New Sepsis Definition (Sepsis-3) and Community-acquired Pneumonia Mortality. A Validation and Clinical Decision-Making Study

Ranzani, Otávio T.; Prina, Elena; Menéndez, Rosário; Ceccato, Adrián; Cillóniz, Catia; Méndez, Raúl; Gabarrús, Albert; Barbeta, Enric; Bassi, Gianluigi Li; Ferrer, Miquel; Torres, Antoni

doi:10.1164/rccm.201611-2262oc

Cited by 149 publications

(126 citation statements)

References 40 publications

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“…Among the assessment tools for predicting mortality in patients with pneumonia, qSOFA reportedly has a relatively low sensitivity of 12-50%, but a relatively high specificity of 88.3-97%. [17][18][19] In the present study regarding NHCAP, similar results to those in previous reports were obtained, although many of the previous reports included CAP patients. [17][18][19] Therefore, qSOFA might be specifically useful for distinguishing patients at a low risk of pneumonia-related mortality.…”

Section: Discussionsupporting

confidence: 90%

“…Furthermore, PSI score is not widely used in clinical settings in Japan because of its relative complexity and the lack of physicians' awareness in addition to its weak power for predicting mortality in NHCAP patients. 16 Recent reports of the efficacy of qSOFA for predicting pneumonia mortality have shown that qSOFA has higher clinical efficacy for predicting in-hospital mortality (AUC 0.697, 95% CI 0.671-0.722) in CAP patients, 17 and Chen et al and Müller et al also reported that qSOFA was useful for predicting 28-day mortality in patients with community-onset pneumonia and communityand hospital-acquired pneumonia, respectively. 18,19 Although qSOFA has been reported to reflect the severity of HCAP in Japan, 20 no reports have clarified the efficacy of qSOFA for predicting mortality in NHCAP patients.…”

Section: Discussionmentioning

confidence: 99%

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Utility of the Quick Sequential Organ Failure Assessment in Japanese patients with nursing‐ and healthcare‐associated pneumonia

Noguchi

Yatera

Naito

et al. 2018

Geriatrics Gerontology Int

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Aim To clarify the utility of sepsis evaluation using the Quick Sequential Organ Failure Assessment (qSOFA) tool in addition to the Pneumonia Severity Index (PSI); age, dehydration, respiration, orientation and blood pressure (A‐DROP) index; and immunodeficiency, respiration, orientation, age and dehydration (I‐ROAD) scoring systems, and risk factor evaluation of potentially drug‐resistant (PDR) pathogens are suggested in the 2017 guidelines for pneumonia of the Japanese Respiratory Society in nursing‐ and healthcare‐associated pneumonia patients. Methods We included 289 hospitalized nursing‐ and healthcare‐associated pneumonia patients between April 2016 and March 2017, and investigated the ability of PSI, A‐DROP, I‐ROAD and qSOFA to predict pneumonia‐related mortality. We also evaluated the associations among the risk factors for PDR pathogens, the detection ratio of PDR pathogens and pneumonia‐related mortality. Results The mortality rate of pneumonia during hospitalization was 6.9% (20/289). The area under the curve for pneumonia‐related mortality predicted using PSI, A‐DROP, I‐ROAD and qSOFA was 0.697 (95% confidence interval [CI] 0.59–0.80), 0.63 (95% CI 0.51–0.76), 0.61 (95% CI 0.52–0.70) and 0.701 (95% CI 0.59–0.81), respectively. In addition, higher areas under the curve were observed for pneumonia‐related mortality predicted according to a combination of PSI and hypoalbuminemia (<2.5 g/dL) (0.75, 95% CI 0.64–0.86), and qSOFA and hypoalbuminemia (0.74, 95% CI 0.62–0.86) than for PSI and qSOFA alone. No significant associations were observed among the risk factors for PDR pathogens, the detection ratios of PDR pathogens and pneumonia‐related mortality. Conclusions qSOFA and the combination of qSOFA and hypoalbuminemia might be simple and useful evaluation tools for predicting pneumonia‐related mortality in nursing‐ and healthcare‐associated pneumonia patients. Geriatr Gerontol Int 2019; 19: 177–183.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Utility of the Quick Sequential Organ Failure Assessment in Japanese patients with nursing‐ and healthcare‐associated pneumonia

Noguchi

Yatera

Naito

et al. 2018

Geriatrics Gerontology Int

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“…Furthermore, even with negative microbiologic testing, providers often continue empiric antibiotics due to concerns of falsely negative results, a practice that drives emergence of antibiotic resistance and increases risk of Clostridium difficile infection (7). In the intensive care unit (ICU), LRTI diagnosis is particularly complex due to a high prevalence of non-infectious inflammatory conditions with overlapping clinical features (8) and a patient demographic that includes severely immunocompromised individuals who may exhibit atypical presentations of pulmonary infections.…”

