Importance of qSOFA Score in Terms of Prognosis and Mortality in Critical Care Patients

ABSTRACT

Background

Recent studies have analyzed the qSOFA (quick sequential organ failure assessment) score as a prognostic indicator in many diseases, particularly sepsis. However, the effect of qSOFA score on prognosis and mortality in critical care patients has not been sufficiently analyzed. There is not enough data, especially regarding its use as critical care mortality and prognosis scoring. In this study, we aimed to analyze the effect of qSOFA score on mortality and prognosis in critical care unit (CCU) patients.

Methods

This study was conducted retrospectively using the chart review method. The APACHE II (Acute Physiology and Chronic Health Evaluation II) and SOFA (Sequential Organ Failure Assessment) scores of patients admitted to our CCU were compared with the qSOFA score. In addition, the need for intubation and mechanical ventilation, short- and long term mortality rates, the relationship between blood gas lactate values and qSOFA score were analyzed.

Results

A total of 1816 patients were included in the study. During critical care follow-up, 374 (20.6%) of our patients died, and at the end of 6 months, 796 (43.8%) of our patients died. A statistically significant association was found between in-hospital mortality and qSOFA, SOFA scores and lactate levels (P = 0.001, P = 0.001, P = 0.01 respectively). A statistically significant association was found between 6-month mortality and SOFA score only. (P = 0.001) The SOFA score appeared to be the most successful predictor of mortality. The cut-off for mortality using the ROC curve was ≥ 7 [sensitivity 78.1%; specificity 85.9%; AUC 0.91; 95% confidence interval (CI), 0.89 to 0.92; P = 0.001]. qSOFA scoring also performed well. The cut-off value for mortality using the ROC curve was ≥ 2 (sensitivity 42.5%; specificity 93.9%; AUC 0.83;95% CI, 0.80-0.85; P = 0.001).

Conclusion

We believe that the qSOFA score can be used as a marker for in-hospital mortality and prognosis in critical care patients. Especially in cases where the qSOFA score is ≥ 2, it provides valuable information regarding mortality and prognosis.

A number of scoring systems such as APACHE II (Acute Physiology and Chronic Health Evaluation II) and SOFA (Sequential Organ Failure Assessment) have been developed to assess parameters such as prognosis, mortality and length of stay in the CCU (Critical care unit).^{1, 2} These systems are used in many CCUs around the world. Sepsis and septic shock are among the most frequently hospitalised patient groups in CCUs. Current sepsis guidelines recommend the use of the qSOFA (quick sequential organ failure assessment) score (Table 1) to diagnose sepsis in the emergency department.^3,4,5 However, the effect of qSOFA score on prognosis and mortality of CCU patients has not been analyzed. There is not enough data, especially regarding its use as critical care mortality and prognosis scoring. In this study, we aimed to analyze the effect of qSOFA score on mortality and prognosis of CCU patients.

Table 1.  Quick sequential organ failure assessment (qSOFA).

Assessment	qSOFA score
Low blood pressure (SBP ≤ 100 mmHg)	1
High respiratory rate (≥ 22 breaths/min)	1
Altered mentation (GCS ≤ 14)	1

GCS, Glasgow Coma Score; SBP, systolic blood pressure.

MATERIALS AND METHODS

Study population and study protocol

This study was conducted retrospectively by file review method. Our study was conducted in the Critical Care Unit of the Emergency Medicine Clinic of Health Sciences University Ankara Training and Research Hospital. Our hospital is an important regional teaching hospital that accepts an average of 10,000 outpatients and 1,000 emergency patients daily. Patients hospitalized in our critical care unit between 1. January 2016 and 1. October 2021 were included in the study. APACHE II and SOFA scores of patients hospitalized in our critical care unit were compared with qSOFA score. In our critical care unit, the qSOFA score is routinely used together with scores such as APACHE II and SOFA. This is due to the fact that our clinic is an emergency medicine and critical care clinic. Because qSOFA score is widely used in emergency medicine practice because it is an easy and fast method. In addition, patients’ diagnoses, etiological and demographic characteristics, length of stay, intubation and mechanical ventilation needs, short and long-term mortality rates, blood gas lactate values and the relationship between qSOFA score were analyzed. Approval for our study was obtained from the Health Sciences University Ankara Training and Research Hospital Clinical Research Ethics Committee on 29/09/2021 with the number E-21-753. The work was done in accordance with the appropriate institutional review body and carried out with the ethical standards set forth in the Helsinki Declaration.

