SOFA score in septic patients: incremental prognostic value over age, comorbidities, and parameters of sepsis severity

Innocenti, Francesca; Tozzi, Camilla; Donnini, Chiara; Villa, Eleonora; Conti, Alberto; Zanobetti, Maurizio; Pini, Riccardo

doi:10.1007/s11739-017-1629-5

Cited by 51 publications

(52 citation statements)

References 35 publications

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“…26 Finally, we avoided the selection of comorbidities based on opinion of experts 27 28 and prevalence data. 22 29 30 Moreover, with the aim of overcoming the limitation of conventional stepwise selection when several predictors must be analysed, 31 32 the LASSO model has been adopted. By shrinking variables with very unstable estimates towards zero, the LASSO model can effectively exclude some irrelevant variables generating sparse estimations.…”

Section: Discussionmentioning

confidence: 99%

Developing and validating a novel multisource comorbidity score from administrative data: a large population-based cohort study from Italy

Corrao

Rea

Martino³

et al. 2017

BMJ Open

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ObjectiveTo develop and validate a novel comorbidity score (multisource comorbidity score (MCS)) predictive of mortality, hospital admissions and healthcare costs using multiple source information from the administrative Italian National Health System (NHS) databases.MethodsAn index of 34 variables (measured from inpatient diagnoses and outpatient drug prescriptions within 2 years before baseline) independently predicting 1-year mortality in a sample of 500 000 individuals aged 50 years or older randomly selected from the NHS beneficiaries of the Italian region of Lombardy (training set) was developed. The corresponding weights were assigned from the regression coefficients of a Weibull survival model. MCS performance was evaluated by using an internal (ie, another sample of 500 000 NHS beneficiaries from Lombardy) and three external (each consisting of 500 000 NHS beneficiaries from Emilia-Romagna, Lazio and Sicily) validation sets. Discriminant power and net reclassification improvement were used to compare MCS performance with that of other comorbidity scores. MCS ability to predict secondary health outcomes (ie, hospital admissions and costs) was also investigated.ResultsPrimary and secondary outcomes progressively increased with increasing MCS value. MCS improved the net 1-year mortality reclassification from 27% (with respect to the Chronic Disease Score) to 69% (with respect to the Elixhauser Index). MCS discrimination performance was similar in the four regions of Italy we tested, the area under the receiver operating characteristic curves (95% CI) being 0.78 (0.77 to 0.79) in Lombardy, 0.78 (0.77 to 0.79) in Emilia-Romagna, 0.77 (0.76 to 0.78) in Lazio and 0.78 (0.77 to 0.79) in Sicily.ConclusionMCS seems better than conventional scores for predicting health outcomes, at least in the general population from Italy. This may offer an improved tool for risk adjustment, policy planning and identifying patients in need of a focused treatment approach in the everyday medical practice.

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Section: Discussionmentioning

confidence: 99%

Developing and validating a novel multisource comorbidity score from administrative data: a large population-based cohort study from Italy

Corrao

Rea

Martino³

et al. 2017

BMJ Open

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“…Several traditional sepsis outcome prediction approaches are currently used in clinical practice, such as the Sequential Organ Failure Assessment (SOFA) [6], the Acute Physiology and Chronic Health Evaluation II (APACHE II) [7], and the Simplified Acute Physiology Score II (SAPS II) [8]. However, their performance (sensitivity, specificity) has not been shown to be adequate for all cases [9].…”

