An observational study on factors associated with ICU mortality in Covid-19 patients and critical review of the literature

Mortality and morbidity in critically ill COVID-19 patients: A systematic review and meta-analysis

BACKGROUND

The COVID-19 pandemic has caused 14.83 million deaths globally. This systematic review and meta-analysis aimed to provide a pooled estimate of the overall mortality and morbidity of critically ill COVID-19 patients.

METHOD

Four electronic databases, Medline/PubMed, the Cochrane Library, the WHO COVID-19 database, and the Web of Science, were used to identify relevant studies. Two authors independently screened the studies, evaluated the eligibility criteria and resolved discrepancies through discussion with the third author. The pooled effect size was computed using STATA software version 14. The Cochran Q test and I2 test were utilized to assess heterogeneity across the studies. Additionally, subgroup analysis, sensitivity analysis, and publication bias were evaluated. It is registered in Prospero with Prospero ID CRD42020212146.

RESULTS

A total of 1003 published articles were screened from various databases, and 24 studies involving a total of 142,291 critically ill COVID-19 participants were selected for inclusion in the review. Among the participants, 67 % were male, and the mean age was 63.43 + SD3.33 years. The mortality rate reported in the individual studies ranged from 4.5 % to 69.5 %. The findings from the analysis revealed that the overall pooled mortality rate was 34 % (95 % confidence interval: 31 %-37 %). Additionally, the findings showed that 62 % of critically ill COVID-19 patients required mechanical ventilation, while 68.7 % of these patients had chronic disease comorbidities.

CONCLUSION

Critically ill COVID-19 patients face a high-risk risk of death, with an estimate of about one in three patients dying from the virus. Notably, a substantial portion of critically ill COVID-19 patients (62 %) require mechanical ventilation; surprisingly, more than two-thirds of patients with COVID-19 have chronic disease comorbidities, highlighting the importance of managing comorbidities in this population.

The Seraph 100® Microbind Affinity Blood Filter Does Not Alter Levels of Circulating or Mucosal Antibodies in Critical COVID-19 Patients

PURIFY-OBS-1 is an observational study evaluating the safety and efficacy of Seraph 100® Microbind Affinity Blood Filter (Seraph 100) use for COVID-19 patients with respiratory failure admitted to the intensive care unit (ICU). The Seraph 100 is a hemoperfusion device containing heparin-coated beads that can bind to, and reduce levels of, some circulating pathogens and inflammatory molecules. This study evaluated whether treatment with the Seraph 100 affected circulating and mucosal antibody levels in critically ill COVID-19 subjects. SARS-CoV-2 anti-spike and anti-nucleocapsid IgG and IgA levels in serum were evaluated at enrollment and on days 1, 4, 7, and 28 after Seraph 100 application, while anti-spike and nucleocapsid IgG, IgA, and secretory IgA levels in tracheal aspirates were evaluated at enrollment and on days 1, 2, 3, 7, and 28. Serum samples were also collected from the pre- and post-filter lines at 1 and 4 h following Seraph 100 application to evaluate the direct impact of the filter on circulating antibody levels. Treatment with the Seraph 100 did not alter the levels of circulating or mucosal antibodies in critically ill COVID-19 subjects admitted to the ICU.

Predictivity of the Prognostic Nutritional Index and Systemic Inflammation Index for All-Cause In-Hospital Mortality in Geriatric and Adult COVID-19 Inpatients