Study inclusion criteria

Patients over the age of 18 who were hospitalized in our critical care unit between 01.01.2016 and 01.10.2021 were included in the study. Patients included and excluded from the study are shown in Fig. 1.

Fig. 1.

 Participant flow diagram.

Study exclusion criteria

• - Pregnant patients

• - Patients under 18 years of age

• - Patients with missing information in their files

• - Patients whose SOFA, qSOFA and APACHE II scores cannot be calculated

• - Patients with missing 6-month mortality information

Statistical analysis

Statistical analysis was performed using SPSS version 21.0 for Windows (SPSS, Chicago, IL). Both visual (histogram and probability plots) and analytical (Kolmogorov-Smirnov and Shapiro-Wilk tests) methods were used to determine whether the data were normally distributed. Descriptive variables are expressed as mean ± SD for normally distributed data and as median and interquartile range (IQR) for non-normally distributed variables. The relationship between qSOFA score and SOFA, APACHE II scores, CCU length of stay and lactate levels was analyzed using Sperman’s correlation test. Logistic and Cox regression models were used to evaluate the associations of in-hospital and 6-month mortality with qSOFA score, SOFA score, APACHE II score, and lactate levels. The utility of qSOFA score, SOFA score, APACHE II score, and lactate level in predicting in-hospital and 6-month mortality in critical care patients was assessed using receiver operating characteristic curves. A P < 0.05 was considered statistically significant. The power of the study was calculated as 95% using a free website (http://www.statisticalsolutions.net/pss_calc.php).

RESULTS

A total of 1816 patients were included in the study. The median age of the patients was 69.5 (IQR:33) years. The gender of our patients was distributed as follows: 982 (54.1%) patients were female and 834 (45.9%) patients were male. During critical care follow-up, 374 (20.6%) of our patients died, and at the end of 6 months, 796 (43.8%) of our patients died. The most common group of patients admitted to hospital were those admitted with a diagnosis of sepsis and septic shock with 434 (23.9%) patients. The median qSOFA score was 1 (IQR: 2), the median SOFA score was 4 (IQR: 7) and the median APACHE II score was 19 (IQR: 15). Demographic data, score values and laboratory data of the 1816 patients who participated in our study are summarised in Table 2.

Table 2.  Demographics and laboratory findings of the study population.

No. of patients	1816
Age, y, median (IQR)	69.5 (33)
Female sex, n (%)	982 (54.1)
qSOFA score median (IQR)	1 (2)
SOFA score median (IQR)	4 (7)
APACHE II score median (IQR)	19 (15)
Lactate median (IQR)	2,3 (2.28)
Length of stay in i care (day) (IQR)	4 (5)
The need for mechanical ventilation n (%)	612 (33.7)
In-hospital mortality n (%)	374 (20.6)
6-month mortality n (%)	796 (43.8)
Diagnosis n (%)	1816 (100)
Sepsis and septic shock	434 (23.9)
Poisoning	338 (18.6)
Cerebrovascular disease	295 (16.2)
Respiratory failure	154 (8.5)
ROSC after CA	117 (6.4)
Acute renal failure	97 (5.3)
Diabetic ketoacidosis	94 (5.2)
Decompensated heart failure	92 (5.1)
Gastrointestinal hemorrhage	83 (4.6)
Pulmonary thromboembolism	34 (1.9)
Status epilepticus	31 (1.7)
Liver failure	20 (1.1)
Anaphylactic shock	14 (0.8)
Multiple trauma	12 (0.7)
Eclampsia	1 (0.1)
Resume n (%)	1816 (100)
Hypertension	780 (42.9)
Diabetes mellitus	596 (32.8)
Coronary artery disease	378 (20.8)
Cerebrovascular disease	160 (8.8)
Heart failure	283 (15.6)
COPD / Asthma	223 (12.3)
Alzheimer’s	84 (4.6)
Cancer	60 (3.3)
Chronic renal disease	53 (2.9)
Chronic liver disease	16 (0.9)
Hyperlipidemia	45 (2.5)
Epilepsy	34 (1.9)

APACHE, Acute Physiology and Chronic Health Evaluation; COPD, Chronic Obstructive Pulmonary Disease; ROSC after CA, return of spontaneous circulation after cardiac arrest; SOFA, Sequential Organ Failure Assessment; qSOFA, quick sequential organ failure assessment.

