Risk factors for severe cases of COVID-19: a retrospective cohort study

Criteria and potential predictors of severity in patients with COVID-19

Background

The challenge in treating severe COVID-19 in the absence of targeted medication is enforcing physicians to search carefully for clinical predictors of severity.

Aim

To define the profile of patients at risk of severe COVID-19 and to assess for certain predictors.

Methods

Confirmed COVID-19 cases were classified into the following: group A: mild/moderate cases and group B: severe/critical cases according to the selected criteria. History, radiological assessment, complete blood count, lactate dehydrogenase (LDH), myocardial enzymes, serum ferritin, and D dimer were assessed. Patients were followed for the need of ICU and mechanical ventilation. Duration till conversion, length of stay, and mortality were recorded.

Results

A total of 202 patients were analyzed. Group B had higher age (53.2 ± 12.6 vs 40.3 ± 10.3, P < 0.001), more prevalence of DM (60.61% vs 16.57% P < 0.001), hypertension (51.52% vs 20.12%, P < 0.001), ischemic heart (27.27% vs 3.55%, P < 0.001), bronchial asthma (36.36% vs 3.55%, P < 0.001), COPD (9.09% vs 1.18%, P = 0.03), higher mean platelet volume (MPV) (12.76 ± 7.13 vs 10.51 ± 7.78 (fL), P < 0.001), higher serum ferritin (954 ± 138 vs 447 ± 166 ng/ml, P < 0.001), higher LDH (604 ± 220 vs 384 ± 183 U/L, P-value < 0.001), higher creatine phosphokinase (24.27 ± 5.82 vs 16.4 ± 4.87 IU/L, P < 0.001), and higher mortality (30.3% vs 0.6%, P < 0.001). Multivariate regression of predictors of severity identified three predictors; age, MPV, serum ferritin, and IHD.

Conclusions

The current study places of interest the characteristic host-related features of severe COVID-19 and draws attention to potential predictors.

COVID-19: risk factors for severe cases of the Delta variant

BACKGROUND

Since April 2021, the SARS-CoV-2 (B.1.167) Delta variant has been rampant worldwide. Recently, this variant has spread in Guangzhou, China. Our objective was to characterize the clinical features and risk factors of severe cases of the Delta variant in Guangzhou.

METHODS

A total of 144 patients with the Delta variant were enrolled, and the data between the severe and non-severe groups were compared. Logistic regression methods and Cox multivariate regression analysis were used to investigate the risk factors of severe cases.

RESULTS

The severity of the Delta variant was 11.1%. Each 1-year increase in age (OR, 1.089; 95% CI, 1.035-1.147; P = 0.001) and each 1-μmol/L increase in total bilirubin (OR, 1.198; 95% CI, 1.021-1.406; P = 0.039) were risk factors for severe cases. Moreover, the risk of progression to severe cases increased 13.444-fold and 3.922-fold when the age was greater than 58.5 years (HR, 13.444; 95% CI, 2.989-60.480; P = 0.001) or the total bilirubin level was greater than 7.23 μmol/L (HR, 3.922; 95% CI, 1.260-12.207; P = 0.018), respectively.

CONCLUSION

Older age and elevated total bilirubin were independent risk factors for severe cases of the Delta variant in Guangzhou, especially if the age was greater than 58.5 years or the total bilirubin level was greater than 7.23 μmol/L.

Chronic Diseases as a Predictor for Severity and Mortality of COVID-19: A Systematic Review With Cumulative Meta-Analysis

Introduction: Given the ongoing coronavirus disease 2019 (COVID-19) pandemic and the consequent global healthcare crisis, there is an urgent need to better understand risk factors for symptom deterioration and mortality among patients with COVID-19. This systematic review aimed to meet the need by determining the predictive value of chronic diseases for COVID-19 severity and mortality.

Methods: We searched PubMed, Embase, Web of Science, and Cumulative Index to Nursing and Allied Health Complete to identify studies published between December 1, 2019, and December 31, 2020. Two hundred and seventeen observational studies from 26 countries involving 624,986 patients were included. We assessed the risk of bias of the included studies and performed a cumulative meta-analysis.

Results: We found that among COVID-19 patients, hypertension was a very common condition and was associated with higher severity, intensive care unit (ICU) admission, acute respiratory distress syndrome, and mortality. Chronic obstructive pulmonary disease was the strongest predictor for COVID-19 severity, admission to ICU, and mortality, while asthma was associated with a reduced risk of COVID-19 mortality. Patients with obesity were at a higher risk of experiencing severe symptoms of COVID-19 rather than mortality. Patients with cerebrovascular disease, chronic liver disease, chronic renal disease, or cancer were more likely to become severe COVID-19 cases and had a greater probability of mortality.

