Comparison of PICU Cost and Severity-Adjusted Cost Between Patients With SIRS-Defined Sepsis and Those With Age-Adapted SOFA-Defined Sepsis.
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SUBMITTER: Zhang X
PROVIDER: S-EPMC7947209 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ImportanceThe Sepsis Prediction Model (SPM) is a proprietary decision support tool created by Epic Systems; it generates a predicting sepsis score (PSS). The model has not undergone validation against existing sepsis prediction tools, such as Systemic Inflammatory Response Syndrome (SIRS), Sequential Organ Failure Assessment (SOFA), or quick Sepsis-Related Organ Failure Asessement (qSOFA).ObjectiveTo assess the validity and timeliness of the SPM compared with SIRS, qSOFA, and SOFA.Design, setting, and participantsThis retrospective cohort study included all adults admitted to 5 acute care hospitals in a single US health system between June 5, 2019, and December 31, 2020. Data analysis was conducted from March 2021 to February 2023.Main outcomes and measuresA sepsis event was defined as receipt of 4 or more days of antimicrobials, blood cultures collected within ±48 hours of initial antimicrobial, and at least 1 organ dysfunction as defined by the organ dysfunction criteria optimized for the electronic health record (eSOFA). Time zero was defined as 15 minutes prior to qualifying antimicrobial or blood culture order.ResultsOf 60 507 total admissions, 1663 (2.7%) met sepsis criteria, with 1324 electronic health record-confirmed sepsis (699 [52.8%] male patients; 298 [22.5%] Black patients; 46 [3.5%] Hispanic/Latinx patients; 945 [71.4%] White patients), 339 COVID-19 sepsis (183 [54.0%] male patients; 98 [28.9%] Black patients; 36 [10.6%] Hispanic/Latinx patients; and 189 [55.8%] White patients), and 58 844 (97.3%; 26 632 [45.2%] male patients; 12 698 [21.6%] Black patients; 3367 [5.7%] Hispanic/Latinx patients; 40 491 White patients) did not meet sepsis criteria. The median (IQR) age was 63 (51 to 73) years for electronic health record-confirmed sepsis, 69 (60 to 77) years for COVID-19 sepsis, and 60 (42 to 72) years for nonsepsis admissions. Within the vendor recommended threshold PSS range of 5 to 8, PSS of 8 or greater had the highest balanced accuracy for classifying a sepsis admission at 0.79 (95% CI, 0.78 to 0.80). Change in SOFA score of 2 or more had the highest sensitivity, at 0.97 (95% CI, 0.97 to 0.98). At a PSS of 8 or greater, median (IQR) time to score positivity from time zero was 68.00 (6.75 to 605.75) minutes. For SIRS, qSOFA, and SOFA, median (IQR) time to score positivity was 7.00 (-105.00 to 08.00) minutes, 74.00 (-22.25 to 599.25) minutes, and 28.00 (-108.50 to 134.00) minutes, respectively.Conclusions and relevanceIn this cohort study of hospital admissions, balanced accuracy of the SPM outperformed other models at higher threshold PSS; however, application of the SPM in a clinical setting was limited by poor timeliness as a sepsis screening tool as compared to SIRS and SOFA.
| S-EPMC10457723 | biostudies-literature
Project description:To determine the relationship between PICU volume and severity-adjusted mortality in a large, national dataset.Retrospective cohort study.The VPS database (VPS, LLC, Los Angeles, CA), a national multicenter clinical PICU database.All patients with discharge dates between September 2009 and March 2012 and valid Pediatric Index of Mortality 2 and Pediatric Risk of Mortality III scores, who were not transferred to another ICU and were seen in an ICU that collected at least three quarters of data.None.Anonymized data received included ICU mortality, hospital and patient demographics, and Pediatric Index of Mortality 2 and Pediatric Risk of Mortality III scores. PICU volume/quarter was determined (VPS sites submit data quarterly) per PICU and was divided by 100 to assess the impact per 100 discharges per quarter (volume). A mixed-effects logistic regression model accounting for repeated measures of patients within ICUs was performed to assess the association of volume on severity-adjusted mortality, adjusting for patient and unit characteristics. Multiplicative interactions between volume and severity of illness were also modeled. We analyzed 186,643 patients from 92 PICUs, with an overall ICU mortality rate of 2.6%. Volume ranged from 0.24 to 8.89 per ICU per quarter; the mean volume was 2.61. The mixed-effects logistic regression model found a small but nonlinear relationship between volume and mortality that varied based on the severity of illness. When severity of illness is low, there is no clear relationship between volume and mortality up to a Pediatric Index of Mortality 2 risk of mortality of 10%; for patients with a higher severity of illness, severity of illness-adjusted mortality is directly proportional to a unit's volume.For patients with low severity of illness, ICU volume is not associated with mortality. As patient severity of illness rises, higher volume units have higher severity of illness-adjusted mortality. This may be related to differences in quality of care, issues with unmeasured confounding, or calibration of existing severity of illness scores.