Section: Introductionmentioning

confidence: 99%

Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation

Wang

Sun

Teng

et al. 2020

BMC Med

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Background: Sepsis is a leading cause of death in intensive care units (ICUs), but outcomes of individual patients are difficult to predict. The recently developed clinical metabolomics has been recognized as a promising tool in the clinical practice of critical illness. The objective of this study was to identify the unique metabolic biomarkers and their pathways in the blood of sepsis nonsurvivors and to assess the prognostic value of these pathways. Methods: We searched PubMed, EMBASE, Cochrane, Web of Science, CNKI, Wangfang Data, and CQVIP from inception until July 2019. Eligible studies included the metabolomic analysis of blood samples from sepsis patients with the outcome. The metabolic pathway was assigned to each metabolite biomarker. The meta-analysis was performed using the pooled fold changes, area under the receiver operating characteristic curve (AUROC), and vote-counting of metabolic pathways. We also conducted a prospective cohort metabolomic study to validate the findings of our meta-analysis. Results: The meta-analysis included 21 cohorts reported in 16 studies with 2509 metabolite comparisons in the blood of 1287 individuals. We found highly limited overlap of the reported metabolite biomarkers across studies. However, these metabolites were enriched in several death-related metabolic pathways (DRMPs) including amino acids, mitochondrial metabolism, eicosanoids, and lysophospholipids. Prediction of sepsis death using DRMPs yielded a pooled AUROC of 0.81 (95% CI 0.76-0.87), which was similar to the combined metabolite biomarkers with a merged AUROC of 0.82 (95% CI 0.78-0.86) (P > 0.05). A prospective metabolomic analysis of 188 sepsis patients (134 survivors and 54 nonsurvivors) using the metabolites from DRMPs produced an AUROC of 0.88 (95% CI 0.78-0.97). The sensitivity and specificity for the prediction of sepsis death were 80.4% (95% CI 66.9-89.4%) and 78.8% (95% CI 62.3-89.3%), respectively. Conclusions: DRMP analysis minimizes the discrepancies of results obtained from different metabolomic methods and is more practical than blood metabolite biomarkers for sepsis mortality prediction. Trial registration: The meta-analysis was registered on OSF Registries, and the prospective cohort study was registered on the Chinese Clinical Trial Registry (ChiCTR1800015321).

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“…Although age or cardiac function is also an incremental prognostic value [ 36 , 37 ], for early evaluation of sepsis, quick SOFA score and screening for patients suspected of having sepsis can be expected to start treatment earlier [ 38 ]. If the severity of sepsis and outcomes could be predicted using the initial simple data at admission after evaluation of sepsis using quick SOFA, physicians could provide a therapeutic plan earlier, in combination with various additional treatments for patients in the high-mortality group.…”

Section: Discussionmentioning

confidence: 99%

Sepsis patients with complication of hypoglycemia and hypoalbuminemia are an early and easy identification of high mortality risk

et al. 2019

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Either hypoglycemia or hypoalbuminemia alone is an independent condition associated with increased risk of mortality in critical illness. This study evaluates whether the mortality risk increases in septic patients if these conditions are combined. Patients admitted to our hospital from 2008 to 2015 who satisfied the definition of sepsis were targeted ( n = 336). We classified cases into three groups based on blood glucose (BG) level measured at admission: hypoglycemia (Hypo-G; BG < 80 mg/dl), intermediate glycemia (Inter-G; 80–199 mg/dl), and hyperglycemia (Hyper-G; ≥ 200 mg/dl) group, and then estimated mortality. We also compared the clinical data of these glycemic groups in combination with hypoalbuminemia (Hypo-A) or Inter-G with non-hypoalbuminemia (Inter-G + Nonhypo-A), as a secondary analysis. Diagnostic cut-off level of Hypo-A (< 2.8 mg/dl) was determined using the ROC curve between blood albumin and mortality. In Hypo-G group ( n = 40), APACHE II/SOFA scores are significantly higher than in the Inter-G ( n = 196) and Hyper-G groups ( n = 100). Mortality is 52.5% in the Hypo-G and 60.0% in the Hypo-G with Hypo-A (Hypo-G + Hypo-A) groups. Significantly higher APACHE II or SOFA scores and mortality are observed in the Hypo-G + Hypo-A group compared to the Inter-G + Nonhypo-A group. A higher mortality risk is observed in cases with Hypo-G + Hypo-A (OR 5.065) than those with Hypo-G (OR 3.503), Inter-G (OR 1.175), Hyper-G (OR 1.756) or Hypo-A (OR 3.243), calculated by a single logistic-regression analysis. Hypo-G + Hypo-A in patients with sepsis is related to higher ICU mortality. Physicians should be keenly aware of these conditions to provide immediate intensive treatment after admission of septic patients.

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SOFA score in septic patients: incremental prognostic value over age, comorbidities, and parameters of sepsis severity

Cited by 51 publications

References 35 publications

Developing and validating a novel multisource comorbidity score from administrative data: a large population-based cohort study from Italy

Developing and validating a novel multisource comorbidity score from administrative data: a large population-based cohort study from Italy

Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation

Sepsis patients with complication of hypoglycemia and hypoalbuminemia are an early and easy identification of high mortality risk

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