Conclusions: COVID-19 patients with chronic diseases were more likely to experience severe symptoms and ICU admission and faced a higher risk of mortality. Aggressive strategies to combat the COVID-19 pandemic should target patients with chronic diseases as a priority.

Myoglobin Offers Higher Accuracy Than Other Cardiac-Specific Biomarkers for the Prognosis of COVID-19

Although sporadic studies have shown that myoglobin may have better prognostic performance than other cardiac markers in COVID-19, a comprehensive comparative study is lacking. Herein, we retrospectively analyzed the clinical and laboratory data of COVID-19 patients admitted to the Guanggu Campus of Wuhan Tongji Hospital from February 9, 2020 to March 30, 2020, intending to compare the prognostic accuracy of three commonly used cardiac markers on COVID-19 mortality. Our results revealed that abnormal increases in myocardial biomarkers were associated with a significantly increased risk of in-hospital mortality with COVID-19. Interestingly, myoglobin, a non-cardiac-specific biomarker, also expressed in skeletal myocytes, had even higher prognostic accuracy than cardiac-specific biomarkers such as high-sensitivity troponin I (hs-TnI) and creatine kinase-MB (CK-MB). More importantly, multivariate Cox analysis showed that myoglobin, rather than hs-TnI or CK-MB, was independently prognostic for in-hospital mortality in COVID-19. These results were further confirmed by subgroup analyses of patients with severe and critical illnesses and those without a history of cardiovascular disease. Our findings suggest that myoglobin may be a reliable marker of illness reflecting general physiological disturbance and help to assess prognosis and treatment response in patients with COVID-19.

Clinical Characteristics and Factors Associated with Disease Progression of Mild to Moderate COVID-19 Patients in a Makeshift (Fangcang) Hospital: A Retrospective Cohort Study

Objective

Information regarding the epidemiology and clinical features of mild to moderate patients caused by COVID-19 in Fangcang Hospital is scarce. Through a retrospective cohort study, the clinical characteristics of COVID-19 patients in Dongxihu Fangcang shelter hospitals were analyzed, and the factors that affected the disease progression of COVID-19 patients were explored.

Methods

The clinical characteristics of 714 patients with COVID-19 were retrospectively analyzed at Dongxihu Fangcang Hospital between February 7 and March 8, 2020. We described the clinical characteristics and distribution of discharge or transfer times for each patient. According to the disease progression of COVID-19 patients, we divided all patients into Non-Deteriorated group and Deteriorated group. Furthermore, binary logistic regression was used for a single outcome and multiple response variables.

Results

We treated 789 patients with mild and moderate COVID-19, of which 714 were included in this study, which included 326 (45.66%) deteriorated patients and 388 (54.34%) non-deteriorated patients. The mean age of the study population was 48.16±12.44 years. Of all patients, 319 (44.7%) were men and 395 (55.3%) were women. The average length of the patient’s stay was 16.08±5.13 days. The most common clinical feature on admission was fever (593 of 714, 83.05%). It is worth noting that 80 (11.20%) of the 714 patients were asymptomatic from exposure to admission. Multivariate logistic regression analysis showed that gender, age, diabetes, respiratory system disease, fever, dyspnea, and nasal congestion were risk factors associated with deterioration in cases with COVID-19 patients, and asymptomatic (OR: 0.058; 95% CI: 0.022–0.155; P<0.001) was the protective factor for deterioration of COVID-19 patients.

Conclusion

Accompanied by chronic diseases, old age, fever, nasal congestion, and dyspnea were factors that influenced the aggravation of COVID-19 patients, and more attention and treatment should be given to these patients.

A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity

BACKGROUND

Cardiovascular disease (CVD), one of the most common comorbidities of coronavirus disease 2019 (COVID-19), has been suspected to be associated with adverse outcomes in COVID-19 patients, but their correlation remains controversial.

METHOD

This is a quantitative meta-analysis on the basis of adjusted effect estimates. PubMed, Web of Science, MedRxiv, Scopus, Elsevier ScienceDirect, Cochrane Library and EMBASE were searched comprehensively to obtain a complete data source up to January 7, 2021. Pooled effects (hazard ratio (HR), odds ratio (OR)) and the 95% confidence intervals (CIs) were estimated to evaluate the risk of the adverse outcomes in COVID-19 patients with CVD. Heterogeneity was assessed by Cochran's Q-statistic, I2test, and meta-regression. In addition, we also provided the prediction interval, which was helpful for assessing whether the variation across studies was clinically significant. The robustness of the results was evaluated by sensitivity analysis. Publication bias was assessed by Begg's test, Egger's test, and trim-and-fill method.

