Complications of Critical COVID-19: Diagnostic and Therapeutic Considerations for the Mechanically Ventilated Patient

Predictors and outcomes of patients with COVID-19 admitted to intensive care units in Pakistan and the development of nosocomial fungal infections: Findings and implications

Objectives

Patients with COVID-19 admitted to intensive care units (ICUs) typically have many complications and co-morbidities, including secondary bacterial and fungal infections, which increase morbidity and mortality. The first step to address this is to measure the prevalence rates, predictors of fungal infections, and outcomes of patients with COVID-19 admitted to ICUs in Pakistan.

Methods

Retrospective review of medical records of patients admitted with COVID-19 to the ICUs of six tertiary care hospitals in Pakistan between March 2020 and June 2023.

Results

A total of 636 patients were included; 68.9% were aged ≥50 years and 62.6% were male. Diabetes mellitus was the commonest co-morbidity (23.7%). A total of 67.8% of patients had severe COVID-19, with 23% critical cases. Antibiotics and antipyretics (all patients) were the most frequently prescribed medicines, along with corticosteroids (72.5%). A total of 63 nosocomial fungal infections developed in 53 patients, with mechanical ventilation and tracheal intubation being significant predictors of secondary fungal infections among patients with COVID-19. The mortality rate was 4.9%, with secondary fungal infections significantly associated with higher mortality.

Conclusions

Approximately 8% of patients with COVID-19 admitted to the ICUs of tertiary developed secondary fungal infections associated with greater mortality. The key factors associated with secondary fungal infections need to be carefully monitored to reduce future mortality in these patients. We will continue to monitor the situation.

Risk factors for mortality in severe COVID-19: Exploring the interplay of immunomodulatory therapy and coinfection

Patients with severe clinical manifestations of coronavirus disease 2019 (COVID-19) present particular diagnostic and management challenges to critical care physicians, including identifying and responding to concurrent bacterial and fungal coinfections. This study evaluates risk factors for in-hospital mortality in patients admitted to the intensive care unit with severe COVID-19 during circulation of the B.1.617.2 (Delta) variant, including the impact of immunomodulators and bacterial and/or fungal coinfection. This retrospective cohort study enrolled patients with severe COVID-19. A Cox proportional hazard ratio analysis identified risk factors for in-hospital mortality. Outcomes were also compared between patients receiving and not receiving immunomodulatory therapy alongside standard care. Ninety patients admitted to the intensive care unit were enrolled. On multivariate analysis, the greatest risk factors for in-hospital mortality were invasive mechanical ventilation (hazard ratio (HR) = 15.27; 95% confidence interval (CI) 3.29-71.0; P < 0.001), elevated body mass index (HR = 1.07 per unit; 95% CI 1.02-1.13; P = 0.007) and older age (HR = 1.53 per decade; 95% CI 1.05-2.24; P = 0.028). Bacterial and/or fungal coinfection occurred at equal frequency in patients receiving and not receiving immunomodulatory therapy. However, in patients receiving immunomodulators, coinfection carried a significantly higher mortality risk (63.0%) compared with those without coinfection (15.4%; P = 0.038). Mortality from severe COVID-19 is significantly higher in older patients and those with elevated body mass index and requiring mechanical ventilation. Immunomodulatory therapy necessitates vigilance towards evolving coinfection in the intensive care setting.

Enhancing COVID-19 CT Image Segmentation: A Comparative Study of Attention and Recurrence in UNet Models

Imaging plays a key role in the clinical management of Coronavirus disease 2019 (COVID-19) as the imaging findings reflect the pathological process in the lungs. The visual analysis of High-Resolution Computed Tomography of the chest allows for the differentiation of parenchymal abnormalities of COVID-19, which are crucial to be detected and quantified in order to obtain an accurate disease stratification and prognosis. However, visual assessment and quantification represent a time-consuming task for radiologists. In this regard, tools for semi-automatic segmentation, such as those based on Convolutional Neural Networks, can facilitate the detection of pathological lesions by delineating their contour. In this work, we compared four state-of-the-art Convolutional Neural Networks based on the encoder-decoder paradigm for the binary segmentation of COVID-19 infections after training and testing them on 90 HRCT volumetric scans of patients diagnosed with COVID-19 collected from the database of the Pisa University Hospital. More precisely, we started from a basic model, the well-known UNet, then we added an attention mechanism to obtain an Attention-UNet, and finally we employed a recurrence paradigm to create a Recurrent-Residual UNet (R2-UNet). In the latter case, we also added attention gates to the decoding path of an R2-UNet, thus designing an R2-Attention UNet so as to make the feature representation and accumulation more effective. We compared them to gain understanding of both the cognitive mechanism that can lead a neural model to the best performance for this task and the good compromise between the amount of data, time, and computational resources required. We set up a five-fold cross-validation and assessed the strengths and limitations of these models by evaluating the performances in terms of Dice score, Precision, and Recall defined both on 2D images and on the entire 3D volume. From the results of the analysis, it can be concluded that Attention-UNet outperforms the other models by achieving the best performance of 81.93%, in terms of 2D Dice score, on the test set. Additionally, we conducted statistical analysis to assess the performance differences among the models. Our findings suggest that integrating the recurrence mechanism within the UNet architecture leads to a decline in the model's effectiveness for our particular application.

