients were adapted to the national management guideline. We estimated receiver operating characteristic (ROC) curves of blood routine parameters as well as their association with COVID-19 disease severity.Results145 COVID-19 patients were included in the study. The median age (range) was 50 (32-63) years, and 75 (51.7%) were men. 101 patients were classified in the non-severe group and 44 patients in the severe group. Based on disease severity, significant differences were observed in the age, gender, comorbidities, and respiratory symptom. Similarly, the biological analysis found significant differences for the neutrophil count, lymphocyte count, eosinophil count, and CRP level. However, according to ROC curves of these laboratory biomarkers, the AUC of CRP at 0.872 was significantly higher than all other parameters. Further, CRP was independently associated with severity of COVID-19 disease (OR = 1.11, 95% IC (1.01-1.22) and or = 1.13, 95% IC (1.04-1.23)).ConclusionsThis study found that the CRP level at admission represent a simple and independent factor that can be useful for early detection of severity during COVID-19 and the easy guidance of primary care.     

Prognostic serum biomarkers in cancer patients with COVID-19: A systematic review

PurposeCancer patients with COVID-19 likely express biomarker changes in circulation. However, the biomarkers used in SARS-CoV-2 infected cancer patients for COVID-19 severity and prognosis are largely unclear. Therefore, this systematic review aims to determine what biomarkers were measured in cancer patients with COVID-19 and their prognostic utility.MethodsA systematic literature review in PubMed, Embase, and Scopus was performed on June 16th, 2021. The search keywords coronavirus, neoplasm, biomarkers, and disease progression were used to filter out 17 eligible studies, which were then carefully evaluated.ResultsA total of 4,168 patients, 16 types of cancer, and 60 biomarkers were included. Seven up-regulated markers, including CRP, d-dimer, ferritin, IL-2R, IL-6, LDH, and PCT, were identified in eligible studies. Albumin and hemoglobin were significantly down-regulated in cancer patients with COVID-19. Moreover, we observed that the SARS-CoV-2 infected cancer patients with lower CRP, ferritin, and LDH levels successfully survived from COVID-19 treatments.ConclusionSeveral important clinical biomarkers, such as CRP, ferritin, and LDH, may serve as the prognostic markers to predict the outcomes following COVID-19 treatment and monitor the deterioration of COVID-19 in cancer patients.     

Diagnosis-wide analysis of COVID-19 complications: an exposure-crossover study

BACKGROUND:Many studies reporting coronavirus disease 2019 (COVID-19) complications have involved case series or small cohorts that could not establish a causal association with COVID-19 or provide risk estimates in different care settings. We sought to study all possible complications of COVID-19 to confirm previously reported complications and to identify potential complications not yet known.METHODS:Using United States health claims data, we compared the frequency of all International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis codes occurring before and after the onset of the COVID-19 pandemic in an exposure-crossover design. We included patients who received a diagnosis of COVID-19 between Mar. 1, 2020, and Apr. 30, 2020, and computed risk estimates and odds ratios (ORs) of association with COVID-19 for every ICD-10-CM diagnosis code.RESULTS:Among 70 288 patients with COVID-19, 69 of 1724 analyzed ICD-10-CM diagnosis codes were significantly associated with COVID-19. Disorders showing both strong association with COVID-19 and high absolute risk included viral pneumonia (OR 177.63, 95% confidence interval [CI] 147.19–214.37, absolute risk 27.6%), respiratory failure (OR 11.36, 95% CI 10.74–12.02, absolute risk 22.6%), acute kidney failure (OR 3.50, 95% CI 3.34–3.68, absolute risk 11.8%) and sepsis (OR 4.23, 95% CI 4.01–4.46, absolute risk 10.4%). Disorders showing strong associations with COVID-19 but low absolute risk included myocarditis (OR 8.17, 95% CI 3.58–18.62, absolute risk 0.1%), disseminated intravascular coagulation (OR 11.83, 95% CI 5.26–26.62, absolute risk 0.1%) and pneumothorax (OR 3.38, 95% CI 2.68–4.26, absolute risk 0.4%).INTERPRETATION:We confirmed and provided risk estimates for numerous complications of COVID-19. These results may guide prognosis, treatment decisions and patient counselling.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel strain of coronavirus that has been identified as the cause of the coronavirus disease 2019 (COVID-19) pandemic. As of Nov. 20, 2020, more than 50 million people have received a diagnosis of COVID-19 globally.¹ The clinical spectrum of disease is wide and can range from symptoms typical of the common cold to respiratory failure and death.² Most patients have mild symptoms and can be managed as outpatients, but as many as 20% have a severe form of the disease requiring admission to hospital, commonly presenting with hypoxia secondary to pneumonia.³Studies also show that COVID-19 is associated with a wide variety of nonrespiratory sequelae, including endothelial, thrombotic, cardiac, inflammatory, neurologic and other complications. ^4–9 Whether these associations are causal is not well established, as many of these findings originate from case reports, which are prone to publication bias and cannot provide risk estimates, or from cohort studies that often do not provide relative risk estimates.An alternative strategy for identifying potential complications of COVID-19 is studying all possible complications as captured in International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10 CM) diagnosis codes, which allows for the discovery of unreported complications and can confirm previously identified ones. The objective of our study was to analyze all diagnoses associated with COVID-19, to identify those that could be complications of the disease and to present both the absolute risk and relative odds of any complications identified.     

