Biomarkers and clinical scores to aid the identification of disease severity and intensive care requirement following activation of an in-hospital sepsis code

Midregional-proAdrenomedullin as a prognostic tool in sepsis and septic shock: A systematic review and meta-analysis

BACKGROUND

Midregional-proAdrenomedullin (MR-proADM) has been recently proposed as a tool in patients with sepsis and septic shock. Our aim was to evaluate the prognostic role of MR-proADM in hospitalized patients with sepsis and septic shock.

METHODS

PRISMA guideline was followed. MEDLINE and EMBASE were searched up to June 2023. Primary outcome was mean difference in MR-proADM among survivors and nonsurvivors, secondary outcome mean difference in MR-proADM according to infection severity and type. Risk of bias was evaluated using Newcastle-Ottawa scale for observational studies and Cochrane tool for randomized trials. Pooled mean differences (MD) with corresponding 95% confidence intervals (CIs) were calculated in a random-effects model.

RESULTS

Twenty-four studies included 6730 adult patients (1208 nonsurvivors and 5522 survivors) and three studies included 195 paediatric patients (30 nonsurvivors and 165 survivors). A total of 10, 4 and 13 studies included, respectively, patients with sepsis (3602 patients), septic shock (386 patients) and a mixed population (2937 patients). Twenty-one studies included patients with different source of infection, three with pneumonia and one with a catheter-related infection. Most studies (n = 12) had a follow-up of 28 days. In adult cohort, pooled mean difference between nonsurvivors and survivors of MR-proADM was 2.55 mmol/L (95% CI: 1.95-3.15) with higher values in patients with septic shock (4.25 mmol/L; 95% CI, 2.23-6.26 mmol/L) than in patients with sepsis (1.77 mmol/L; 95% CI: 1.11-2.44 mmol/L). In paediatric cohort, pooled mean difference was 3.11 mmol/L (95% CI: -0.02-6.24 mmol/L).

CONCLUSIONS

Higher values of MR-proADM are detectable in nonsurvivors adult and paediatric-hospitalized patients with sepsis or septic shock.

Current perspectives in the management of sepsis and septic shock

Within patients with sepsis, there exists significant heterogeneity, and while all patients should receive conventional therapy, there are subgroups of patients who may benefit from specific therapies, often referred to as rescue therapies. Therefore, the identification of these specific patient subgroups is crucial and lays the groundwork for the application of precision medicine based on the development of targeted interventions. Over the years, efforts have been made to categorize sepsis into different subtypes based on clinical characteristics, biomarkers, or underlying mechanisms. For example, sepsis can be stratified into different phenotypes based on the predominant dysregulated host response. These phenotypes can range from hyperinflammatory states to immunosuppressive states and even mixed phenotypes. Each phenotype may require different therapeutic approaches to improve patient outcomes. Rescue strategies for septic shock may encompass various interventions, such as immunomodulatory therapies, extracorporeal support (e.g., ECMO), or therapies targeted at specific molecular or cellular pathways involved in the pathophysiology of sepsis. In recent years, there has been growing interest in precision medicine approaches to sepsis and phenotype identification. Precision medicine aims to tailor treatments to each individual patient based on their unique characteristics and disease mechanisms.

Early Diagnosis of Sepsis: The Role of Biomarkers and Rapid Microbiological Tests

Sepsis is a medical emergency resulting from a dysregulated response to an infection, causing preventable deaths and a high burden of morbidity. Protocolized and accurate interventions in sepsis are time-critical. Therefore, earlier recognition of cases allows for preventive interventions, early treatment, and improved outcomes. Clinical diagnosis of sepsis by clinical scores cannot be considered an early diagnosis, given that underlying molecular pathophysiological mechanisms have been activated in the preceding hour or days. There is a lack of a widely available tool enhancing preclinical diagnosis of sepsis. Sophisticated technologies for sepsis prediction have several limitations, including high costs. Novel technologies for fast molecular and microbiological diagnosis are focusing on bedside point-of-care combined testing to reach most settings where sepsis represents a challenge.