SARS-CoV-2 suppresses TLR4-induced immunity by dendritic cells via C-type lectin receptor DC-SIGN

SARS-CoV-2 causes COVID-19, an infectious disease with symptoms ranging from a mild cold to severe pneumonia, inflammation, and even death. Although strong inflammatory responses are a major factor in causing morbidity and mortality, superinfections with bacteria during severe COVID-19 often cause pneumonia, bacteremia and sepsis. Aberrant immune responses might underlie increased sensitivity to bacteria during COVID-19 but the mechanisms remain unclear. Here we investigated whether SARS-CoV-2 directly suppresses immune responses to bacteria. We studied the functionality of human dendritic cells (DCs) towards a variety of bacterial triggers after exposure to SARS-CoV-2 Spike (S) protein and SARS-CoV-2 primary isolate (hCoV-19/Italy). Notably, pre-exposure of DCs to either SARS-CoV-2 S protein or a SARS-CoV-2 isolate led to reduced type I interferon (IFN) and cytokine responses in response to Toll-like receptor (TLR)4 agonist lipopolysaccharide (LPS), whereas other TLR agonists were not affected. SARS-CoV-2 S protein interacted with the C-type lectin receptor DC-SIGN and, notably, blocking DC-SIGN with antibodies restored type I IFN and cytokine responses to LPS. Moreover, blocking the kinase Raf-1 by a small molecule inhibitor restored immune responses to LPS. These results suggest that SARS-CoV-2 modulates DC function upon TLR4 triggering via DC-SIGN-induced Raf-1 pathway. These data imply that SARS-CoV-2 actively suppresses DC function via DC-SIGN, which might account for the higher mortality rates observed in patients with COVID-19 and bacterial superinfections.

Immunologic and vascular biomarkers of mortality in critical COVID-19 in a South African cohort

Introduction

Biomarkers predicting mortality among critical Coronavirus disease 2019 (COVID-19) patients provide insight into the underlying pathophysiology of fatal disease and assist with triaging of cases in overburdened settings. However, data describing these biomarkers in Sub-Saharan African populations are sparse.

Methods

We collected serum samples and corresponding clinical data from 87 patients with critical COVID-19 on day 1 of admission to the intensive care unit (ICU) of a tertiary hospital in Cape Town, South Africa, during the second wave of the COVID-19 pandemic. A second sample from the same patients was collected on day 7 of ICU admission. Patients were followed up until in-hospital death or hospital discharge. A custom-designed 52 biomarker panel was performed on the Luminex® platform. Data were analyzed for any association between biomarkers and mortality based on pre-determined functional groups, and individual analytes.

Results

Of 87 patients, 55 (63.2%) died and 32 (36.8%) survived. We found a dysregulated cytokine response in patients who died, with elevated levels of type-1 and type-2 cytokines, chemokines, and acute phase reactants, as well as reduced levels of regulatory T cell cytokines. Interleukin (IL)-15 and IL-18 were elevated in those who died, and levels reduced over time in those who survived. Procalcitonin (PCT), C-reactive protein, Endothelin-1 and vascular cell adhesion molecule-1 were elevated in those who died.

Discussion

These results show the pattern of dysregulation in critical COVID-19 in a Sub-Saharan African cohort. They suggest that fatal COVID-19 involved excessive activation of cytotoxic cells and the NLRP3 (nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3) inflammasome. Furthermore, superinfection and endothelial dysfunction with thrombosis might have contributed to mortality. HIV infection did not affect the outcome. A clinically relevant biosignature including PCT, pH and lymphocyte percentage on differential count, had an 84.8% sensitivity for mortality, and outperformed the Luminex-derived biosignature.

Outcomes and characteristics of patients hospitalized for COVID-19 in British Columbia, Ontario and Quebec during the Omicron wave

BACKGROUND

Omicron is the current predominant variant of concern of SARS-CoV-2. We hypothesized that vaccination alters outcomes of patients hospitalized with COVID-19 during the Omicron wave and that these patients have different characteristics and outcomes than in previous waves.

