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Original Article
Infection Prognostic value of novel indices combining Shock Index, Reverse Shock Index, age, and oxygen saturation for predicting mortality in COVID-19 patients in Iran at emergency department triage: a cross-sectional study
Acute and Critical Care 2025;40(3):425-434.
DOI: https://doi.org/10.4266/acc.005040
Published online: August 29, 2025

1Department of Emergency Medicine, Kerman University of Medical Sciences, Kerman, Iran

2Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

Corresponding author: Mehdi Torabi Department of Emergency Medicine, Kerman University of Medical Sciences, Gharani Ave, Kerman 7613747181, Iran Tel: +98-91-3199-2016, Fax: +98-343-2474-638 Email: mtorabi1390@yahoo.com
• Received: December 28, 2024   • Revised: June 18, 2025   • Accepted: July 4, 2025

© 2025 The Korean Society of Critical Care Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Background
    The objective of the study was to investigate the role of the Shock Index (SI), the Reverse Shock Index (RSI) along with oxygen saturation in predicting mortality in coronavirus disease 2019 (COVID-19).
  • Methods
    This cross-sectional study was conducted at an academic hospital over a period of 6 months and involved patients over the age of 18 who had been diagnosed with COVID-19 via positive polymerase chain reaction tests. The data were recorded anonymously using a checklist. The study focused on indices such as the SI and RSI, both alone and in conjunction with age and oxygen saturation, to predict hospital mortality. Statistical analysis was conducted using SPSS software.
  • Results
    The study involved 500 COVID-19 patients with a 14.4% mortality rate. Key differences were found between survival and mortality groups in terms of age, vital signs except diastolic blood pressure, length of stay, and a series of laboratory tests. Logistic regression showed gender, oxygen saturation, hemoglobin, direct bilirubin, lactate dehydrogenase, D-dimer, and Age SI/oxygen saturation (SpO2) and RSI×SpO2/Age indices significantly associated with hospital mortality. Receiver operating characteristic analysis indicated Age SI/SpO2 and RSI×SpO2/Age as effective mortality predictors, exhibiting an area under the curve of 0.80 and achieving a sensitivity, specificity, and accuracy of over 70%.
  • Conclusions
    The combination of SI, the RSI along with hypoxia, and age has been identified as a potentially more significant role in ruling out hospital mortality in COVID-19 patients than vital signs alone, given the established role of hypoxia as a major risk factor in such cases.
  • Key Words: COVID-19; mortality; oxygen saturation; vital signs
Coronavirus disease 2019 (COVID-19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused a high mortality in a pandemic. Meanwhile, emergency departments (EDs) were heavily involved in this outbreak. Therefore, rapid determination of the assignment of patients in the ED is of great importance [1,2]. Triage systems were implemented to prioritize patients based on the severity of their symptoms and the likelihood of requiring intensive care. This approach helped in managing the overwhelming number of patients and ensuring that those in critical condition received timely medical attention [3,4].
The role of vital signs in triage in determining the prognosis of critically ill patients referred to the ED is very important, although their accuracy in predicting the outcome of patients referred to the hospital can vary [5,6]. The utilization of these vital signs has led to the development of indices such as the Shock Index (SI), the reverse SI, and the age SI. The SI, defined as the ratio of heart rate to systolic blood pressure, the Reverse Shock Index (RSI), defined as the ratio of systolic blood pressure to heart rate, and the Age SI, defined as the SI multiplied by age, have been shown to be valuable predictors of mortality in patients [7-10]. These indices played a more significant key role in determining the prognosis of patients compared to vital signs. However, it seems that these indices may have more certainty in predicting the prognosis of patients along with other factors related to the disease. It has been seen that the SI, along with the Glasgow Coma Scale (GCS), can be very helpful in predicting the mortality of trauma patients, which is probably due to the role of GCS in these patients. Several studies were conducted in this field and confirmed that by adding GCS to these indices, the certainty of the predictive role of these indices can be increased [11,12].
Hypoxia, characterized by low oxygen saturation, is a critical factor in assessing the severity and prognosis of COVID-19 patients upon arrival at the ED triage. The virus primarily targets the respiratory system, leading to complications such as pneumonia and acute respiratory distress syndrome, which can result in significant hypoxemia [13]. Monitoring oxygen saturation is essential for identifying patients at risk of worsen outcomes and determining the need for interventions such as supplemental oxygen or mechanical ventilation. Studies have shown that early detection and management of hypoxia can improve patient outcomes by preventing the progression to more severe respiratory failure. Therefore, assessing oxygen saturation levels is a vital component of the triage process in emergency settings during the COVID-19 pandemic [14].
Although the prognostic role of these indices has been seen in COVID-19 patients, but considering the respiratory involvement in COVID-19 patients, it is possible that the value of the predictive role of these indices can be increased by using a combination of oxygen saturation in these indices. With these interpretations, we created several new indices using the SI and RSI along with oxygen saturation. Accordingly, the aim of the study was to investigate the prognostic value of the SI and RSI along with oxygen saturation for mortality prediction in COVID-19 patients presenting to the ED triage.
The study was approved by the Research Ethics Committee of Kerman. University of Medical Sciences (IR.KMU.AH.REC.1401.270). The collection of data was conducted without the requirement for informed consent as the data collection forms were completed anonymously and the results were disseminated without any reference to the participants' identities.
Study Design and Setting
This cross-sectional study was conducted on patients diagnosed with SARS-CoV-2 who were referred to the ED of Afzalipour Academic Hospital, located in the southeast of Iran, Kerman, during a 6-month period from April to October 2021.
Patient Selection
The study included all patients aged 18 years or older diagnosed with SARS-CoV-2, confirmed by a positive oropharyngeal or nasopharyngeal polymerase chain reaction test. Patients under the age of 18 with a negative test result, and pregnant patients and incomplete records were excluded from the study (Figure 1).
Data Extraction