A Focus on the Pathophysiology of Adrenomedullin Expression: Endothelitis and Organ Damage in Severe Viral and Bacterial Infections

Adrenomedullin (ADM) is a peptide hormone produced primarily in the adrenal glands, playing a crucial role in various physiological processes. As well as improving vascular integrity and decreasing vascular permeability, ADM acts as a vasodilator, positive inotrope, diuretic, natriuretic and bronchodilator, antagonizing angiotensin II by inhibiting aldosterone secretion. ADM also has antihypertrophic, anti-apoptotic, antifibrotic, antioxidant, angiogenic and immunoregulatory effects and antimicrobial properties. ADM expression is upregulated by hypoxia, inflammation-inducing cytokines, viral or bacterial substances, strength of shear stress, and leakage of blood vessels. These pathological conditions are established during systemic inflammation that can result from infections, surgery, trauma/accidents or burns. The ability to rapidly identify infections and the prognostic, predictive power makes it a valuable tool in severe viral and bacterial infections burdened by high incidence and mortality. This review sheds light on the pathophysiological processes that in severe viral or bacterial infections cause endothelitis up to the development of organ damage, the resulting increase in ADM levels dosed through its more stable peptide mid-regional proadrenomedullin (MR-proADM), the most significant studies that attest to its diagnostic and prognostic accuracy in highlighting the severity of viral or bacterial infections and appropriate therapeutic insights.

Acute Kidney Injury and Sepsis after Cardiac Surgery: The Roles of Tissue Inhibitor Metalloproteinase-2, Insulin-like Growth Factor Binding Protein-7, and Mid-Regional Pro-Adrenomedullin

BACKGROUND

Identifying a panel of markers detecting kidney injury before the glomerular filtration rate reduction is a challenge to improving the diagnosis and management of acute kidney injury (AKI) in septic patients. This study evaluated the roles of tissue inhibitor metal proteinase-2, insulin growth factor binding protein-7 (TIMP2*IGFBP7), and mid-regional pro-adrenomedullin (MR-proADM) in patients with AKI.

PATIENTS AND METHODS

This study was prospectively conducted in an intensive care unit (ICU) enrolling 230 patients who underwent cardiac surgery. Biomarkers were evaluated before and after 4 h of the cardiac surgery.

RESULTS

Whereas urine and creatinine alterations appeared at 23.2 (12.7-36.5) hours after cardiac surgery, urinary TIMP2*IGBP7 levels were higher at 4 h in AKI patients (1.1 ± 0.4 mg/L vs. 0.08 ± 0.02 mg/L; p < 0.001). Its concentration > 2 mg/L increases AKI risk within the following 24 h, clearly identifying the population at high risk of renal replacement therapy (RRT). In patients with sepsis, MR-proADM levels were 2.3 nmol/L (0.7-7.8 nmol/L), with the highest values observed in septic shock patients (5.6 nmol/L (3.2-18 nmol/L)) and a better diagnostic profile than procalcitonin and C-reactive protein to identify septic patients. MR-proADM values > 5.1 nmol/L and urine TIMP2*IGBP7 levels > 2 mg/L showed a significantly faster progression to RRT, with a mean follow-up time of 1.1 days.

CONCLUSIONS

TIMP2*IGBP7 and MR-proADM precociously diagnose AKI in septic patients after cardiac surgery, giving prognostic information for RRT requirement.

Use of Biomarkers to Improve 28-Day Mortality Stratification in Patients with Sepsis and SOFA ≤ 6

Early diagnosis and appropriate treatments are crucial to reducing mortality risk in septic patients. Low SOFA scores and current biomarkers may not adequately discern patients that could develop severe organ dysfunction or have an elevated mortality risk. The aim of this prospective observational study was to evaluate the predictive value of the biomarkers mid-regional pro-adrenomedullin (MR-proADM), procalcitonin (PCT), C-reactive protein (CRP), and lactate for 28-day mortality in patients with sepsis, and patients with a SOFA score ≤6. 284 were included, with a 28-day all-cause mortality of 8.45% (n = 24). Non-survivors were older (p = 0.003), required mechanical ventilation (p = 0.04), were ventilated for longer (p = 0.02), and had higher APACHE II (p = 0.015) and SOFA (p = 0.027) scores. Lactate showed the highest predictive ability for all-cause 28-day mortality, with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (0.55-0.79). The AUROC for all-cause 28-day mortality in patients with community-acquired infection was 0.69 (0.57-0.84) for SOFA and 0.70 (0.58-0.82) for MR-proADM. A 2.1 nmol/L cut-off point for this biomarker in this subgroup of patients discerned, with 100% sensibility, survivors from non-survivors at 28 days. In patients with community-acquired sepsis and initial SOFA score ≤ 6, MR-proADM could help identify patients at risk of 28-day mortality.

