Inpatients With Brain Damage, Impaired Airways, and Severely Restricted Daily Activities Have an Increased Infection Rate During the COVID-19 Pandemic: A Single-Center Retrospective Analysis From Wuhan

High myoglobin level as an independent risk factor for death in elderly patients with critical COVID-19 infection: a retrospective case-control study

AIM

This study aimed to discover risk factors for death in patients with critical COVID-19 infection in order to identify patients with a higher risk of death at an early stage.

METHODS

We retrospectively analyzed the clinical data of patients with critical COVID-19 infection from April 2022 to June 2022. Data were collected from the electronic medical records. Propensity matching scores were used to reduce the effect of confounding factors, such as patient baseline variables. Independent risk factors affecting patient prognosis were assessed using univariate logistic regression and multivariate logistic regression analysis. Restricted cubic spline curves were used to assess the relationship between independent and dependent variables.

RESULTS

The data of 132 patients with critical COVID-19 infection were included in the study. Of the 132 patients, 79 survived and 53 died. Among laboratory indicators, patients who died had higher proportions of abnormalities in procalcitonin, aspartate aminotransferase (AST), creatinine, cardiac troponin I, and myoglobin. Univariate and multivariate logistic regression analyses suggested that abnormal AST (OR = 4.98, P = 0.02), creatinine (OR = 7.93, P = 0.021), and myoglobin (OR = 103.08, P = 0.002) were independent risk factors for death. After correction for AST and creatinine, a linear relationship between myoglobin and risk of death in patients was found using restricted cubic splines.

CONCLUSION

High myoglobin level is an independent risk factor for death and is therefore a prognostic marker in elderly patients with severe COVID-19 infection.

Development and validation of a prediction model for mortality in critically ill COVID-19 patients

Background

Early prediction of prognosis may help early treatment measures to reduce mortality in critically ill coronavirus disease (COVID-19) patients. The study aimed to develop a mortality prediction model for critically ill COVID-19 patients.

Methods

This retrospective study analyzed the clinical data of critically ill COVID-19 patients in an intensive care unit between April and June 2022. Propensity matching scores were used to reduce the effect of confounding factors. A predictive model was built using logistic regression analysis and visualized using a nomogram. Calibration and receiver operating characteristic (ROC) curves were used to estimate the accuracy and predictive value of the model. Decision curve analysis (DCA) was used to examine the value of the model for clinical interventions.

Results

In total, 137 critically ill COVID-19 patients were enrolled; 84 survived, and 53 died. Univariate and multivariate logistic regression analyses revealed that aspartate aminotransferase (AST), creatinine, and myoglobin levels were independent prognostic factors. We constructed logistic regression prediction models using the seven least absolute shrinkage and selection operator regression-selected variables (hematocrit, red blood cell distribution width-standard deviation, procalcitonin, AST, creatinine, potassium, and myoglobin; Model 1) and three independent factor variables (Model 2). The calibration curves suggested that the actual predictions of the two models were similar to the ideal predictions. The ROC curve indicated that both models had good predictive power, and Model 1 had better predictive power than Model 2. The DCA results suggested that the model intervention was beneficial to patients and patients benefited more from Model 1 than from Model 2.

Conclusion

The predictive model constructed using characteristic variables screened using LASSO regression can accurately predict the prognosis of critically ill COVID-19 patients. This model can assist clinicians in implementing early interventions. External validation by prospective large-sample studies is required.

Myoglobin and troponin as prognostic factors in patients with COVID-19 pneumonia

BACKGROUND

The outbreak of novel coronavirus pneumonia 2019 (COVID-19) has caused millions of deaths worldwide. It is well documented that troponin predicts the prognosis of patients. Myoglobin is not only an important marker of myocardial injury, but it indicates systemic muscle damage. However, its relationship with COVID-19 was rarely reported. The present study compared the predictive value of troponin and myoglobin on the final prognosis of COVID-19 patients by analyzing the clinical characteristics and serum levels of myoglobin and troponin in severe/critical COVID-19 patients.

METHODS

We enrolled 499 consecutive eligible hospitalized patients with severe/critical COVID-19 from February 14 to March 24, 2020 at Leishenshan Hospital, Wuhan, China. Clinical characteristics and laboratory data were collected and compared between the patients who died and survived. We analyzed the receiver operating characteristic curves of myoglobin and troponin. Then, the patients were divided into myo⁺ group, myo^- group, tro⁺ group, and tro^- group, and survival curves were analyzed. The prognostic predictable values of myoglobin and troponin were further analyzed using Cox multifactorial analysis.