The study was conducted as a census, and data collection was carried out from the records by registering in a checklist. The checklist encompassed variables including age, gender, vital signs, length of stay (LOS), laboratory tests, indices, and patient outcome. The vital signs of patients at the time of admission, as documented in the ED triage, were retrieved from the records. The laboratory tests conducted during the patient's stay were also retrieved from the records. The indices encompassed the SI (ratio of heart rate to systolic blood pressure), age SI (product of age multiplied by SI), ratio of SI to oxygen saturation, ratio of age SI to oxygen saturation, RSI (ratio of systolic blood pressure to heart rate), ratio of RSI to age, RSI multiplied by oxygen saturation, RSI multiplied by oxygen saturation divided to age. These indices were calculated by the software after extracting vital signs from the records.
Outcome Measured
The study's primary outcome was defined as either hospital mortality or survival. The secondary objective was to examine the predictive value of other variables especially new indices for hospital mortality.
Statistical Analysis
The data were analyzed using SPSS software version 27.0 (IBM Corp.). The qualitative variables were expressed as frequency (percentage). For data that conformed to a normal distribution, we presented the data as the mean±standard deviation of the data. For data that exhibited a non-normal distribution, we presented the data as the median and its interquartile range. The chi-square test was employed to assess the relationship between the dichotomous qualitative variable and other qualitative variables. In order to analyze the difference between quantitative variables and dichotomous qualitative variables, the Mann-Whitney U-test was used in the case of non-normal distribution, and the Student t-test was used in the case of parametric conditions. A P-value of less than 0.05 was considered statistically significant.
Univariate logistic regression was then used to examine the association between patient outcomes and variables. Variables with P-values less than 0.2 were entered into the multivariate model and analyzed using the backward elimination method [15]. Odds ratios (ORs) and confidence intervals were subsequently calculated to assess the intensity of the association between variables and patient outcomes. Finally, receiver operating characteristic (ROC) curves were generated for indices that demonstrated a significant relationship with hospital mortality, and at the optimal cut-off, the area under the curve (AUC), sensitivity, specificity, predictive value, likelihood ratio, and accuracy were calculated.
The patient demographic characteristics, vital signs, laboratory tests, and indices of 500 patients with confirmed cases of COVID-19 patients are shown in Table 1. The mortality rate in the hospital was documented to be 72 patients (14.4%). The findings were also reported separately for the survival and mortality groups. The mean age of the patients included in the study was 51±1 years, with a median age of 47 years. Furthermore, the distribution of patients across age groups revealed that 238 (47.6%) were male and 262 (52.4%) were female. A non-significant difference was observed between the two groups in terms of gender (P=0.14), while a significant difference was identified between the two groups in terms of age (P<0.0001). While the number of female participants exceeded that of males, the mortality rate was higher among males (55.6% vs. 44.4%). An examination of the vital signs revealed a statistically significant difference between the two groups with the exception of diastolic blood pressure (P<0.05). Furthermore, a statistically significant difference was observed in the LOS leading to death, with a longer duration observed in the deceased patients compared to those who survived (P<0.0001). As illustrated in Table 1, a statistically significant difference was observed in laboratory test results between the two patient groups. This discrepancy was evident in parameters such as WBC, hemoglobin, blood urea nitrogen (BUN), creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), bilirubin, blood glucose, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR) and D-dimer levels. The magnitude of this difference was statistically significant at the P<0.05 level. Subsequent to the extraction of indices from vital signs, a comparative analysis was conducted to ascertain the difference in these indices between survival and mortality patients. While we had hypothesized that this difference would be significant in terms of SI and RSI between the two groups of patients, this was not the case. However, when examining other indices, such as Age SI, SI/oxygen saturation (SpO2), Age SI/SpO2, RSI/Age, RSI×SpO2, and RSI×SpO2/Age, significant differences were observed between the two groups with patient mortality (P<0.0001).
To assess the strength of the association between variables and patient outcomes, i.e., mortality, logistic regression and OR analyses were employed. Univariate analysis revealed a significant relationship between the variables of age, systolic blood pressure, heart rate, respiratory rate, oxygen saturation, LOS, laboratory tests (WBC, hemoglobin, BUN, AST, bilirubin, blood glucose, LDH, ESR and D-dimer) and the indices (Age SI, SI/SpO2, Age SI/SpO2, RSI/Age, RSI, RSI×SpO2, and RSI×SpO2/Age) with mortality. Subsequently, the variables with P-values less than 0.2 were entered into the multivariate regression model and analyzed using the backward elimination method. This analysis revealed that only the variables of gender, oxygen saturation, hemoglobin, direct bilirubin, LDH, D-dimer, and the two indices (Age SI/SpO2 and RSI×SpO2/Age) exhibited a statistically significant relationship with the patients' outcomes (Table 2).
Finally, the ROC curve for the two indices (Age SI/SpO2 and RSI×SpO2/Age) was used to determine their predictive role (Figures 2 and 3). In the context of mortality prediction, both Age SI/SpO2 at a cutoff of 0.52 and RSI×SpO2/Age at a cutoff of 1.9 were identified as effective predictors, exhibiting an AUC of 0.8 and achieving a sensitivity, specificity, and accuracy of over 70%. The OR of the Age SI /SpO2 index was 8.23, indicating that for every unit increase from the cutoff of 0.52, the risk of mortality in patients increased by more than 8 times. The OR of RSI×SpO2/Age at a cutoff of 1.9 was also reported to be 0.12, indicating that with a one-unit increase, the risk of mortality decreased by 88% (Table 3 and 4).
