The Usefulness of Shock Index and Modified Shock Index in Predicting the Outcome of COVID-19 Patients

Association of Shock Indices with Peri-Intubation Hypotension and Other Outcomes: A Sub-Study of the KEEP PACE Trial

BACKGROUND

Based on current evidence, there appears to be an association between peri-intubation hypotension and patient morbidity and mortality. Studies have identified shock indices as possible pre-intubation risk factors for peri-intubation hypotension. Thus, we sought to evaluate the association between shock index (SI), modified shock index (MSI), and diastolic shock index (DSI) and peri-intubation hypotension along with other outcomes.

METHODS

The present study is a sub-study of a randomized controlled trial involving critically ill patients undergoing intubation. We defined peri-intubation hypotension as a decrease in mean arterial pressure <65 mm Hg and/or a reduction of 40% from baseline; or the initiation of, or increase in infusion dosage of, any vasopressor medication (bolus or infusion) during the 30-min period following intubation. SI, MSI, and DSI were analyzed as continuous variables and categorically using pre-established cut-offs. We also explored the effect of age on shock indices.

RESULTS

A total of 151 patients were included in the analysis. Mean pre-intubation SI was 1.0  ±  0.3, MSI 1.5  ±  0.5, and DSI 1.9  ±  0.7. Increasing SI, MSI, and DSI were significantly associated with peri-intubation hypotension (OR [95% CI] per 0.1 increase  =  1.16 [1.04, 1.30], P  =  .009 for SI; 1.14 [1.05, 1.24], P  =  .003 for MSI; and 1.11 [1.04, 1.19], P  =  .003 for DSI). The area under the ROC curves did not differ across shock indices (0.66 vs 0.67 vs 0.69 for SI, MSI, and DSI respectively; P  =  .586). Increasing SI, MSI, and DSI were significantly associated with worse sequential organ failure assessment (SOFA) score (spearman rank correlation: r  =  0.30, r  =  0.40, and r  =  0.45 for SI, MSI, and DSI, respectively, all P < .001) but not with other outcomes. There was no significant impact when incorporating age.

CONCLUSIONS

Increasing SI, MSI, and DSI were all significantly associated with peri-intubation hypotension and worse SOFA scores but not with other outcomes. Shock indices remain a useful bedside tool to assess the potential likelihood of peri-intubation hypotension.

TRIAL REGISTRATION

ClinicalTrials.gov identifier - NCT02105415.

Does the choice of induction agent in rapid sequence intubation in the emergency department influence the incidence of post-induction hypotension?

OBJECTIVE

To describe the effects of different induction agents on the incidence of post-induction hypotension (PIH) and its associated interventions during rapid sequence intubation (RSI) in the ED.

METHODS

A single centre retrospective study of patients intubated between 2018 and 2021 was conducted in a regional Australian ED. The impact of induction agent choice, in addition to demographic and clinical factors on the incidence of PIH were determined using descriptive statistics and a multivariate analysis presented as adjusted odds ratios (aORs) and their 95% confidence intervals (CIs).

RESULTS

Ketamine and propofol, used either individually or in conjunction with fentanyl, were significantly associated with PIH (ketamine aOR 4.5, 95% CI 1.35-14.96; propofol aOR 4.88, 95% CI 1.46-16.29). Age >60 years was associated with a greater requirement for vasopressors (aOR 4.46, 95% CI 2.49-7.97) and a higher risk of mortality after RSI (aOR 4.2, 95% CI 1.87-9.40). Patients with a shock index >1.0 were significantly more likely to require vasopressors (aOR 5.13, 95% CI 2.35-11.2) and have a cardiac arrest within 15 min of RSI (aOR 3.56, 95% CI 1.07-11.8).

CONCLUSIONS

Exposure to both propofol and ketamine is significantly associated with PIH after RSI, alongside age and shock index. PIH is likely multifactorial in nature, and this data supports the sympatholytic effect of induction agents as the underlying cause of PIH rather than the choice of agent itself. Further prospective work including a randomised controlled trial between induction agents is justified to further clarify this important clinical question.