Long COVID in Patients With Mild to Moderate Disease: Do Thyroid Function and Autoimmunity Play a Role?

ObjectivePost-acute sequelae of coronavirus disease 2019 (COVID-19) or long COVID (LC) is an emerging global health issue. Fatigue is a common feature. Whether thyroid function and autoimmunity play a role is uncertain. We aimed to evaluate the prevalence and predictors of LC and the potential role of thyroid function and autoimmunity in LC.MethodsWe included consecutive adults without a known thyroid disorder who were admitted to a major COVID-19 center for confirmed COVID-19 from July to December 2020. Thyroid function tests and antithyroid antibodies were measured for all patients on admission and at follow-up. LC was defined by the presence or persistence of symptoms upon follow-up.ResultsIn total, 204 patients (median age, 55.0 years; 95 men [46.6%]) were reassessed at a median of 89 days (interquartile range, 69-99) after acute COVID-19. Of the 204 patients, 41 (20.1%) had LC. Female sex (adjusted odds ratio, 2.48; P = .018) and severe acute respiratory syndrome coronavirus 2 polymerase chain reaction cycle threshold value of <25 on admission (adjusted odds ratio, 2.84; P = .012) independently predicted the occurrence of LC. Upon follow-up, most abnormal thyroid function tests in acute COVID-19 resolved, and incident thyroid dysfunction was rare. Nonetheless, we observed incident antithyroid peroxidase (anti-TPO) positivity. Although baseline or follow-up thyroid function tests were not associated with the occurrence of LC, among 172 patients with symptomatic acute COVID-19, symptom resolution was more likely in those with positive anti-TPO upon follow-up (P = .043).ConclusionLC is common among COVID-19 survivors, with females and those with higher viral load in acute COVID-19 particularly being vulnerable. The observation of incident anti-TPO positivity warrants further follow-up for thyroid dysfunction. Whether anti-TPO plays a protective role in LC remains to be elucidated.     

Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: A cohort study using linked primary care,secondary care,and death registration data in the OpenSAFELY platform

BackgroundThere is concern about medium to long-term adverse outcomes following acute Coronavirus Disease 2019 (COVID-19), but little relevant evidence exists. We aimed to investigate whether risks of hospital admission and death, overall and by specific cause, are raised following discharge from a COVID-19 hospitalisation.Methods and findingsWith the approval of NHS-England, we conducted a cohort study, using linked primary care and hospital data in OpenSAFELY to compare risks of hospital admission and death, overall and by specific cause, between people discharged from COVID-19 hospitalisation (February to December 2020) and surviving at least 1 week, and (i) demographically matched controls from the 2019 general population; and (ii) people discharged from influenza hospitalisation in 2017 to 2019. We used Cox regression adjusted for age, sex, ethnicity, obesity, smoking status, deprivation, and comorbidities considered potential risk factors for severe COVID-19 outcomes.We included 24,673 postdischarge COVID-19 patients, 123,362 general population controls, and 16,058 influenza controls, followed for ≤315 days. COVID-19 patients had median age of 66 years, 13,733 (56%) were male, and 19,061 (77%) were of white ethnicity. Overall risk of hospitalisation or death (30,968 events) was higher in the COVID-19 group than general population controls (fully adjusted hazard ratio [aHR] 2.22, 2.14 to 2.30, p < 0.001) but slightly lower than the influenza group (aHR 0.95, 0.91 to 0.98, p = 0.004). All-cause mortality (7,439 events) was highest in the COVID-19 group (aHR 4.82, 4.48 to 5.19 versus general population controls [p < 0.001] and 1.74, 1.61 to 1.88 versus influenza controls [p < 0.001]). Risks for cause-specific outcomes were higher in COVID-19 survivors than in general population controls and largely similar or lower in COVID-19 compared with influenza patients. However, COVID-19 patients were more likely than influenza patients to be readmitted or die due to their initial infection or other lower respiratory tract infection (aHR 1.37, 1.22 to 1.54, p < 0.001) and to experience mental health or cognitive-related admission or death (aHR 1.37, 1.02 to 1.84, p = 0.039); in particular, COVID-19 survivors with preexisting dementia had higher risk of dementia hospitalisation or death (age- and sex-adjusted HR 2.47, 1.37 to 4.44, p = 0.002). Limitations of our study were that reasons for hospitalisation or death may have been misclassified in some cases due to inconsistent use of codes, and we did not have data to distinguish COVID-19 variants.ConclusionsIn this study, we observed that people discharged from a COVID-19 hospital admission had markedly higher risks for rehospitalisation and death than the general population, suggesting a substantial extra burden on healthcare. Most risks were similar to those observed after influenza hospitalisations, but COVID-19 patients had higher risks of all-cause mortality, readmission or death due to the initial infection, and dementia death, highlighting the importance of postdischarge monitoring.

