The effect of age on ventilation management and clinical outcomes in critically ill COVID-19 patients--insights from the PRoVENT-COVID study

Tocilizumab is associated with reduced delirium and coma in critically ill patients with COVID-19

Recent preclinical studies demonstrate a direct pathological role for the interleukin-6 (IL-6) pathway in mediating structural and functional delirium-like phenotypes in animal models of acute lung injury. Tocilizumab, an IL-6 pathway inhibitor, has shown reduced duration of ventilator dependency and mortality in critically ill patients with COVID-19. In this study, we test the hypothesis that tocilizumab is associated with reduced delirium/coma prevalence in critically ill patients with COVID-19. 253 patients were included in the study cohort, 69 in the tocilizumab group and 184 in the historical control group who did not receive tocilizumab. Delirium was assessed using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) with a positive score indicating delirium. Coma was defined as a Richmond Agitation-Sedation Scale score of - 4 or - 5. Tocilizumab was associated with significantly greater number of days alive without delirium/coma (tocilizumab [7 days (IQR: 3-9 days)] vs control [3 days (IQR: 1-8 days)]; p < 0.001). These results remained significant after adjusting for age, sex, sepsis, Charlson Comorbidity Index, Sequential Organ Failure Assessment score, and median daily dose of analgesics/sedatives ( β ^  = 0.671, p = 0.010). There were no significant differences in mortality ( β ^  = - 0.204, p = 0.561), ventilator duration ( β ^  = 0.016, p = 0.956), and ICU or hospital length of stay ( β ^  = - 0.134, p = 0.603; β ^  = 0.003, p = 0.991, respectively). Tocilizumab use was associated with significantly increased number of days without delirium/coma. Confirmation of these findings in randomized prospective studies may inform a novel paradigm of pharmacological amelioration of delirium/coma during critical illness.

Age and Comorbidity Profiles as Predictors of Mechanical Ventilation Duration in COVID-19 ICU Patients: A Retrospective Study in Saudi Arabia

Background The COVID-19 pandemic has highlighted the critical importance of understanding factors that impact outcomes for intensive care unit patients, especially those necessitating mechanical ventilation. This study aims to examine the influence of age and comorbidities on the duration of mechanical ventilation among COVID-19 patients in ICU settings, building on existing research that indicates the significant effects of these factors on patient outcomes. Methods A retrospective observational study was conducted involving COVID-19 patients in ICU who required mechanical ventilation. Selection criteria included ICU admission and the necessity for mechanical ventilation. Data collection focused on patient demographics, specifically age and comorbidities such as diabetes and hypertension, alongside the total duration of mechanical ventilation. The analysis utilized descriptive statistics, comparative methods, and regression modeling. Results The analysis revealed that older patients and those with certain comorbidities, notably diabetes and hypertension, typically experienced prolonged periods of mechanical ventilation. These findings are consistent with existing literature, underscoring the critical role of age and comorbidity in the management of COVID-19, in ICU patients. Conclusion This study sheds light on the significant factors influencing the duration of mechanical ventilation in COVID-19 ICU patients. The results emphasize the need for personalized treatment approaches in the ICU, particularly for older patients and those with specific comorbidities. These insights have substantial implications for clinical practice and public health, indicating the necessity for adaptable ventilation strategies and informed resource allocation. Furthermore, the findings pave the way for future research aimed at optimizing treatment protocols for diverse patient demographics in critical care settings.

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons

Purpose

The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary MIDRC dataset compared to the United States general population (US Census) and COVID-19 positive case counts from the Centers for Disease Control and Prevention (CDC).

Approach

The Jensen-Shannon distance (JSD), a measure of similarity of two distributions, was used to longitudinally measure the representativeness of the distribution of (1) all unique patients in the MIDRC data to the 2020 US Census and (2) all unique COVID-19 positive patients in the MIDRC data to the case counts reported by the CDC. The distributions were evaluated in the demographic categories of age at index, sex, race, ethnicity, and the combination of race and ethnicity.

Results

Representativeness of the MIDRC data by ethnicity and the combination of race and ethnicity was impacted by the percentage of CDC case counts for which this was not reported. The distributions by sex and race have retained their level of representativeness over time.

Conclusion

The representativeness of the open medical imaging datasets in the curated public data commons at MIDRC has evolved over time as the number of contributing institutions and overall number of subjects have grown. The use of metrics, such as the JSD support measurement of representativeness, is one step needed for fair and generalizable AI algorithm development.