The prognostic significance of shock indices in critically ill patients is well established. In patients with SARS-CoV-2, given the involvement of the lung as a target organ, hypoxia, along with shock indices, especially the Age SI and the RSI/Age, can provide a more reliable index than other shock indices in predicting hospital mortality. SpO2 (oxygen saturation) is a critical biomarker in COVID-19, as hypoxia is strongly associated with disease severity and mortality. Studies have shown that low SpO2 levels, particularly in the context of “silent hypoxia,” are prevalent in COVID-19 patients and correlate with higher risks of intensive care unit (ICU) admission and in-hospital mortality. For instance, research has identified that SpO2 levels dropping to 70%–80% in COVID-19 patients, even without overt respiratory distress, are linked to severe outcomes [16,17]. Also, hypoxia in patients with SARS-CoV-2 infection has been identified as a risk factor for progression to severe and critical stages of the disease [18]. The presence of silent hypoxia has been observed to exacerbate the risk of harm to these patients [19]. Furthermore, hypoxia has been identified as a pivotal risk factor in determining the prognosis of patients, with the capacity to predict hospital mortality in isolation [20]. Consequently, hypoxia is recognized as a significant risk factor for these patients, as demonstrated in this study.
Age is a well-established risk factor for COVID-19 mortality, with older patients exhibiting higher rates of severe outcomes due to comorbidities and reduced physiological reserve In-hospital mortality increased markedly with increasing age. A sample of adults hospitalized with laboratory-confirmed COVID-19 with older age were associated with higher risks of ICU admission and in-hospital mortality [21,22]. This study showed that in patients with SARS-CoV-2, hypoxia combined with increasing Age, SI and RSI plays a significant role in ruling out hospital mortality.
The assessment of mortality risk in hospitalized patients with COVD-19 is imperative for the timely administration of medical interventions. The development of rapid and accurate triage tools can facilitate the prediction of high-risk patient conditions with greater efficiency and precision. Concomitantly, the role of shock indices in determining the prognosis of patients with COVD-19 may prove beneficial. In a study, Avci and Doğanay [23] compared the SI with other indices in terms of hospital mortality of patients with COVD-19 and concluded that the SI has more value in determining patient mortality than other indices such as the Age SI, although they also confirmed the prognostic role of other indices. However, a contradictory study by Rensen et al. [24] failed to demonstrate the usefulness of the SI in predicting hospital mortality or identifying high-risk patients in a cohort study conducted on patients with confirmed cases of the disease. In a meta-analysis by Alsagaff et al. [25], the role of the SI in predicting hospital mortality was considered effective, although the recommendation was to conduct larger studies. The prognostic significance of hypoxia in patients with SARS-CoV-2 infection underscores the potential value of integrating oxygenation metrics with other indices in prognostication. Ates et al. [26] investigated the prognostic role of Respiratory Rate Oxygenation along with other shock indices in predicting mortality in patients with COVD-19. The study noted that this index, in contrast to the SI, possesses a more substantial prognostic significance. Additionally, the study underscored the pivotal role of age in this context. Consequently, the integration of the SI with oxygen saturation and age may enhance the diagnostic efficacy for critical illnesses in patients [26]. In support of this assertion, Hsieh et al. [27] in their study found that the role of Age SI/oxygen saturation and Age SI was more effective than SI alone in predicting hospital mortality and the need for ICU admission in patients with confirmed cases of severe acute respiratory syndrome caused by the novel coronavirus. In a separate study by Oh and Lee [28], the prognostic significance of shock indices in patients with SARS-CoV-2 was examined. It was observed that the combination of SI/oxygen saturation and Age SI exhibited a more robust predictive capability for hospital mortality compared to SI alone In contrast, this study suggests that, given the high negative predictive value, Age SI/SpO2 may be more useful for ruling out mortality risk rather than definitively identifying high-risk patients.
The RSI is another index whose prognostic role in predicting mortality in patients with SARS-CoV-2 infection may be effective. This index, which is used to assess hemodynamics in patients, can enhance the accuracy of predicting the condition of critically ill patients when combined with other factors, such as the GCS. In their study on patients with COVD-19, Wu et al. [29] investigated the prognostic role of the RSI in combination with GCS in these patients. Their findings indicated that a straightforward calculation method can be employed to reliably predict patient hospitalization and mortality. In a separate study, Matsuda et al. [30] reported that the prognostic role of this index in sepsis conditions is superior to that of the SI. However, this index appears to be more advantageous in trauma conditions [31-33]. Given the predominant role of hypoxia in patients with SARS caused by SARS-CoV-2 compared to the GCS, we investigated the prognostic role of oxygen saturation along with the RSI and age in these patients. In this study, the relatively low positive predictive value (PPV; approximately 30%) RSI×SpO₂/Age indicates a high rate of false positives, suggesting these indices are better suited for ruling out mortality risk than definitively identifying high-risk patients.
It is imperative to acknowledge the limitations inherent to this study. The retrospective and single-center nature of the study were unavoidable limitations. Additionally, the exclusion of patients under the age of 18, and pregnant patients from the study constitutes a significant limitation. Additionally, challenges arose during the review of archival files, largely due to deficiencies inherent in the documentation. The low PPV (approximately 30%) of the indices limits their specificity for identifying high-risk patients, potentially leading to over-triage in busy ED settings. This underscores the need for integration with other diagnostic tools and validation in diverse cohorts to refine thresholds and improve predictive accuracy.
The utilization of vital signs-derived indices within the ED triage setting may prove efficacious in predicting mortality among patients diagnosed with SARS-CoV-2. The combination of SI or RSI along with hypoxia, and age have been identified as potentially more significant role in ruling out hospital mortality in patients with this condition than vital signs alone, given the established role of hypoxia as a major risk factor in such cases. Future studies should validate the prognostic utility of Age SI/SpO₂ and RSI×SpO₂/Age in multicenter cohorts to ensure generalizability across diverse populations.
▪ The role of vital signs in triage in determining the prognosis of coronavirus disease 2019 (COVID-19) patients is crucial.
▪ The combination of Shock Index or Reverse Shock Index along with hypoxia and age have been identified as potentially more effective prognostic indicators in predicting hospital mortality in COVID-19 patients.