The correlation between qSOFA score and SOFA, APACHE II scores, CCU length of stay and lactate levels at the time of initial hospitalisation were analyzed. A statistically significant and strong correlation was found between qSOFA score and SOFA and APACHE II scores (cc: 0.729, P = 0.001; cc: 0.736, P = 0.001 respectively). However, although there was a statistically significant correlation between patients’ initial lactate levels and length of stay in the CCU, the strength of the correlation was weak to moderate (cc: 0.402, P = 0.402) (cc: 0.402, P = 0.001; cc: 0.230, P = 0.001). The correlation analyzes are summarised in Table 3.

Table 3. Correlation between patients' qSOFASOFA II scores and lactate levels.

Correlation		SOFA score	qSOFA score	APACHE II score	Lactate level	LOS in IC
SOFA score	cc P value	1	0.729 0.001	0.776 0.001	0.422 0.001	0.234 0.001
qSOFA score	cc P value	0.729 0.001	1	0.736 0.001	0.402 0.001	0.230 0.001
APACHEII score	cc P value	0.776 0.001	0.736 0.001	1	0.407 0.001	0.238 0.001
Lactate level	cc P value	0.422 0.001	0.402 0.001	0.407 0.001	1	0.014 0.554
LOS in CC	cc P value	0.234 0.001	0.230 0.001	0.238 0.001	0.014 0.554	1

APACHE, Acute Physiology and Chronic Health Evaluation; CC, correlation coefficient; LOS in CC, Length of stay in critical care; SOFA, Sequential Organ Failure Assessment; Sperman's Correlation Test; qSOFA, quick sequential organ failure assessment.

In-hospital and 6-month mortality, the need for mechanical ventilation and the relationship between the scores and various factors were analyzed using logistic regression and cox regression models. A statistically significant association was found between in-hospital mortality and qSOFA, SOFA scores and lactate levels (P = 0.001, P = 0.001, P =0.01 respectively). A statistically significant association was found between 6-month mortality and SOFA score only. (P = 0.001) There was a statistically significant association between need for mechanical ventilation and qSOFA score, SOFA and APACHE II scores (P = 0.001, P = 0.001, P = 0.019 respectively) The analysis of logistic regression and cox regression models is shown in Table 4.

Table 4.  Risk factors that are effective in predicting the need for mechanical ventilation and mortality of patients.

Risk factors	In-hospital mortality		6-month mortality		The need for MV
	RR (%95 Cl)	P-value	HR (%95 Cl)	P-value	RR (%95 Cl)	P-value
Age	1.02 (1.01–1.03)	0.001	0.99 (0.98–1.00)	0.001	1.00 (0.99–1.01)	0.55
Sex	1.17 (0.85–1.62)	0.32	0.93 (0.82–1.05)	0.254	0.87 (0.63–1.23)	0.44
LOS in CC	0.98 (0.95–1.00)	0.19	1.00 (0.99–1.02)	0.782	1.01 (0.98–1.04)	0.30
qSOFA score	1.57 (1.23–1.99)	0.001*	0.94 (0.84–1.05)	0.239	0.59 (0.45–0.75)	0.001*
SOFA score	1.41 (1.33–1.49)	0.001	0.90 (0.87–0.92)	0.001	0.57 (0.53–0.61)	0.001
APACHE II	1.01 (0.99–1.04)	0.15	0.99 (0.98–1.01)	0.227	0.96 (0.94–0.99)	0.019
Lactate level	1.06 (1.01–1.12)	0.01	0.99 (0.96–1.02)	0.418	0.98 (0.92–1.03)	0.51

APACHE II, Acute Physiology and Chronic Health Evaluation; HR, Hazard Ratio - 6-month mortality (Cox Regression); LOS in CC, Length of stay in critical care; MV, Mechanical ventilation, Mortality (Log Regression); SOFA, Sequential Organ Failure Assessment; The need for mechanical ventilation (Log Regression); qSOFA, quick sequential organ failure assessment.

