- Email: [email protected]
A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU
Journal of Critical Care 41 (2017) 191–193
Contents lists available at ScienceDirect
Journal of Critical Care journal homepage: www.jccjournal.org
A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU Shahla Siddiqui, MBBS, DABA, FCCM ⁎, Maureen Chua, MBBs, MMed, Venkatesan Kumaresh, MBBS, FRCA, EDIC, Robin Choo, MS a
Anaesthesia and Intensive Care, Khoo Teck Puat Hospital, Singapore MOhh, Singapore KTPH, Singapore d Yishun Comm. Hospital, Singapore. b c
a r t i c l e
i n f o
Available online xxxx Keywords: Sepsis 3 q SOFA Risk stratification
a b s t r a c t Introduction: The 2015sepsis definitions suggest using the quick SOFA score for risk stratification of sepsis patients among other changes in sepsis definition. Our aim was to validate the q sofa score for diagnosing sepsis and comparing it to traditional scores of pre ICU admission sepsis outcome prediction such as EWS and SIRS in our setting in order to predict mortality and length of stay. Methods: This was a retrospective cohort study. We retrospectively calculated the q sofa, SIRS and EWS scores of all ICU patients admitted with the diagnosis of sepsis at our center in 2015. This was analysed using STATA 12. Logistic regression and ROC curves were used for analysis in addition to descriptive analysis. Results: 58 patients were included in the study. Based on our one year results we have shown that although q SOFA is more sensitive in predicting LOS in ICU of sepsis patients, the EWS score is more sensitive and specific in predicting mortality in the ICU of such patients when compared to q SOFA and SIRS scores. Conclusion: In conclusion, we find that in our setting, EWS is better than SIRS and q SOFA for predicting mortality and perhaps length of stay as well. The q Sofa score remains validated for diagnosis of sepsis. © 2017 Elsevier Inc. All rights reserved.
1. Introduction Since the advent of the new sepsis definitions by The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) [1] in early 2016 many publications urge the validation of the suggested q SOFA score in local contexts. The authors of the new definitions themselves urge further epidemiological research in this arena. Sepsis is defined as “a life threatening syndrome which is due to a dysregulated host response and causes organ dysfunction” [2]. Patients admitted with sepsis to the ICU were evaluated for severity using the SIRS (systemic inflammatory response score) or EWS (early warning score), however after the new definition has been published we are urged to use q SOFA score in the preadmission period for prediction of adverse outcomes [3]. SIRS has been the oldest definition of mild sepsis but has been criticized for having a poor specificity [4]. The presence of N 2 SIRS criteria in non-infectious cases has led to its use being obsolete in sepsis outcomes prediction. The early warning score based on 6 physiologic scores have been widely adopted in UK hospitals and is the norm for pre ICU assessment in sepsis patients [5]. A score of four is a ⁎ Corresponding author. E-mail address: [email protected] (S. Siddiqui).
http://dx.doi.org/10.1016/j.jcrc.2017.05.017 0883-9441/© 2017 Elsevier Inc. All rights reserved.
threshold for ICU admission but is not specific for sepsis. The q SOFA score is a composite of clinical signs (hypotension b 100 SBP, altered consciousness, GCS b 15, and a respiratory rate N 22 bpm) which has a high internal validity in the Sepsis 3 study for outcome prediction. The score ranges from 0 to 3 points. The presence of 2 or more q SOFA points at the onset of infection was associated with a greater risk of death or prolonged intensive care unit stay [6]. These are outcomes that are more common in infected patients who may be septic than those with uncomplicated infection. Based upon these findings, the Third International Consensus Definitions for Sepsis recommends q SOFA as a simple prompt to identify infected patients outside the ICU. The internal validity of the q SOFA score for predicting poor outcomes (LOS and mortality) was high. The authors concluded that the initial, retrospective analysis indicated that q SOFA could be a useful clinical tool, especially to physicians and other practitioners working outside the ICU to promptly identify infected patients likely to fare poorly [7]. However, because most of the data were extracted from only US databases, the task force strongly encourages prospective validation in non-US health care settings to confirm its robustness and potential for incorporation into future clinical management [8]. Our aim was to compare the q SOFA score with SIRS and EWS score traditionally used in our setting for pre ICU risk prediction in sepsis
192
S. Siddiqui et al. / Journal of Critical Care 41 (2017) 191–193
patients. We wished not only to validate q SOFA for diagnosis of sepsis but also to study its efficacy in predicting mortality and length of stay.