Mid-regional proadrenomedullin (MR-proADM), C-reactive protein (CRP) and other biomarkers in the early identification of disease progression in patients with COVID-19 in the acute NHS setting

AIMS

There is a lack of biomarkers validated for assessing clinical deterioration in patients with COVID-19 on presentation to secondary or tertiary care. This evaluation looked at the potential clinical application of C reactive protein (CRP), procalcitonin, mid-regional proadrenomedullin (MR-proADM) and white cell count to support prediction of clinical outcomes.

METHODS

135 patients presenting to Hampshire Hospitals NHS Foundation Trust between April and June 2020 confirmed to have COVID-19 via reverse-transcription-qPCR were included. Biomarkers from within 24 hours of presentation were used to predict disease progression by Cox regression and area under the receiver operating characteristic curves. The endpoints assessed were 30-day all-cause mortality, intubation and ventilation, critical care admission and non-invasive ventilation (NIV) use.

RESULTS

Elevated MR-proADM was shown to have the greatest ability to predict 30-day mortality adjusting for age, cardiovascular disease, renal disease and neurological disease. A significant association was also noted between raised MR-proADM and CRP concentrations and the requirement for critical care admission and NIV.

CONCLUSIONS

The measurement of MR-proADM and CRP in patients with confirmed COVID-19 infection on admission shows significant potential to support clinicians in identifying those at increased risk of disease progression and need for higher level care, subsequently enabling prompt escalation in clinical interventions.

Time to decision in sepsis

OBJECTIVE

This study aimed to identify the common barriers leading to delayed initial management, microbiological diagnosis, and appropriate empirical antimicrobial treatment in sepsis.

METHODS

A cross-sectional study was performed by the application of a population-based survey. Four different surveys were designed, targeting the healthcare personnel located in main hospital areas [emergency department (SEMES); infectious diseases and clinical microbiology-microbiological diagnosis (SEIMC-M); intensive care and infectious diseases, (SEMICYUC-GTEIS); and infectious diseases and clinical microbiology-clinical diagnosis, (SEIMC-C)].

RESULTS

A total of 700 valid surveys were collected from June to November 2019: 380 (54.3%) of SEMES, 127 (18.1%) of SEIMC-M, 97 (13.9%) de SEMICYUC-GTEIS and 96 (13.7%) of SEIMC-C, in 270 hospitals of all levels of care. The qSOFA score was used as a screening tool. The most used biomarker was procalcitonin (n=92, 39.8%). The sepsis code was implemented in 157 of 235 participating centers (66.2%), particularly in tertiary level hospitals. The mean frequency of contaminated blood cultures was 8.9% (8.7). In 85 (78.7%) centers, positive results of blood cultures were available within the first 72 hours and were communicated to the treating physician effectively by phone or e-mail in 76 (81.7%) cases. The main reason for escalating treatment was clinical deterioration, and the reason for de-escalating antimicrobials was significantly different between the specialties. Quality indicators were not frequently monitored among the different participating centers.

CONCLUSIONS

There are significant barriers that hinder adequate management processes in sepsis in Spanish hospitals.

Characterization of a proteomic profile associated with organ dysfunction and mortality of sepsis and septic shock

INTRODUCTION

The search for new biomarkers that allow an early diagnosis in sepsis and predict its evolution has become a necessity in medicine. The objective of this study is to identify, through omics techniques, potential protein biomarkers that are expressed in patients with sepsis and their relationship with organ dysfunction and mortality.

METHODS

Prospective, observational and single-center study that included adult patients (≥ 18 years) who were admitted to a tertiary hospital and who met the criteria for sepsis. A mass spectrometry-based approach was used to analyze the plasma proteins in the enrolled subjects. Subsequently, using recursive feature elimination classification and cross-validation with a vector classifier, an association of these proteins with mortality and organ dysfunction was established. The protein-protein interaction network was analyzed with String software.

RESULTS

141 patients were enrolled in this study. Mass spectrometry identified 177 proteins. Of all of them, and by recursive feature elimination, nine proteins (GPX3, APOB, ORM1, SERPINF1, LYZ, C8A, CD14, APOC3 and C1QC) were associated with organ dysfunction (SOFA > 6) with an accuracy of 0.82 ± 0.06, precision of 0.85 ± 0.093, sensitivity 0.81 ± 0.10, specificity 0.84 ± 0.10 and AUC 0.82 ± 0.06. Twenty-two proteins (CLU, LUM, APOL1, SAA1, CLEBC3B, C8A, ITIH4, KNG1, AGT, C7, SAA2, APOH, HRG, AFM, APOE, APOC1, C1S, SERPINC1, IGFALS, KLKB1, CFB and BTD) were associated with mortality with an accuracy of 0.86 ± 0.05, a precision of 0.91 ± 0.05, a sensitivity of 0.91 ± 0.05, a specificity of 0.72 ± 0.17, and an area under the curve (AUC) of 0.81 ± 0.08 with a confidence interval of 95%.