Gas-exchange deficit and systemic hypoperfusion in COVID-19 and non-COVID-19 young adult patients with pneumonia

BACKGROUND

Lung damage leading to gas-exchange deficit and sepsis leading to systemic hypoperfusion are well-known features of severe pneumonia. Although frequently described in COVID-19, their prognostic impact in COVID-19-related pneumonia versus COVID-19-unrelated pneumonia has never been compared. This study assesses fundamental gas-exchange and hemodynamic parameters and explores their prognostic impact in COVID-19 pneumonia and non-COVID-19 pneumonia.

METHODS

We prospectively evaluated arterial pO2/FiO2, alveolar to arterial O2 gradient, shock index, and serum lactate in 126 COVID-19 pneumonia patients, aged 18-65, presenting to the emergency department with acute, non-hypercapnic respiratory failure. As a control group we identified 1:1 age-, sex-, and pO2/FiO2-matched COVID-19-urelated pneumonia patients. Univariate and multivariable predictors of 30-day survival were identified in both groups.

RESULTS

COVID-19 patients showed lower arterial serum lactate concentration (P<0.001) and shock index (P<0.001) values as compared to non-COVID-19 patients. While we did not observe differences in lactate concentration or in shock index values in deceased vs. surviving COVID-19 patients (P=0.7 and P=0.6, respectively), non-COVID-19 deceased patients showed significantly higher lactate and shock index than non-COVID-19 survivors (P<0.001 and P=0.03). The pO2/FiO2 was the most powerful determinant of survival by Cox regression multivariate analysis in COVID-19 patients (P=0.006), while it was lactate in non-COVID-19 patients (P=0.001).

CONCLUSIONS

As compared to COVID19-unrelated pneumonia, COVID-19 pneumonia outcome seems more strictly correlated to the extent of lung damage, rather than to the systemic circulatory and metabolic derangements typical of sepsis.

Reverse shock index multiplied by simplified motor score as a predictor of clinical outcomes for patients with COVID-19

BACKGROUND

The reverse shock index (rSI) combined with the Simplified Motor Score (sMS), that is, the rSI-sMS, is a novel and efficient prehospital triage scoring system for patients with COVID-19. In this study, we evaluated the predictive accuracy of the rSI-sMS for general ward and intensive care unit (ICU) admission among patients with COVID-19 and compared it with that of other measures, including the shock index (SI), modified SI (mSI), rSI combined with the Glasgow Coma Scale (rSI-GCS), and rSI combined with the GCS motor subscale (rSI-GCSM).

METHODS

All patients who visited the emergency department of Taipei Tzu Chi Hospital between January 2021 and June 2022 were included in this retrospective cohort. A diagnosis of COVID-19 was confirmed through a SARS-CoV-2 reverse-transcription polymerase chain reaction test or SARS-CoV-2 rapid test with oropharyngeal or nasopharyngeal swabs and was double confirmed by checking International Classification of Diseases, Tenth Revision, Clinical Modification codes in electronic medical records. In-hospital mortality was regarded as the primary outcome, and sepsis, general ward or ICU admission, endotracheal intubation, and total hospital length of stay (LOS) were regarded as secondary outcomes. Multivariate logistic regression was used to determine the relationship between the scoring systems and the three major outcomes of patients with COVID-19, including. The discriminant ability of the predictive scoring systems was investigated using the area under the receiver operating characteristic curve, and the most favorable cutoff value of the rSI-sMS for each major outcome was determined using Youden's index.