RESULTS

Myoglobin and troponin were significantly elevated in the death group (134.4 [interquartile range (IQR) 24.80, 605] vs 38.02 [IQR 3.87, 11.73]ng/ml, p<0.001), and troponin was also significantly elevated in the death group (0.01 [IQR 0.01, 0.01] vs 0.04 [IQR 0.02, 0.15]ng/ml, p<0.001). The ROC curves demonstrated that the area under the curve when using myoglobin to predict patient death was 0.911, with a threshold of 1.17, which was equivalent to troponin. Kaplan-Meier survival analysis revealed a significantly lower survival curve in the myo⁺ group than the myo^- group. Multifactor Cox survival analysis showed that troponin was no longer significant (HR=0.98, 95% CI 0.92-1.03, p=0.507), but elevated myoglobin was an independent predictor of death in COVID-19 patients (HR=1.001, 95% CI 1.001-1.002, p<0.001). The analysis of the Cox model for predicting patient death and plotting decision curves suggested that the single factor myoglobin model was superior to troponin, and the predictive value of the multifactor model was superior to the single-factor analyses.

CONCLUSIONS

In severe/critical COVID-19 patients, myoglobin and troponin were predictors of mortality and the probability of conversion to critical illness, and myoglobin may be superior to troponin for predictive value.

Myoglobin and troponin as prognostic factors in patients with COVID-19 pneumonia

Background

The outbreak of novel coronavirus pneumonia 2019 (COVID-19) has caused millions of deaths worldwide. It is well documented that troponin predicts the prognosis of patients. Myoglobin is not only an important marker of myocardial injury, but it indicates systemic muscle damage. However, its relationship with COVID-19 was rarely reported. The present study compared the predictive value of troponin and myoglobin on the final prognosis of COVID-19 patients by analyzing the clinical characteristics and serum levels of myoglobin and troponin in severe/critical COVID-19 patients.

Methods

We enrolled 499 consecutive eligible hospitalized patients with severe/critical COVID-19 from February 14 to March 24, 2020 at Leishenshan Hospital, Wuhan, China. Clinical characteristics and laboratory data were collected and compared between the patients who died and survived. We analyzed the receiver operating characteristic curves of myoglobin and troponin. Then, the patients were divided into myo⁺ group, myo^- group, tro⁺ group, and tro^- group, and survival curves were analyzed. The prognostic predictable values of myoglobin and troponin were further analyzed using Cox multifactorial analysis.

Results

Myoglobin and troponin were significantly elevated in the death group (134.4 [interquartile range (IQR) 24.80, 605] vs 38.02 [IQR 3.87, 11.73] ng/ml, p < 0.001), and troponin was also significantly elevated in the death group (0.01 [IQR 0.01, 0.01] vs 0.04 [IQR 0.02, 0.15] ng/ml, p < 0.001). The ROC curves demonstrated that the area under the curve when using myoglobin to predict patient death was 0.911, with a threshold of 1.17, which was equivalent to troponin. Kaplan-Meier survival analysis revealed a significantly lower survival curve in the myo⁺ group than the myo^- group. Multifactor Cox survival analysis showed that troponin was no longer significant (HR = 0.98, 95% CI 0.92-1.03, p = 0.507), but elevated myoglobin was an independent predictor of death in COVID-19 patients (HR = 1.001, 95% CI 1.001-1.002, p < 0.001). The analysis of the Cox model for predicting patient death and plotting decision curves suggested that the single factor myoglobin model was superior to troponin, and the predictive value of the multifactor model was superior to the single-factor analyses.

Conclusions

In severe/critical COVID-19 patients, myoglobin and troponin were predictors of mortality and the probability of conversion to critical illness, and myoglobin may be superior to troponin for predictive value.

Rehabilitation and COVID-19: the Cochrane Rehabilitation 2020 rapid living systematic review. Update as of August 31st, 2020

INTRODUCTION

A monthly systematic review update is carried out to maintain the currency of scientific literature on rehabilitation of patients with COVID-19 and/or describing consequences due to the disease and its treatment, as they relate to limitations in functioning of rehabilitation interest. The aim of this study was to provide an updated summary of the available evidence published in August 2020.

EVIDENCE ACQUISITION

An extensive search on the main medical literature databases from August 1^st, 2020 to August 31^st, 2020 was performed, according to the methodology described in the second edition of the Cochrane Rehabilitation 2020 rapid living systematic review.

EVIDENCE SYNTHESIS

After removing duplicates, 1136 papers were identified, and 51 studies were finally included. According to OCEBM 2011 Levels of Evidence Table, they were Level 4 in most cases (76.5%) and Level 3 in the remaining (23.5%). Randomized controlled trials (RCTs) were not found. Thirty-two studies (62.7%) included COVID-19 patients who were assessed in the acute (20/32) or postacute phases (12/32). The other studies reported data on the impact of COVID-19 infection (7/19) or on the effect of lockdown restrictions (12/19) on subjects with pre-existing health conditions.

CONCLUSIONS

The scientific literature of August 2020 mainly focused on limitations in functioning of nervous system structure and related functions. Albeit the increased availability of data from analytical studies (both cohort and cross-sectional), there is still a lack of well-conducted Level 2 studies, to improve the knowledge on the effects of rehabilitation in COVID-19 patients.