Background: The prognostic nutritional index (PNI) and the systemic immune inflammation index (SII) have been used as simple risk-stratification predictors for COVID-19 severity and mortality in the general population. However, the associations between these indices and mortality might differ due to age-related changes such as inflammaging and several comorbid conditions in older patients. Therefore, we aimed to compare the predictivity of the PNI and SII for mortality among hospitalized older patients and patients under 65 years old. Methods: Patients hospitalized with COVID-19 from March 2020 to December 2020 were retrospectively included. The PNI and SII were calculated from hospital records within the first 48 h after admission. Data were evaluated in the whole group and according to age groups (≥65 < years). Receiver operating characteristic curves were drawn to evaluate the predictivity of the PNI and SII. Results: Out of 407 patients included in this study, 48.4% (n = 197) were older patients, and 51.6% (n = 210) were under 65 years old. For mortality, the area under the curve (AUC) of the PNI and SII in the adult group (<65 years) was 0.706 (95% CI 0.583-0.828) (p = 0.003) and 0.697 (95% CI 0.567-0.827) (p < 0.005), respectively. The AUC of the PNI and SII in the older group was 0.515 (95% CI 0.427-0.604) (p = 0.739) and 0.500 (95% CI 0.411-0.590) (p = 0.993). Conclusions: The accuracy of the PNI and SII in predicting mortality in adult COVID-19 patients seemed to be fair, but no association was found in geriatric patients in this study. The predictivity of the PNI and SII for mortality varies according to age groups.

Impact on pulmonary, cardiac, and renal function and long-term quality of life after hospitalization for acute respiratory distress syndrome due to COVID-19: Protocol of the Post-COVID Brazil 3 study

RATIONALE

Evidence about long-term sequelae after hospitalization for acute respiratory distress syndrome due to COVID-19 is still scarce.

PURPOSE

To evaluate changes in pulmonary, cardiac, and renal function and in quality of life after hospitalization for acute respiratory distress syndrome secondary to COVID-19.

METHODS

This will be a multicenter case-control study of 220 participants. Eligible are patients who are hospitalized for acute respiratory distress syndrome due to COVID-19. In the control group, individuals with no history of hospitalization in the last 12 months or long-term symptoms of COVID-19 will be selected. All individuals will be subjected to pulmonary spirometry with a carbon monoxide diffusion test, chest tomography, cardiac and renal magnetic resonance imaging with gadolinium, ergospirometry, serum and urinary creatinine, total protein, and urinary microalbuminuria, in addition to quality-of-life questionnaires. Patients will be evaluated 12 months after hospital discharge, and controls will be evaluated within 90 days of inclusion in the study. For all the statistical analyses, p < 0.05 is the threshold for significance.

RESULTS

The primary outcome of the study will be the pulmonary diffusing capacity for carbon monoxide measured after 12 months. The other parameters of pulmonary, cardiac, and renal function and quality of life are secondary outcomes.

CONCLUSION

This study aims to determine the long-term sequelae of pulmonary, cardiac, and renal function and the quality of life of patients hospitalized for acute respiratory distress syndrome due to COVID-19 in the Brazilian population.

Back to the future: the novel art of digital auscultation applied in a prospective observational study of critically ill Covid-19 patients

BACKGROUND

The Covid-19 pandemic has caused immense pressure on Intensive Care Units (ICU). In patients with severe ARDS due to Covid-19, respiratory mechanics are important for determining the severity of lung damage. Lung auscultation could not be used during the pandemic despite its merit. The main objective of this study was to investigate associations between lung auscultatory sound features and lung mechanical properties, length of stay (LOS) and survival, in adults with severe Covid-19 ARDS.

METHODS

Consecutive patients admitted to a large ICU between 2020 and 2021 (n = 173) were included. Digital stethoscopes obtained auscultatory sounds and stored them in an on-line database for replay and further processing using advanced AI techniques. Correlation and regression analysis explored relationships between digital auscultation findings and lung mechanics or the ICU outcome. The resulting annotated lung sounds database is also publicly available as supplementary material.

RESULTS

The presence of squawks was associated with the ICU LOS, outcome and 90-day mortality. Other features (age, SOFA score & oxygenation index upon admission, minimum crackle entropy) had significant impact on outcome. Additional features affecting the 90-d survival were age and mean crackle entropy. Multivariate logistic regression showed that survival was affected by age, baseline SOFA, baseline oxygenation index and minimum crackle entropy.

CONCLUSIONS

Respiratory mechanics were associated with various adventitious sounds, whereas the lung sound analytics and the presence of certain adventitious sounds correlated with the ICU outcome and the 90-d survival. Spectral features of crackles sounds can serve as prognostic factors for survival, highlighting the importance of digital auscultation.