Table 2 The association between different sepsis assessment tools and mortality. Model
Unadjusted OR (95% CI)
p-Value
Adjusteda OR (95% CI)
p-Value
q SOFA SIRS EWS
2.08 (0.99–4.37) 2.45 (1.01–5.92) 1.62 (1.22–2.16)
0.053 0.047 0.001
2.53 (1.10–5.82) 2.82 (1.09–7.25) 1.92 (1.24–2.96)
0.029 0.032 0.003
1.1. Subjects and methods 1.1.1. Study sample After obtaining an IRB waiver, we conducted a retrospective cohort study on all adult ICU or High dependency unit admissions in the ICUs of Khoo Teck Puat Hospital, with the presumed diagnosis of ‘sepsis’. Medical, surgical and cardiac ICUs were included during Jan–December 2015. Exclusion criteria included patients admitted without a diagnosis of sepsis. Data collected included demographics, SIRS; EWS and q SOFA scores calculated for each patient from their pre ICU admission computerized vitals chart as well as our outcomes: mortality and ICU Length of stay. Data was recovered using the Philips IntelliSpace Critical Care and anesthesia system used in our ICU as well as the Sunrise Clinical Manager system for ward and ICU data. All scores were manually calculated by the authors and analysed. Our hospital is a 600 bedded regional hospital with 36 ICU and High dependency beds. 1.1.2. Statistical methods Descriptive statistics were carried out. Logistic regression models were used to examine the associations between mortality and each of the sepsis assessment tools: q SOFA, SIRS and EWS. We assessed each model's discrimination using the area under the receiver operator characteristics (ROC) curve, the C-statistics. Length of stay was naturally a skew distribution with no zero (and outpatient visits were counted as 1 day of LOS). Zero-truncated Poisson regression models were used to examine the associations between length of stay and each of sepsis assessment tools. All analyses were carried out using Stata 12. 2. Results 58 adult patients were admitted to the ICUs of Khoo Teck Puat Hospital with a diagnosis of ‘sepsis’. Our mean age was 64.4 ± 12.9 years (Table 1). Of these 63.8% were Chinese, 17.2% Malay, 12.1% Indian and 6.9% others, representing the usual distribution of ethnicities in Singapore. 44.8% were admitted to the surgical ICU (SICU), 32.8% to MICU and 22.4% to CCU. 44.8% of the patients had a q SOFA score of ≥ 2, 62.1% had a SIRS score N 2 and the mean EWS score was 4.5 ± 3.4 Table 1 Characteristics of patients. Range Age, mean ± SD y Ethnicity, n (%) Chinese Malay Indian Others Ward, n (%) W36 SICU W26 CCU W26 MICU q SOFA, mean ± SD q SOFA, n (%) q SOFA b 2 q SOFA ≥ 2 SIRS, mean ± SD SIRS, n (%) SIRS ≤ 2 SIRS N 2 EWS, mean ± SD Mortality, n (%) No Yes ICU length of stay, mean ± SD day Notes: SD = Standard Deviation.
64.4 ± 12.9
a
Adjusted with age and ethnicity.
