Skip to main content
Download PDF

The prehospital NEW score to assess septic shock in-hospital, 30-day and 90-day mortality

BMC Infectious Diseases volume 24, Article number: 213 (2024) Cite this article

Abstract

Background

The early identification of sepsis presenting a high risk of deterioration is a daily challenge to optimise patient pathway. This is all the most crucial in the prehospital setting to optimize triage and admission into the appropriate unit: emergency department (ED) or intensive care unit (ICU). We report the association between the prehospital National Early Warning Score 2 (NEWS-2) and in-hospital, 30 and 90-day mortality of SS patients cared for in the pre-hospital setting by a mobile ICU (MICU).

Methods

Septic shock (SS) patients cared for by a MICU between 2016, April 6th and 2021 December 31st were included in this retrospective cohort study. The NEWS-2 is based on 6 physiological variables (blood pressure, heart rate, respiratory rate, temperature, oxygen saturation prior oxygen supplementation, and level of consciousness) and ranges from 0 to 20. The Inverse Probability Treatment Weighting (IPTW) propensity method was applied to assess the association with in-hospital, 30 and 90-day mortality. A NEWS-2 ≥ 7 threshold was chosen for increased clinical deterioration risk definition and usefulness in clinical practice based on previous reports.

Results

Data from 530 SS patients requiring MICU intervention in the pre-hospital setting were analysed. The mean age was 69 ± 15 years and presumed origin of sepsis was pulmonary (43%), digestive (25%) or urinary (17%) infection. In-hospital mortality rate was 33%, 30 and 90-day mortality were respectively 31% and 35%. A prehospital NEWS-2 ≥ 7 is associated with an increase in-hospital, 30 and 90-day mortality with respective RRa = 2.34 [1.39–3.95], 2.08 [1.33–3.25] and 2.22 [1.38–3.59]. Calibration statistic values for in-hospital mortality, 30-day and 90-day mortality were 0.54; 0.55 and 0.53 respectively.

Conclusion

A prehospital NEWS-2 ≥ 7 is associated with an increase in in-hospital, 30 and 90-day mortality of septic shock patients cared for by a MICU in the prehospital setting. Prospective studies are needed to confirm the usefulness of NEWS-2 to improve the prehospital triage and orientation to the adequate facility of sepsis.

Peer Review reports

Introduction

During the last twenty years, despite research on prevention and treatments, the mortality and the morbidity rates of sepsis remain stable [1, 2]. To date, whatever the initial stage of sepsis, this latter one is responsible of 20% of all deaths worldwide, approximately 11 million deaths ever year [3]. Sepsis is also a major cause of death among hospitalized patients, especially in intensive care unit (ICU) [4, 5] where mortality and morbidity rates are estimated of 37.3% and 10.4% [6].

On 2017 the World Health Assembly and the World Health Organization defined that prevention, diagnosis, and sepsis management are the main priorities to decrease morbidity and mortality [7]. It was underpinned that sepsis outcome depends on early identification and treatment implementation with hemodynamic optimization and antibiotic therapy (ABT) administration [8, 9] both included in a bundle of care [10].

In and, out-of-hospital sepsis diagnosis and severity evaluation are the bundle of care first steps aiming to determine the appropriate level of care. Because 70% of sepsis occurs outside a hospital environment, a special attention is needed to help physician for sepsis diagnosis and severity assessment to optimize triaging between ambulatory treatment, ward, emergency department (ED) or ICU admission [11]. Outside hospital setting, severity assessment is mainly based on clinical signs due to the absence of biomarker availability [12,13,14]. Different sepsis severity assessment scores have been developed, to enhance clinical diagnostic performance, despite to date no score was prospectively validated for pre-hospital use [15, 16].

In 2012, the Royal College of Physicians launched the National Early Warning Score (NEWS) to improve the outcomes of patients suffering from acute illness [17]. The NEWS score aims to triggering a rapid and effective clinical response, in time, person and place because the triad: early detection, timeliness of response and competency of the clinical response directly impact the outcome [18,19,20,21,22,23,24,25].

This study aims to describe the association between the prehospital National Early Warning Score 2 (NEWS-2) and in-hospital, 30 and 90-day mortality of SS patients cared for in the pre-hospital setting by a mobile ICU (MICU).