Evaluation of Clinical Characteristics of Critically Ill COVID-19 Patients With Renal Failure

INTRODUCTION

This study aimed to investigate the clinical characteristics and prognostic factors of critically ill COVID-19 patients with renal failure admitted to the ICU.

METHODS

We analyzed 300 adult patients with SARS-CoV-2 infection admitted to the ICU between November 1, 2020, and June 1, 2022. Demographic data, renal function parameters, and outcomes were collected and analyzed.

RESULTS

The median age was 72 years, and 54.3% were men. Mechanical ventilation was required for 86.3% of patients, with 71.0% needing invasive ventilation. Renal failure was present in 43.3% of patients at ICU admission, significantly associated with older age, higher mechanical and invasive ventilation needs, and increased ICU mortality (76.9% vs. 51.8%, p<0.001). Patients with renal failure had elevated levels of urea, creatinine, C-reactive protein (CRP), D-dimer, white blood cell (WBC), neutrophil (Neu), and procalcitonin (PCT) (p<0.001 for all). Among patients with acute kidney injury (AKI), those with AKI had significantly higher median age (75 vs. 66 years, p<0.001), mechanical ventilation requirement (93.6% vs. 74.3%, p<0.001) and ICU mortality (79.1% vs. 35.4%, p<0.001). Elevated levels of urea (76 vs. 44 mg/dL, p<0.001) and creatinine (1.4 vs. 0.8 mg/dL, p<0.001), as well as inflammatory markers CRP and D-dimer (p=0.001), were observed in AKI patients. Survivors had lower median age (66.0 vs. 74.0 years, p<0.001) and lower prevalence of chronic kidney disease (CKD) (4.5% vs. 12.8, p=0.019) and AKI (34.8% vs. 78.7%, p<0.001). Non-survivors exhibited higher levels of urea, creatinine, lactate dehydrogenase (LDH), CRP, ferritin, and D-dimer (p<0.001 for all).

CONCLUSION

Renal failure and AKI are prevalent in critically ill COVID-19 patients and are associated with worse outcomes. Elevated creatinine and urea levels at ICU admission are significant predictors of ICU mortality, underscoring the importance of early recognition and management of renal impairment in these patients.

Infection with the multidrug-resistant Klebsiella pneumoniae New Delhi metallo-B-lactamase strain in patients with COVID-19: Nec Hercules contra plures?

Background

During the coronavirus disease 2019 (COVID-19) pandemic, in patients treated for SARS-CoV-2 infection, infections with the Klebsiella pneumoniae bacteria producing New Delhi metallo-B-lactamase (NDM) carbapenemase in the USA, Brazil, Mexico, and Italy were observed, especially in intensive care units (ICUs). This study aimed to assess the impact of Klebsiella pneumoniae NDM infection and other bacterial infections on mortality in patients treated in ICUs due to COVID-19.

Methods

The 160 patients who qualified for the study were hospitalized in ICUs due to COVID-19. Three groups were distinguished: patients with COVID-19 infection only (N = 72), patients with COVID-19 infection and infection caused by Klebsiella pneumoniae NDM (N = 30), and patients with COVID-19 infection and infection of bacterial etiology other than Klebsiella pneumoniae NDM (N = 58). Mortality in the groups and chosen demographic data; biochemical parameters analyzed on days 1, 3, 5, and 7; comorbidities; and ICU scores were analyzed.

Results

Bacterial infection, including with Klebsiella pneumoniae NDM type, did not elevate mortality rates. In the group of patients who survived the acute phase of COVID-19 the prolonged survival time was demonstrated: the median overall survival time was 13 days in the NDM bacterial infection group, 14 days in the other bacterial infection group, and 7 days in the COVID-19 only group. Comparing the COVID-19 with NDM infection and COVID-19 only groups, the adjusted model estimated a statistically significant hazard ratio of 0.28 (p = 0.002). Multivariate analysis revealed that age, APACHE II score, and CRP were predictors of mortality in all the patient groups.