ROC analysis was performed for in-hospital mortality and prognostic scoring and lactate level. Performance characteristics (area under the curve, sensitivity, specificity) of qSOFA, SOFA, APACHE II score and lactate level for predicting mortality were calculated. The SOFA score appeared to be the most successful predictor of mortality. The cut-off for mortality using the ROC curve was ≥ 7 [sensitivity, 78.1%; specificity, 85.9%; area under the curve, 0.91; 95% confidence interval (CI), 0.89 to 0.92; P = 0.001]. qSOFA scoring also performed well. The cut-off value for mortality using the ROC curve was ≥ 2 [sensitivity, 42.5%; specificity, 93.9%; area under the curve, 0.83; 95% CI, 0.80-0.85; P = 0.001]. ROC analysis was performed for 6-month mortality, prognostic scores and lactate level. The performance characteristics (area under the curve, sensitivity, specificity) of qSOFA, SOFA, APACHE II score and lactate level in predicting 6-month mortality were calculated. The SOFA score appeared to be the most successful predictor of 6-month mortality. The cut-off for mortality using the ROC curve was ≥ 6 (sensitivity, 60.6%; specificity, 86.1%; area under the curve, 0.83; 95% CI, 0.82- 0.85; P = 0.001). qSOFA scoring was also notable for its high specificity. The cut-off value for mortality using the ROC curve was ≥ 2 (sensitivity, 26.9%; specificity, 96.9%; area under the curve, 0.78; 95% CI, 0.76–0.80; P = 0.001) Analyzes of APACHE II and lactate levels are also shown in the figure (Fig. 2 and Table 5).

Fig. 2.

 Receiver operating characteristic curve of qSOFA, SOFA, APACHE II scores and lactate level to predict in hospital and 6-month mortality.

Table 5.  Receiver operating characteristic curve of qSOFA, SOFA scores and lactate level to predict in hospital and 6-month mortality.

	AUC (95% CI)	P- value	Cutoff value	Sensitivity	Specificity	+ PV	–PV
SOFA score
In hospital mortality	0.91 (0.89–0.92)	0.001	≥ 7	%78.1	%85.9	%59	%93.8
6-month mortality	0.83 (0.82–0.85)	0.001	≥ 6	%60.6	%86.1	%77.2	%73.7
APACHE II score
In hospital mortality	0.84 (0.83–0.86)	0.001	≥ 22	%79.9	%73.5	%43.9	%93.4
6-month mortality	0.82 (0.80–0.84)	0.001	≥ 21	%67.1	%79.1	%71.5	%75.5
qSOFA score
In hospital mortality	0.83 (0.80–0.85)	0.001*	≥ 2	%42.5	%93.9	%64.6	%86.3
6-month mortalityv	0.78 (0.76–0.80)	0.001*	≥ 2	%26.9	%96.9	%87	%62.9
Lactate level
In hospital mortality	0.73 (0.70–0.76)	0.001	≥ 2.8	%67.9	%69.5	%36.6	%89.3
6-month mortality	0.65 (0.63–0.67)	0.001	≥ 2.7	%53.3	%69.8	%57.9	%65.7

APACHE, Acute Physiology and Chronic Health Evaluation; AUC, Area under the curve; PV, Predictive value; SOFA, Sequential Organ Failure Assessment; qSOFA, Quick sequential organ failure assessment.

Patients diagnosed with sepsis and septic shock constituted 23.9% of our patients. For this reason, we thought that statistical evaluation of qSOFA might yield results in favor of qSOFA. We performed statistics again on 1382 patients, excluding sepsis and septic shock patients. During critical care follow-up, 235 (17%) of our patients died, and at the end of 6 months, 515 (37.3%) of our patients died. Logistic regression and cox regression models were also repeated. SOFA [RR (95% Cl), 1.38 (1.29–1.48); P = 0.001], qSOFA [RR (95% Cl), 1.57 (1.19–2.08); P = 0.001] scores, age [RR (95% CI), 1.03 (1.01–1.04); P = 0.001] and lactate level [RR (95% Cl), 1.06 (1.00–1.12); P = 0.048] and in-hospital mortality were found to be statistically significantly associated. SOFA [RR (95% Cl), 1.07 (1.04–1.10); P = 0.001], qSOFA [RR (95% Cl), 1.17 (1.03–1.34); P = 0.02] scores and age [RR (95% CI), 1.03 (1.02–1.03); P = 0.001] and 6-month mortality were found to be statistically significantly associated. In the same way, ROC analysis was performed again. Similar results were obtained in the ROC analysis. Results of ROC analysis between SOFA, qSOFA, APACHE II and lactate values ​​and in-hospital mortality: AUC: 0.91, P = 0.001; AUC:0.85, P = 0.001; AUC:0.87, P = 0.001; AUC: 0.74, P = 0.001; respectively. Results of ROC analysis between SOFA, qSOFA, APACHE II and lactate values ​​and 6-month mortality: AUC: 0.85, P = 0.001; AUC:0.79, P = 0.001; AUC:0.84, P = 0.001; AUC: 0.65, P = 0.001; respectively. All of these results support our initial results.