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

This study was supported by Clinical Research Center of Afzalipour Academic Hospital, Kerman University of Medical Science, Kerman, Iran.

ACKNOWLEDGMENTS

None.

AUTHOR CONTRIBUTIONS

Conceptualization: MT, AN, NNB. Methodology: MT, NNB, MM. Formal analysis: MT, MM. Data curation: AN, Visualization: MT, AN, NNB, MM. Project administration: MT, AN, NNB, MM. Funding acquisition: MT, AN, NNB, MM. Writing - original draft: MT. Writing - review & editing: MT, MM. All authors read and agreed to the published version of the manuscript.

Figure 1.
Flowchart showing enrollment of patients.
acc-005040f1.jpg
Figure 2.
Receiver operating characteristic (ROC) curve for Age SI/SpO2 in predicting mortality in coronavirus disease 2019 (COVID-19). SI: Shock Index; SpO2: oxygen saturation.
acc-005040f2.jpg
Figure 3.
Receiver operating characteristic (ROC) curve for RSI×SpO2/Age in predicting mortality in coronavirus disease 2019 (COVID-19). RSI: Revere Shock Index; SpO2: oxygen saturation.
acc-005040f3.jpg
Table 1.
Characteristics, vital signs, laboratory data, and indices in COVID-19 patients
Variable Total patients (n=500)
 Survival (n=428)
 Mortality (n=72)
 P-value
Mean±SD Median (IQR) Mean±SD Median (IQR) Mean±SD Median (IQR)
Characteristics
 Age (yr) 51±1 47 (42.0–61.0) 49±17 46 (32.5–59.5) 64±20 72 (55.5–88.5) <0.0001
 Sex, no. (%) 0.14
  Male 238 (47.6) 198 (46.3) 40 (55.6)
  Female 262 (52.4) 230 (53.7) 32 (44.4)
 Vital sign
  SBP (mm Hg) 116.9±13.6 120 (112.5–127.5) 116.4±13.3 115 (107.5–122.5) 120.1±15.4 120 (110.0–130.0) 0.03
  DBP (mm Hg) 74.3±10.0 75 (70.0–80.0) 74.5±10.1 75 (70.0–80.0) 73.4±9.1 70 (65.0–75.0) 0.36
  Heart rate (beats/min) 95.1±16.6 92 (81.5–102.5) 94.6±16.7 92 (83.5–100.5) 98.6±15.4 98 (87.0–109.0) 0.01
  Respiratory rate (/min) 19.9±2.7 20 (18.0–22.0) 19.8±2.8 20 (18.5–21.5) 20.8±2.3 21 (20.0–22.0) <0.0001
  SpO2 (%) 87.2±5.1 88 (83.7– 90.6) 88.1±4.3 89 (86.5–91.5) 81.8±5.9 83 (78.5–87.5) <0.0001
  LOS (day) 7.0±5.8 5 (2.0–8.0) 6.5±5.3 5 (3.5–6.5) 10.2±7.6 8 (3.5–12.5) <0.0001
Laboratory data
 WBC (103 cells/mm3) 7.6±5.2 6.2 (4.15–8.25) 7.1±4.1 6.1 (4.35–7.85) 10.6±9.0 8.3 (5.2–11.4) <0.0001
 Hemoglobin (g/dl) 14.3±2.2 14.2 (12.8–15.6) 14.4±2.1 14.3 (13.1–15.5) 13.5±2.8 13.2 (11.0–15.4) 0.02
 Platelet (103/mm3) 196.6±85.3 179 (125.5–232.5) 199.0±86. 5 180.0 (128.0–232.0) 181.2±76.5 178 (89.0–267.0) 0.79
 BUN (mg/dl) 45.8±34.5 40 (30.0–50.0) 43.4±33.2 38 (29.0–47.0) 60.4±38.4 52 (42.5–61.5) <0.0001
 Creatinine (mg/dl) 1.1±0.7 1 (0.8–1.2) 1.1±0.8 1 (0.85–1.15) 1.19±0.3 1.2 (0.9–1.5) 0.001
 AST (U/L) 54.6±40.5 42 (25.5–58.5) 51.3±39.2 37 (22.0–52.0) 75.1±43.1 62 (42.0–82.0) <0.0001
 ALT (U/L) 57.7±93.1 35 (18.0–52.0) 57.4±97.7 32 (16.0–48.0) 60.0±57.2 42 (21.0–63.0) 0.02
 Bilirubin total (mg/dl) 1.0±0.4 0.9 (0.7–1.1) 0.9±0.4 0.9 (0.7–1.1) 1.1±0.4 1.1 (0.85–1.35) <0.0001
 Bilirubin direct (mg/dl) 0.4±0.2 0.3 (0.2–0.5) 0.3±0.2 0.3 (0.2–0.4) 0.5±0.3 0.5 (0.35–0.65) <0.0001
 Blood glucose (mg/dl) 138.9±78.5 109 (69.5–148.5) 135.0±74.3 108 (81.0–135.0) 163.0±98.2 135 (90.5–179.5) 0.05
 LDH (U/L) 679.2±373.0 621 (434.5–807.5) 630.4±352.1 585 (378.5–791.5) 983.1±357.5 894 (723.5–1064.5) <0.0001
 ESR (mm/hr) 36.5±43.8 26 (10.5–41.5) 34.3±23.0 26 (11.0–41.0) 50.1±102.4 20 (10.0–30.0) 0.02
 CRP (mg/L) 25.4±23.3 15 (3.3–26.7) 25.0±22.7 15 (6.0–24.0) 28.3±26.4 15 (0.0–30.0) 0.11
 D-dimer (μg/ml) 0.9±2.0 0.4 (0.3–0.5) 0.6±1.2 0.4 (0.35–0.45) 2.49±4.0 0.5 (0.25–0.75) <0.0001
Indices
 Shock Index 0.8±0.2 0.8 (0.7–0.9) 0.8±0.2 0.8 (0.7–0.9) 0.8±0.2 0.8 (0.7–1.0) 0.19
 Age SI 41.4±18.3 37.7 (28.5–47.0) 39.6±17.8 36.2 (26.6–45.8) 59.5±17.8 49 (37.3–60.8) <0.0001
 SI/SpO2 0.0±0.0 0.0 (0.0–0.0) 0.0±0.0 0.0 (0.0–0.0) 0.01±0.0 0.0 (0.0–0.0) <0.0001
 Age SI/SpO2 0.5±0.2 0.4 (0.3–0.5) 0.5±0.2 0.4 (0.3–0.5) 0.6±0.2 0.6 (0.5–0.7) <0.0001
 RSI 1.3±0.3 1.25 (1.1–1.4) 1.3±0.3 1.3 (1.2–1.5) 1.3±0.3 1.3 (1.1–1.6) 0.19
 RSI/Age 0.02±0.01 0.02 (0.01–0.02) 0.02±0.01 0.02 (0.01–0.02) 0.02±0.00 0.02 (0.01–0.02) <0.0001
 RSI×SpO2 110.5±23.8 107.6 (95.7–119.6) 111.8±23.8 108.8 (93.2–124.4) 102.1±22.2 100.8 (82.9–118.8) <0.0001
 RSI×SpO2/Age 2.4±1.0 2.3 (1.8–2.8) 2. 6±1.0 2.4 (1.7–3.1) 1.7±0.5 1.7 (1.4–2.1) <0.0001

COVID-19: coronavirus disease 2019; SD: standard deviation; IQR: interquartile range; SBP: systolic blood pressure; DBP: diastolic blood pressure; SpO2: oxygen saturation; LOS: length of stay; WBC: white blood cell count; BUN: blood urea nitrogen; AST: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; ESR: erythrocyte sedimentation rate; CRP: c-reactive protein; SI: Shock Index; RSI: Revere Shock Index.