Methods

Population

As previously reported, in France, pre-hospital emergency system (PEMS) relies on the Service d’Aide Médicale d’Urgence (SAMU) [12, 13, 15, 26, 27]. Briefly, SAMU is composed of dispatch operators and emergency physicians [28] with a unique national phone number, the “15”. After a telephone discussion with the patient, or a relative, or a witness, the physician, based on patient’s medical history and reported symptoms, in case of life-threatening emergencies, may decide to dispatch a mobile intensive care unit (MICU) team to the scene. The MICU team, a driver, a nurse and an emergency physician, is equipped to face initial management of major organ failures [28].

All adults patients aged ≥ 18 years, cared for by a MICU from SAMU 75 Necker - Enfants Malades Hospital, SAMU 75 Lariboisière Hospital, SAMU 75 Pitié Salpêtrière Hospital, SAMU 75 Hôtel Dieu Hospital, Paris, Assistance Publique - Hôpitaux de Paris, Paris– France; Paris Fire Brigade Emergency Medical Service, Paris– France; SAMU 972 Fort de France University Hospital, La Martinique– France; SAMU 31 University Toulouse Hospital, Toulouse– France and SAMU 31 Castres Hospital, Castres– France, between 2016, April 6th, and 2021, December 31st, were included in this retrospective study based on 2012 sepsis-2 conference septic shock definition [29]. Eligible patients were identified using electronic research using septic shock or severe sepsis keywords. No exclusion criteria were used in this study.

Ethical considerations

The French Society of Anaesthesiology and Intensive Care ethics committee (Reference: IRB00010254-2017-026, 2017/12/12), the Ethics Committee for Behavioural and Health Research (CERCES Reference 2018-04, 2018/01/16) and the National Heart Agency (2017-A02335-48–2017/07/30) approved the trial protocol waiving patient consent for this retrospective study.

Data collection

A standardized data collection template was used in order to minimize data abstraction bias [30].

Patients’ demographic characteristics (age, weight, height, calculated body mass index (BMI) and gender), prehospital supposed origin of sepsis, initial prehospital vital signs values (systolic (SBP), diastolic (DBP) and mean blood (MBP) pressure, heart rate (HR), pulse oximetry (SpO2), respiratory rate (RR), body core temperature and Glasgow coma scale (GCS)), skin mottling score (SMS from 0 to 5), capillary refill time (CRT) (seconds), duration of prehospital care, prehospital treatments delivered (antibiotic therapy (ABT) type and dose, fluid volume expansion type and dose, catecholamine type and dose) were collected from MICU pre-hospital medical records. Comorbidities: hypertension, coronary heart disease (CHD), chronic cardiac failure (CCF), chronic renal failure (CRF), chronic obstructive pulmonary disease (COPD), diabetes mellitus and history of cancer, were also collected from pre and in-hospital medical reports. Length of stay in the ICU, length of stay in the hospital, 30 and 90-day mortality were retrieved from in-hospital medical records. In France, the hospital patient monitoring software enables to know the vital status even if the patient is no longer hospitalised. Thus, the vital status “alive” or “dead” on day-90 was available for each analysed patient.

Simplified acute physiology score (SAPS2) [31] was calculated 24 h after hospital admission.

Statistical analysis

A mean with standard deviation was used to express quantitative parameters with a gaussian distribution, median with interquartile range [Q1-Q3] for quantitative parameters with a non-normal distribution and absolute values and percentages for qualitative parameters.

The main outcomes were in-hospital, 30 and 90-day mortality of septic shock patients initially cared for by a MICU in the pre-hospital setting.

The NEWS-2 was calculated based on the sum of the worst value of the 6 following physiological variables: blood pressure, heart rate, respiratory rate, temperature, oxygen saturation prior oxygen supplementation, and level of consciousness according to the 2017 Royal College of Physicians.

guidelines [17]. The NEWS-2 ranges from 0 to 20.

A NEWS-2 ≥ 7 threshold was chosen for increased clinical deterioration risk definition and usefulness in clinical practice based on previous report [17].