RESULTS

After 74,183 patients younger than 20 years (n = 11,572) and without COVID-19 (n = 62,611) were excluded, 9,282 patients with COVID-19 (median age: 45 years, interquartile range: 33-60 years, 46.1% men) were identified as eligible for inclusion in the study. The rate of in-hospital mortality was determined to be 0.75%. The rSI-sMS scores were significantly lower in the patient groups with sepsis, hyperlactatemia, admission to a general ward, admission to the ICU, total length of stay ≥ 14 days, and mortality. Compared with the SI, mSI, and rSI-GCSM, the rSI-sMS exhibited a significantly higher accuracy for predicting general ward admission, ICU admission, and mortality but a similar accuracy to that of the rSI-GCS. The optimal cutoff values of the rSI-sMS for predicting general ward admission, ICU admission, and mortality were calculated to be 3.17, 3.45, and 3.15, respectively, with a predictive accuracy of 86.83%, 81.94%%, and 90.96%, respectively.

CONCLUSIONS

Compared with the SI, mSI, and rSI-GCSM, the rSI-sMS has a higher predictive accuracy for general ward admission, ICU admission, and mortality among patients with COVID-19.

Shock and modified shock indices in predicting poisoning severity and outcomes in acute aluminum phosphide poisoned patients

Background

Severe refractory hypotension and cardiogenic shock are the main contributors to death in acute aluminum phosphide (ALP) poisoning. Shock index (SI) and modified shock index (MSI) are easily obtained parameters that reflect shock at an early stage.

Aim

This study aimed to evaluate the role of SI and MSI in the prediction of the severity and outcomes of acute ALP poisoned patients.

Patients and methods

This cross sectional study was conducted on patients admitted to Tanta University Poison Control Centre with acute ALP poisoning from April 2022 to March 2023. Socio-demographics and toxicological data were taken, findings of clinical examination and laboratory investigations were recoded, SI was calculated by dividing heart rate over systolic blood pressure, and MSI was obtained by dividing heart rate over mean arterial pressure. Poisoning severity was assessed using poisoning severity score (PSS). Patients were divided into groups according to intensive care unit (ICU) admission and mortality.

Results

The study enrolled 94 patients. The median values of SI and MSI were significantly higher in ICU-admitted patients and non-survivors rather than their comparable groups. Significant positive correlations were observed between each of SI and MSI and PSS. At cut-off >1.14, SI conveyed fair performance to predict ICU admission and mortality (AUC = 0.710 and 0.739, respectively). Similarly, MSI had fair performance to predict ICU admission (AUC = 0.731) and mortality (AUC = 0.744) at cut-off >1.47 and >1.5, respectively.

Conclusion

Both SI and MSI could be considered simple bedside adjuncts to predict ICU admission and mortality in acute ALP poisoning.

Preoperative shock index in major abdominal emergency surgery

Introduction

Major abdominal emergency surgery (MAES) patients have a high risk of mortality and complications. The time-sensitive nature of MAES necessitates an easily calculable risk-scoring tool. Shock index (SI) is obtained by dividing heart rate (HR) by systolic blood pressure (SBP) and provides insight into a patient's haemodynamic status. We aimed to evaluate SI's usefulness in predicting postoperative mortality, acute kidney injury (AKI), requirements for intensive care unit (ICU) and high-dependency monitoring, and the ICU length of stay (LOS).

Method

We retrospectively reviewed 212,089 MAES patients from January 2013 to December 2020. The cohort was propensity matched, and 3960 patients were included. The first HR and SBP recorded in the anaesthesia chart were used to calculate SI. Regression models were used to investigate the association between SI and outcomes. The relationship between SI and survival was explored with Kaplan-Meier curves.

Results

There were significant associations between SI and mortality at 1 month (odds ratio [OR] 2.40 [1.67-3.39], P<0.001), 3 months (OR 2.13 [1.56-2.88], P<0.001), and at 2 years (OR 1.77 [1.38-2.25], P<0.001). Multivariate analysis revealed significant relationships between SI and mortality at 1 month (OR 3.51 [1.20-10.3], P=0.021) and at 3 months (OR 3.05 [1.07-8.54], P=0.034). Univariate and multivariate analysis also revealed significant relationships between SI and AKI (P<0.001), postoperative ICU admission (P<0.005) and ICU LOS (P<0.001). SI does not significantly affect 2-year mortality.