The obesity paradox in Japanese COVID-19 patients

Purpose: To investigate the effect of obesity on mortality and invasive respiratory care (IRC) in patients with COVID-19. Methods: We studied 1,105 patients for 34 months and collected data. The primary outcome was all-cause death at 29 days. The secondary outcome was IRC indicated by a pulse oximetry rate below 93% at a mask oxygenation rate of 5 L/min or more. Results: Age- and sex-adjusted multivariate regression analysis for 29-day deaths showed the significance of body mass index (BMI) > 19.6 kg/m2 (odds ratio 0.117, 95% confidence interval 0.052-0.265, P<0.001). The graphs with BMI in the abscissa showed, within a BMI between 11 and 25 kg/m2, a decreasing pattern for mortality and IRC rate, and no increase in overweight. Conclusion: In Japanese COVID-19 patients, the risk of mortality and the IRC rate decreased in underweight patients and remained low in overweight patients, suggesting the importance of the obesity paradox.

Risk factors associated with mortality among elderly patients with COVID-19: Data from 55 intensive care units in Spain

INTRODUCTION AND OBJECTIVES

Critically-ill elderly ICU patients with COVID-19 have poor outcomes. We aimed to compare the rates of in-hospital mortality between non-elderly and elderly critically-ill COVID-19 ventilated patients, as well as to analyze the characteristics, secondary outcomes and independent risk factors associated with in-hospital mortality of elderly ventilated patients.

PATIENTS AND METHODS

We conducted a multicentre, observational cohort study including consecutive critically-ill patients admitted to 55 Spanish ICUs due to severe COVID-19 requiring mechanical ventilation (non-invasive respiratory support [NIRS; include non-invasive mechanical ventilation and high-flow nasal cannula] and invasive mechanical ventilation [IMV]) between February 2020 and October 2021.

RESULTS

Out of 5,090 critically-ill ventilated patients, 1,525 (27%) were aged ≥70 years (554 [36%] received NIRS and 971 [64%] received IMV. In the elderly group, median age was 74 years (interquartile range 72-77) and 68% were male. Overall in-hospital mortality was 31% (23% in patients <70 years and 50% in those ≥70 years; p<0.001). In-hospital mortality in the group ≥70 years significantly varied according to the modality of ventilation (40% in NIRS vs. 55% in IMV group; p<0.001). Factors independently associated with in-hospital mortality in elderly ventilated patients were age (sHR 1.07 [95%CI 1.05-1.10], p<0.001); previous admission within the last 30 days (sHR 1.40 [95%CI 1.04-1.89], p = 0.027); chronic heart disease (sHR 1.21 [95%CI 1.01-1.44], p = 0.041); chronic renal failure (sHR 1.43 [95%CI 1.12- 1.82], p = 0.005); platelet count (sHR 0.98 [95% CI 0.98-0.99], p<0.001); IMV at ICU admission (sHR 1.41 [95% CI 1.16- 1.73], p<0.001); and systemic steroids (sHR 0.61 [95%CI 0.48- 0.77], p<0.001).

CONCLUSIONS

Amongst critically-ill COVID-19 ventilated patients, those aged ≥70 years presented significantly higher rates of in-hospital mortality than younger patients. Increasing age, previous admission within the last 30 days, chronic heart disease, chronic renal failure, platelet count, IMV at ICU admission and systemic steroids (protective) all comprised independent factors for in-hospital mortality in elderly patients.

Age and sex differentially shape brain networks in Parkinson's disease

AIMS

Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients.

METHODS

Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated.

RESULTS

Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients.

CONCLUSION

Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.

Outcomes comparison between the first and the subsequent SARS-CoV-2 waves - a systematic review and meta-analysis

Background

In the beginning of the SARS-CoV-2 pandemic, health care professionals dealing with COVID-19 had to rely exclusively on general supportive measures since specific treatments were unknown. The subsequent waves could be faced with new diagnostic and therapeutic tools (e.g., anti-viral medications and vaccines). We performed a meta-analysis and systematic review to compare clinical endpoints between the first and subsequent waves.

Methods

Three databases were assessed. The primary outcome was in-hospital mortality. The secondary outcomes were intensive care unit (ICU) mortality, ICU length of stay (LOS), acute renal failure, extracorporeal membrane oxygenation (ECMO) implantation, mechanical ventilation time, hospital LOS, systemic thromboembolism, myocarditis and ventilator associated pneumonia.

Results

A total of 25 studies with 126,153 patients were included. There was no significant difference for the primary endpoint (OR=0.94, 95% CI 0.83-1.07, p=0.35). The first wave group presented higher rates of ICU LOS (SMD= 0.23, 95% CI 0.11-0.35, p<0.01), acute renal failure (OR=1.71, 95% CI 1.36-2.15, p<0.01) and ECMO implantation (OR=1.64, 95% CI 1.06-2.52, p=0.03). The other endpoints did not show significant differences.

Conclusions

The analysis suggests that the first wave group, when compared with the subsequent waves group, presented higher rates of ICU LOS, acute renal failure and ECMO implantation, without significant difference in in-hospital or ICU mortality, mechanical ventilation time, hospital LOS, systemic thromboembolism, myocarditis or ventilator- associated pneumonia.