Conclusion

In patients treated for SARS-CoV-2 infection acquiring a bacterial infection due to prolonged hospitalization associated with the treatment of COVID-19 did not elevate mortality rates. The data suggests that in severe COVID-19 patients who survived beyond the first week of hospitalization, bacterial infections, particularly Klebsiella pneumoniae NDM, do not significantly impact mortality. Multivariate analysis revealed that age, APACHE II score, and CRP were predictors of mortality in all the patient groups.

Personalized Assessment of Mortality Risk and Hospital Stay Duration in Hospitalized Patients with COVID-19 Treated with Remdesivir: A Machine Learning Approach

Background: Despite advancements in vaccination, early treatments, and understanding of SARS-CoV-2, its impact remains significant worldwide. Many patients require intensive care due to severe COVID-19. Remdesivir, a key treatment option among viral RNA polymerase inhibitors, lacks comprehensive studies on factors associated with its effectiveness. Methods: We conducted a retrospective study in 2022, analyzing data from 252 hospitalized COVID-19 patients treated with remdesivir. Six machine learning algorithms were compared to predict factors influencing remdesivir's clinical benefits regarding mortality and hospital stay. Results: The extreme gradient boost (XGB) method showed the highest accuracy for both mortality (95.45%) and hospital stay (94.24%). Factors associated with worse outcomes in terms of mortality included limitations in life support, ventilatory support needs, lymphopenia, low albumin and hemoglobin levels, flu and/or coinfection, and cough. For hospital stay, factors included vaccine doses, lung density, pulmonary radiological status, comorbidities, oxygen therapy, troponin, lactate dehydrogenase levels, and asthenia. Conclusions: These findings underscore XGB's effectiveness in accurately categorizing COVID-19 patients undergoing remdesivir treatment.

Association between Post-Hospitalization Psychological Distress, Exercise Capacity, Physical Function and Health Status in COVID-19 Survivors

This study aims to determine whether post-hospitalization psychological distress is associated with exercise capacity, physical function and health status in COVID-19 survivors. In this observational study, hospitalized COVID patients were included and divided into two groups according to the mental component summary subscale of the 12-item Short-Form Health Survey. Patients with a score ≤ 45 were included in the psychological distress group, and patients with a score > 45 were included in the non-psychological distress group. The main variables were exercise capacity, physical function, and health status. Patients were evaluated at discharge, 3 months, and at 6 months follow-up. Finally, a total of 60 patients were included in the study. Significant differences were found in exercise capacity, physical function, and health status (p < 0.05), with worse results in the group with psychological distress at discharge and 3 months follow-up. At 6 months after discharge, COVID patients with psychological distress exhibited worse results in exercise capacity, physical function, and health status, being significant exercise capacity and physical function (p < 0.05). It can be concluded that COVID patients with psychological distress at hospital discharge reported worse exercise capacity, physical function and health status at hospital discharge, 3 months and 6 months follow-up.

Atorvastatin for reduction of 28-day mortality in severe and critical COVID-19 patients: a randomized controlled trial

BACKGROUND

COVID-19 is an abnormal host response to the SARS-CoV-2 infection, which is associated with endothelial dysfunction and multi-organ failure. Atorvastatin has been proposed to reduce COVID-19 severity and mortality in chronic and de-novo users.

METHODS

This randomized double-blind trial included 220 COVID-19 patients admitted to Mansoura University's isolation hospital in Egypt. One hundred and ten cases were given 40 mg of atorvastatin once daily for 28 days (group A), while 110 received a placebo (group B). All patients received treatment as per hospital protocol. The primary outcome is all-cause mortality at 28 days. We also tracked 6-month mortality, time to clinical improvement, the risk of invasive mechanical ventilation, acute kidney injury, potential adverse events, and hospital and intensive care length of stay.