METHODS

This is a substudy of the Host Response Mediators in Coronavirus (COVID-19) Infection (ARBs CORONA I) trial, which included adults admitted to hospital with acute COVID-19 up to July 2022 from 9 hospitals in British Columbia, Ontario and Quebec. We excluded emergency department visits without hospital admission, readmissions and admissions for another reason. Using adjusted regression analysis, we compared mortality and organ dysfunction between vaccinated (≥ 2 doses) and unvaccinated patients during the Omicron wave, as well as between all patients in the Omicron and first 3 waves of the COVID-19 pandemic.

RESULTS

During the Omicron wave, 28-day mortality was significantly lower in vaccinated (n = 19/237) than unvaccinated hospitalized patients (n = 12/127) (adjusted odds ratio [OR] 0.36, 95% confidence interval [CI] 0.15-0.89); vaccinated patients had lower risk of admission to the intensive care unit, invasive ventilation and acute respiratory distress syndrome and shorter hospital length of stay. Patients hospitalized during the Omicron wave had more comorbidities than in previous waves, and lower 28-day mortality than in waves 1 and 2 (adjusted OR 0.38, 95% CI 0.24-0.59; and 0.42, 95% CI 0.26-0.65) but not wave 3 (adjusted OR 0.81, 95% CI 0.43-1.51) and had less organ dysfunction than in the first 2 waves.

INTERPRETATION

Patients who were at least double vaccinated had lower mortality than unvaccinated patients hospitalized during the Omicron wave. Patients hospitalized during the Omicron wave had more chronic disease and lower mortality than in the first 2 waves, but not wave 3. Changes in vaccination, treatments and predominant SARS-CoV-2 variant may have decreased mortality in patients hospitalized during the Omicron wave.

Risk Factors Associated with the Development of Hospital-Acquired Infections in Hospitalized Patients with Severe COVID-19

Recognition of risk factors for hospital-acquired infections (HAI) in patients with COVID-19 is warranted. We aimed to describe factors associated with the development of HAI in patients with severe COVID-19. We conducted a retrospective cohort study including all adult patients admitted with severe COVID-19 between March 2020 and November 2020. The primary outcome was HAI development. Bivariate and multiple logistic regression models were constructed. Among 1540 patients, HAI occurred in 221 (14%). A total of 299 episodes of HAI were registered. The most common HAI were hospital-acquired/ventilation-associated pneumonia (173 episodes) and primary bloodstream infection (66 episodes). Death occurred in 387 (35%) patients and was more frequent in patients with HAI (38% vs. 23%, p < 0.01). Early mechanical ventilation (aOR 18.78, 95% CI 12.56-28.07), chronic kidney disease (aOR 3.41, 95% CI 1.4-8.27), use of corticosteroids (aOR 2.95, 95% CI 1.92-4.53) and tocilizumab (aOR 2.68, 95% CI 1.38-5.22), age ≥ 60 years (aOR 1.91, 95% CI 1.27-2.88), male sex (aOR 1.52, 95% CI 1.03-2.24), and obesity (aOR 1.49, 95% CI 1.03-2.15) were associated with HAI. In patients with severe COVID-19, mechanical ventilation within the first 24 h upon admission, chronic kidney disease, use of corticosteroids, use of tocilizumab, age ≥ 60 years, male sex, and obesity were associated with a higher risk of HAI.

Acute Myositis in a Pregnant Woman Complicated With COVID-19 and Hyperemesis Gravidarum: A Case Report

Myalgia is the most frequently reported neuromuscular symptom in COVID-19 patients, with a frequency of around 20% in pregnant women. Acute myositis due to COVID-19 is severe and requires medical intervention. There have been some reports of acute myositis due to COVID-19, mostly in elderly men, but rarely in pregnant women. Here we report a case of a pregnant woman who was diagnosed with acute myositis following COVID-19 illness early in her pregnancy. She had been affected by morning sickness since the 6th week of gestation and was diagnosed with COVID-19 at the 12th week. Muscle pain appeared in her limbs 5 days after the diagnosis of COVID-19, with a predominance of pain in the lower limbs, and her gait gradually became unstable. We concluded that it was acute myositis complicated by COVID-19 and hypokalemia, but we could not determine whether hypokalemia or COVID-19 or both were the cause of the muscle damage in this case. Pregnant women diagnosed with COVID-19 often complain of myalgia and fatigue, and when a pregnant woman's symptoms are severe we should keep in mind that they may be suffering from muscle damage that needs medical intervention.

