Less is more: an ecological and economic point of view on appropriate use of lab testing for COVID-19 patients

Herpes zoster in older adults: Impact on carbon footprint in the United States

We provide estimates for (I) annual herpes zoster (HZ) cases, (II) carbon costs related to healthcare utilization, and (III) annual carbon emissions due to HZ among ≥50 years of age (YOA) United States (US) population. We estimated the annual number of HZ cases in the US based on available incidence data and demographic data of individuals ≥50 YOA. Both the healthcare resource utilization (HCRU) associated with HZ cases and the unit carbon dioxide equivalent (i.e. CO2e) costs associated with each type of HCRU in the US were estimated based on literature and studies available online. The carbon footprint associated with HZ annually among US adults ≥50 YOA was estimated by multiplying the unit carbon estimates by the HCRU. In the US population aged ≥50 YOA in 2020 (i.e. approximately 118 million), approximately 1.1 million cases of HZ occur annually assuming no vaccination. Based on 2 sources of HCRU the average kgCO2e per HZ patient ranged from 61.0 to 97.6 kgCO2e, with values by age group ranging from 40.9 kgCO2e in patients aged 50-59 to 195.9 kgCO2e in patients ≥80 YOA. The total annual HZ associated carbon ranged between 67,000 and 107,000 tons of CO2e in the US population aged ≥50 YOA. The impact of HZ on carbon footprint in the US results in considerable greenhouse gas (GHG)emissions. Assuming no vaccination, the burden of HZ is projected to rise over the coming years with the aging populations consequently worsening its impact on GHG emissions. (Figure 1).

Mitochondrial Dysfunction in Peripheral Blood Mononuclear Cells as Novel Diagnostic Tools for Non-Alcoholic Fatty Liver Disease: Visualizing Relationships with Known and Potential Disease Biomarkers

Non-alcoholic fatty liver disease (NAFLD) is a health emergency worldwide due to its high prevalence and the lack of specific therapies. Noninvasive biomarkers supporting NAFLD diagnosis are urgently needed. Liver mitochondrial dysfunction is a central NAFLD pathomechanism that changes throughout disease progression. Blood-cell bioenergetics reflecting mitochondrial organ dysfunction is emerging for its potential applications in diagnostics. We measured real-time mitochondrial respirometry in peripheral blood mononuclear cells (PBMCs), anthropometric parameters, routine blood analytes, and circulating cytokines from a cohort of NAFLD patients (N = 19) and non-NAFLD control subjects (N = 18). PBMC basal respiration, ATP-linked respiration, maximal respiration, and spare respiratory capacity were significantly reduced in NAFLD compared to non-NAFLD cases. Correlation plots were applied to visualize relationships between known or potential NAFLD-related biomarkers, while non-parametric methods were applied to identify which biomarkers are NAFLD predictors. Basal and ATP-linked mitochondrial respiration were negatively correlated with triglycerides and fasting insulin levels and HOMA index. Maximal and spare respiratory capacity were negatively correlated with IL-6 levels. All the mitochondrial respiratory parameters were positively correlated with HDL-cholesterol level and negatively correlated with fatty liver index. We propose including blood cell respirometry in panels of NAFLD diagnostic biomarkers to monitor disease progression and the response to current and novel therapies, including mitochondrial-targeted ones.

Inclusion of Environmental Spillovers in Applied Economic Evaluations of Healthcare Products

OBJECTIVES

Climate change and environmental factors have an impact on human health and the ecosystem. The healthcare sector is responsible for substantial environmental pollution. Most healthcare systems rely on economic evaluation to select efficient alternatives. Nevertheless, environmental spillovers of healthcare treatments are rarely considered whether it is from a cost or a health perspective. The objective of this article is to identify economic evaluations of healthcare products and guidelines that have included any environmental dimensions.

METHODS

Electronic searches of 3 literature databases (PubMed, Scopus, and EMBASE) and official health agencies guidelines were conducted. Documents were considered eligible if they assessed the environmental spillovers within the economic evaluation of a healthcare product or provided any recommendations on the inclusion of environmental spillovers in the health technology assessment process.