with a range of 0–12. The overall mortality was 17.2%. The ICU length of stay (LOS) was 6.3 ± 11.6 days with a range of 1 to 87 days. All three sepsis assessment tools were found to have associations with mortality in ICU patient subjects (Table 2). We found that a higher q SOFA score had an unadjusted Odds Ratio (OR) of 2.08 (p-value = 0.053, 95% Confidence Interval (CI) 0.99–4.37) for in patient mortality. Higher SIRS score had an unadjusted OR of 2.45 (p-value = 0.047, 95% CI 1.01–5.92) and a higher EWS score had an unadjusted OR of 1.62 (p-value = 0.001, 95% CI 1.22–2.16) for in patient mortality. With model adjustments for patient's age and ethnicity, a higher q SOFA score had an adjusted Odds Ratio (OR) of 2.53 (p-value = 0.029, 95% Confidence Interval (CI) 1.10–5.82) for in patient mortality. A higher SIRS score had an adjusted OR of 2.82 (p-value = 0.032, 95% CI 1.09– 7.25) and a higher EWS score had an adjusted OR of 1.92 (p-value = 0.003, 95% CI 1.24–2.96) for in patient mortality. When we compare the ROC curves of each sepsis assessment tools with patient mortality (Fig. 1), EWS has the highest C-statistic, 0.8781, followed by SIRS, 0.7073, and q SOFA, 0.6875. The C-statistics is the area under the ROC curve where the true positive rate (sensitivity) is plotted in the function of the false positive rate (1-specificity) for different threshold points of a parameter. With adjustments for age and ethnicity, the adjusted C-statistics are 0.7432, 0.7739 and 0.9068 for q SOFA, SIRS and EWS respectively. Therefore, EWS had the highest unadjusted (univariate) C-statistic to predict mortality. When we take the EWS threshold score of 6, the true positive rate is 0.90 and the false positive rate is 0.23. This means that EWS has a stronger power to discriminate mortality than SIRS and q SOFA because of EWS's wider range (0−12) then SIRS's (0–4) and q SOFA's (0–3). The length of stay may have associations with the sepsis assessment tools as well (Table 3). For every unit increase of q SOFA score, there was an unadjusted log rate increase of 0.32 days in the length of stay (pvalue = 0.001, 95% CI 0.13–0.51). SIRS had an increased unadjusted log rate of 0.18 (p-value = 0.061, 95% CI –0.01–0.36) and EWS had 0.12 (p-value = 0.008, 95% CI 0.03–0.21). Adjusting the model for the
24–87
37 (63.8) 10 (17.2) 7 (12.1) 4 (6.9) 26 (44.8) 13 (22.4) 19 (32.8) 1.5 ± 1.0
0–3
32 (55.2) 26 (44.8) 2.6 ± 1.2
0–4
22 (37.9) 36 (62.1) 4.5 ± 3.4
0–12
48 (82.8) 10 (17.2) 6.3 ± 11.6
1–87 Fig. 1. Combined ROC curves of q SOFA, SIRS and EWS with patient mortality outcome.
S. Siddiqui et al. / Journal of Critical Care 41 (2017) 191–193 Table 3 The association between different sepsis assessment tools and length of stay. Model
Unadjusted Coef (95% CI)
p-Value
Adjusteda Coef (95% CI)
p-Value
q SOFA SIRS EWS
0.32 (0.13–0.51) 0.18 (−0.01–0.36) 0.12 (0.03–0.21)
0.001 0.061 0.008
0.36 (0.10–0.63) 0.16 (−0.04–0.36) 0.15 (0.03–0.27)
0.007 0.109 0.015
a
Adjusted with age and ethnicity.