| S-EPMC5215123 | biostudies-literature
Project description:PurposeThe Sepsis-3 consensus task force defined sepsis as life-threatening organ dysfunction caused by dysregulated host response to infection. However, the clinical criteria for this definition were neither designed for nor validated in children. We validated the performance of SIRS, age-adapted SOFA, quick SOFA and PELOD-2 scores as predictors of outcome in children.MethodsWe performed a multicentre binational cohort study of patients < 18 years admitted with infection to ICUs in Australia and New Zealand. The primary outcome was ICU mortality. SIRS, age-adapted SOFA, quick SOFA and PELOD-2 scores were compared using crude and adjusted area under the receiver operating characteristic curve (AUROC) analysis.ResultsOf 2594 paediatric ICU admissions due to infection, 151 (5.8%) children died, and 949/2594 (36.6%) patients died or experienced an ICU length of stay ≥ 3 days. A ≥ 2-point increase in the individual score was associated with a crude mortality increase from 3.1 to 6.8% for SIRS, from 1.9 to 7.6% for age-adapted SOFA, from 1.7 to 7.3% for PELOD-2, and from 3.9 to 8.1% for qSOFA (p < 0.001). The discrimination of outcomes was significantly higher for SOFA (adjusted AUROC 0.829; 0.791-0.868) and PELOD-2 (0.816; 0.777-0.854) than for qSOFA (0.739; 0.695-0.784) and SIRS (0.710; 0.664-0.756).ConclusionsSIRS criteria lack specificity to identify children with infection at substantially higher risk of mortality. We demonstrate that adapting Sepsis-3 to age-specific criteria performs better than Sepsis-2-based criteria. Our findings support the translation of Sepsis-3 into paediatric-specific sepsis definitions and highlight the importance of robust paediatric organ dysfunction characterization.
| S-EPMC5816088 | biostudies-literature
Project description:BackgroundWith Sepsis-3, the increase in sequential organ failure assessment (SOFA) as a clinical score for the identification of patients with sepsis and quickSOFA (qSOFA) for the identification of patients at risk of sepsis outside the intensive care unit (ICU) were introduced in 2016. However, their validity has been questioned, and their applicability in different settings and subgroups, such as hematological cancer patients, remains unclear. We therefore assessed the validity of SOFA, qSOFA, and the systemic inflammatory response syndrome (SIRS) criteria regarding the diagnosis of sepsis and the prediction of in-hospital mortality in a multicenter cohort of hematological cancer patients treated on ICU and non-ICU settings.MethodsWe retrospectively calculated SIRS, SOFA, and qSOFA scores in our cohort and applied the definition of sepsis as "life-threatening organ dysfunction caused by dysregulated host response to infection" as reference. Discriminatory capacity was assessed using the area under the receiver operating characteristic curve (AUROC).ResultsAmong 450 patients with hematological cancer (median age 58?years, 274 males [61%]), 180 (40%) had sepsis of which 101 (56%) were treated on ICU. For the diagnosis of sepsis, sensitivity was 86%, 64%, and 42% for SIRS, SOFA, and qSOFA, respectively. However, the AUROCs of SOFA and qSOFA indicated better discrimination for sepsis than SIRS (SOFA, 0.69 [95% CI, 0.64-0.73] p?<?0.001; qSOFA, 0.67 [95% CI, 0.62-0.71] p?<?0.001; SIRS, 0.57 [95% CI, 0.53-0.61] p?<?0.001).In-hospital mortality was 40% and 14% in patients with and without sepsis, respectively (p?<?0.001). Regarding patients with sepsis, mortality was similar in patients with positive and negative SIRS scores (39% vs. 40% (p?=?0.899), respectively). For patients with qSOFA ??2, mortality was 49% compared to 33% for those with qSOFA <?2 (p?=?0.056), and for SOFA 56% vs. 11% (p?<?0.001), respectively. SOFA allowed significantly better discrimination for in-hospital mortality (AUROC 0.74 [95% CI, 0.69-0.79] p?<?0.001) than qSOFA (AUROC 0.65 [95% CI, 0.60-0.71] p?<?0.001) or SIRS (AUROC 0.49 [95% CI, 0.44-0.54] p?<?0.001).ConclusionsAn increase in SOFA score of ??2 had better prognostic accuracy for both diagnosis of sepsis and in-hospital mortality in this setting, and especially on ICU, we observed limited validity of SIRS criteria and qSOFA in identifying hematological patients with sepsis and at high risk of death.
