Use of prehospital qSOFA in predicting in-hospital mortality in patients with suspected infection: A retrospective cohort study

Using Life-Saving Interventions to Determine Optimal Vital Sign Ranges among Adults Encountered by Emergency Medical Services

BACKGROUND

Vital signs are an essential component of the prehospital assessment of patients encountered in an emergency response system and during mass-casualty disaster events. Limited data exist to define meaningful vital sign ranges to predict need for advanced care.

STUDY OBJECTIVES

The aim of this study was to identify vital sign ranges that were maximally predictive of requiring a life-saving intervention (LSI) among adults cared for by Emergency Medical Services (EMS).

METHODS

A retrospective study of adult prehospital encounters that resulted in hospital transport by an Advanced Life Support (ALS) provider in the 2022 National EMS Information System (NEMSIS) dataset was performed. The outcome was performance of an LSI, a composite measure incorporating critical airway, medication, and procedural interventions, categorized into eleven groups: tachydysrhythmia, cardiac arrest, airway, seizure/sedation, toxicologic, bradycardia, airway foreign body removal, vasoactive medication, hemorrhage control, needle decompression, and hypoglycemia. Cut point selection was performed in a training partition (75%) to identify ranges for heart rate (HR), respiratory rate (RR), systolic blood pressure (SBP), oxygen saturation, and Glasgow Coma Scale (GCS) by using an approach intended to prioritize specificity, keeping sensitivity constrained to at least 25%.

RESULTS

Of 18,259,766 included encounters (median age 63 years; 51.8% male), 6.3% had at least one LSI, with the most common being airway interventions (2.2%). Optimal ranges for vital signs included 47-129 beats/minute for HR, 8-30 breaths/minute for RR, 96-180mmHg for SBP, >93% for oxygen saturation, and >13 for GCS. In the test partition, an abnormal vital sign had a sensitivity of 75.1%, specificity of 66.6%, and positive predictive value (PPV) of 12.5%. A multivariable model encompassing all vital signs demonstrated an area under the receiver operator characteristic curve (AUROC) of 0.78 (95% confidence interval [CI], 0.78-0.78). Vital signs were of greater accuracy (AUROC) in identifying encounters needing airway management (0.85), needle decompression (0.84), and tachydysrhythmia (0.84) and were lower for hemorrhage control (0.52), hypoglycemia management (0.68), and foreign body removal (0.69).

CONCLUSION

Optimal ranges for adult vital signs in the prehospital setting were statistically derived. These may be useful in prehospital protocols and medical alert systems or may be incorporated within prediction models to identify those with critical illness and/or injury for patients with out-of-hospital emergencies.

Correlation of vital sign centiles with in-hospital outcomes among adults encountered by emergency medical services

BACKGROUND

Vital signs are a critical component of the prehospital assessment. Prior work has suggested that vital signs may vary in their distribution by age. These differences in vital signs may have implications on in-hospital outcomes or be utilized within prediction models. We sought to (1) identify empirically derived (unadjusted) cut points for vital signs for adult patients encountered by emergency medical services (EMS), (2) evaluate differences in age-adjusted cutoffs for vital signs in this population, and (3) evaluate unadjusted and age-adjusted vital signs measures with in-hospital outcomes.

METHODS

We used two multiagency EMS data sets to derive (National EMS Information System from 2018) and assess agreement (ESO, Inc., from 2019 to 2021) of vital signs cutoffs among adult EMS encounters. We compared unadjusted to age-adjusted cutoffs. For encounters within the ESO sample that had in-hospital data, we compared the association of unadjusted cutoffs and age-adjusted cutoffs with hospitalization and in-hospital mortality.