DISCUSSION

Current sepsis guidelines recommend the use of the qSOFA score to diagnose sepsis in emergency departments.³ In addition, qSOFA score has been analyzed in recent studies as a prognostic indicator in many diseases, especially sepsis. However, the effect of qSOFA score on prognosis and mortality in CCU patients has not been sufficiently analyzed. In this study of 1816 patients, we aimed to analyze the effect of qSOFA score on mortality and prognosis in the CCU. Our results showed that qSOFA score may be a good predictor of CCU mortality [RR (95% Cl), 1.57 (1.23–1.99); P = 0.001]. When qSOFA score was ≥ 2, it had a sensitivity of 42.5%, specificity of 93.9% and negative predictive value of 86.3% for critical care mortality. (AUC: 0.83; 95% CI, 0.80-0.85; P = 0.001) It was also effective in determining the need for mechanical ventilation, suggesting that it may be a good indicator of prognosis [RR (95% CI), 0.59 (0.45–0.75); P = 0.001]. However, it was not found to be effective in predicting long-term mortality [HR (95% CI), 0.94 (0.84–1.05); P = 0.239].

The relationship between qSOFA and prognosis and mortality in sepsis and septic shock has been extensively studied in the literature. There are many studies on this topic. In a prospective study conducted by Oduncu et al.⁶ on 463 sepsis patients, the specificity for mortality when qSOFA ≥ 2 was found to be 91.3%, sensitivity 39.2%, AUC:0.758 (P < 0.0001). In the meta-analysis conducted by Toh Leong Tan et al.,⁷ which included 36 studies with patients outside the CCU, the sensitivity and specificity of qSOFA were 48% and 86% for short-term mortality and 32% and 92% for long-term mortality, respectively (P = 0.05). The results of these 2 studies are similar to our study. Askim et al.⁸ analyzed the performance of the qSOFA score in identifying severe sepsis and predicting sepsis-related mortality in a study of 1535 patients presenting to the emergency department with infectious clinical findings. In this observational, prospective cohort study, the qSOFA score failed to identify two-thirds of patients with severe sepsis. In addition, its low sensitivity for predicting 7-day and 30-day mortality suggested that the qSOFA score could not be used as a risk stratification tool. Yonathan Freund et al.⁹ conducted a multicentre prospective cohort study of 879 patients admitted to the emergency department with suspected infection to determine whether the qSOFA score was more effective in predicting in-hospital mortality than systemic inflammatory response syndrome (SIRS) and severe sepsis criteria. The qSOFA performed better than both SIRS and severe sepsis in predicting in-hospital mortality, with an area under the receiver operating curve (AUROC) of 0.80 (95% CI, 0.74–0.85) versus 0.65 (95% CI, 0.59–0.70) for both SIRS and severe sepsis (P < 0.001; incremental AUROC, 0.15; 95% CI, 0.09–0.22). Our study concluded that it may be a good predictor of in-hospital mortality and the need for mechanical ventilation.

Although there are not many studies in the literature analysing the relationship between qSOFA and prognosis and mortality in CCU patients, we examined the original articles and reviews that came to our attention as a result of our research. Shahla Siddiqui et al.¹⁰ analyzed the use of qSOFA score as a marker of mortality and CCU length of stay in sepsis patients admitted to the CCU. In the study of 58 patients, they concluded that the qSOFA score was more sensitive than SIRS and EWS scores in predicting CCU length of stay, and that the EWS score was more sensitive and specific than SIRS and qSOFA in predicting mortality. Jun-Yu Wang et al.¹¹ compared qSOFA, SOFA, APACHE II and MEDS (Mortality in Emergency Department Sepsis) scores for 28-day mortality in a study of 477 patients admitted to the emergency department with suspected infection and admitted to critical care. Although MEDS was superior, other scores gave similar results. (The area under the receiver operating characteristic curve of qSOFA was lower than that of MEDS (0.666 vs. 0.751; P < 0.05) and similar to that of SOFA (0.729) and APACHE II (0.732) in predicting 28-day mortality.) When the qSOFA score was ≥ 2, it had a sensitivity of 42.9%, specificity of 82.6%, and negative predictive value of 68.8% for 28-day mortality. In our study, the qSOFA score performed similarly to SOFA and APACHE II scores; when ≥ 2, it had similar sensitivity and specificity values as in the study by Jun-Yu Wang et al. Bodin Khwannimit et al.¹² concluded that the SOFA score was more effective in predicting in-hospital mortality than qSOFA and SIRS scores in a study of 2247 sepsis patients admitted to the CCU [SOFA (AUC 0.839), qSOFA (AUC 0.814, P = 0.003) and SIRS (AUC 0.587, P < 0.0001)]. In our study, the SOFA score was found to be superior.