Krishnan Bhaskaran and co-workers study health outcomes after admission with COVID-19 and subsequent discharge.     

Incidence and impact of cardiac arrhythmias in coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis

BackgroundStudies have shown that cardiac arrhythmias may occur in up to 44% of patients with severe coronavirus disease 2019 (COVID-19) and has been associated with an increased risk of death. This systematic review and meta-analysis aimed to evaluate the incidence of cardiac arrhythmias in patients with COVID-19 and their implications on patient prognosis.MethodsWe performed a systematic literature search from PubMed, SCOPUS, Europe PMC, Cochrane Central Databases, and Google Scholar + Preprint Servers. The primary endpoint of the study was poor outcomes including mortality, severe COVID-19, and the need for ICU care.ResultsA total of 4 studies including 784 patients were analyzed. The incidence of arrhythmia in patients with COVID-19 was 19% (9–28%; I²: 91.45). Arrhythmia occurred in 48% (38–57%; I²: 48.08) of patients with poor outcome and 6% (1–12%; I²: 85.33%) of patients without poor outcome. Patients with COVID-19 experiencing arrhythmia had an increased risk of poor outcome (RR 7.96 [3.77, 16.81], p < 0.001; I²: 71.1%). The funnel-plot analysis showed an asymmetrical funnel plot with most of the studies on the right side of the effect estimate. The regression-based Egger’s test showed indication of small-study effects (p = 0.001).ConclusionCardiac arrhythmias were significantly associated with an increased risk of poor outcome in COVID-19. Arrhythmias were observed in 19% of patients with COVID-19 and in 48% of patients with COVID-19 and poor outcomes.     

Correlation of Hemoglobin A1C and Outcomes in Patients Hospitalized With COVID-19

ObjectiveDiabetes is a known risk factor for severe coronavirus disease 2019 (COVID-19). We conducted this study to determine if there is a correlation between hemoglobin A1C (HbA1C) level and poor outcomes in hospitalized patients with diabetes and COVID-19.MethodsThis is a retrospective, single-center, observational study of patients with diabetes (defined by an HbA1C level of ≥6.5% or known medical history of diabetes) who had a confirmed case of COVID-19 and required hospitalization. All patients were admitted to our institution between March 3, 2020, and May 5, 2020. HbA1C results for each patient were divided into quartiles: 5.1% to 6.7% (32-50 mmol/mol), 6.8% to 7.5% (51-58 mmol/mol), 7.6% to 8.9% (60-74 mmol/mol), and >9% (>75 mmol/mol). The primary outcome was in-hospital mortality. Secondary outcomes included admission to an intensive care unit, invasive mechanical ventilation, acute kidney injury, acute thrombosis, and length of hospital stay.ResultsA total of 506 patients were included. The number of deaths within quartiles 1 through 4 were 30 (25%), 37 (27%), 34 (27%), and 24 (19%), respectively. There was no statistical difference in the primary or secondary outcomes among the quartiles, except that acute kidney injury was less frequent in quartile 4.ConclusionThere was no significant association between HbA1C level and adverse clinical outcomes in patients with diabetes who are hospitalized with COVID-19. HbA1C levels should not be used for risk stratification in these patients.     