RESULTS

We included 13,405,858 and 18,682,684 encounters in the derivation and validation samples, respectively. Both extremely high and extremely low vital signs demonstrated stepwise increases in admission and in-hospital mortality. When evaluating age-based centiles with vital signs, a gradual decline was noted at all extremes of heart rate (HR) with increasing age. Extremes of systolic blood pressure at upper and lower margins were greater in older age groups relative to younger age groups. Respiratory rate (RR) cut points were similar for all adult age groups. Compared to unadjusted vital signs, age-adjusted vital signs had slightly increased accuracy for HR and RR but lower accuracy for SBP for outcomes of mortality and hospitalization.

CONCLUSIONS

We describe cut points for vital signs for adults in the out-of-hospital setting that are associated with both mortality and hospitalization. While we found age-based differences in vital signs cutoffs, this adjustment only slightly improved model performance for in-hospital outcomes.

Prediction of unfavorable outcomes in community-acquired bacteremia by SIRS, SOFA and qSOFA scores

BACKGROUND

Sepsis diagnostic and prognostic scoring systems have changed over time. It remains uncertain which scoring system is the best predictor of unfavorable outcomes. We aimed to evaluate prediction of community-acquired bacteremia (CAB) outcomes using on-admission systemic inflammatory response syndrome (SIRS), sequential organ failure assessment (SOFA) and quick sequential organ failure assessment (qSOFA).

METHODS

We present a retrospective observational cohort study of consecutive adult patients hospitalized with CAB over ten years. SIRS, qSOFA and SOFA scores calculated on admission were dichotomized as ≥2 or 0-1. Raw and adjusted incidence of a composite unfavorable outcome (death, septic shock, invasive mechanical ventilation, extra-corporeal membrane oxygenation, renal replacement therapy) over 35 days were compared.

RESULTS

Among 1930 patients, 1221 (63.3%) had SIRS, 196 (10.2%) had qSOFA, and 1117 (57.9%) had SOFA≥2. Respective raw and adjusted probabilities of the outcome were similar. Incidence for qSOFA≥2 was high (41.3%) and still considerable for qSOFA 0-1 (5.4%). SOFA≥2 indicated higher risk than SIRS≥2 (14.7% vs. 12.4%), while SOFA 0-1 indicated lower risk than SIRS 0-1 (1.2% vs. 3.1%). This relationship between SOFA and SIRS was also observed in patients with qSOFA 0-1.

CONCLUSIONS

qSOFA≥2 was associated with highest probability of unfavorable outcome, but dichotomized SOFA was more precise at high vs. low-risk distinction. Consecutive use of dichotomized qSOFA and SOFA on admission of adults with CAB enables fast and reliable identification of patients at high (qSOFA≥2, risk ~≥35%), moderate (qSOFA 0-1, SOFA≥2, risk ~10%), and low risk (qSOFA 0-1, SOFA 0-1, risk 1-2%) of subsequent unfavorable events.

Prehospital pulse pressure and mortality of septic shock patients cared for by a mobile intensive care unit

BACKGROUND

Septic shock medical treatment relies on a bundle of care including antibiotic therapy and hemodynamic optimisation. Hemodynamic optimisation consists of fluid expansion and norepinephrine administration aiming to optimise cardiac output to reach a mean arterial pressure of 65mmHg. In the prehospital setting, direct cardiac output assessment is difficult because of the lack of invasive and non-invasive devices. This study aims to assess the relationship between 30-day mortality and (i) initial pulse pressure (iPP) as (ii) pulse pressure variation (dPP) during the prehospital stage among patients cared for SS by a prehospital mobile intensive care unit (MICU).

METHODS

From May 09th, 2016 to December 02nd, 2021, septic shock patients requiring MICU intervention were retrospectively analysed. iPP was calculated as the difference between systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the first contact between the patient and the MICU team prior to any treatment and, dPP as the difference between the final PP (the difference between SBP and DBP at the end of the prehospital stage) and iPP divided by prehospital duration. To consider cofounders, the propensity score method was used to assess the relationship between (i) iPP < 40mmHg, (ii) positive dPP and 30-day mortality.