patient's age and ethnicity, q SOFA had an increase adjusted log rate of 0.36 days in the length of stay (p-value = 0.007, 95% CI 0.10–0.63). SIRS had an increased adjusted log rate of 0.16 days (p-value = 0.109, 95% CI –0.04–0.36) and EWS had 0.15 days (p-value = 0.015, 95% CI 0.03–0.27). All unadjusted and adjusted scores are significant but only SIRS adjusted score is non-significant for predicting an increased length of stay. EWS had the highest pseudo R-square of the zero truncated Poisson model of predicting length of stay (unadjusted = 0.1028; adjusted = 0.1912) as compared to SIRS's pseudo R-square (unadjusted = 0.0205; adjusted = 0.0780) and q SOFA's pseudo R-square (unadjusted = 0.0556; adjusted = 0.1257) [9]. EWS therefore could be a better predictor of LOS compared to SIRS and q SOFA score as well. 3. Conclusions Based on our one year results we have shown that although q SOFA is sensitive in diagnosis of sepsis, it remains deficient in predicting LOS and mortality in ICU of sepsis patients. The EWS score is more sensitive and specific in predicting mortality in the ICU of such patients when compared to q SOFA and SIRS scores. Although the q SOFA score was designed to accurately predict sepsis diagnosis, it has been shown to have good internal validity for outcomes prediction in other initial studies. However, as urged by the Consensus group local validation for such
193
definitions and scores is required before international acceptance can occur. Our limitations were the small sample size of sepsis patients over one year. In conclusion, we find that in our setting, EWS is better than SIRS and q SOFA for predicting mortality and perhaps length of stay as well. Contributions SS - conception, data collection, analysis, manuscript writing MC - data collection, editing VK - concept, data collection RC - analysis References [1] 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 Feb 23;315(8):801–10. [2] Giamarellos-Bourboulis EJ, Tsaganos T, Tsangaris I, Lada M, Routsi C, Sinapidis D, et al. Validation of the new sepsis-3 definitions: proposal for improvement in early risk identification. Clin Microbiol Infect 2016 Nov 14;23(2):104–9. [3] Finkelsztein Eli J, 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. [4] Balk RA. Systemic inflammatory response syndrome (SIRS): where did it come from and is it still relevant today? Virulence 2014;5(1):20–6. http://dx.doi.org/10.4161/ viru.27135. [5] Bhattacharjee P, Edelson DP, Churpek MM. Identifying patients with sepsis on the hospital wards. Chest 2016 Jun 30 (Epub 2016 Jun 30). [6] Shankar-Hari M, Deutschman CS, Singer M. Do we need a new definition of sepsis? Intensive Care Med 2015 May;41(5):909–11. [7] Seymour CW, Liu V, Iwashyna TJ, et al. Assessment of clinical criteria for sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis3). JAMA 2016;315(8):762–77. [8] Vincent Jean-Louis, Martin Greg S, Mitchell M. Levy q SOFA does not replace SIRS in the definition of sepsis. Crit Care 2016;20:210. [9] IWM Verburg, de Keizer NF, de Jonge E, Peek N. Comparison of regression methods for modeling intensive care length of stay. Salluh JIF, ed. PLoS ONE 2014;9(10):e109684.
Contents lists available at ScienceDirect
Journal of Critical Care journal homepage: www.jccjournal.org
A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU Shahla Siddiqui, MBBS, DABA, FCCM ⁎, Maureen Chua, MBBs, MMed, Venkatesan Kumaresh, MBBS, FRCA, EDIC, Robin Choo, MS a
Anaesthesia and Intensive Care, Khoo Teck Puat Hospital, Singapore MOhh, Singapore KTPH, Singapore d Yishun Comm. Hospital, Singapore. b c
a r t i c l e
i n f o
Available online xxxx Keywords: Sepsis 3 q SOFA Risk stratification
a b s t r a c t Introduction: The 2015sepsis definitions suggest using the quick SOFA score for risk stratification of sepsis patients among other changes in sepsis definition. Our aim was to validate the q sofa score for diagnosing sepsis and comparing it to traditional scores of pre ICU admission sepsis outcome prediction such as EWS and SIRS in our setting in order to predict mortality and length of stay. Methods: This was a retrospective cohort study. We retrospectively calculated the q sofa, SIRS and EWS scores of all ICU patients admitted with the diagnosis of sepsis at our center in 2015. This was analysed using STATA 12. Logistic regression and ROC curves were used for analysis in addition to descriptive analysis. Results: 58 patients were included in the study. Based on our one year results we have shown that although q SOFA is more sensitive in predicting LOS in ICU of sepsis patients, the EWS score is more sensitive and specific in predicting mortality in the ICU of such patients when compared to q SOFA and SIRS scores. Conclusion: In conclusion, we find that in our setting, EWS is better than SIRS and q SOFA for predicting mortality and perhaps length of stay as well. The q Sofa score remains validated for diagnosis of sepsis. © 2017 Elsevier Inc. All rights reserved.