CONCLUSION

In sepsis there are proteomic patterns associated with organ dysfunction and mortality.

Functional characterization of MLH1 missense variants unveils mechanisms of pathogenicity and clarifies role in cancer

Lynch syndrome is a heritable condition caused by a heterozygous germline inactivating mutation of the DNA mismatch repair (MMR) genes, most commonly the MLH1 gene. However, one third of the identified alterations are missense variants, for which the clinical significance is unclear in many cases. We have identified three MLH1 missense alterations (p.(Glu736Lys), p.(Pro640Thr) and p.(Leu73Pro)) in six individuals from large Tunisian families. For none of these alterations, a classification of pathogenicity was available, consequently diagnosis, predictive testing and targeted surveillance in affected families was impossible. We therefore performed functional laboratory testing using a system testing stability as well as catalytic activity that includes clinically validated reference variants. Both p.(Leu73Pro) and p.(Pro640Thr) were found to be non-functional due to severe defects in protein stability and catalytic activity. In contrast, p.(Glu736Lys) was comparable to the wildtype protein and therefore considered a neutral substitution. Analysis of residue conservation and of the structural roles of the substituted residues corroborated these findings. In conjunction with the available clinical data, two variants fulfil classification criteria for class 4 "likely pathogenic". The findings of this work clarify the mechanism of pathogenicity of two unclear MLH1 variants and enables predictive testing and targeted surveillance in members of carrier families worldwide.

Precision medicine in sepsis and septic shock: From omics to clinical tools

Sepsis is a heterogeneous disease with variable clinical course and several clinical phenotypes. As it is associated with an increased risk of death, patients with this condition are candidates for receipt of a very well-structured and protocolized treatment. All patients should receive the fundamental pillars of sepsis management, which are infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms. Herein, we will review the framework for identifying subpopulations of patients with sepsis, septic shock, and multiorgan dysfunction who may benefit from specific therapies. Some of these approaches are still in the early stages of research, while others are already in routine use in clinical practice, but together will help in the effective generation and safe implementation of precision medicine in sepsis.

Circulating MR-proADM levels, as an indicator of endothelial dysfunction, for early risk stratification of mid-term mortality in COVID-19 patients

Objectives

Thromboinflammation, resulting from a complex interaction between thrombocytopathy, coagulopathy, and endotheliopathy, contributes to increased mortality in COVID-19 patients. MR-proADM, as a surrogate of adrenomedullin system disruption, leading to endothelial damage, has been reported as a promising biomarker for short-term prognosis. We evaluated the role of MR-proADM in the mid-term mortality in COVID-19 patients.

Methods

A prospective, observational study enrolling COVID-19 patients from August to October 2020. A blood sample for laboratory test analysis was drawn on arrival in the emergency department. The primary endpoint was 90-day mortality. The area under the curve (AUC) and Cox regression analyses were used to assess discriminatory ability and association with the endpoint.

Results

A total of 359 patients were enrolled, and the 90-day mortality rate was 8.9%. ROC AUC for MR-proADM predicting 90-day mortality was 0.832. An optimal cutoff of 0.80 nmol/L showed a sensitivity of 96.9% and a specificity of 58.4%, with a negative predictive value of 99.5%. Circulating MR-proADM levels (inverse transformed), after adjusting by a propensity score including eleven potential confounders, were an independent predictor of 90-day mortality (HR: 0.162 [95% CI: 0.043-0.480])

Conclusions

Our data confirm that MR-proADM has a role in the mid-term prognosis of COVID-19 patients and might assist physicians with risk stratification.

The Surviving Sepsis Campaign: research priorities for the administration, epidemiology, scoring and identification of sepsis

Objective

To identify priorities for administrative, epidemiologic and diagnostic research in sepsis.

Design

As a follow-up to a previous consensus statement about sepsis research, members of the Surviving Sepsis Campaign Research Committee, representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine addressed six questions regarding care delivery, epidemiology, organ dysfunction, screening, identification of septic shock, and information that can predict outcomes in sepsis.