Section: Introductionmentioning

confidence: 99%

Integrating Host Response and Unbiased Microbe Detection for Lower Respiratory Tract Infection Diagnosis in Critically Ill Adults

Kalantar

Moazed

Christenson

et al. 2018

Preprint

135

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Lower respiratory tract infections (LRTI) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, non-infectious inflammatory syndromes resembling LRTI further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed rules-based and logistic regression models (RBM, LRM) in a derivation cohort of 20 patients with LRTI or non-infectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with non-infectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an AUC of 0.96 (95% CI = 0.86 - 1.00), the diversity metric with an AUC of 0.80 (95% CI = 0.63 – 0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI = 0.75 – 1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome and host transcriptome may hold promise as a novel tool for LRTI diagnosis.SIGNIFICANCE STATEMENTLower respiratory tract infections (LRTI) are the leading cause of infectious disease-related death worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, non-infectious respiratory syndromes that resemble LRTI further complicate diagnosis and confound targeted treatment. To address this, we developed a novel metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, airway microbiome and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.

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“…14,15 Elevations in the SI indicate an increased heart rate or decreased systolic blood pressure. After the publication of SEPSIS-3, 2 some investigators reported that the qSOFA score predicted the mortality of patients in EDs with infections, such as pneumonia, [19][20][21] or regardless of suspected infections; 7,22 furthermore, the qSOFA score was superior to the SIRS criteria for predicting mortality. In the present study, the SI had the highest specificity and lowest sensitivity for mortality among the three indicators tested.…”

Section: W E Compared Three Simple and Commonly Usedmentioning

confidence: 99%

“…Therefore, the SIRS criteria could be more useful for predicting admission than in-hospital mortality. After the publication of SEPSIS-3, 2 some investigators reported that the qSOFA score predicted the mortality of patients in EDs with infections, such as pneumonia, [19][20][21] or regardless of suspected infections; 7,22 furthermore, the qSOFA score was superior to the SIRS criteria for predicting mortality. 23 In this cohort, the AUROC of the qSOFA score to predict in-hospital mortality was superior to that of the SIRS criteria and SI in prehospital emergency patients and it had similar AUROC for mortality in a previous study.…”

Section: W E Compared Three Simple and Commonly Usedmentioning

confidence: 99%

Comparative study on quick sequential organ failure assessment, systemic inflammatory response syndrome and the shock index in prehospital emergency patients: single‐site retrospective study

Harada

Takahashi

Haga³

et al. 2019

Acute Medicine & Surgery

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Aim The quick sequential organ failure assessment (qSOFA) score, shock index (SI), and systemic inflammatory response syndrome (SIRS) criteria are simple indicators for the mortality of patients in the emergency department (ED). These simple indicators using only vital signs might be more useful in prehospital care than in the ED due to their quick calculation. However, these indicators have not been compared in prehospital settings. The aim of the present study is to compare these indicators measured in prehospital care and verify whether the qSOFA score is useful for prehospital triage. Methods We undertook a single‐site retrospective study on patients transferred by ambulance to the Kumamoto Medical Center ED (Kumamoto, Japan) between January 2015 and December 2016. We compared areas under the receiver operating characteristic (AUROC) curves of the qSOFA score, SI, and SIRS criteria measured in prehospital care. We also carried out sensitivity and specificity analyses using the Youden index. Results A total of 4,827 patients were included in the present study. The AUROC (95% confidence interval) of the qSOFA score for in‐hospital mortality was 0.64 (0.61–0.67), which was significantly higher than those of the SIRS criteria (0.59 [0.56–0.62]) and SI (0.58 [0.54–0.62]). According to the optimal cut‐off values (qSOFA ≥ 2) decided on as the Youden index, the sensitivity of the qSOFA score was 52.3% and its specificity was 69.9%. Conclusions The qSOFA score had the highest AUROC among three indicators. However, it might not be practical in actual prehospital triage due to its low sensitivity.

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New Sepsis Definition (Sepsis-3) and Community-acquired Pneumonia Mortality. A Validation and Clinical Decision-Making Study

Abstract: qSOFA and CRB outperformed SIRS and presented better clinical usefulness as prompt tools for patients with community-acquired pneumonia in the emergency department. Among the tools for a comprehensive patient assessment, PSI had the best decision-aid tool profile.

Cited by 149 publications

References 40 publications

Utility of the Quick Sequential Organ Failure Assessment in Japanese patients with nursing‐ and healthcare‐associated pneumonia

Utility of the Quick Sequential Organ Failure Assessment in Japanese patients with nursing‐ and healthcare‐associated pneumonia

Integrating Host Response and Unbiased Microbe Detection for Lower Respiratory Tract Infection Diagnosis in Critically Ill Adults

Comparative study on quick sequential organ failure assessment, systemic inflammatory response syndrome and the shock index in prehospital emergency patients: single‐site retrospective study

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