Population-based evaluation of the effectiveness of nirmatrelvir–ritonavir for reducing hospital admissions and mortality from COVID-19

Background:A randomized controlled trial involving a high-risk, unvaccinated population that was conducted before the Omicron variant emerged found that nirmatrelvir–ritonavir was effective in preventing progression to severe COVID-19. Our objective was to evaluate the effectiveness of nirmatrelvir–ritonavir in preventing severe COVID-19 while Omicron and its subvariants predominate.Methods:We conducted a population-based cohort study in Ontario that included all residents who were older than 17 years of age and had a positive polymerase chain reaction test for SARS-CoV-2 between Apr. 4 and Aug. 31, 2022. We compared patients treated with nirmatrelvir–ritonavir with patients who were not treated and measured the primary outcome of hospital admission from COVID-19 or all-cause death at 1–30 days, and a secondary outcome of all-cause death. We used weighted logistic regression to calculate weighted odds ratios (ORs) with confidence intervals (CIs) using inverse probability of treatment weighting (IPTW) to control for confounding.Results:The final cohort included 177 545 patients, 8876 (5.0%) who were treated with nirmatrelvir–ritonavir and 168 669 (95.0%) who were not treated. The groups were well balanced with respect to demographic and clinical characteristics after applying stabilized IPTW. We found that the occurrence of hospital admission or death was lower in the group given nirmatrelvir–ritonavir than in those who were not (2.1% v. 3.7%; weighted OR 0.56, 95% CI 0.47–0.67). For death alone, the weighted OR was 0.49 (95% CI 0.39–0.62). Our findings were similar across strata of age, drug–drug interactions, vaccination status and comorbidities. The number needed to treat to prevent 1 case of severe COVID-19 was 62 (95% CI 43–80), which varied across strata.Interpretation:Nirmatrelvir–ritonavir was associated with significantly reduced odds of hospital admission and death from COVID-19, which supports use to treat patients with mild COVID-19 who are at risk for severe disease.

Antiviral therapies to treat COVID-19 and prevent severe outcomes such as hospital admission and death are valuable tools in the global pandemic response. The Evaluation of protease inhibition for COVID-19 in high-risk patients (EPIC-HR) randomized controlled trial (RCT) of nirmatrelvir–ritonavir identified an 89% reduction in progression to severe COVID-19 in participants at high risk of severe disease who were treated, compared with placebo.¹ However, the trial was conducted between July and December 2021, which was before the emergence of the Omicron variant that is less virulent than the progenitor virus,² and excluded vaccinated people, as well as those taking medications with potential drug interactions.¹ The Evaluation of protease inhibition for COVID-19 in standard-risk patients (EPIC-SR) trial recently reported nonsignificant findings in a press release.³In real-world evaluations of nirmatrelvir–ritonavir while the Omicron variant and its subvariants were predominating, a significant protective effect was seen in adults 65 years of age and older in Israel.⁴ A retrospective cohort study involving patients with COVID-19 who attended designated outpatient clinics in Hong Kong between Feb. 16 and Mar. 31, 2022, identified a reduced risk of hospital admission in adults when given nirmatrelvir–ritonavir, albeit attenuated compared with the EPIC-HR trial.⁵ Studies that have stratified participants by vaccination status identified similar reductions in relative risk in vaccinated cohorts but with smaller reductions in absolute risk because of the lower baseline risk of hospital admission or death from COVID-19.^4,6,7 Observational studies have risks of bias that include residual confounding and immortal time bias.⁸In Ontario, nirmatrelvir–ritonavir became widely available and funded for all patients in the community by April 2022, with clinical criteria set by the government limiting access only to patients who were older, had comorbidities or were undervaccinated.^9,10 The Ontario COVID-19 Science Advisory Table provided clinical practice guidance to Ontario clinicians on the use of therapeutics for COVID-19 with stricter high-risk criteria based on patients who were most likely to benefit from the limited supplies of antiviral drug at the time.¹¹ A large proportion of patients who received nirmatrelvir–ritonavir in Ontario would have been excluded from the EPIC-HR trial population (e.g., those previously vaccinated or receiving concomitant medications with significant drug–drug interactions). Observational data evaluating use of nirmatrelvir–ritonavir can inform future policy and guidelines. Our objective was to evaluate the effectiveness of nirmatrelvir–ritonavir on health outcomes, including hospital admission and death from COVID-19, while Omicron and its subvariants predominated.     