Methods

Six questions from the Scoring/Identification and Administration sections of the original Research Priorities publication were explored in greater detail to better examine the knowledge gaps and rationales for questions that were previously identified through a consensus process.

Results

The document provides a framework for priorities in research to address the following questions: (1) What is the optimal model of delivering sepsis care?; (2) What is the epidemiology of sepsis susceptibility and response to treatment?; (3) What information identifies organ dysfunction?; (4) How can we screen for sepsis in various settings?; (5) How do we identify septic shock?; and (6) What in-hospital clinical information is associated with important outcomes in patients with sepsis?

Conclusions

There is substantial knowledge of sepsis epidemiology and ways to identify and treat sepsis patients, but many gaps remain. Areas of uncertainty identified in this manuscript can help prioritize initiatives to improve an understanding of individual patient and demographic heterogeneity with sepsis and septic shock, biomarkers and accurate patient identification, organ dysfunction, and ways to improve sepsis care.

MR-proADM as marker of endotheliitis predicts COVID-19 severity

BACKGROUND

Early identification of patients at high risk of progression to severe COVID-19 constituted an unsolved challenge. Although growing evidence demonstrates a direct association between endotheliitis and severe COVID-19, the role of endothelial damage biomarkers has been scarcely studied. We investigated the relationship between circulating mid-regional proadrenomedullin (MR-proADM) levels, a biomarker of endothelial dysfunction, and prognosis of SARS-CoV-2-infected patients.

METHODS

Prospective observational study enrolling adult patients with confirmed COVID-19. On admission to emergency department, a blood sample was drawn for laboratory test analysis. Primary and secondary endpoints were 28-day all-cause mortality and severe COVID-19 progression. Area under the curve (AUC) and multivariate regression analysis were employed to assess the association of the biomarker with the established endpoints.

RESULTS

A total of 99 patients were enrolled. During hospitalization, 25 (25.3%) cases progressed to severe disease and the 28-day mortality rate was of 14.1%. MR-proADM showed the highest AUC to predict 28-day mortality (0.905; [CI] 95%: 0.829-0.955; P < .001) and progression to severe disease (0.829; [CI] 95%: 0.740-0.897; P < .001), respectively. MR-proADM plasma levels above optimal cut-off (1.01 nmol/L) showed the strongest independent association with 28-day mortality risk (hazard ratio [HR]: 10.470, 95% CI: 2.066-53.049; P < .005) and with progression to severe disease (HR: 6.803, 95% CI: 1.458-31.750; P = .015).

CONCLUSION

Mid-regional proadrenomedullin was the biomarker with highest performance for prognosis of death and progression to severe disease in COVID-19 patients and represents a promising predictor for both outcomes, which might constitute a potential tool in the assessment of prognosis in early stages of this disease.

MR-proAdrenomedullin as a predictor of renal replacement therapy in a cohort of critically ill patients with COVID-19

BACKGROUND

About 20% of ICU patients with COVID-19 require renal replacement therapy (RRT). Mid-regional pro-adrenomedullin (MR-proADM) might be used for risk assessment. This study investigates MR-proADM for RRT prediction in ICU patients with COVID-19.

METHODS

We analysed data of consecutive patients with COVID-19, requiring ICU admission at a university hospital in Germany between March and September 2020. Clinical characteristics, details on AKI, and RRT were assessed. MR-proADM was measured on admission.

RESULTS

64 patients were included (49 (77%) males). Median age was 62.5y (54-73). 47 (73%) patients were ventilated and 50 (78%) needed vasopressors. 25 (39%) patients had severe ARDS, and 10 patients needed veno-venous extracorporeal membrane oxygenation. 29 (45%) patients required RRT; median time from admission to RRT start was 2 (1-9) days. MR-proADM on admission was higher in the RRT group (2.491 vs. 1.23 nmol/l; p = 0.002) and showed the highest correlation with renalSOFA. ROC curve analysis showed that MR-proADM predicts RRT with an AUC of 0.69 (95% CI: 0.543-0.828; p = 0.019). In multivariable logistic regression MR-proADM was an independent predictor (OR: 3.813, 95% CI 1.110-13.102, p<0.05) for RRT requirement.

CONCLUSION

AKI requiring RRT is frequent in ICU patients with COVID-19. MR-proADM on admission was able to predict RRT requirement, which may be of interest for risk stratification and management.