The relationship between each covariate and in-hospital, 30-day and 90-day mortality rates were assessed by bivariate and multivariate analyses. The NEWS-2 was analysed, as a continuous variable and as a binary variable using a threshold of NEWS ≥ 7 because its association with increased clinical deterioration risk. Results are expressed by an Odd Ratio (OR) and adjusted Odd Ratio (aOR) with a 95% confidence interval [95 CI].

A log binomial regression weighted with the inverse probability of treatment (IPTW) propensity score method was computed taking into potential cofounders. The propensity score aims to decrease bias due to non-randomized treatment allocation [32]. Cofounders included in the IPTW propensity analysis were: age, cancer history, CRF, COPD, CHD, diabetes mellitus, CCF, SAPS2, prehospital ABT administration, prehospital fluid volume expansion and prehospital catecholamine infusion. The selection of variables included in the multivariable analysis was done a priori guided by previous knowledge of factors known to influence septic shock survival. Results were expressed as adjusted risk ratio (RR) [95 CI].

All tests were 2-sided with a statistically significant p-value considered as < 0 0.05.

All analyses were performed using R 3.4.2 (http://www.R-project.org; the R Foundation for Statistical Computing, Vienna, Austria).

Results

Population characteristics

Between 2021, April 6th, and 2021, December 31st, 530 patients requiring pre-hospital MICU intervention for septic shock were analysed. The missing data rate was lower than 1%; these data were deleted for the statistical analysis.

Of the 7 participating centres, 165 patients (31%) were included by the Paris Fire Brigade Emergency Medical Service, 104 patients (20%) by SAMU 31 Toulouse, 77 patients (15%) by SAMU 75 Necker, 71 patients (13%) by SAMU Castres, 51 patients (10%) by SAMU 972 La Martinique, 31 patients (6%) by SAMU 75 Lariboisière, 14 patients (3%) by SAMU 75 Hôtel Dieu and 17 patients (3%) by SAMU 75 Pitié Salpétrière.

The overall population mean age was 69 ± 15 years and 341 patients (64%) were male gender.

One hundred eighty (34%) patients died during hospital stay, 164 (31%) patients had died by day-30, and 184 (35%) had died by day-90.

Table 1 summarise the populations’ demographic and clinical characteristics (Table 1).

Table 1 Population demographic and first prehospital clinical characteristics. Results are expressed as mean with standard deviation for quantitative parameters with gaussian distribution, as median with interquartile range for quantitative parameters with non-normal distribution and, as absolute value and percentage for qualitative parameters. p-value corresponds to the comparison between alive and deceased patients. p-value in bold indicates a significant difference between alive and deceased patients
Full size table

Presumed origin of septic shock was mainly pulmonary (43%), digestive (25%) or urinary (17%) (Table 2).

Table 2 Presumed origin of septic shock. Data are expressed as an absolute value with a percentage of all cases (due to rounding, total overpasses 100%)
Full size table

Prehospital setting

The mean duration of prehospital care was 71 ± 34 min, pre-hospital fluid expansion consisted on crystalloids (100%) with a mean volume of 932 ± 573 ml and 155 (29%) patients received norepinephrine infusion with a median dose of 1.0 [0.5–2.0] mg.h− 1.

Prehospital ABT was administered in 132 patients (25%) and no significant difference was observed between patients surviving or dying, at hospital, at 30 or 90 day (Table 1). The antibiotics were principally 3rd generation cephalosporins (n = 98, 75%).

Hospital stays

The median length of stay in the ICU was 4 [2–8] days and the median in-hospital length of stay was 10 [5–18] days.

The mean SAPS2 score was 60 ± 21 with significant difference between patients surviving or dying in hospital, at day-30 and day-90 (Table 1).

Prehospital NEWS-2

The mean overall prehospital NEWS-2 was 9 ± 3, with 406 patients (77%) patients having a prehospital NEWS-2 ≥ 7.

Bivariate logistic analysis revealed a significant association between prehospital NEWS (continuous variable) and in-hospital mortality (OR = 2.14 [1.19–3.83], p = 0.01), 28-day mortality (OR = 2.41 [1.33–4.36], p = 0.003) and 90-day mortality (OR = 1.88 [1.05–3.35], p = 0.03).

Using a threshold of a prehospital NEWS-2 ≥ 7, the association remains significant for in-hospital mortality (OR = 1.62 [1.04–2.58], p = 0.04), 28-day mortality (OR = 1.94 [1.22–3.18], p = 0.01) but not for 90-day mortality (OR = 1.43 [0.93–2.24], p = 0.11).