RESULTS

The 28-day all-cause mortality was 52/104 (50%) in group A vs. 54/103 (52.4%) in group B, odds ratio (OR) = 0.907 (0.526, 1.565), P = 0.727; adjusted OR = 0.773 (0.407, 1.47), P = 0.433. Six-month mortality occurred in 53/102 (52%) and 59/79 (60.8%) in group A vs. B, respectively, P = 0.208. Among hospital survivors in group A vs. group B, the median time to clinical improvement was 10 days (7-14) vs. 10 (7-15), P = 0.715; the duration of hospital stay was 10 days (7-14) vs. 10 (8-17), P = 0.378. Discontinuation was higher in group B (four vs. one), but statistically insignificant, P = 0.369.

CONCLUSIONS

In adults with severe or critical COVID-19, atorvastatin did not reduce the risk of 28-day or 6-month mortality and did not shorten the length of hospital stay or time to clinical improvement. Trial registration Clinical Trial Registry (NCT04952350) on July 1st, 2021. https://clinicaltrials.gov/ct2/show/NCT04952350.

IoT platforms assessment methodology for COVID-19 vaccine logistics and transportation: a multi-methods decision making model

The supply chain management (SCM) of COVID-19 vaccine is the most daunting task for logistics and supply managers due to temperature sensitivity and complex logistics process. Therefore, several technologies have been applied but the complexity of COVID-19 vaccine makes the Internet of Things (IoT) a strong use case due to its multiple features support like excursion notification, data sharing, connectivity management, secure shipping, real-time tracking and monitoring etc. All these features can only feasible through choosing and deploying the right IoT platform. However, selection of right IoT platform is also a major concern due to lack of experience and technical knowledge of supply chain managers and diversified landscape of IoT platforms. Therefore, we introduce a decision making model for evaluation and decision making of IoT platforms that fits for logistics and transportation (L&T) process of COVID-19 vaccine. This study initially identifies the major challenges addressed during the SCM of COVID-19 vaccine and then provides reasonable solution by presenting the assessment model for selection of rational IoT platform. The proposed model applies hybrid Multi Criteria Decision Making (MCDM) approach for evaluation. It also adopts Estimation-Talk-Estimation (ETE) approach for response collection during the survey. As, this is first kind of model so the proposed model is validated and tested by conducting a survey with experts. The results of the proposed decision making model are also verified by Simple Additive Weighting (SAW) technique which indicates higher results accuracy and reliability of the proposed model. Similarly, the proposed model yields the best possible results and it can be judged by the precision, accuracy and recall values i.e. 93%, 93% and 94% respectively. The survey-based testing also suggests that this model can be adopted in practical scenarios to deal with complexities which may arise during the decision making of IoT platform for COVID-19 SCM process.

The Real Impact of Age on Mortality in Critically Ill COVID-19 Patients

OBJECTIVE

The impact of severe infection from COVID-19 and the resulting need for life support in an ICU environment is a fact that caused immense pressure in healthcare systems around the globe. Accordingly, elderly people faced multiple challenges, especially after admission to the ICU. On this basis, we performed this study to assess the impact of age on COVID-19 mortality in critically ill patients.

MATERIALS AND METHODS

In this retrospective study, we collected data from 300 patients who were hospitalized in the ICU of a Greek respiratory hospital. We split patients into two age groups using a threshold of 65 years old. The primary objective of the study was the survival of patients in a follow up period of 60 days after their admission to the ICU. Secondary objectives were to determine whether mortality is affected by other factors, including sepsis and clinical and laboratory factors, Charlson Comorbidity Index (CCI), APACHE II and d-dimers, CRP, etc. Results: The survival of all patients in the ICU was 75.7%. Those in the <65 years old age group expressed a survival rate of 89.3%, whereas those in the ≥65 years old age group had a survival rate of 58% (p-value < 0.001). In the multivariate Cox regression, the presence of sepsis and an increased CCI were independent predictors of mortality in 60 days (p-value < 0.001), while the age group did not maintain its statistical significance (p-value = 0.320).

CONCLUSIONS

Age alone as a simple number is not capable of predicting mortality in patients with severe COVID-19 in the ICU. We must use more composite clinical markers that may better reflect the biological age of patients, such as CCI. Moreover, the effective control of infections in the ICU is of utmost importance for the survival of patients, since avoiding septic complications can drastically improve the prognosis of all patients, regardless of age.