RESULTS

Among the 530 patients analysed, pulmonary, digestive, and urinary infections were suspected among 43%, 25% and 17% patients, respectively. The 30-day overall mortality rate reached 31%. Cox regression analysis showed an association between 30-day mortality and (i) iPP < 40mmHg; aHR of 1.61 [1.03-2.51], and (ii) a positive dPP; aHR of 0.56 [0.36-0.88].

CONCLUSION

The current study reports an association between 30-day mortality rate and iPP < 40mmHg and a positive dPP among septic shock patients cared for by a prehospital MICU. A negative dPP could be helpful to identify septic shock with higher risk of poor outcome despite prehospital hemodynamic optimization.

The prognostic utility of prehospital qSOFA in addition to emergency department qSOFA for sepsis in patients with suspected infection: A retrospective cohort study

BACKGROUND

The quick sequential organ failure assessment (qSOFA) was widely used to estimate the risks of sepsis in patients with suspected infection in the prehospital and emergency department (ED) settings. Due to the insufficient sensitivity of qSOFA on arrival at the ED (ED qSOFA), the Surviving Sepsis Campaign 2021 recommended against using qSOFA as a single screening tool for sepsis. However, it remains unclear whether the combined use of prehospital and ED qSOFA improves its sensitivity for identifying patients at a higher risk of sepsis at the ED.

METHODS

We retrospectively analyzed the data from the ED of a tertiary medical center in Japan from April 2018 through March 2021. Among all adult patients (aged ≥18 years) transported by ambulance to the ED with suspected infection, we identified patients who were subsequently diagnosed with sepsis based on the Sepsis-3 criteria. We compared the predictive abilities of prehospital qSOFA, ED qSOFA, and the sum of prehospital and ED qSOFA (combined qSOFA) for sepsis in patients with suspected infection at the ED.

RESULTS

Among 2,407 patients with suspected infection transported to the ED by ambulance, 369 (15%) patients were subsequently diagnosed with sepsis, and 217 (9%) died during hospitalization. The sensitivity of prehospital qSOFA ≥2 and ED qSOFA ≥2 were comparable (c-statistics for sepsis [95%CI], 0.57 [0.52-0.62] vs. 0.55 [0.50-0.60]). However, combined qSOFA (cutoff, ≥3 [max 6]) was more sensitive than ED qSOFA (cutoff, ≥2) for identifying sepsis (0.67 [95%CI, 0.62-0.72] vs. 0.55 [95%CI, 0.50-0.60]). Using combined qSOFA, we identified 44 (12%) out of 369 patients who were subsequently diagnosed with sepsis, which would have been missed using ED qSOFA alone.

CONCLUSIONS

Using both prehospital and ED qSOFA could improve the screening ability of sepsis among patients with suspected infection at the ED.

Is Prehospital Assessment of qSOFA Parameters Associated with Earlier Targeted Sepsis Therapy? A Retrospective Cohort Study

BACKGROUND

This study aimed to determine whether prehospital qSOFA (quick sequential organ failure assessment) assessment was associated with a shortened 'time to antibiotics' and 'time to intravenous fluid resuscitation' compared with standard assessment.

METHODS

This retrospective study included patients who were referred to our Emergency Department between 2014 and 2018 by emergency medical services, in whom sepsis was diagnosed during hospitalization. Two multivariable regression models were fitted, with and without qSOFA parameters, for 'time to antibiotics' (primary endpoint) and 'time to intravenous fluid resuscitation'.

RESULTS

In total, 702 patients were included. Multiple linear regression analysis showed that antibiotics and intravenous fluids were initiated earlier if infections were suspected and emergency medical services involved emergency physicians. A heart rate above 90/min was associated with a shortened time to antibiotics. If qSOFA parameters were added to the models, a respiratory rate ≥ 22/min and altered mentation were independent predictors for earlier antibiotics. A systolic blood pressure ≤ 100 mmHg and altered mentation were independent predictors for earlier fluids. When qSOFA parameters were added, the explained variability of the model increased by 24% and 38%, respectively (adjusted R² 0.106 versus 0.131 for antibiotics and 0.117 versus 0.162 for fluids).