Propensity IPTW analyses

The log binomial regression weighted with the IPTW observed an association between a prehospital NEWS-2 ≥ 7 and in-hospital mortality: RRa = 2.34 [1.39–3.95], 30-day mortality: RR = 2.08 [1.33–3.25] and 90-day mortality: RRa = 2.22 [1.38–3.59].

Initial lactate was missing for 218 patients (41%) and initial skin mottling score missing for 220 patients (42%); both covariables were not included in the model.

The calibration statistic values were: 0.54; 0.55 and 0.53 respectively for in-hospital mortality, 30-day mortality and 90-day mortality.

Discussion

Here we report a positive association between in-hospital, 30 and 90-day mortality and (i) the prehospital NEWS-2, (ii) prehospital NEWS-2 ≥ 7 and among septic shock patients cared for in the pre-hospital setting by a mobile intensive care unit.

Previous reports underpinned that around one-third of potentially preventable deaths in the United Kingdom were related to poor clinical monitoring and/or inadequate response to clinical deterioration supporting that patients should be addressed to the most appropriate setting for clinical care [33], justifying NEWS-2 widespread deployment [17]. It is all the most true for sepsis for which diagnosis, severity assessment and treatment initiation does not suffer from any delay [14, 34, 35]. Beyond out- and in-hospital care aiming to improve sepsis outcome, early diagnosis and severity are cornerstones to decrease sepsis related mortality by initiation of the sepsis survival chain [36]. Early diagnosis is also recognised as an essential leverage arm to prevent potentially preventable deaths as it allows early initiation of treatment. Daily, PEMS are faced to a challenge aiming to, as quickly as possible, establish a right diagnosis and assess severity to adequately guide the patient towards the optimal care pathway for his or her disease. To establish a diagnosis and a clinical monitoring, simple and objective clinical tools usable at any time and reproduced by different caregivers are necessary. This is all the more important when diagnostic certainty is uncertain and/or urgent, even when combining both clinical and paraclinical, for example biological, variables, in the grey zone decision making [37]. Some clinical parameters, e.g., SMS, CRT [12, 13], are subjective and may be caught out in some situation, for example hypothermia.

Because of the lack of specificity of a single clinical sign [14], scoring system was developed to improve sensitivity and sensibility. For sepsis, the most known scores are which SOFA [38], Mortality in Emergency Department Sepsis (MEDS) [39], Predisposition, Infection, Response and Organ dysfunction (PIRO) [40] and q-SOFA since 2016 [14]. Although the latter does not require biological results and is recommended because of its simplicity outside ICU [41], q-SOFA validity remains under debate [13, 15, 16, 40, 42,43,44]. To date, in the prehospital setting, no score is validated, thus, sepsis severity assessment and prognostication still remain on clinical evaluation [45].

The score has several advantages, including: its ease of establishment since all the variables are accessible in the pre-hospital setting, its inter-observer reproducibility, and the possibility of being repeated over time in order to evaluate the treatment effect. However, one of the weakness is that NEWS-2 does not include age and major comorbidities, both reflecting frailty [46, 47] and associated with poor sepsis outcome [48,49,50].

Limitations

The current study suffers from limitations. Because of the retrospective study design, we cannot exclude that a potential selection bias affects the results validity. In addition, we are unable to conclude on a causal link between the NEWS-2 and mortality related to septic shock and sepsis. We cannot exclude unknown or missed confounders during the analysis. The NEWS-2 performance and external validation need to be confirmed by prospective studies, although the inclusion of centres of varying size and geography (a large city - Paris, one medium-sized city - Toulouse and one rural city– Castres) seems promising and represents a study strength. The study population was only adults; consequently, results extrapolation to sepsis and to paediatric population is not possible. We should keep in mind that some NEWS-2 variables may be influenced by patient previous medications, e.g., beta-blocker therapy, restricting their contribution to the NEWS-2.

Beyond all these limitations, the NEWS-2 seems to be an adequate tool for pre-hospital sepsis screening of a high risk of poor evolution and should be considered as an aid to clinical decision making, not a barrier or alternative to skilled clinical judgement.