| S-EPMC6686367 | biostudies-literature
Project description:Background: Recent attempts to translate Sepsis-3 criteria to children have been restricted to PICU patients and did not target children in emergency departments (ED). We assessed the prognostic accuracy of the age-adjusted quick Sequential Organ Failure Assessment score (qSOFA) and compared the performance to SIRS and the quick Pediatric Logistic Organ Dysfunction-2 score (qPELOD-2). We studied whether the addition of lactate (qSOFA-L) would increase prognostic accuracy. Methods: Non-academic, single-center, retrospective study in children visiting the ED and admitted with suspected bacterial infection between March 2013 and January 2018. We defined suspected bacterial infection as initiation of antibiotic therapy within 24 h after ED entry. Age-adjusted qSOFA, SIRS, qPELOD-2, and qSOFA-L scores were compared by area under the receiver operating characteristics curve (AUROC) analysis. Primary outcome measure was PICU transfer and/or mortality and secondary outcome was prolonged hospital length of stay. Results: We included 864 ED visits [474 (55%) male; median age 2.5 years; IQR 9 months-6 years], of which 18 were transferred to a PICU and 6 ended in death [composite outcome PICU transfer and/or mortality; 23 admissions (2.7%)]. 179 (22.2%) admissions resulted in prolonged hospital length of stay. PICU transfer and/or death was present in 22.5% of visits with qSOFA≥2 (n = 40) compared to 2.0% of visits with qSOFA<2 (n = 444) (p < 0.01). qSOFA tends to be the best predictor of PICU transfer and/or mortality (AUROC 0.72 (95% CI, 0.57-0.86) compared to SIRS [0.64 (95% CI, 0.53-0.74), p = 0.23] and qPELOD-2 [0.60 (95% CI, 0.45-0.76), p = 0.03)]. Prolonged hospital length of stay was poorly predicted by qSOFA (AUROC 0.53, 95% CI 0.46-0.59), SIRS (0.49, 95% CI 0.44-0.54), and qPELOD-2 (0.51, 95%CI 0.45-0.57). qSOFA-L resulted in an AUROC of 0.67 (95% CI, 0.50-0.84) for PICU transfer and/or mortality and an AUROC of 0.56 (95% CI, 0.46-0.67) for prolonged hospital length of stay. Conclusion: The currently proposed bedside risk-stratification tool of Sepsis-3 criteria, qSOFA, shows moderate prognostic accuracy for PICU transfer and/or mortality in children visiting the ED with suspected bacterial infection. The addition of lactate did not improve prognostic accuracy. Future prospective studies in larger ED populations are needed to further determine the utility of the qSOFA score.