CONCLUSION

Prehospital assessment of qSOFA parameters was associated with a shortened time to a targeted sepsis therapy.

Association between prehospital shock index variation and 28-day mortality among patients with septic shock

PURPOSE

Septic shock (SS) hyperdynamic phase is characterized by tachycardia and low-blood pressure reflecting the relative hypovolemia. Shock index (SI), the ratio between heart rate and systolic blood pressure, is a simple objective tool, usable for SS prognosis assessment. This study aims to evaluate the relationship between prehospital SI variation and 28-day mortality of SS patients initially cared for in prehospital setting by a mobile intensive care unit (mICU).

METHODS

From April 6th, 2016 to December 31st, 2020, 406 patients with SS requiring prehospital mICU were retrospectively analyzed. Initial SI, i.e. first measurement after mICU arrival to the scene, and final SI, i.e. last measurement of the prehospital stage, were used to calculate delta SI (initial SI-final SI) and to define positive and negative delta SI. A survival analysis after propensity score matching compared the 28-day mortality of SS patients with positive/negative delta SI.

RESULTS

The main suspected origins of infection were pulmonary (42%), digestive (25%) and urinary (17%). The 28-day overall mortality reached 29%. Cox regression analysis revealed a significant association between 28-day mortality and delta SI. A negative delta SI was associated with an increase in mortality (adjusted hazard ratio (HRa) of 1.88 [1.07-3.31] (p = 0.03)), whereas a positive delta SI was associated with a mortality decrease (HRa = 0.53 [0.30-0.94] (p < 10-3)).

CONCLUSION

Prehospital hemodynamic delta SI among SS patients cared for by a mICU is associated with 28-day mortality. A negative prehospital delta SI could help physicians to identify SS with higher risk of 28-day mortality.

Relationship between the prehospital quick Sequential Organ Failure Assessment and prognosis in patients with sepsis or suspected sepsis: a population-based ORION registry

Aim

The quick Sequential Organ Failure Assessment (qSOFA) was proposed for use as a simple screening tool for sepsis. In this study, we evaluated the relationship between the prehospital use of qSOFA and prognosis in patients with sepsis or suspected sepsis using the population‐based Osaka Emergency Information Research Intelligent Operation Network (ORION) registry, which compiles prehospital ambulance data and in‐hospital information.

Methods

The study enrolled 437,974 patients in the ORION registry from January 1 to December 31, 2016. We selected hospitalized patients with sepsis or suspected sepsis using the appropriate codes from the International Classification of Diseases revision 10. We excluded patients with: (i) missing data (outcome, Japan Coma Scale, respiratory rate, and blood pressure); (ii) respiratory rate ≥60/min; and (iii) blood pressure ≥250 mmHg. These measures were evaluated by ambulance personnel when they first contacted the patient in the prehospital setting. The primary end‐point was discharge to death.

Results

In total, 12,646 patients (median age, 78 [interquartile range, 65–85] years; male, n = 6,760 [53.5%]) were eligible for our analysis. In a multivariable logistic regression analysis adjusted for confounding factors, the proportion of patients discharged to death was significantly higher for those evaluated as qSOFA positive (≥2 points) than qSOFA negative (≤1 point) (265/2,250 [11.78%] vs. 415/10,396 [3.99%]; adjusted odds ratio 2.91; 95% confidence interval, 2.47–3.43; P < 0.0001). The specificity and sensitivity were 83.4% and 39.0%, respectively, and the area under the receiver operating characteristic curve for qSOFA positive was 0.61.

Conclusions

The qSOFA evaluated by ambulance personnel in the prehospital setting was significantly associated with prognosis in patients with sepsis or suspected sepsis.

Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study

BACKGROUND

Identification of patients on admission to hospital with coronavirus infectious disease 2019 (COVID-19) pneumonia who can develop poor outcomes has not yet been comprehensively assessed.