Predictors of Severe COVID-19 in Patients With Diabetes: A Multicenter Review

ObjectiveDiabetes is an independent risk factor for severe SARS-CoV-2 infections. This study aims to elucidate the risk factors predictive of more severe outcomes in patients with diabetes by comparing the clinical characteristics of those requiring inpatient admissions with those who remain outpatient.MethodsA retrospective review identified 832 patients—631 inpatients and 201 outpatients—with diabetes and a positive SARS-CoV-2 test result between March 1 and June 15, 2020. Comparisons between the outpatient and inpatient cohorts were conducted to identify risk factors associated with severity of disease determined by admission rate and mortality. Previous dipeptidyl peptidase 4 inhibitor use and disease outcomes were analyzed.ResultsRisk factors for increased admission included older age (odds ratio [OR], 1.04 [95% CI, 1.01-1.06]; P = .003), the presence of chronic kidney disease (OR, 2.32 [1.26-4.28]; P = .007), and a higher hemoglobin A1c at the time of admission (OR, 1.25 [1.12-1.39]; P < .001). Lower admission rates were seen in those with commercial insurance. Increased mortality was seen in individuals with older age (OR, 1.09 [1.07-1.11]; P < .001), higher body mass index number (OR, 1.04 [1.01-1.07]; P = .003), and higher hemoglobin A1c value at the time of diagnosis of COVID-19 (OR, 1.12 [1.01-1.24]; P = .028) and patients requiring hospitalization. Lower mortality was seen in those with hyperlipidemia. Dipeptidyl peptidase 4 inhibitor use prior to COVID-19 infection was not associated with a decreased hospitalization rate.ConclusionThis retrospective review offers the first analysis of outpatient predictors for admission rate and mortality of COVID-19 in patients with diabetes.     

Characteristics and outcomes of hospital admissions for COVID-19 and influenza in the Toronto area

BACKGROUND:Patient characteristics, clinical care, resource use and outcomes associated with admission to hospital for coronavirus disease 2019 (COVID-19) in Canada are not well described.METHODS:We described all adults with COVID-19 or influenza discharged from inpatient medical services and medical–surgical intensive care units (ICUs) between Nov. 1, 2019, and June 30, 2020, at 7 hospitals in Toronto and Mississauga, Ontario. We compared patient outcomes using multivariable regression models, controlling for patient sociodemographic factors and comorbidity level. We validated the accuracy of 7 externally developed risk scores to predict mortality among patients with COVID-19.RESULTS:There were 1027 hospital admissions with COVID-19 (median age 65 yr, 59.1% male) and 783 with influenza (median age 68 yr, 50.8% male). Patients younger than 50 years accounted for 21.2% of all admissions for COVID-19 and 24.0% of ICU admissions. Compared with influenza, patients with COVID-19 had significantly greater in-hospital mortality (unadjusted 19.9% v. 6.1%, adjusted relative risk [RR] 3.46, 95% confidence interval [CI] 2.56–4.68), ICU use (unadjusted 26.4% v. 18.0%, adjusted RR 1.50, 95% CI 1.25–1.80) and hospital length of stay (unadjusted median 8.7 d v. 4.8 d, adjusted rate ratio 1.45, 95% CI 1.25–1.69). Thirty-day readmission was not significantly different (unadjusted 9.3% v. 9.6%, adjusted RR 0.98, 95% CI 0.70–1.39). Three points-based risk scores for predicting in-hospital mortality showed good discrimination (area under the receiver operating characteristic curve [AUC] ranging from 0.72 to 0.81) and calibration.INTERPRETATION:During the first wave of the pandemic, admission to hospital for COVID-19 was associated with significantly greater mortality, ICU use and hospital length of stay than influenza. Simple risk scores can predict in-hospital mortality in patients with COVID-19 with good accuracy.

International studies report that patients admitted to hospital with coronavirus disease 2019 (COVID-19) have high rates of critical illness and mortality.^1–5 Two small Canadian case series have described care for critically ill patients with COVID-19 and found mortality rates of up to 25%.^6,7 However, outcomes of patients admitted to hospital for COVID-19 in Canada are not well described, particularly outside of intensive care units (ICUs). Case fatality rates for COVID-19 vary dramatically worldwide,⁸ and outcomes of patients admitted to hospital for COVID-19 in Canada may differ from other countries because of differences in populations, public health and health care systems.Seasonal influenza is a useful comparator for COVID-19^9–11 as it is another respiratory virus, familiar to the general public, with high rates of morbidity and mortality. The purpose of this study was to describe patient characteristics, resource use, clinical care and outcomes for patients admitted to hospital with COVID-19 in Ontario, Canada, using influenza as a comparator. We also validated the performance of various prognostic risk scores for in-hospital mortality among patients with COVID-19.     