Conclusion

SI is useful in predicting postopera-tive mortality at 1 month, 3 months, AKI, postoperative ICU admission and ICU LOS.

Shock index in the emergency department as a predictor for mortality in COVID-19 patients: A systematic review and meta-analysis

Background

The shock index (SI) ratio serves as a straightforward predictor to identify patients who are either at risk of or experiencing shock. COVID-19 patients with shock face increased mortality risk and reduced chances of recovery. This review aims to determine the role of SI in the emergency department (ED) to predict COVID-19 patient outcomes.

Methods

The systematic search was conducted in PubMed, ProQuest, Scopus, and ScienceDirect on June 16, 2023. We included observational studies evaluating SI in ED and COVID-19 patient outcomes. Random-effect meta-analysis was done to generate odds ratios of SI as the predictor of intensive care unit (ICU) admission and mortality. The sensitivity and specificity of SI in predicting these outcomes were also pooled, and a summary receiver operating characteristics (sROC) curve was generated.

Results

A total of eight studies involving 4557 participants were included in the pooled analysis. High SI was found to be associated with an increased risk of ICU admission (OR 5.81 [95%CI: 1.18-28.58], p = 0.03). Regarding mortality, high SI was linked to higher rates of in-hospital (OR 7.45 [95%CI: 2.44-22.74], p = 0.0004), within 30-day (OR 7.34 [95%CI: 5.27-10.21], p < 0.00001), and overall (OR 7.52 [95%CI: 3.72-15.19], p < 0.00001) mortality. The sensitivity and specificity of SI for predicting ICU admission were 76.2% [95%CI: 54.6%-89.5%] and 64.3% [95%CI: 19.6%-93.0%], respectively. In terms of overall mortality, the sensitivity and specificity were 54.0% (95%CI: 34.3%-72.6%) and 85.9% (95%CI: 75.8%-92.3%), respectively, with only subtle changes for in-hospital and within 30-day mortality. Adjustment of SI cut-off to >0.7 yielded improved sensitivity (95%CI: 78.0% [59.7%-89.4%]) and specificity (95%CI: 76.8% [41.7%-93.9%]) in predicting overall mortality.

Conclusion

SI in emergency room may be a simple and useful triage instrument for predicting ICU admission and mortality in COVID-19 patients. Future well-conducted studies are still needed to corroborate the findings of this study.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Prognostic Performance of Shock Index, Diastolic Shock Index, Age Shock Index, and Modified Shock Index in COVID-19 Pneumonia

OBJECTIVE

We aimed to compare the prognostic accuracy of shock indexes in terms of mortality in patients hospitalized with coronavirus disease 2019 (COVID-19) pneumonia.

METHODS

Hospitalized patients whose COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR) test results were positive, had thoracic computed tomography (CT) scan performed, and had typical thoracic CT findings for COVID-19 were included in the study.

RESULTS

Eight hundred one patients were included in the study. Chronic obstructive pulmonary disease, congestive heart failure, chronic neurological diseases, chronic renal failure, and a history of malignancy were found to be chronic diseases that were significantly associated with mortality in patients with COVID-19 pneumonia. White blood cell, neutrophil, lymphocyte, C reactive protein, creatinine, sodium, aspartate aminotransferase, alanine aminotransferase, total bilirubin, high sensitive troponin, d-dimer, hemoglobin, and platelet had a statistically significant relationship with in-hospital mortality in patients with COVID-19 pneumonia. The area under the curve (AUC) values of shock index (SI), age shock index (aSI), diastolic shock index (dSI), and modified shock index (mSI) calculated to predict mortality were 0.772, 0.745, 0.737, 0.755, and Youden Index J (YJI) values were 0.523, 0.396, 0.436, 0.452, respectively.

CONCLUSIONS

The results of this study show that SI, dSI, mSI, and aSI are effective in predicting in-hospital mortality.