OBJECTIVE

To compare severity scores used for community-acquired pneumonia to identify high-risk patients with COVID-19 pneumonia.

DESIGN

PSI, CURB-65, qSOFA, and MuLBSTA, a new score for viral pneumonia, were calculated on admission to hospital to identify high-risk patients for in-hospital mortality, admission to an intensive care unit (ICU), or use of mechanical ventilation. Area under receiver operating characteristics curve (AUROC), sensitivity, and specificity for each score were determined and AUROC was compared among them.

PARTICIPANTS

Patients with COVID-19 pneumonia included in the SEMI-COVID-19 Network.

KEY RESULTS

We examined 10,238 patients with COVID-19. Mean age of patients was 66.6 years and 57.9% were males. The most common comorbidities were as follows: hypertension (49.2%), diabetes (18.8%), and chronic obstructive pulmonary disease (12.8%). Acute respiratory distress syndrome (34.7%) and acute kidney injury (13.9%) were the most common complications. In-hospital mortality was 20.9%. PSI and CURB-65 showed the highest AUROC (0.835 and 0.825, respectively). qSOFA and MuLBSTA had a lower AUROC (0.728 and 0.715, respectively). qSOFA was the most specific score (specificity 95.7%) albeit its sensitivity was only 26.2%. PSI had the highest sensitivity (84.1%) and a specificity of 72.2%.

CONCLUSIONS

PSI and CURB-65, specific severity scores for pneumonia, were better than qSOFA and MuLBSTA at predicting mortality in patients with COVID-19 pneumonia. Additionally, qSOFA, the simplest score to perform, was the most specific albeit the least sensitive.

The sensitivity of qSOFA calculated at triage and during emergency department treatment to rapidly identify sepsis patients

The quick sequential organ failure assessment (qSOFA) score has been proposed as a means to rapidly identify adult patients with suspected infection, in pre-hospital, Emergency Department (ED), or general hospital ward locations, who are in a high-risk category with increased likelihood of "poor outcomes:" a greater than 10% chance of dying or an increased likelihood of spending 3 or more days in the ICU. This score is intended to replace the use of systemic inflammatory response syndrome (SIRS) criteria as a screening tool; however, its role in ED screening and identification has yet to be fully elucidated. In this retrospective observational study, we explored the performance of triage qSOFA (tqSOFA), maximum qSOFA, and first initial serum lactate (> 3 mmol/L) at predicting in-hospital mortality and compared these results to those for the initial SIRS criteria obtained in triage. A total of 2859 sepsis cases were included and the in-hospital mortality rate was 14.4%. The sensitivity of tqSOFA ≥ 2 and maximum qSOFA ≥ 2 to predict in-hospital mortality were 33% and 69%, respectively. For comparison, the triage SIRS criteria and the initial lactate > 3 mmol/L had sensitivities of 82% and 65%, respectively. These results demonstrate that in a large ED sepsis database the earliest measurement of end organ impairment, tqSOFA, performed poorly at identifying patients at increased risk of mortality and maximum qSOFA did not significantly outperform initial serum lactate levels.

Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study

Background

Although multiple prediction models have been developed to predict hospital admission to emergency departments (EDs) to address overcrowding and patient safety, only a few studies have examined prediction models for prehospital use. Development of institution-specific prediction models is feasible in this age of data science, provided that predictor-related information is readily collectable.

Objective

We aimed to develop a hospital admission prediction model based on patient information that is commonly available during ambulance transport before hospitalization.

Methods

Patients transported by ambulance to our ED from April 2018 through March 2019 were enrolled. Candidate predictors were age, sex, chief complaint, vital signs, and patient medical history, all of which were recorded by emergency medical teams during ambulance transport. Patients were divided into two cohorts for derivation (3601/5145, 70.0%) and validation (1544/5145, 30.0%). For statistical models, logistic regression, logistic lasso, random forest, and gradient boosting machine were used. Prediction models were developed in the derivation cohort. Model performance was assessed by area under the receiver operating characteristic curve (AUROC) and association measures in the validation cohort.