Prevalence and characteristics of malaria among COVID-19 individuals: A systematic review,meta-analysis,and analysis of case reports

BackgroundThe world population is currently at a very high risk of Coronavirus disease-2019 (COVID-19), caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). People who live in malaria-endemic areas and get infected by SARS-CoV-2 may be at increased risk of severe COVID-19 or unfavorable disease outcomes if they ignore their malaria status. Therefore, the present study aimed to synthesize, qualitatively and quantitatively, information on the prevalence and characteristics of malaria infection among COVID-19-infected individuals. The findings will help us better understand this particular comorbidity during the COVID-19 pandemic.MethodsThe systematic review protocol was registered at the International Prospective Register of Systematic Reviews (PROSPERO) with the identification number: CRD42021247521. We searched for studies reporting on the coinfection of COVID-19 and malaria in PubMed, Web of Science, and Scopus from inception to March 27, 2021 using Medical Subject Headings (MeSH) terms. The study’s methodological quality in the search output was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Tools for cross-sectional study. The pooled prevalence of Plasmodium spp. infection among patients infected with COVID-19 was estimated using the random effect model and then graphically presented as forest plots. The heterogeneity among the included studies was assessed using Cochrane Q and I² statistics. The characteristics of patients co-infected with COVID-19 and malaria were derived from case reports and series and were formally analyzed using simple statistics.ResultsTwelve of 1,207 studies reporting the coinfection of COVID-19 and malaria were selected for further analysis. Results of quantitative synthesis show that the pooled prevalence of Plasmodium spp. infection (364 cases) among COVID–19 individuals (1,126 cases) is 11%, with a high degree of heterogeneity (95% CI: 4%–18%, I²: 97.07%, 5 studies). Most of the coinfections were reported in Nigeria (336 cases), India (27 cases), and the Democratic Republic of Congo (1 case). Results of qualitative synthesis indicate that patients with coinfection are typically symptomatic at presentation with mild or moderate parasitemia. An analysis of case reports and series indicates that co-infected individuals often display thrombocytopenia, lymphopenia, and elevated bilirubin levels. Among four patients (30%) who required treatment with intravenous artesunate, one experienced worsened clinical status after administering the drug. One serious outcome of coinfection involved a pregnant woman who experienced fetal abortion due to the initial misdiagnosis of malaria.ConclusionsAll individuals in malaria-endemic regions who are febrile or display symptoms of COVID-19 should be evaluated for malaria to avoid serious complications. Further prospective studies are required to investigate the burden and outcomes of COVID-19 in malaria-endemic regions. Prompt management is required to prevent serious outcomes in individuals co-infected with COVID-19 and malaria.     

Incidence,co-occurrence,and evolution of long-COVID features: A 6-month retrospective cohort study of 273,618 survivors of COVID-19