| S-EPMC6174358 | biostudies-literature
Project description:Hepatic encephalopathy (HE) is a complication associated with worst prognosis in decompensated liver cirrhosis (LC) patients. Previous studies have identified prognostic factors for HE, and recent studies reported an association between systemic inflammatory response syndrome (SIRS) and liver disease. This study aimed to identify prognostic factors for 30-day mortality in alcoholic LC patients with HE who visited the emergency department (ED).This was a retrospective study of alcoholic LC patients with HE from January 1, 2010, to April 30, 2015. The baseline characteristics, complications of portal hypertension, laboratory values, Child-Pugh class, Model for End-stage Liver Disease (MELD) score, chronic liver failure-sequential organ failure assessment (CLIF-SOFA) score, and SIRS criteria were assessed. The presence of 2 or more SIRS criteria was considered SIRS. The primary outcomes were 30-day mortality and prognostic factors for patients with HE visiting the ED.In total, 105 patients who met the inclusion criteria were analyzed. Overall, the 30-day mortality rate was 6.7% (7 patients).Significant variables were hepatorenal syndrome, international normalized ratio, white blood cell count, total bilirubin level, MELD score CLIF-SOFA score, and SIRS in univariate analysis. CLIF-SOFA score and SIRS were the significant factors in the multivariate analysis (hazard ratio 5.56, 15.98; 95% confidence interval 1.18-26.18, 1.58-161.37; P = 0.03, P = 0.02). The mortality rates differed according to the CLIF-SOFA score (P?<?0.01).The CLIF-SOFA score and SIRS in alcoholic LC patients with HE visiting the ED are independent predictors of 30-day mortality.
| S-EPMC4937904 | biostudies-other
Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples
2015-10-24 | GSE74224 | GEO
Project description:The most common scoring system for critically ill patients is the Sequential Organ Failure Assessment (SOFA) score. Little is known about specific molecular signaling networks underlying the SOFA criteria. We characterized these networks and identified specific key regulatory molecules. We prospectively studied seven patients with sepsis and six controls with high-throughput RNA sequencing (RNAseq). Quantitative reverse transcription PCR (RT-qPCR) confirmation was performed in a second independent cohort. Differentially and significantly expressed miRNAs and their target mRNA transcripts were filtered for admission SOFA criteria and marker RNAs for the respective criteria identified. We bioinformatically constructed molecular signaling networks specifically reflecting these criteria followed by RT-qPCR confirmation of RNAs with important regulatory functions in the networks in the second cohort. RNAseq identified 82 miRNAs (45% upregulated) and 3254 mRNAs (50% upregulated) differentially expressed between sepsis patients and controls. Bioinformatic analysis characterized 6 miRNAs and 76 mRNA target transcripts specific for the SOFA criteria. RT-qPCR validated miRNA and mRNAs included IGFBP2 (respiratory system); MMP9 and PDE4B (nervous system); PPARG (cardiovascular system); AKR1B1, ANXA1, and LNC2/NGAL (acute kidney injury); GFER/ALR (liver); and miR-30c-3p (coagulopathy). There are specific canonical networks underlying the SOFA score. Key regulatory miRNA and mRNA transcripts support its biologic validity.
| S-EPMC8468706 | biostudies-literature
Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator
2015-10-24 | E-GEOD-74224 | biostudies-arrayexpress
Project description:Sepsis can be caused by malaria infection, but little is known about the utility of the quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) and SOFA score in malaria. We conducted a prospective observational study from March 2013 to February 2017 to examine adults admitted with community-acquired infection in a tertiary-care hospital in Ubon Ratchathani, Northeast Thailand (Ubon-sepsis). Subjects were classified as having sepsis if they had a modified SOFA score ≥2 within 24 hours of admission. Serum was stored and later tested for malaria parasites using a nested PCR assay. Presence of severe malaria was defined using modified World Health Organization criteria. Of 4,989 patients enrolled, 153 patients (3%) were PCR positive for either Plasmodium falciparum (74 [48%]), P. vivax (69 [45%]), or both organisms (10 [7%]). Of 153 malaria patients, 80 were severe malaria patients presenting with sepsis, 70 were non-severe malaria patients presenting with sepsis, and three were non-severe malaria patients presenting without sepsis. The modified SOFA score (median 5; IQR 4-6; range 1-18) was strongly correlated with malaria severity determined by the number of World Health Organization severity criteria satisfied by the patient (Spearman's rho = 0.61, p<0.001). Of 80 severe malaria patients, 2 (2.5%), 11 (14%), 62 (77.5%) and 5 (6%), presented with qSOFA scores of 0, 1, 2 and 3, respectively. Twenty eight-day mortality was 1.3% (2/153). In conclusion, qSOFA and SOFA can serve as markers of disease severity in adults with malarial sepsis. Patients presenting with a qSOFA score of 1 may also require careful evaluation for sepsis; including diagnosis of cause of infection, initiation of medical intervention, and consideration for referral as appropriate.
| S-EPMC6785116 | biostudies-literature