Conclusion

Among sepsis patient requiring prehospital mobile intensive care unit intervention, a prehospital NEWS-2 ≥ 7 is associated with an increase in in-hospital, 30 and 90-day mortality. However, prospective studies are needed to confirm the usefulness of NEWS-2 to improve the prehospital triage, patient orientation to the optimal pathway and sepsis related mortality.

Data availability

The dataset analyzed during the current study are not publicly available because their containing information that could compromise the privacy of research participants but are available from the corresponding author on reasonable request.

Abbreviations

BMI:

Body mass index

MICU:

Mobile intensive care unit

aHR:

Adjusted hazard ratio

ED:

Emergency department

ICU:

Intensive care unit

SAMU:

Urgent Medical Aid Service

ABT:

Antibiotic therapy

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

MBP:

Mean blood pressure

HR:

Heart rate

SpO2:

Pulse oximetry

RR:

Respiratory rate

GCS:

Glasgow coma scale

SMS:

Skin mottling score

CRT:

Capillary refill time

SOFA:

Sequential Organ Failure Assessment

qSOFA:

Quick Sequential Organ Failure Assessment

SAPS-2:

Simplified Acute Physiology Score

PEMS:

Prehospital emergency medical service

RRa:

Adjusted risk ratio

ORa:

Adjusted odd ratio

CHD:

Coronary heart disease

CCF:

Chronic cardiac failure

CRF:

Chronic renal failure

COPD:

Chronic obstructive pulmonary disease

IPTW:

Inverse Probability Treatment Weighting

NEWS-2:

National Early Warning Score 2

References

  1. Ferrer R, Artigas A, Levy MM, Blanco J, Gonzalez-Diaz G, Garnacho-Montero J, et al. Improvement in process of care and outcome after a multicenter severe sepsis educational program in Spain. JAMA. 2008;299(19):2294–303.

    Article  CAS  PubMed  Google Scholar 

  2. Nguyen HB, Van Ginkel C, Batech M, Banta J, Corbett SW. Comparison of predisposition, Insult/Infection, response, and organ dysfunction, Acute Physiology and Chronic Health evaluation II, and Mortality in Emergency Department Sepsis in patients meeting criteria for early goal-directed therapy and the severe sepsis resuscitation bundle. J Crit Care. 2012;27(4):362–9.

    Article  PubMed  Google Scholar 

  3. Rudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, et al. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the global burden of Disease Study. Lancet. 2020;395(10219):200–11.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348(16):1546–54.

    Article  PubMed  Google Scholar 

  5. Weng L, Zeng XY, Yin P, Wang LJ, Wang CY, Jiang W, et al. Sepsis-related mortality in China: a descriptive analysis. Intensive Care Med. 2018;44(7):1071–80.

    Article  PubMed  Google Scholar 

  6. Vincent JL, Jones G, David S, Olariu E, Cadwell KK. Frequency and mortality of septic shock in Europe and North America: a systematic review and meta-analysis. Crit Care. 2019;23(1):196.

    Article  PubMed  PubMed Central  Google Scholar 

  7. ASSEMBLY SWH. Improving the prevention, diagnosis and clinical management of sepsis. 2017.

  8. Epstein L, Dantes R, Magill S, Fiore A. Varying estimates of Sepsis Mortality using death certificates and administrative codes–United States, 1999–2014. MMWR Morb Mortal Wkly Rep. 2016;65(13):342–5.

    Article  PubMed  Google Scholar 

  9. Medicine SoCC. Surviving sepsis campaign: updated bundles in response to new evidence. Mount Prospect, IL. Surviving Sepsis Campaign;. 2015(Apr).

  10. Leisman DE, Doerfler ME, Ward MF, Masick KD, Wie BJ, Gribben JL, et al. Survival benefit and cost savings from compliance with a simplified 3-Hour Sepsis bundle in a series of prospective, multisite, observational cohorts. Crit Care Med. 2017;45(3):395–406.

    Article  PubMed  Google Scholar 

  11. Esteban A, Frutos-Vivar F, Ferguson ND, Penuelas O, Lorente JA, Gordo F, et al. Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;35(5):1284–9.