In a study of 1641 pneumonia patients, Yun-Xia Chen et al.¹³ concluded that a qSOFA score ≥ 2 was more effective than CRB-65 (confusion, respiratory rate ≥ 30/minute, systolic blood pressure < 90 mmHg or diastolic blood pressure ≤ 60 mmHg, age ≥ 65 years) in determining the need for critical care admission and in predicting mortality. Sethi et al.¹⁴ in a study of 1002 CCU patients emphasised that the APACHE II score had a direct relationship with multimorbidity compared with the qSOFA score and that patients with multiple comorbidities had higher APACHE II scores. They concluded that the APACHE II score was a better indicator for predicting the need for CCU admission than the qSOFA score. In our study, the qSOFA score was more successful than the APACHE II score in predicting in-hospital mortality, and the APACHE II and qSOFA scores had very similar curves and values in the ROC analysis.

The need for mechanical ventilation in patients in critical care is one of the factors that negatively affects the prognosis.¹⁵ The results we obtained; It suggested that the qSOFA score could be effective in determining the need for mechanical ventilation and could also be a good indicator for prognosis [RR (95% CI), 0.59 (0.45–0.75); P = 0.001]. In the study conducted by Suresh et al.¹⁶ on 116 patients diagnosed with Covid 19 infection; Glasgow coma score, NEWS and qSOFA scores were found to be effective in predicting the need for mechanical ventilation [for qSOFA: RR (95% CI), 1.962 (1.038-3.708); P = 0.038]. Regina and colleagues¹⁷ created a multivariable regression model to determine the need for 14-day mechanical ventilation in 145 Covid 19 patients. We had 36 (24.8%) patients who required mechanical ventilation. Age, male gender, qSOFA score ≥ 2, bilateral lung infiltration, CRP of 40 mg/l or greater were found to be effective in predicting the need for mechanical ventilation. [qSOFA score ≥ 2 (OR 7.24, 95% CI 1.64–32.03, P = 0.009)]. Studies in the literature support our results.

We have several limitations in our study. One of these is that our study is single-centered. Another limitation is that our patients’ APACHE II scores may be high due to various chronic diseases. Another condition is that the mortality cut-off value of the SOFA score is ≥ 7. This value is low compared to the literature. When the patient characteristics in Table-2 are examined, it will be seen that there are patient groups with a relatively better course, such as many poisonings and diabetic ketoacidosis, in our patient groups. Due to this situation, we think that the average SOFA score and the cut-off SOFA score for mortality are lower.

We work as an emergency medicine and critical care clinic. Our critical care unit is a type of intensive care unit where patients who apply to the emergency department and need intensive care are admitted after the necessary procedures are performed. All kinds of emergency patients such as sepsis, cardiac arrest, acute myocardial infarction, poisonings, diabetic emergencies, etc. are admitted to our critical care unit. Patients who are followed up on a more chronic basis, such as postoperative patients admitted to other intensive care units, acute exacerbations of chronic diseases, and palliative care patients, are not admitted to our critical care unit. Therefore, our patient population is an acute emergency patient group and the results of this study are more suitable for intensive care units such as emergency critical care units. We cannot say that it is generally applicable to all intensive care units. This is the underlying reason why qSOFA is preferred over APACHE II. Since we are dealing with more acute patient groups, we think qSOFA is a more practical and easy method. In addition, since parameters such as the chronic disease tab and laboratory results in APACHE scoring are not available in qSOFA, we think that it is more useful for emergency critical care since the decision is made with the patient’s first vital signs.

In conclusion, we believe that the qSOFA score can be used as a marker for in-hospital mortality and prognosis in critical care patients. Especially in cases where the qSOFA score is ≥ 2, it provides valuable information regarding mortality and prognosis. When CCU prognostic scores such as SOFA and APACHE II are evaluated together with the qSOFA score, much more valuable predictions can be made. However, it is clear that more studies are needed to make a definitive judgement about the prediction of long-term mortality.