RESULT

Our results revealed that COVID-19 patients with pre-existing CVD tended more to adverse outcomes on the basis of 203 eligible studies with 24,032,712 cases (pooled ORs = 1.41, 95% CIs: 1.32-1.51, prediction interval: 0.84-2.39; pooled HRs = 1.34, 95% CIs: 1.23-1.46, prediction interval: 0.82-2.21). Further subgroup analyses stratified by age, the proportion of males, study design, disease types, sample size, region and disease outcomes also showed that pre-existing CVD was significantly associated with adverse outcomes among COVID-19 patients.

CONCLUSION

Our findings demonstrated that pre-existing CVD was an independent risk factor associated with adverse outcomes among COVID-19 patients.

SARS-CoV-2 Infection and the Kidneys: An Evolving Picture

Since December 2019, a novel coronavirus known as Severe Acute Respiratory Virus 2 (SARS-CoV-2) has caused an outbreak of a respiratory illness worldwide. Even though SARS-CoV-2 primarily affects the respiratory system, other organs such as the heart and kidneys are implicated. The pathophysiology of Acute Kidney Injury (AKI) in coronavirus 2019 (COVID-19) patients is not clearly defined. Direct kidney injury results from virus entry through angiotensin-converting enzyme-2 (ACE2) receptors which are highly expressed by the podocytes and proximal convoluted tubules, as suggested by "viral-like" particles on electron microscopy. However, the link between the presence of viral particles in kidney tissue and kidney injury has not been fully explained. Furthermore, it is also hypothesized that collapsing focal segmental glomerulosclerosis (FSGS), myoglobin toxicity, sepsis-linked, and glomeruli fibrin thrombi is part of the mechanism for AKI. Reported cases link FSGS and high-risk apolipoprotein 1 (APOL1) alleles in patients of African ancestry. Typically, these patients present with AKI and nephrotic-range proteinuria. The rate of AKI in hospitalized patients is high and associated with a higher mortality rate in older patients with comorbidities. Even higher mortality is now being reported in patients with chronic kidney disease and kidney transplant recipients due to immune system dysfunction. Herein, we review the current literature on kidney disease and pathogenesis in COVID-19 patients.

Possible role of higher serum level of myoglobin as predictor of worse prognosis in Sars-Cov 2 hospitalized patients. A monocentric retrospective study

BACKGROUND

Limited data on myoglobin and infectious diseases are available. In this study, we evaluate the potential role of myoglobin in predicting poor outcome in patients with Sars-Cov2 pneumonia.

METHODS

One hundred and twenty-one Sars-Cov 2 patients with an average age of 69.9 ± 13.2 years, and symptoms duration of 8.8 ± 7.9 days were enrolled in the study. At the admission, the serum levels of myoglobin, erythrocyte sedimentation rate, C reactive protein (CRP), procalcitonin, ferritin, creatine phosphokinase, creatinine, fibrinogen, d-dimers, lactic dehydrogenase, troponin (Tn-I), creatine kinase myocardial band (CK-MB), complement fractions C3 and C4, immunoglobulins, interleukin 6 were evaluated. We also assessed the patients' complete clinical history and performed a thorough physical examination including age, disease history, and medications.

RESULTS

Twenty-four (20%) patients died, and 18 (15%) patients required intensive care. The mean time between symptoms onset and death was 12.4 days ± 9.1. Univariate analysis of the patients' data highlighted some independent risk factors for mortality in COVID-19, including higher neutrophils rate (HR: 1.171), lower lymphocyte rate (HR: 0.798), high CK-MB serum levels (HR: 1.6), high Tn-I serum levels (HR: 1.03), high myoglobin serum levels (HR: 1.014), Alzheimer (HR 5.8), and higher CRP values (HR: 1.011). Cox regression analysis model revealed that higher serum values of myoglobin (HR 1.003; 95%CI: 1.001-1.006; p = 0.01), and CRP (HR 1.012; 95% CI: 1.001-1.023; p = 0.035) could be predictors of mortality in COVID-19 patients. The value of the myoglobin level for predicting 28 days-mortality using ROC curve was 121.8 ng/dL. Lower survival rate was observed in patients with serum levels of myoglobin>121.8 ng/dL (84% vs 20% respectively, p = 0.0001).