Table 2.
Univariate and multivariate regression analysis of variables according to their association with mortality in COVID-19 patients
Variable Univariate logistic regression P-value Multivariate logistic regression P-value
Age 1.05 (1.03–1.06) <0.001
Sex 0.14 <0.001
 Female 0.68 (0.41–1.13) 0.13 (0.04–0.38)
 Male Reference Reference
SBP 1.01 (1.00–1.003) 0.02
DBP 0.98 (0.96–1.01) 0.32
Heart rate 1.02 (1.00–1.03) 0.002
Respiratory rate 1.19 (1.10–1.29) <0.001
SpO2 0.79 (0.75–0.84) <0.001 0.82 (0.75–0.89) <0.001
LOS 1.08 (1.04–1.12) <0.001
WBC 1.10 (1.05–1.15) <0.001
Hemoglobin 0.83 (0.74–0.93) <0.001 0.59 (0.47–0.73) <0.001
Platelet 1.00 (0.99–1.00) 0.82
BUN 1.01 (1.00–1.01) 0.001
Creatinine 1.13 (0.85–1.50) 0.38
AST 1.01 (1.00–1.01) <0.001
ALT 1.00 (0.99–1.00) 0.97
Bilirubin total 3.00 (1.74–5.15) <0.001
Bilirubin direct 16.47 (6.21–43.68) <0.001 21.37 (4.78–95.61) <0.001
Blood sugar 1.00 (1.00–1.00) 0.01
LDH 1.00 (1.00–1.05) <0.001 1.003 (1.002–1.005) <0.001
ESR 1.00 (1.00–1.01) <0.001
CRP 1.00 (0.99–1.01) 0.24
D-imer 1.35 (1.19–1.54) <0.001 1.32 (1.06–1.63) 0.01
SI 2.13 (0.74–6.11) 0.16
Age SI 1.03 (1.02–1.04) <0.001
SI/SpO2 1.11 (1.10–1.12) 0.001
Age SI/SpO2 17.15 (6.42–45.83) <0.001 0.01 (0.00–0.08) <0.001
RSI 0.54 (0.21–1.43) <0.001
RSI/Age 0.95 (0.88–1.11) <0.001
RSI×SpO2 0.97 (0.96–0.98) <0.001
RSI×SpO2/Age 0.19 (0.12–0.30) <0.001 0.01 (0.00–0.05) <0.001

Values are presented as odds ratio (95% CI).

COVID-19: coronavirus disease 2019; SBP: systolic blood pressure; DBP: diastolic blood pressure; SpO2: oxygen saturation; LOS: length of stay; WBC: white blood cell count; BUN: blood urea nitrogen; AST: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; ESR: erythrocyte sedimentation rate; CRP: c-reactive protein; SI: Shock Index; RSI: Revere Shock Index.

Table 3.
Predictive value of Age SI/SpO₂ for mortality in COVID-19 patients (cutoff=0.52)
AUC Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR (+) LR (–) Accuracy (%) OR (95% CI)
Age SI/SpO2 0.80 75 73.3 32.1 94.6 2.81 0.34 73.6 8.23 (4.63–14.63)

SI: Shock Index; SpO2: oxygen saturation; COVID-19: coronavirus disease 2019; AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value; LR: likelihood ratio; OR: odds ratio.

Table 4.
Predictive value of RSI×SpO₂/Age for mortality in COVID-19 patients (cutoff=1.90)
AUC Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR (+) LR (–) Accuracy (%) OR (95% CI)
RSI×SpO2/Age 0.80 73.3 75 33 94.4 2.93 0.36 74.8 0.12 (0.06–0.21)

RSI: Revere Shock Index; SpO2: oxygen saturation; COVID-19: coronavirus disease 2019; AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value; LR: likelihood ratio; OR: odds ratio.

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        Prognostic value of novel indices combining Shock Index, Reverse Shock Index, age, and oxygen saturation for predicting mortality in COVID-19 patients in Iran at emergency department triage: a cross-sectional study
        Acute Crit Care. 2025;40(3):425-434.   Published online August 29, 2025
        DOI: https://doi.org/10.4266/acc.005040
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      Prognostic value of novel indices combining Shock Index, Reverse Shock Index, age, and oxygen saturation for predicting mortality in COVID-19 patients in Iran at emergency department triage: a cross-sectional study
      Image Image Image
      Figure 1. Flowchart showing enrollment of patients.
      Figure 2. Receiver operating characteristic (ROC) curve for Age SI/SpO2 in predicting mortality in coronavirus disease 2019 (COVID-19). SI: Shock Index; SpO2: oxygen saturation.
      Figure 3. Receiver operating characteristic (ROC) curve for RSI×SpO2/Age in predicting mortality in coronavirus disease 2019 (COVID-19). RSI: Revere Shock Index; SpO2: oxygen saturation.

      Figure 1.

      Figure 2.

      Figure 3.