1. Introduction Since the advent of the new sepsis definitions by The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) [1] in early 2016 many publications urge the validation of the suggested q SOFA score in local contexts. The authors of the new definitions themselves urge further epidemiological research in this arena. Sepsis is defined as “a life threatening syndrome which is due to a dysregulated host response and causes organ dysfunction” [2]. Patients admitted with sepsis to the ICU were evaluated for severity using the SIRS (systemic inflammatory response score) or EWS (early warning score), however after the new definition has been published we are urged to use q SOFA score in the preadmission period for prediction of adverse outcomes [3]. SIRS has been the oldest definition of mild sepsis but has been criticized for having a poor specificity [4]. The presence of N 2 SIRS criteria in non-infectious cases has led to its use being obsolete in sepsis outcomes prediction. The early warning score based on 6 physiologic scores have been widely adopted in UK hospitals and is the norm for pre ICU assessment in sepsis patients [5]. A score of four is a ⁎ Corresponding author. E-mail address: [email protected] (S. Siddiqui).
http://dx.doi.org/10.1016/j.jcrc.2017.05.017 0883-9441/© 2017 Elsevier Inc. All rights reserved.
threshold for ICU admission but is not specific for sepsis. The q SOFA score is a composite of clinical signs (hypotension b 100 SBP, altered consciousness, GCS b 15, and a respiratory rate N 22 bpm) which has a high internal validity in the Sepsis 3 study for outcome prediction. The score ranges from 0 to 3 points. The presence of 2 or more q SOFA points at the onset of infection was associated with a greater risk of death or prolonged intensive care unit stay [6]. These are outcomes that are more common in infected patients who may be septic than those with uncomplicated infection. Based upon these findings, the Third International Consensus Definitions for Sepsis recommends q SOFA as a simple prompt to identify infected patients outside the ICU. The internal validity of the q SOFA score for predicting poor outcomes (LOS and mortality) was high. The authors concluded that the initial, retrospective analysis indicated that q SOFA could be a useful clinical tool, especially to physicians and other practitioners working outside the ICU to promptly identify infected patients likely to fare poorly [7]. However, because most of the data were extracted from only US databases, the task force strongly encourages prospective validation in non-US health care settings to confirm its robustness and potential for incorporation into future clinical management [8]. Our aim was to compare the q SOFA score with SIRS and EWS score traditionally used in our setting for pre ICU risk prediction in sepsis
192
S. Siddiqui et al. / Journal of Critical Care 41 (2017) 191–193
patients. We wished not only to validate q SOFA for diagnosis of sepsis but also to study its efficacy in predicting mortality and length of stay.
Table 2 The association between different sepsis assessment tools and mortality. Model
Unadjusted OR (95% CI)
p-Value
Adjusteda OR (95% CI)
p-Value
q SOFA SIRS EWS
2.08 (0.99–4.37) 2.45 (1.01–5.92) 1.62 (1.22–2.16)
0.053 0.047 0.001
2.53 (1.10–5.82) 2.82 (1.09–7.25) 1.92 (1.24–2.96)
0.029 0.032 0.003
1.1. Subjects and methods 1.1.1. Study sample After obtaining an IRB waiver, we conducted a retrospective cohort study on all adult ICU or High dependency unit admissions in the ICUs of Khoo Teck Puat Hospital, with the presumed diagnosis of ‘sepsis’. Medical, surgical and cardiac ICUs were included during Jan–December 2015. Exclusion criteria included patients admitted without a diagnosis of sepsis. Data collected included demographics, SIRS; EWS and q SOFA scores calculated for each patient from their pre ICU admission computerized vitals chart as well as our outcomes: mortality and ICU Length of stay. Data was recovered using the Philips IntelliSpace Critical Care and anesthesia system used in our ICU as well as the Sunrise Clinical Manager system for ward and ICU data. All scores were manually calculated by the authors and