CONCLUSION

Our results suggest that higher serum levels of myoglobin could be a considerable and effective predictor of poor outcomes in COVID-19 patients; a careful follow-up in these patients is strongly suggested. The possibility of enhancing these findings in other cohorts of COVID-19 patients could validate the clinical value of myoglobin as a biomarker for worse prognosis in COVID-19.

Development and validation of a predictive model to determine the level of care in patients confirmed with COVID-19

BACKGROUND

The COVID-19 pandemic has imposed significant challenges on hospital capacity. While mitigating unnecessary crowding in hospitals is favourable to reduce viral transmission, it is more important to prevent readmissions with impaired clinical status due to initially inappropriate level of care. A validated predictive tool to assist clinical decisions for patient triage and facilitate remote stratification is of critical importance.

METHODS

We conducted a retrospective study in patients with confirmed COVID-19 stratified into two levels of care, namely ambulatory care and hospitalization. Data on socio-demographics, clinical symptoms, and comorbidities were collected during the first (N = 571) and second waves (N = 174) of the pandemic in Belgium (2 March to 6 December 2020). Univariate and multivariate logistic regressions were performed to build and validate the prediction model.

RESULTS

Significant predictors of hospitalization were old age (OR = 1.08, 95%CI:1.06-1.10), male gender (OR = 4.41, 95%CI: 2.58-7.52), dyspnoea (OR 6.11, 95%CI: 3.58-10.45), dry cough (OR 2.89, 95%CI: 1.54-5.41), wet cough (OR 4.62, 95%CI: 1.93-11.06), hypertension (OR 2.20, 95%CI: 1.17-4.16) and renal failure (OR 5.39, 95%CI: 1.00-29.00). Rhinorrhea (OR 0.43, 95%CI: 0.24-0.79) and headache (OR 0.36, 95%CI: 0.20-0.65) were negatively associated with hospitalization. A receiver operating characteristic (ROC) curve was constructed and the area under the ROC curve was 0.931 (95% CI: 0.910-0.953) for the prediction model (first wave) and 0.895 (95% CI: 0.833-0.957) for the validated dataset (second wave).

CONCLUSION

With a good discriminating power, the prediction model might identify patients who require ambulatory care or hospitalization and support clinical decisions by Emergency Department staff and general practitioners.

Myoglobin and C-reactive protein are efficient and reliable early predictors of COVID-19 associated mortality

Since the emergence of SARS-CoV-2, numerous studies have been attempting to determine biomarkers, which could rapidly and efficiently predict COVID-19 severity, however there is lack of consensus on a specific one. This retrospective cohort study is a comprehensive analysis of the initial symptoms, comorbidities and laboratory evaluation of patients, diagnosed with COVID-19 in Huoshenshan Hospital, Wuhan, from 4th February to 12th March, 2020. Based on the data collected from 63 severely ill patients from the onset of symptoms till the full recovery or demise, we found not only age (average 70) but also blood indicators as significant risk factors associated with multiple organ failure. The blood indices of all patients showed hepatic, renal, cardiac and hematopoietic dysfunction with imbalanced coagulatory biomarkers. We noticed that the levels of LDH (85%, P < .001), HBDH (76%, P < .001) and CRP (65%, P < .001) were significantly elevated in deceased patients, indicating hepatic impairment. Similarly, increased CK (15%, P = .002), Cre (37%, P = 0.102) and CysC (74%, P = 0.384) indicated renal damage. Cardiac injury was obvious from the significantly elevated level of Myoglobin (52%, P < .01), Troponin-I (65%, P = 0.273) and BNP (50%, P = .787). SARS-CoV-2 disturbs the hemolymphatic system as WBC# (73%, P = .002) and NEUT# (78%, P < .001) were significantly elevated in deceased patients. Likewise, the level of D-dimer (80%, P < .171), PT (87%, P = .031) and TT (57%, P = .053) was elevated, indicating coagulatory imbalances. We identified myoglobin and CRP as specific risk factors related to mortality and highly correlated to organ failure in COVID-19 disease.