    Article  PubMed  Google Scholar 

  12. Jouffroy R, Pierre Tourtier J, Gueye P, Bloch-Laine E, Bounes V, Debaty G et al. Prehospital shock index to assess 28-day mortality for septic shock. Am J Emerg Med. 2019.

  13. Jouffroy R, Saade A, Tourtier JP, Gueye P, Bloch-Laine E, Ecollan P, et al. Skin mottling score and capillary refill time to assess mortality of septic shock since pre-hospital setting. Am J Emerg Med. 2019;37(4):664–71.

    Article  PubMed  Google Scholar 

  14. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus definitions for Sepsis and septic shock (Sepsis-3). JAMA. 2016;315(8):801–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Jouffroy R, Saade A, Carpentier A, Ellouze S, Philippe P, Idialisoa R, et al. Triage of septic patients using qSOFA criteria at the SAMU Regulation: a retrospective analysis. Prehosp Emerg Care. 2018;22(1):84–90.

    Article  CAS  PubMed  Google Scholar 

  16. Jouffroy R, Saade A, Ellouze S, Carpentier A, Michaloux M, Carli P, et al. Prehospital triage of septic patients at the SAMU regulation: comparison of qSOFA, MRST, MEWS and PRESEP scores. Am J Emerg Med. 2018;36(5):820–4.

    Article  CAS  PubMed  Google Scholar 

  17. Physicians RCo. National Early Warning Score (NEWS) 2. Standardising the assessment of acute-illnessseverity in the NHS. 2017.

  18. Smith GB, Prytherch DR, Jarvis S, Kovacs C, Meredith P, Schmidt PE, et al. A comparison of the ability of the Physiologic Components of Medical Emergency Team Criteria and the U.K. National Early warning score to discriminate patients at risk of a range of adverse clinical outcomes. Crit Care Med. 2016;44(12):2171–81.

    Article  PubMed  Google Scholar 

  19. Smith GB, Prytherch DR, Schmidt P, Featherstone PI, Knight D, Clements G, et al. Hospital-wide physiological surveillance-a new approach to the early identification and management of the sick patient. Resuscitation. 2006;71(1):19–28.

    Article  PubMed  Google Scholar 

  20. Albur M, Hamilton F, MacGowan AP. Early warning score: a dynamic marker of severity and prognosis in patients with Gram-negative bacteraemia and sepsis. Ann Clin Microbiol Antimicrob. 2016;15:23.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Gao H, McDonnell A, Harrison DA, Moore T, Adam S, Daly K, et al. Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward. Intensive Care Med. 2007;33(4):667–79.

    Article  PubMed  Google Scholar 

  22. Keep JW, Messmer AS, Sladden R, Burrell N, Pinate R, Tunnicliff M, et al. National early warning score at Emergency Department triage may allow earlier identification of patients with severe sepsis and septic shock: a retrospective observational study. Emerg Med J. 2016;33(1):37–41.

    Article  CAS  PubMed  Google Scholar 

  23. Silcock DJ, Corfield AR, Gowens PA, Rooney KD. Validation of the National Early warning score in the prehospital setting. Resuscitation. 2015;89:31–5.

    Article  PubMed  Google Scholar 

  24. Shaw J, Fothergill RT, Clark S, Moore F. Can the prehospital national early warning score identify patients most at risk from subsequent deterioration? Emerg Med J. 2017;34(8):533–7.

    Article  PubMed  Google Scholar 

  25. Badriyah T, Briggs JS, Meredith P, Jarvis SW, Schmidt PE, Featherstone PI, et al. Decision-tree early warning score (DTEWS) validates the design of the National Early warning score (NEWS). Resuscitation. 2014;85(3):418–23.

    Article  PubMed  Google Scholar 

  26. Jouffroy R, Saade A, Muret A, Philippe P, Michaloux M, Carli P, et al. Fluid resuscitation in pre-hospital management of septic shock. Am J Emerg Med. 2018;36(10):1754–8.

    Article  PubMed  Google Scholar 

  27. Jouffroy R, Gilbert B, Tourtier JP, Bloch-Laine E, Ecollan P, Boularan J, et al. Prehospital Bundle of Care based on antibiotic therapy and hemodynamic optimization is Associated with a 30-Day mortality decrease in patients with septic shock. Crit Care Med. 2022;50(10):1440–8.