      Prognostic value of novel indices combining Shock Index, Reverse Shock Index, age, and oxygen saturation for predicting mortality in COVID-19 patients in Iran at emergency department triage: a cross-sectional study
      Variable Total patients (n=500)
      		 Survival (n=428)
      		 Mortality (n=72)
      		 P-value
      Mean±SD Median (IQR) Mean±SD Median (IQR) Mean±SD Median (IQR)
      Characteristics
       Age (yr) 51±1 47 (42.0–61.0) 49±17 46 (32.5–59.5) 64±20 72 (55.5–88.5) <0.0001
       Sex, no. (%) 0.14
        Male 238 (47.6) 198 (46.3) 40 (55.6)
        Female 262 (52.4) 230 (53.7) 32 (44.4)
       Vital sign
        SBP (mm Hg) 116.9±13.6 120 (112.5–127.5) 116.4±13.3 115 (107.5–122.5) 120.1±15.4 120 (110.0–130.0) 0.03
        DBP (mm Hg) 74.3±10.0 75 (70.0–80.0) 74.5±10.1 75 (70.0–80.0) 73.4±9.1 70 (65.0–75.0) 0.36
        Heart rate (beats/min) 95.1±16.6 92 (81.5–102.5) 94.6±16.7 92 (83.5–100.5) 98.6±15.4 98 (87.0–109.0) 0.01
        Respiratory rate (/min) 19.9±2.7 20 (18.0–22.0) 19.8±2.8 20 (18.5–21.5) 20.8±2.3 21 (20.0–22.0) <0.0001
        SpO2 (%) 87.2±5.1 88 (83.7– 90.6) 88.1±4.3 89 (86.5–91.5) 81.8±5.9 83 (78.5–87.5) <0.0001
        LOS (day) 7.0±5.8 5 (2.0–8.0) 6.5±5.3 5 (3.5–6.5) 10.2±7.6 8 (3.5–12.5) <0.0001
      Laboratory data
       WBC (103 cells/mm3) 7.6±5.2 6.2 (4.15–8.25) 7.1±4.1 6.1 (4.35–7.85) 10.6±9.0 8.3 (5.2–11.4) <0.0001
       Hemoglobin (g/dl) 14.3±2.2 14.2 (12.8–15.6) 14.4±2.1 14.3 (13.1–15.5) 13.5±2.8 13.2 (11.0–15.4) 0.02
       Platelet (103/mm3) 196.6±85.3 179 (125.5–232.5) 199.0±86. 5 180.0 (128.0–232.0) 181.2±76.5 178 (89.0–267.0) 0.79
       BUN (mg/dl) 45.8±34.5 40 (30.0–50.0) 43.4±33.2 38 (29.0–47.0) 60.4±38.4 52 (42.5–61.5) <0.0001
       Creatinine (mg/dl) 1.1±0.7 1 (0.8–1.2) 1.1±0.8 1 (0.85–1.15) 1.19±0.3 1.2 (0.9–1.5) 0.001
       AST (U/L) 54.6±40.5 42 (25.5–58.5) 51.3±39.2 37 (22.0–52.0) 75.1±43.1 62 (42.0–82.0) <0.0001
       ALT (U/L) 57.7±93.1 35 (18.0–52.0) 57.4±97.7 32 (16.0–48.0) 60.0±57.2 42 (21.0–63.0) 0.02
       Bilirubin total (mg/dl) 1.0±0.4 0.9 (0.7–1.1) 0.9±0.4 0.9 (0.7–1.1) 1.1±0.4 1.1 (0.85–1.35) <0.0001
       Bilirubin direct (mg/dl) 0.4±0.2 0.3 (0.2–0.5) 0.3±0.2 0.3 (0.2–0.4) 0.5±0.3 0.5 (0.35–0.65) <0.0001
       Blood glucose (mg/dl) 138.9±78.5 109 (69.5–148.5) 135.0±74.3 108 (81.0–135.0) 163.0±98.2 135 (90.5–179.5) 0.05
       LDH (U/L) 679.2±373.0 621 (434.5–807.5) 630.4±352.1 585 (378.5–791.5) 983.1±357.5 894 (723.5–1064.5) <0.0001
       ESR (mm/hr) 36.5±43.8 26 (10.5–41.5) 34.3±23.0 26 (11.0–41.0) 50.1±102.4 20 (10.0–30.0) 0.02
       CRP (mg/L) 25.4±23.3 15 (3.3–26.7) 25.0±22.7 15 (6.0–24.0) 28.3±26.4 15 (0.0–30.0) 0.11
       D-dimer (μg/ml) 0.9±2.0 0.4 (0.3–0.5) 0.6±1.2 0.4 (0.35–0.45) 2.49±4.0 0.5 (0.25–0.75) <0.0001