BackgroundLong-COVID refers to a variety of symptoms affecting different organs reported by people following Coronavirus Disease 2019 (COVID-19) infection. To date, there have been no robust estimates of the incidence and co-occurrence of long-COVID features, their relationship to age, sex, or severity of infection, and the extent to which they are specific to COVID-19. The aim of this study is to address these issues.Methods and findingsWe conducted a retrospective cohort study based on linked electronic health records (EHRs) data from 81 million patients including 273,618 COVID-19 survivors. The incidence and co-occurrence within 6 months and in the 3 to 6 months after COVID-19 diagnosis were calculated for 9 core features of long-COVID (breathing difficulties/breathlessness, fatigue/malaise, chest/throat pain, headache, abdominal symptoms, myalgia, other pain, cognitive symptoms, and anxiety/depression). Their co-occurrence network was also analyzed. Comparison with a propensity score–matched cohort of patients diagnosed with influenza during the same time period was achieved using Kaplan–Meier analysis and the Cox proportional hazard model. The incidence of atopic dermatitis was used as a negative control.Among COVID-19 survivors (mean [SD] age: 46.3 [19.8], 55.6% female), 57.00% had one or more long-COVID feature recorded during the whole 6-month period (i.e., including the acute phase), and 36.55% between 3 and 6 months. The incidence of each feature was: abnormal breathing (18.71% in the 1- to 180-day period; 7.94% in the 90- to180-day period), fatigue/malaise (12.82%; 5.87%), chest/throat pain (12.60%; 5.71%), headache (8.67%; 4.63%), other pain (11.60%; 7.19%), abdominal symptoms (15.58%; 8.29%), myalgia (3.24%; 1.54%), cognitive symptoms (7.88%; 3.95%), and anxiety/depression (22.82%; 15.49%). All 9 features were more frequently reported after COVID-19 than after influenza (with an overall excess incidence of 16.60% and hazard ratios between 1.44 and 2.04, all p < 0.001), co-occurred more commonly, and formed a more interconnected network. Significant differences in incidence and co-occurrence were associated with sex, age, and illness severity. Besides the limitations inherent to EHR data, limitations of this study include that (i) the findings do not generalize to patients who have had COVID-19 but were not diagnosed, nor to patients who do not seek or receive medical attention when experiencing symptoms of long-COVID; (ii) the findings say nothing about the persistence of the clinical features; and (iii) the difference between cohorts might be affected by one cohort seeking or receiving more medical attention for their symptoms.ConclusionsLong-COVID clinical features occurred and co-occurred frequently and showed some specificity to COVID-19, though they were also observed after influenza. Different long-COVID clinical profiles were observed based on demographics and illness severity.

Maxime Taquet and colleagues investigate the incidence, co-occurrence and evolution of long-COVID features in more than a quarter of a million people.     

The Impact of COVID-19 Viral Infection on the Hypothalamic-Pituitary-Adrenal Axis

ObjectiveTo study the adrenocortical response to an acute coronavirus disease-2019 (COVID-19) infection.MethodsMorning plasma cortisol, adrenocorticotropic hormone (ACTH), and dehydroepiandrosterone sulfate levels were measured in 28 consecutive patients with COVID-19 (16 men, 12 women, median age 45.5 years, range 25-69 years) on day 1 to 2 of hospital admission. These tests were repeated twice in 20 patients and thrice in 15 patients on different days. The hormone levels were correlated with severity of the disease.ResultsThe median morning cortisol level was 196 (31-587) nmol/L. It was <100 nmol/L in 8 patients (28.6%), <200 nmol/L in 14 patients (50%), and <300 nmol/L in 18 patients (64.3%). The corresponding ACTH values had a median of 18.5 ng/L (range 4-38 ng/L), and the ACTH level was <10 ng/L in 7 patients (26.9%), <20 ng/L in 17 patients (60.7%), and <30 ng/L in 23 patients (82.1%). The repeated testing on different days showed a similar pattern. Overall, if a cutoff level of <300 nmol/L is considered abnormal in the setting of acute disease, 9 patients (32%) had cortisol levels below this limit, regardless of whether the test was done only once (3 patients) or 3 times (6 patients). When the disease was more severe, the patients had lower cortisol and ACTH levels, suggesting a direct link between the COVID-19 infection and impaired glucocorticoid response.ConclusionUnexpectedly, the adrenocortical response in patients with COVID-19 infection was impaired, and a significant percentage of the patients had plasma cortisol and ACTH levels consistent with central adrenal insufficiency.     

Heart rate variability as a marker of cardiovascular dysautonomia in post-COVID-19 syndrome using artificial intelligence

IntroductionCardiovascular dysautonomia comprising postural orthostatic tachycardia syndrome (POTS) and orthostatic hypotension (OH) is one of the presentations in COVID-19 recovered subjects. We aim to determine the prevalence of cardiovascular dysautonomia in post COVID-19 patients and to evaluate an Artificial Intelligence (AI) model to identify time domain heart rate variability (HRV) measures most suitable for short term ECG in these subjects.MethodsThis observational study enrolled 92 recently COVID-19 recovered subjects who underwent measurement of heart rate and blood pressure response to standing up from supine position and a 12-lead ECG recording for 60 s period during supine paced breathing. Using feature extraction, ECG features including those of HRV (RMSSD and SDNN) were obtained. An AI model was constructed with ShAP AI interpretability to determine time domain HRV features representing post COVID-19 recovered state. In addition, 120 healthy volunteers were enrolled as controls.ResultsCardiovascular dysautonomia was present in 15.21% (OH:13.04%; POTS:2.17%). Patients with OH had significantly lower HRV and higher inflammatory markers. HRV (RMSSD) was significantly lower in post COVID-19 patients compared to healthy controls (13.9 ± 11.8 ms vs 19.9 ± 19.5 ms; P = 0.01) with inverse correlation between HRV and inflammatory markers. Multiple perceptron was best performing AI model with HRV(RMSSD) being the top time domain HRV feature distinguishing between COVID-19 recovered patients and healthy controls.ConclusionPresent study showed that cardiovascular dysautonomia is common in COVID-19 recovered subjects with a significantly lower HRV compared to healthy controls. The AI model was able to distinguish between COVID-19 recovered patients and healthy controls.     