Mid-regional pro-adrenomedullin as a supplementary tool to clinical parameters in cases of suspicion of infection in the emergency department

INTRODUCTION

Mid-regional proadrenomedullin (MR-proADM), a novel biomarker, has recently gained interest particularly with regards to its potential in assisting clinicians' decision making in patients with suspicion of infection in the emergency department (ED). A group of international experts, with research and experience in MR-proADM applications, produced this review based on their own experience and the currently available literature.

AREAS COVERED

The review provides evidence related to MR-proADM as a triaging tool in avoiding unnecessary admissions to hospital and/or inadequate discharge, and identifying patients most at risk of deterioration. It also covers the use of MR-proADM in the context of COVID-19. Moreover, the authors provide a proposal on how to incorporate MR-proADM into patients' clinical pathways in an ED setting.

EXPERT OPINION

The data we have so far on the application of MR-proADM in the ED is promising. Incorporating it into clinical scoring systems may aid the clinician's decision making and recognizing the 'ill looking well' and the 'well looking ill' sooner. However there are still many gaps in our knowledge especially during the ongoing COVID-19 waves. There is also a need for cost-effectiveness analysis studies especially in the era of increasing cost pressures on health systems globally.

Integrating infection and sepsis management through holistic early warning systems and heuristic approaches: a concept proposal

This is a first attempt to integrate the three pillars of infection management: the infection prevention and control (IPC), and surveillance (IPCS), antimicrobial stewardship (AMS), and rapid identification and management of sepsis (RIMS). The new 'Sepsis-3' definition extrapolates the diagnosis of sepsis from our previously slightly naïve concept of a stepwise evolving pattern. In doing so, however, we have placed the transition from infection toward sepsis in the domain of uncertainty and time-dependency. This now demands that clinical judgment be used in the risk stratification of patients with infection, and that pragmatic local solutions be used to prompt clinicians to evaluate formally for sepsis. We feel it is necessary to stimulate the development of a new generation of concepts and models aiming at embracing uncertainty. We see the opportunity for a heuristic approach focusing on the relevant clinical predictors at hand allowing to navigate the uncertainty of infection diagnosis under time constraints. The diverse and situated clinical approaches eventually emerging need to focus on the understanding of infection as the unbalanced interactions of host, pathogen, and environment. In order extend such approach throughout the patient journey we propose a holistic early warning system underpinned by the risk-based categories of hazards and vulnerabilities iteratively fostered by the information gathered by the infection prevention control and surveillance, clinical microbiology, and clinical chemistry services.

Hypernatremia and moderate-to-severe hyponatremia are independent predictors of mortality in septic patients at emergency department presentation: A sub-group analysis of the need-speed trial

STUDY OBJECTIVE

Early risk stratification of septic patients presenting to the emergency department (ED) is challenging. The aim of the study was to evaluate the prognostic role of plasmatic sodium level (_PNa⁺) derangements at ED presentation in septic patients.

METHODS

According to _PNa⁺ at ED presentation patients were divided in eunatremic (136-145 mEq/L), hypernatremic (>145 mEq/L) and hyponatremic (<136 mEq/L). Hyponatremic patients were subsequently divided in mild (130-135 mEq/L), moderate (125-129 mEq/L) and severe (<125 mEq/L). 7 and 30-day mortality was evaluated according to _PNa⁺ derangements and the degree of hyponatremia. The same analysis was then performed only in respiratory tract infection-related (RTI-r) sepsis patients.

RESULTS

879 septic patients were included in this analysis, 40.3% had hyponatremia, 5.7% hypernatremia. Hypernatremia showed higher mortality rates at both endpoints compared to eunatremia and hyponatremia (p<0.0001 for both). Eunatremia and mild hyponatremia were compared vs. moderate-to-severe hyponatremia showing a significant difference in terms of 7 and 30-day survival (p = 0.004 and p = 0.007, respectively). The Cox proportional model identified as independent predictors of 7 and 30-day mortality moderate-to-severe hyponatremia (HR 4.89[2.38-10.03] and 1.79[1.07-3.01], respectively) and hypernatremia (HR 3.52[1.58-7.82] and 2.14[1.17-3.92], respectively). The same analysis was performed in patients with respiratory tract infection-related sepsis (n = 549), with similar results.

CONCLUSION

Both hypernatremia and moderate-to-severe hyponatremia at ED presentation independently predict mortality in septic patients, allowing early risk stratification and suggesting more aggressive therapeutic strategies.

Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.

Clinical Decision Support Tool and Rapid Point-of-Care Platform for Determining Disease Severity in Patients with COVID-19

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.