      Indices
       Shock Index 0.8±0.2 0.8 (0.7–0.9) 0.8±0.2 0.8 (0.7–0.9) 0.8±0.2 0.8 (0.7–1.0) 0.19
       Age SI 41.4±18.3 37.7 (28.5–47.0) 39.6±17.8 36.2 (26.6–45.8) 59.5±17.8 49 (37.3–60.8) <0.0001
       SI/SpO2 0.0±0.0 0.0 (0.0–0.0) 0.0±0.0 0.0 (0.0–0.0) 0.01±0.0 0.0 (0.0–0.0) <0.0001
       Age SI/SpO2 0.5±0.2 0.4 (0.3–0.5) 0.5±0.2 0.4 (0.3–0.5) 0.6±0.2 0.6 (0.5–0.7) <0.0001
       RSI 1.3±0.3 1.25 (1.1–1.4) 1.3±0.3 1.3 (1.2–1.5) 1.3±0.3 1.3 (1.1–1.6) 0.19
       RSI/Age 0.02±0.01 0.02 (0.01–0.02) 0.02±0.01 0.02 (0.01–0.02) 0.02±0.00 0.02 (0.01–0.02) <0.0001
       RSI×SpO2 110.5±23.8 107.6 (95.7–119.6) 111.8±23.8 108.8 (93.2–124.4) 102.1±22.2 100.8 (82.9–118.8) <0.0001
       RSI×SpO2/Age 2.4±1.0 2.3 (1.8–2.8) 2. 6±1.0 2.4 (1.7–3.1) 1.7±0.5 1.7 (1.4–2.1) <0.0001
      Variable Univariate logistic regression P-value Multivariate logistic regression P-value
      Age 1.05 (1.03–1.06) <0.001
      Sex 0.14 <0.001
       Female 0.68 (0.41–1.13) 0.13 (0.04–0.38)
       Male Reference Reference
      SBP 1.01 (1.00–1.003) 0.02
      DBP 0.98 (0.96–1.01) 0.32
      Heart rate 1.02 (1.00–1.03) 0.002
      Respiratory rate 1.19 (1.10–1.29) <0.001
      SpO2 0.79 (0.75–0.84) <0.001 0.82 (0.75–0.89) <0.001
      LOS 1.08 (1.04–1.12) <0.001
      WBC 1.10 (1.05–1.15) <0.001
      Hemoglobin 0.83 (0.74–0.93) <0.001 0.59 (0.47–0.73) <0.001
      Platelet 1.00 (0.99–1.00) 0.82
      BUN 1.01 (1.00–1.01) 0.001
      Creatinine 1.13 (0.85–1.50) 0.38
      AST 1.01 (1.00–1.01) <0.001
      ALT 1.00 (0.99–1.00) 0.97
      Bilirubin total 3.00 (1.74–5.15) <0.001
      Bilirubin direct 16.47 (6.21–43.68) <0.001 21.37 (4.78–95.61) <0.001
      Blood sugar 1.00 (1.00–1.00) 0.01
      LDH 1.00 (1.00–1.05) <0.001 1.003 (1.002–1.005) <0.001
      ESR 1.00 (1.00–1.01) <0.001
      CRP 1.00 (0.99–1.01) 0.24
      D-imer 1.35 (1.19–1.54) <0.001 1.32 (1.06–1.63) 0.01
      SI 2.13 (0.74–6.11) 0.16
      Age SI 1.03 (1.02–1.04) <0.001
      SI/SpO2 1.11 (1.10–1.12) 0.001
      Age SI/SpO2 17.15 (6.42–45.83) <0.001 0.01 (0.00–0.08) <0.001
      RSI 0.54 (0.21–1.43) <0.001
      RSI/Age 0.95 (0.88–1.11) <0.001
      RSI×SpO2 0.97 (0.96–0.98) <0.001
      RSI×SpO2/Age 0.19 (0.12–0.30) <0.001 0.01 (0.00–0.05) <0.001
      AUC Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR (+) LR (–) Accuracy (%) OR (95% CI)
      Age SI/SpO2 0.80 75 73.3 32.1 94.6 2.81 0.34 73.6 8.23 (4.63–14.63)
      AUC Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR (+) LR (–) Accuracy (%) OR (95% CI)
      RSI×SpO2/Age 0.80 73.3 75 33 94.4 2.93 0.36 74.8 0.12 (0.06–0.21)
      Table 1. Characteristics, vital signs, laboratory data, and indices in COVID-19 patients