Results

Of 5145 patients transported by ambulance, including deaths in the ED and hospital transfers, 2699 (52.5%) required hospital admission. Prediction performance was higher with the addition of predictive factors, attaining the best performance with an AUROC of 0.818 (95% CI 0.792-0.839) with a machine learning model and predictive factors of age, sex, chief complaint, and vital signs. Sensitivity and specificity of this model were 0.744 (95% CI 0.716-0.773) and 0.745 (95% CI 0.709-0.776), respectively.

Conclusions

For patients transferred to EDs, we developed a well-performing hospital admission prediction model based on routinely collected prehospital information including chief complaints.

Prehospital lactate clearance is associated with reduced mortality in patients with septic shock

BACKGROUND

Assessment of disease severity in patients with septic shock (SS) is crucial in determining optimal level of care. In both pre- and in-hospital settings, blood lactate measurement is broadly used in combination with the clinical evaluation of patients as the clinical picture alone is not sufficient for assessing disease severity and outcomes.

METHODS

From 15th April 2017 to 15th April 2019, patients with SS requiring prehospital mobile Intensive Care Unit intervention (mICU) were prospectively included in this observational study. Prehospital blood lactate clearance was estimated by the difference between prehospital (time of first contact between the patients and the mICU prior to any treatment) and in-hospital (at hospital admission) blood lactate levels divided by prehospital blood lactate.

RESULTS

Among the 185 patients included in this study, lactate measurement was missing for six (3%) in the prehospital setting and for four (2%) at hospital admission, thus 175 (95%) were analysed for prehospital blood lactate clearance (mean age 70 ± 14 years). Pulmonary, digestive and urinary infections were probably the cause of the SS in respectively 56%, 22% and 10% of the cases. The 30-day overall mortality was 32%. Mean prehospital blood lactate clearance was significantly different between patients who died and those who survived (respectively 0.41 ± 2.50 mmol.l^-1 vs 1.65 ± 2.88 mmol.l^-1, p = 0.007). Cox regression analysis showed that 30-day mortality was associated with prehospital blood lactate clearance > 10% (HRa [CI95] = 0.49 [0.26-0.92], p = 0.028) and prehospital blood lactate clearance < 10% (HRa [CI95] = 2.04 [1.08-3.84], p = 0.028).

CONCLUSION

A prehospital blood lactate clearance < 10% is associated with 30-day mortality increase in patients with SS handled by the prehospital mICU. Further studies will be needed to evaluate if prehospital blood lactate clearance alone or combined with clinical scores could affected the triage decision-making process for those patients.

Pre-Hospital Lactatemia Predicts 30-Day Mortality in Patients with Septic Shock-Preliminary Results from the LAPHSUS Study

Background: Assessment of disease severity in patients with septic shock (SS) is crucial in determining optimal level of care. In both pre- and in-hospital settings, the clinical picture alone is not sufficient for assessing disease severity and outcomes. Because blood lactate level is included in the clinical criteria of SS it should be considered to improve the assessment of its severity. This study aims to investigate the relationship between pre-hospital blood lactate level and 30-day mortality in patients with SS. Methods: From 15 April 2017 to 15 April 2019, patients with SS requiring pre-hospital Mobile Intensive Care Unit intervention (MICU) were prospectively included in the LAPHSUS study, an observational, non-randomized controlled study. Pre-hospital blood lactate levels were measured at the time of first contact between the patients and the MICU. Results: Among the 183 patients with septic shock requiring action by the MICU drawn at random from LAPHSUS study patients, six (3%) were lost to follow-up on the 30th day and thus 177 (97%) were analyzed for blood lactate levels (mean age 70 ± 14 years). Pulmonary, urinary and digestive infections were probably the cause of the SS in respectively 58%, 21% and 11% of the cases. The 30-day overall mortality was 32%. Mean pre-hospital lactatemia was significantly different between patients who died and those who survived (respectively 7.1 ± 4.0 mmol/L vs. 5.9 ± 3.5 mmol/L, p < 10⁻³). Using Cox regression analysis adjusted for potential confounders we showed that a pre-hospital blood lactate level ≥ 4 mmol/L significantly predicted 30-day mortality in patients with SS (adjusted hazard ratio = 2.37, 95%CI (1.01–5.57), p = 0.04). Conclusion: In this study, we showed that pre-hospital lactatemia predicts 30-day mortality in patients with septic shock handled by the MICU. Further studies will be needed to evaluate if pre-hospital lactatemia alone or combined with clinical scores could affect the triage decision-making process for those patients.