analysed. Our hospital is a 600 bedded regional hospital with 36 ICU and High dependency beds. 1.1.2. Statistical methods Descriptive statistics were carried out. Logistic regression models were used to examine the associations between mortality and each of the sepsis assessment tools: q SOFA, SIRS and EWS. We assessed each model's discrimination using the area under the receiver operator characteristics (ROC) curve, the C-statistics. Length of stay was naturally a skew distribution with no zero (and outpatient visits were counted as 1 day of LOS). Zero-truncated Poisson regression models were used to examine the associations between length of stay and each of sepsis assessment tools. All analyses were carried out using Stata 12. 2. Results 58 adult patients were admitted to the ICUs of Khoo Teck Puat Hospital with a diagnosis of ‘sepsis’. Our mean age was 64.4 ± 12.9 years (Table 1). Of these 63.8% were Chinese, 17.2% Malay, 12.1% Indian and 6.9% others, representing the usual distribution of ethnicities in Singapore. 44.8% were admitted to the surgical ICU (SICU), 32.8% to MICU and 22.4% to CCU. 44.8% of the patients had a q SOFA score of ≥ 2, 62.1% had a SIRS score N 2 and the mean EWS score was 4.5 ± 3.4 Table 1 Characteristics of patients. Range Age, mean ± SD y Ethnicity, n (%) Chinese Malay Indian Others Ward, n (%) W36 SICU W26 CCU W26 MICU q SOFA, mean ± SD q SOFA, n (%) q SOFA b 2 q SOFA ≥ 2 SIRS, mean ± SD SIRS, n (%) SIRS ≤ 2 SIRS N 2 EWS, mean ± SD Mortality, n (%) No Yes ICU length of stay, mean ± SD day Notes: SD = Standard Deviation.
64.4 ± 12.9
a
Adjusted with age and ethnicity.
with a range of 0–12. The overall mortality was 17.2%. The ICU length of stay (LOS) was 6.3 ± 11.6 days with a range of 1 to 87 days. All three sepsis assessment tools were found to have associations with mortality in ICU patient subjects (Table 2). We found that a higher q SOFA score had an unadjusted Odds Ratio (OR) of 2.08 (p-value = 0.053, 95% Confidence Interval (CI) 0.99–4.37) for in patient mortality. Higher SIRS score had an unadjusted OR of 2.45 (p-value = 0.047, 95% CI 1.01–5.92) and a higher EWS score had an unadjusted OR of 1.62 (p-value = 0.001, 95% CI 1.22–2.16) for in patient mortality. With model adjustments for patient's age and ethnicity, a higher q SOFA score had an adjusted Odds Ratio (OR) of 2.53 (p-value = 0.029, 95% Confidence Interval (CI) 1.10–5.82) for in patient mortality. A higher SIRS score had an adjusted OR of 2.82 (p-value = 0.032, 95% CI 1.09– 7.25) and a higher EWS score had an adjusted OR of 1.92 (p-value = 0.003, 95% CI 1.24–2.96) for in patient mortality. When we compare the ROC curves of each sepsis assessment tools with patient mortality (Fig. 1), EWS has the highest C-statistic, 0.8781, followed by SIRS, 0.7073, and q SOFA, 0.6875. The C-statistics is the area under the ROC curve where the true positive rate (sensitivity) is plotted in the function of the false positive rate (1-specificity) for different threshold points of a parameter. With adjustments for age and ethnicity, the adjusted C-statistics are 0.7432, 0.7739 and 0.9068 for q SOFA, SIRS and EWS respectively. Therefore, EWS had the highest unadjusted (univariate) C-statistic to predict mortality. When we take the EWS threshold score of 6, the true positive rate is 0.90 and the false positive rate is 0.23. This means that EWS has a stronger power to discriminate mortality than SIRS and q SOFA because of EWS's wider range (0−12) then SIRS's (0–4) and q SOFA's (0–3). The length of stay may have associations with the sepsis assessment tools as well (Table 3). For every unit increase of q SOFA score, there was an unadjusted log rate increase of 0.32 days in the length of stay (pvalue = 0.001, 95% CI 0.13–0.51). SIRS had an increased unadjusted log rate of 0.18 (p-value = 0.061, 95% CI –0.01–0.36) and EWS had 0.12 (p-value = 0.008, 95% CI 0.03–0.21). Adjusting the model for the
24–87
37 (63.8) 10 (17.2) 7 (12.1) 4 (6.9) 26 (44.8) 13 (22.4) 19 (32.8) 1.5 ± 1.0
0–3
32 (55.2) 26 (44.8) 2.6 ± 1.2
0–4
22 (37.9) 36 (62.1) 4.5 ± 3.4
0–12
48 (82.8) 10 (17.2) 6.3 ± 11.6
1–87 Fig. 1. Combined ROC curves of q SOFA, SIRS and EWS with patient mortality outcome.