The association of COVID-19 severity and susceptibility and genetic risk factors: A systematic review of the literature

BACKGROUND

COVID-19 is associated with several risk factors such as distinct ethnicities (genetic ancestry), races, sexes, age, pre-existing comorbidities, smoking, and genetics. The authors aim to evaluate the correlation between variability in the host genetics and the severity and susceptibility towards COVID-19 in this study.

METHODS

Following the PRISMA guidelines, we retrieved all the relevant articles published until September 15, 2021, from two online databases: PubMed and Scopus.

FINDINGS

High-risk HLA haplotypes, higher expression of ACE polymorphisms, and several genes of cellular proteases such as TMPRSS2, FURIN, TLL-1 increase the risk of susceptibility and severity of COVID-19. In addition, upregulation of several genes encoding for both innate and acquired immune systems proteins, mainly CCR5, IFNs, TLR, DPPs, and TNF, positively correlate with COVID-19 severity. However, reduced expression or polymorphisms in genes affecting TLR and IFNλ increase COVID-19 severity.

CONCLUSION

Higher expression, polymorphisms, mutations, and deletions of several genes are linked with the susceptibility, severity, and clinical outcomes of COVID-19. Early treatment and vaccination of individuals with genetic predisposition could help minimize the severity and mortality associated with COVID-19.

Extracorporeal membrane oxygenation during the first three waves of the coronavirus disease 2019 pandemic: A retrospective single-center registry study

BACKGROUND

Despite increasing knowledge about the optimal treatment for patients with severe COVID-19, data from different cohorts suggested that survival of patients treated with ECMO seemed to decline over the course of the pandemic.

METHODS

In this non-interventional retrospective single-center registry study we analyzed all consecutive patients tested positive for SARS-CoV-2 infection and supported with VV ECMO in our center during the first three waves of the pandemic. From March 2020 through June 2021, 59 patients have been included.

RESULTS

Overall 90-day survival was 32%. Besides changes in drug treatment for COVID-19 and a lower PaO₂ /FiO₂ ratio before ECMO initiation during the third wave, all other patient baseline characteristics were similar during the three waves. Survival rate was highest during the first wave and lowest during the third wave, yet this difference was not statistically significant.

CONCLUSIONS

VV ECMO has shown to be a feasible and safe support option for patients with severe respiratory failure due to COVID-19. The results from this single-center study confirm findings from other cohorts showing declining survival rates of patients treated with VV ECMO during the COVID-19 pandemic, however, the specific reasons for this finding remain unclear.

Extracorporeal membrane oxygenation during the first three waves of the coronavirus disease 2019 pandemic - a retrospective single-center registry study

Background

Despite increasing knowledge about the optimal treatment for patients with severe COVID‐19, data from different cohorts suggested that survival of patients treated with ECMO seemed to decline over the course of the pandemic.

Methods

In this non‐interventional retrospective single‐center registry study we analyzed all consecutive patients tested positive for SARS‐CoV‐2 infection and supported with VV ECMO in our center during the first three waves of the pandemic. From March 2020 through June 2021, 59 patients have been included.

Results

Overall 90‐day survival was 32%. Besides changes in drug treatment for COVID‐19 and a lower PaO₂/FiO₂ ratio before ECMO initiation during the third wave, all other patient baseline characteristics were similar during the three waves. Survival rate was highest during the first wave and lowest during the third wave, yet this difference was not statistically significant.

Conclusions

VV ECMO has shown to be a feasible and safe support option for patients with severe respiratory failure due to COVID‐19. The results from this single‐center study confirm findings from other cohorts showing declining survival rates of patients treated with VV ECMO during the COVID‐19 pandemic, however, the specific reasons for this finding remain unclear.

Subarachnoid hemorrhage: management considerations for COVID-19

Subarachnoid hemorrhage (SAH) has deleterious outcomes for patients, and during the hospital stay, patients are susceptible to vasospasm and delayed cerebral ischemia. Coronavirus disease 2019 (COVID-19) has been shown to worsen hypertension through angiotensin-converting enzyme 2 (ACE2) activity, therefore, predisposing to aneurysm rupture. The classic renin-angiotensin pathway activation also predisposes to vasospasm and subsequent delayed cerebral ischemia. Matrix metalloproteinase 9 upregulation can lead to an inflammatory surge, which worsens outcomes for patients. SAH patients with COVID-19 are more susceptible to ventilator-associated pneumonia, reversible cerebral vasoconstriction syndrome, and respiratory distress. Emerging treatments are warranted to target key components of the anti-inflammatory cascade. The aim of this review is to explore how the COVID-19 virus and the intensive care unit (ICU) treatment of severe COVID can contribute to SAH.