Increased sTREM-1 plasma concentrations are associated with poor clinical outcomes in patients with COVID-19

Patients with sepsis display increased concentrations of sTREM-1 (soluble Triggering Receptor Expressed on Myeloid cells 1), and a phase II clinical trial focusing on TREM-1 modulation is ongoing. We investigated whether sTREM-1 circulating concentrations are associated with the outcome of patients with coronavirus disease 2019 (COVID-19) to assess the role of this pathway in COVID-19. This observational study was performed in two independent cohorts of patients with COVID-19. Plasma concentrations of sTREM-1 were assessed after ICU admission (pilot cohort) or after COVID-19 diagnosis (validation cohort). Routine laboratory and clinical parameters were collected from electronic patient files. Results showed sTREM-1 plasma concentrations were significantly elevated in patients with COVID-19 (161 [129–196] pg/ml) compared to healthy controls (104 [75–124] pg/ml; P<0.001). Patients with severe COVID-19 needing ICU admission displayed even higher sTREM-1 concentrations compared to less severely ill COVID-19 patients receiving clinical ward-based care (235 [176–319] pg/ml and 195 [139–283] pg/ml, respectively, P = 0.017). In addition, higher sTREM-1 plasma concentrations were observed in patients who did not survive the infection (326 [207–445] pg/ml) compared to survivors (199 [142–278] pg/ml, P<0.001). Survival analyses indicated that patients with higher sTREM-1 concentrations are at higher risk for death (hazard ratio = 3.3, 95%CI: 1.4–7.8). In conclusion, plasma sTREM-1 concentrations are elevated in patients with COVID-19, relate to disease severity, and discriminate between survivors and non-survivors. This suggests that the TREM-1 pathway is involved in the inflammatory reaction and the disease course of COVID-19, and therefore may be considered as a therapeutic target in severely ill patients with COVID-19.     

COVID-19 compromises iron homeostasis: Transferrin as a target of investigation

ImportanceSince the beginning of the COVID-19 pandemic, numerous metabolic alterations have been observed in individuals with this disease. It is known that SARS-CoV-2 can mimic the action of hepcidin, altering intracellular iron metabolism, but gaps remain in the understanding of possible outcomes in other pathways involved in the iron cycle.ObjectiveTo profile iron, ferritin and hepcidin levels and transferrin receptor gene expression in patients diagnosed with COVID-19 between June 2020 and September 2020.Design, setting and participantsCross-sectional study that evaluated iron metabolism markers in 427 participants, 218 with COVID-19 and 209 without the disease.ExposuresThe primary exposure was positive diagnose to COVID-19 in general population of Santo André and São Bernardo cities. The positive and negative diagnose were determinate through RT-qPCR.Main outcomes and measuresDevido a evidências de alterações do ciclo do ferro em pacientes diagnosticados com COVID-19 e devido a corregulação entre hepcidina e receptor de transferrina, uma análise da expressão gênica deste último, poderia trazer insights sobre o estado de ferro celular. A hipótese foi confirmada, mostrando aumento da expressão de receptor de transferrina concomitante com redução do nível de hepcidina circulante.ResultsSerum iron presented lower values in individuals diagnosed with COVID-19, whereas serum ferritin presented much higher values in infected patients. Elderly subjects had lower serum iron levels and higher ferritin levels, and men with COVID-19 had higher ferritin values than women. Serum hepcidin was lower in the COVID-19 patient group and transferrin receptor gene expression was higher in the infected patient group compared to controls.Conclusions and relevanceCOVID-19 causes changes in several iron cycle pathways, with iron and ferritin levels being markers that reflect the state and evolution of infection, as well as the prognosis of the disease. The increased expression of the transferrin receptor gene suggests increased iron internalization and the mimicry of hepcidin action by SARS-CoV-2, reduces iron export via ferroportin, which would explain the low circulating levels of iron by intracellular trapping.