S. Siddiqui et al. / Journal of Critical Care 41 (2017) 191–193 Table 3 The association between different sepsis assessment tools and length of stay. Model
Unadjusted Coef (95% CI)
p-Value
Adjusteda Coef (95% CI)
p-Value
q SOFA SIRS EWS
0.32 (0.13–0.51) 0.18 (−0.01–0.36) 0.12 (0.03–0.21)
0.001 0.061 0.008
0.36 (0.10–0.63) 0.16 (−0.04–0.36) 0.15 (0.03–0.27)
0.007 0.109 0.015
a
Adjusted with age and ethnicity.
patient's age and ethnicity, q SOFA had an increase adjusted log rate of 0.36 days in the length of stay (p-value = 0.007, 95% CI 0.10–0.63). SIRS had an increased adjusted log rate of 0.16 days (p-value = 0.109, 95% CI –0.04–0.36) and EWS had 0.15 days (p-value = 0.015, 95% CI 0.03–0.27). All unadjusted and adjusted scores are significant but only SIRS adjusted score is non-significant for predicting an increased length of stay. EWS had the highest pseudo R-square of the zero truncated Poisson model of predicting length of stay (unadjusted = 0.1028; adjusted = 0.1912) as compared to SIRS's pseudo R-square (unadjusted = 0.0205; adjusted = 0.0780) and q SOFA's pseudo R-square (unadjusted = 0.0556; adjusted = 0.1257) [9]. EWS therefore could be a better predictor of LOS compared to SIRS and q SOFA score as well. 3. Conclusions Based on our one year results we have shown that although q SOFA is sensitive in diagnosis of sepsis, it remains deficient in predicting LOS and mortality in ICU of sepsis patients. The EWS score is more sensitive and specific in predicting mortality in the ICU of such patients when compared to q SOFA and SIRS scores. Although the q SOFA score was designed to accurately predict sepsis diagnosis, it has been shown to have good internal validity for outcomes prediction in other initial studies. However, as urged by the Consensus group local validation for such
193
definitions and scores is required before international acceptance can occur. Our limitations were the small sample size of sepsis patients over one year. In conclusion, we find that in our setting, EWS is better than SIRS and q SOFA for predicting mortality and perhaps length of stay as well. Contributions SS - conception, data collection, analysis, manuscript writing MC - data collection, editing VK - concept, data collection RC - analysis References [1] 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 Feb 23;315(8):801–10. [2] Giamarellos-Bourboulis EJ, Tsaganos T, Tsangaris I, Lada M, Routsi C, Sinapidis D, et al. Validation of the new sepsis-3 definitions: proposal for improvement in early risk identification. Clin Microbiol Infect 2016 Nov 14;23(2):104–9. [3] Finkelsztein Eli J, 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. [4] Balk RA. Systemic inflammatory response syndrome (SIRS): where did it come from and is it still relevant today? Virulence 2014;5(1):20–6. http://dx.doi.org/10.4161/ viru.27135. [5] Bhattacharjee P, Edelson DP, Churpek MM. Identifying patients with sepsis on the hospital wards. Chest 2016 Jun 30 (Epub 2016 Jun 30). [6] Shankar-Hari M, Deutschman CS, Singer M. Do we need a new definition of sepsis? Intensive Care Med 2015 May;41(5):909–11. [7] Seymour CW, Liu V, Iwashyna TJ, et al. Assessment of clinical criteria for sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis3). JAMA 2016;315(8):762–77. [8] Vincent Jean-Louis, Martin Greg S, Mitchell M. Levy q SOFA does not replace SIRS in the definition of sepsis. Crit Care 2016;20:210. [9] IWM Verburg, de Keizer NF, de Jonge E, Peek N. Comparison of regression methods for modeling intensive care length of stay. Salluh JIF, ed. PLoS ONE 2014;9(10):e109684.