Febrile neutropenia in patients with acute myeloid leukemia: Outcome in relation to qSOFA score, C-reactive protein, and blood culture findings

OBJECTIVES

To evaluate quick Sequential Organ Failure Assessment (qSOFA) score during febrile neutropenia (FN) in adult patients receiving intensive chemotherapy for acute myeloid leukemia (AML).

METHODS

qSOFA score, as well as the association of qSOFA score with ICU admission, infectious mortality, blood culture findings, and C-reactive protein (CRP) measurements during FN were assessed among 125 adult AML patients with 355 FN periods receiving intensive chemotherapy in a tertiary care hospital from November 2006 to December 2018.

RESULTS

The multivariate model for qSOFA score ≥ 2 included CRP ≥ 150 mg/L on d0-2 [OR 2.9 (95% CI 1.1-7.3), P = .026], Gram-negative bacteremia [OR 2.7 (95% CI 1.1-6.9), P = .034], and treatment according to AML-2003 vs more recent protocols [OR 2.7 (95% CI 1.0-7.4), P = .047]. Age or gender did not gain significance in the model. qSOFA score ≥ 2 was associated with ICU treatment and infectious mortality during FN with sensitivity and specificity of 0.700 and 0.979, and 1.000 and 0.971, respectively.

CONCLUSION

qSOFA offers a useful tool to evaluate the risk of serious complications in AML patients during FN.

Screening strategies to identify sepsis in the prehospital setting: a validation study

BACKGROUND

In the prehospital setting, differentiating patients who have sepsis from those who have infection but no organ dysfunction is important to initiate sepsis treatments appropriately. We aimed to identify which published screening strategies for paramedics to use in identifying patients with sepsis provide the most certainty for prehospital diagnosis.

METHODS

We identified published strategies for screening by paramedics through a literature search. We then conducted a validation study in Alberta, Canada, from April 2015 to March 2016. For adult patients (≥ 18 yr) who were transferred by ambulance, we linked records to an administrative database and then restricted the search to patients with infection diagnosed in the emergency department. For each patient, the classification from each strategy was determined and compared with the diagnosis recorded in the emergency department. For all strategies that generated numeric scores, we constructed diagnostic prediction models to estimate the probability of sepsis being diagnosed in the emergency department.

RESULTS

We identified 21 unique prehospital screening strategies, 14 of which had numeric scores. We linked a total of 131 745 eligible patients to hospital databases. No single strategy had both high sensitivity (overall range 0.02-0.85) and high specificity (overall range 0.38-0.99) for classifying sepsis. However, the Critical Illness Prediction (CIP) score, the National Early Warning Score (NEWS) and the Quick Sepsis-Related Organ Failure Assessment (qSOFA) score predicted a low to high probability of a sepsis diagnosis at different scores. The qSOFA identified patients with a 7% (lowest score) to 87% (highest score) probability of sepsis diagnosis.

INTERPRETATION

The CIP, NEWS and qSOFA scores are tools with good predictive ability for sepsis diagnosis in the prehospital setting. The qSOFA score is simple to calculate and may be useful to paramedics in screening patients with possible sepsis.