RESULTS

From the 3878 records identified, 62 documents were deemed eligible and 18 were published in 2021 and 2022. The environmental spillovers considered were carbon dioxide (CO₂) emissions, water or energy consumption, and waste disposal. The environmental spillovers were mainly assessed using the lifecycle assessment (LCA) approach while the economic analysis was mostly limited to costs. Only 9 documents, including the guidelines of 2 health agencies presented theoretical and practical ways to include environmental spillovers into the decision-making process.

CONCLUSIONS

There is a clear lack of methods on whether environmental spillovers should be included in health economic evaluation and how this should be done. If healthcare systems want to reduce their environment footprint, the development of methodology which integrates environmental dimensions in health technology assessment will be key.

Predictive markers for clinical outcomes in a cohort of diabetic patients hospitalized for COVID-19

INTRODUCTION

The role of glycemic control, both prior and during hospitalization, on mortality from COVID-19 in diabetic patients is debated. Furthermore, it is not clear whether hyperglycemia has a direct effect or requires inflammatory mechanisms.

OBJECTIVE

To identify predictors of clinical outcomes (in-hospital mortality, length of hospitalization, respiratory failure, need for intensive care), considering hyperglycemia, inflammation markers and clinical history.

METHODS

Retrospective observational study of 291 diabetic patients hospitalized with COVID-19 in the Spedali Civili di Brescia from February 1th 2020 to March 31th 2021, with also outpatient electronic records. Glucose, inflammatory parameters, creatinine were collected within 24 h after admission to the hospital. A causal mediation analysis allowed the estimation of the direct and indirect effects of hyperglycemia on mortality.

RESULTS

Glucose at admission ≥ 165 mg/dL and reduced renal function were associated with an increased risk of in-hospital mortality and length of hospitalization (all p < 0.001), while an increase in inflammatory parameters was significantly associated with an increased risk of all outcomes. High basophil count was associated with reduced mortality (p < 0.001). Hyperglycemia had a direct effect on mortality (p < 0.001); the indirect, through inflammatory markers, was significant only for absolute neutrophil count, C-Reactive protein and procalcitonin (p = 0.007, p = 0.029, p = 0.042). Patients with microvascular complications and with chronic kidney disease showed higher mortality (p = 0.03, p = 0.01).

CONCLUSIONS

Hyperglycemia at admission, renal function and inflammatory parameters were found to be predictors of in-hospital mortality, while an increased basophil count was protective. Hyperglycemia had a direct effect on mortality, the indirect effect was only through few markers and markedly lower than the direct one.

Exploratory COVID-19 death risk score based on basic laboratory tests and physiological clinical measurements

BACKGROUND

In the event of a sudden shortage of medical resources, a rapid, simple, and accurate prediction model is essential for the 30-day mortality rate of patients with COVID-19.

METHODS

This retrospective study compared the characteristics of the survivals and non-survivals of 278 patients with COVID-19. Logistic regression analysis was performed to obtain the "COVID-19 death risk score" (CDRS) model. Using the area under the receiver operating characteristic (AUROC) curve and Hosmer-Lemeshow goodness-of-fit test, discrimination and calibration were assessed. Internal validation was conducted using a regular bootstrap method.

RESULTS

A total of 63 (22.66%) of 278 included patients died. The logistic regression analysis revealed that high-sensitivity C-reactive protein (hsCRP; odds ratio [OR]=1.018), D-dimer (OR=1.101), and respiratory rate (RR; OR=1.185) were independently associated with 30-day mortality. CDRS was calculated as follows: CDRS=-10.245+(0.022×hsCRP)+(0.172×D-dimer)+(0.203×RR). CDRS had the same predictive effect as the sequential organ failure assessment (SOFA) and "confusion, uremia, respiratory rate, blood pressure, and age over 65 years" (CURB-65) scores, with AUROCs of 0.984 for CDRS, 0.975 for SOFA, and 0.971 for CURB-65, respectively. And CDRS showed good calibration. The AUROC through internal validations was 0.980 (95% confidence interval [CI]: 0.965-0.995). Regarding the clinical value, the decision curve analysis of CDRS showed a net value similar to that of CURB-65 in this cohort.

CONCLUSION

CDRS is a novel, efficient and accurate prediction model for the early identification of COVID-19 patients with poor outcomes. Although it is not as advanced as the other models, CDRS had a similar performance to that of SOFA and CURB-65.