      COVID-19: coronavirus disease 2019; SD: standard deviation; IQR: interquartile range; SBP: systolic blood pressure; DBP: diastolic blood pressure; SpO2: oxygen saturation; LOS: length of stay; WBC: white blood cell count; BUN: blood urea nitrogen; AST: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; ESR: erythrocyte sedimentation rate; CRP: c-reactive protein; SI: Shock Index; RSI: Revere Shock Index.

      Table 2. Univariate and multivariate regression analysis of variables according to their association with mortality in COVID-19 patients

      Values are presented as odds ratio (95% CI).

      COVID-19: coronavirus disease 2019; SBP: systolic blood pressure; DBP: diastolic blood pressure; SpO2: oxygen saturation; LOS: length of stay; WBC: white blood cell count; BUN: blood urea nitrogen; AST: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; ESR: erythrocyte sedimentation rate; CRP: c-reactive protein; SI: Shock Index; RSI: Revere Shock Index.

      Table 3. Predictive value of Age SI/SpO₂ for mortality in COVID-19 patients (cutoff=0.52)

      SI: Shock Index; SpO2: oxygen saturation; COVID-19: coronavirus disease 2019; AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value; LR: likelihood ratio; OR: odds ratio.

      Table 4. Predictive value of RSI×SpO₂/Age for mortality in COVID-19 patients (cutoff=1.90)

      RSI: Revere Shock Index; SpO2: oxygen saturation; COVID-19: coronavirus disease 2019; AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value; LR: likelihood ratio; OR: odds ratio.

      Table 1.

      Table 2.

      Table 3.

      Table 4.

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