Clinical characteristics and analysis of risk factors for disease progression of COVID-19: A retrospective Cohort Study

Objective: Since December 2019, an outbreak of coronavirus disease 2019 (COVID 19) has been experienced from Wuhan, China to the world. A retrospective cohort study was conducted to summarize the clinical characteristics of patients with COVID-19 and to explore the risk factors affecting the disease duration in Jiangan Fangcang shelter hospital, Wuhan, China. Methods: Clinical characteristics of 409 patients with COVID-19 were retrospectively analyzed. We describe the clinical characteristics and distribution of discharge time or transfer time for each patient. Then we performed univariate and multivariate Cox regression analysis to identify potential risk factors for progression from non-severe to severe COVID-19 or death. Results: The median disease duration of all patients was 23 days (IQR 19-28). The main symptoms of the patient were fever (95.6%), cough (74.3%), tiredness (21.5%), and so on. Comorbidities mainly included hypertension (30.6%) diabetes (17.6%) and heart disease (12.5%). The univariate Cox regression analysis showed that old age, number of symptoms, the combination of hypertension, heart disease and pulmonary disease were associated with the progression of disease. The multivariate Cox regression analysis showed that old age (HR: 7.294; 95% CI: 1.442-36.888; P = 0.016), the combination of hypertension (HR: 2.230; 95% CI: 1.090-4.562; P = 0.028) and heart disease (HR: 2.650; 95% CI: 1.079-6.510; P = 0.034) were independent risk factors for progression of COVID-19. Conclusions: The age of the patient, the combination of hypertension and heart disease were independent risk factors for the progression of COVID-19. Cautions should be raised for patients with these risk factors.

Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19

BACKGROUND

Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk of developing serious illness.

METHODS

We retrospectively analyzed 114 patients with COVID-19 at the Jinyintan Hospital, Wuhan based on their clinical and laboratory data. Patients were categorized into severe and mild to moderate disease groups. We analyzed the potential of serological inflammation indicators in predicting the severity of COVID-19 in patients using univariate and multivariate logistic regression, receiver operating characteristic curves, and nomogram analysis. The Spearman method was used to understand the correlation between the serological biomarkers and duration of hospital stay.

RESULTS

Patients with severe disease had reduced neutrophils and lymphocytes; severe coagulation dysfunction; altered content of biochemical factors (such as urea, lactate dehydrogenase); elevated high sensitivity C-reactive protein levels, neutrophil-lymphocyte, platelet-lymphocyte, and derived neutrophil-lymphocyte ratios, high sensitivity C-reactive protein-prealbumin ratio (HsCPAR), systemic immune-inflammation index, and high sensitivity C-reactive protein-albumin ratio (HsCAR); and low lymphocyte-monocyte ratio, prognostic nutritional index (PNI), and albumin-to-fibrinogen ratio. PNI, HsCAR, and HsCPAR correlated with the risk of severe disease. The nomogram combining the three parameters showed good discrimination with a C-index of 0.873 and reliable calibration. Moreover, HsCAR and HsCPAR correlated with duration of hospital stay.

CONCLUSION

Taken together, PNI, HsCAR, and HsCPAR may serve as accurate biomarkers for the prediction of disease severity in patients with COVID-19 upon admission/hospitalization.

Euthyroid Sick Syndrome in Patients With COVID-19

Background

Coronavirus disease 2019 (COVID-19) has been shown to affect almost every organ throughout the body. However, it is not clear whether the thyroid gland is impaired in COVID-19 patients. Euthyroid sick syndrome (ESS) is usually associated with the disease severity and deterioration prognosis in critical illness. In this study, the thyroid function of COVID-19 patients was assessed and factors associated with outcomes were analyzed to determine the potential predictive value of ESS.

Methods

Clinical and laboratory data of COVID-19 patients with or without ESS in Changsha, China, were collected and analyzed on admission. Kaplan-Meier curve and cox regression model were utilized to determine the correlation between ESS and the endpoints. Subsequently, a receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performances of FT3 and C-reactive protein (CRP) in the disease severity.

Results

Forty-one (27.52%) cases of COVID-19 patients diagnosed with ESS. ESS patients had higher proportions of fever, shortness of breath, hypertension, diabetes, and severe events than those of non-ESS patients. The levels of erythrocyte sedimentation rate and C-reactive protein, and the positive rate of procalcitonin were significantly higher, whereas the lymphocyte count was apparently lower in ESS patients than in non-ESS patients. The regression analysis showed that ESS was significantly associated with the disease severity of COVID-19 (HR = 2.515, 95% CI: 1.050-6.026, P = 0.039). The areas under the curve (AUCs) for predicting the severe disease were [0.809 (95% CI 0.727-0.892), P < 0.001] and [0.792 (95% CI 0.689-0.895), P < 0.001] for FT3 and CRP, respectively.

Conclusion

ESS was significantly associated with the disease severity and inflammatory parameters in COVID-19 patients.