    Article  CAS  PubMed  Google Scholar 

  28. Adnet F, Lapostolle F. International EMS systems: France. Resuscitation. 2004;63(1):7–9.

    Article  PubMed  Google Scholar 

  29. Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, et al. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med. 2013;41(2):580–637.

    Article  PubMed  Google Scholar 

  30. Gearing RE, Mian IA, Barber J, Ickowicz A. A methodology for conducting retrospective chart review research in child and adolescent psychiatry. J Can Acad Child Adolesc Psychiatry. 2006;15(3):126–34.

    PubMed  PubMed Central  Google Scholar 

  31. Le Gall JR, Lemeshow S, Saulnier F. A new simplified Acute Physiology score (SAPS II) based on a European/North American multicenter study. JAMA. 1993;270(24):2957–63.

    Article  PubMed  Google Scholar 

  32. Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550–60.

    Article  CAS  PubMed  Google Scholar 

  33. Hogan H, Healey F, Neale G, Thomson R, Vincent C, Black N. Preventable deaths due to problems in care in English acute hospitals: a retrospective case record review study. BMJ Qual Saf. 2012;21(9):737–45.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Chen AX, Simpson SQ, Pallin DJ. Sepsis guidelines. N Engl J Med. 2019;380(14):1369–71.

    Article  PubMed  Google Scholar 

  35. Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving Sepsis Campaign: International guidelines for Management of Sepsis and Septic Shock 2021. Crit Care Med. 2021;49(11):e1063–e143.

    Article  PubMed  Google Scholar 

  36. Jouffroy R, Gueye P. Intensive care unit versus high-dependency care unit admission on mortality in patients with septic shock: let’s think to the survival chain concept for septic shock. J Intensive Care. 2022;10(1):52.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Cannesson M, Le Manach Y, Hofer CK, Goarin JP, Lehot JJ, Vallet B, et al. Assessing the diagnostic accuracy of pulse pressure variations for the prediction of fluid responsiveness: a gray zone approach. Anesthesiology. 2011;115(2):231–41.

    Article  PubMed  Google Scholar 

  38. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, Bruining H, et al. The SOFA (Sepsis-related Organ failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-related problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707–10.

    Article  CAS  PubMed  Google Scholar 

  39. Shapiro NI, Wolfe RE, Moore RB, Smith E, Burdick E, Bates DW. Mortality in Emergency Department Sepsis (MEDS) score: a prospectively derived and validated clinical prediction rule. Crit Care Med. 2003;31(3):670–5.

    Article  PubMed  Google Scholar 

  40. Marshall JC. The PIRO (predisposition, insult, response, organ dysfunction) model: toward a staging system for acute illness. Virulence. 2014;5(1):27–35.

    Article  PubMed  ADS  Google Scholar 

  41. Freund Y, Lemachatti N, Krastinova E, Van Laer M, Claessens YE, Avondo A, et al. Prognostic accuracy of Sepsis-3 criteria for In-Hospital mortality among patients with suspected infection presenting to the Emergency Department. JAMA. 2017;317(3):301–8.

    Article  PubMed  Google Scholar 

  42. Vafaei A, Heydari K, Hashemi-Nazari SS, Izadi N, Hassan Zadeh H. PIRO, SOFA and MEDS scores in Predicting one-Month Mortality of Sepsis patients; a diagnostic accuracy study. Arch Acad Emerg Med. 2019;7(1):e59.

    PubMed  PubMed Central  Google Scholar 

  43. Askim A, Moser F, Gustad LT, Stene H, Gundersen M, Asvold BO, et al. Poor performance of quick-SOFA (qSOFA) score in predicting severe sepsis and mortality - a prospective study of patients admitted with infection to the emergency department. Scand J Trauma Resusc Emerg Med. 2017;25(1):56.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Finkelsztein EJ, Jones DS, Ma KC, Pabon MA, Delgado T, Nakahira K, et al. Comparison of qSOFA and SIRS for predicting adverse outcomes of patients with suspicion of sepsis outside the intensive care unit. Crit Care. 2017;21(1):73.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Guirgis FW, Jones L, Esma R, Weiss A, McCurdy K, Ferreira J, et al. Managing sepsis: electronic recognition, rapid response teams, and standardized care save lives. J Crit Care. 2017;40:296–302.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Diaconu K, Falconer J, Vidal N, O’May F, Azasi E, Elimian K, et al. Understanding fragility: implications for global health research and practice. Health Policy Plan. 2020;35(2):235–43.

    Article  PubMed  Google Scholar 

  47. Xue QL. The frailty syndrome: definition and natural history. Clin Geriatr Med. 2011;27(1):1–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Blot S, Cankurtaran M, Petrovic M, Vandijck D, Lizy C, Decruyenaere J, et al. Epidemiology and outcome of nosocomial bloodstream infection in elderly critically ill patients: a comparison between middle-aged, old, and very old patients. Crit Care Med. 2009;37(5):1634–41.

    Article  PubMed  Google Scholar 

  49. Martin GS, Mannino DM, Moss M. The effect of age on the development and outcome of adult sepsis. Crit Care Med. 2006;34(1):15–21.

    Article  PubMed  Google Scholar 

  50. Muscedere J, Waters B, Varambally A, Bagshaw SM, Boyd JG, Maslove D, et al. The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis. Intensive Care Med. 2017;43(8):1105–22.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

None.

Funding

none.

Author information

Authors and Affiliations

  1. Intensive Care Unit, Ambroise Paré Hospital– Assistance Publique Hôpitaux Paris, 9 avenue Charles De Gaulle, 92100, Boulogne-Billancourt, Paris, France

    Romain Jouffroy

  2. IRMES - Institute for Research in Medicine and Epidemiology of Sport, INSEP, Paris, France

    Romain Jouffroy

  3. INSERM U-1018, Centre de recherche en Epidémiologie et Santé des Populations - U1018 INSERM, Paris Saclay University, Villejuif, France

    Romain Jouffroy

  4. SAMU 972, Centre Hospitalier Universitaire de Martinique, Fort-de-France Martinique, France

    Romain Jouffroy, Florian Négrello, Jean Limery & Papa Gueye

  5. UR5_3 PC2E, University of the Antilles, French West Indies, France

    Romain Jouffroy, Florian Négrello, Jean Limery & Papa Gueye

  6. Department of Emergency Medicine, SAMU 31, University Hospital of Toulouse, Toulouse, France

    Basile Gilbert & Vincent Bounes

  7. Paris Fire Brigade, Paris, France

    Stéphane Travers

  8. Emergency Department, Cochin Hospital, Paris, France

    Emmanuel Bloch-Laine

  9. Emergency Department, SMUR, Hôtel Dieu Hospital, Paris, France

    Emmanuel Bloch-Laine

  10. Intensive Care Unit, SMUR, Pitie Salpêtriere Hospital, 47 Boulevard de l’Hôpital, 75013, Paris, France

    Patrick Ecollan

  11. Centre Hospitalier Intercommunal Castres-Mazamet, Castres, France

    Josiane Boularan

  12. Intensive Care Unit, Anaesthesiology, SAMU, Necker Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France

    Benoit Vivien

Authors
  1. Romain Jouffroy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florian Négrello
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jean Limery
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Basile Gilbert
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stéphane Travers
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Emmanuel Bloch-Laine
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Patrick Ecollan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Josiane Boularan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Vincent Bounes
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Benoit Vivien
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Papa Gueye
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: RJ, PG. Methodology: RJ. Data curation: RJ, FN, JL, BG, ST, EBL, PE, VB, JB, BV, PG. Writing- Original draft preparation: RJ, FN, JL, BG, PG. Investigation: RJ, PG. Supervision: RJ, PG. Validation: RJ, PG. Writing- Reviewing and Editing: RJ, FN, JL, BG, ST, EBL, PE, VB, JB, BV, PG.

Corresponding author

Correspondence to Romain Jouffroy.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the French Society of Anaesthesia and Intensive Care ethics committee on December 12th, 2017 (Ref number: IRB 00010254-2017-026). The French Society of Anaesthesia and Intensive Care ethics committee waived the patient informed consent for participation in this retrospective study. All experiments were performed in accordance with the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jouffroy, R., Négrello, F., Limery, J. et al. The prehospital NEW score to assess septic shock in-hospital, 30-day and 90-day mortality. BMC Infect Dis 24, 213 (2024). https://doi.org/10.1186/s12879-024-09104-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-024-09104-7

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us