Modified shock index and mortality rate of emergency 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.

The Respiratory Rate, Age, and Mean Arterial Pressure (RAM) Index: A Novel Prognostic Tool to Predict Mortality among Adult Patients with Acute Heart Failure in the Emergency Department

Background and Objectives: Acute heart failure (AHF) is a life-threatening condition frequently encountered in the emergency department (ED). Identifying reliable prognostic indicators for in-hospital mortality is crucial for risk stratification and the appropriate management of AHF patients. This study aimed to assess the most effective method for predicting in-hospital mortality among various physiological parameters in patients with AHF presenting to the ED. Additionally, the study evaluated the effectiveness of the RAM index-respiratory rate (RR), age, and mean arterial pressure (MAP)-derived from the shock index (SI) by replacing heart rate with RR, as a novel prognostic tool. This was compared with the SI and its other derivatives to predict in-hospital mortality in adult patients with AHF presenting to the ED. Materials and Methods: This is a retrospective study conducted in the ED of an urban medical center, enrolling adult patients with signs and symptoms of AHF, who met the epidemiological diagnosis criteria, between January 2017 and December 2021. Baseline physiological parameters, including the RR, heart rate, systolic blood pressure, and diastolic blood pressure, were recorded upon ED admission. The RAM index was calculated as the RR multiplied by the age divided by the MAP. Statistical analysis was performed, including univariate analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis. Results: A total of 2333 patients were included in the study. A RAM index > 18.6 (area under ROC curve (AUROC): 0.81; 95% confidence interval (CI): 0.79-0.83) had a superior mortality discrimination ability compared to an SI > 0.77 (AUROC: 0.75; 95% CI: 0.72-0.77), modified shock index > 1.11 (AUROC: 0.75; 95% CI: 0.73-0.77), age shock index > 62.7 (AUROC: 0.74; 95% CI: 0.72-0.76), and age-modified shock index > 79.9 (AUROC: 0.75; 95% CI: 0.73-0.77). A RAM index > 18.6 demonstrated a 7.36-fold higher risk of in-hospital mortality with a sensitivity of 0.80, specificity of 0.68, and negative predictive value of 0.97. Conclusions: The RAM index is an effective tool to predict mortality in AHF patients presenting to the ED. Its superior performance compared to traditional SI-based parameters suggests that the RAM index can aid in risk stratification and the early identification of high-risk patients, facilitating timely and aggressive treatment strategies.

Tools for Screening, Predicting, and Evaluating Sepsis and Septic Shock: A Comprehensive Review

Sepsis is characterized by life-threatening organ dysfunction due to dysregulated host response to infection. It can progress to cause circulatory and cellular/metabolic abnormalities, resulting in septic shock that may significantly increase mortality. The pathophysiology of sepsis involves a complex interplay of invading pathogens and the body's immune defense, causing alteration in normal homeostasis, eventually leading to derangements in the cellular, humoral, circulatory, and metabolic functions. Several scoring systems have been developed to rapidly predict or suspect sepsis, such as Sequential Organ Failure Assessment (SOFA), modified SOFA (mSOFA), quick SOFA (qSOFA), shock index (SI), and modified SI (mSI). Each of these scores has been utilized for triaging patients with sepsis, and as per medical advancements these scoring systems have been modified to include or exclude certain criteria to improve their clinical utility. This review aims to compare the individual scores and their usage for sepsis that may be used for laying the foundation for early recognition and prediction of sepsis and for formulating more precise definitions in the future.

Shock index and shock index, pediatric age-adjusted as predictors of mortality in pediatric patients with trauma: A systematic review and meta-analysis

This study aimed to assess the predictive ability of the shock index (SI) and the shock index, pediatric age-adjusted (SIPA) for mortality among pediatric patients with trauma (aged ≤ 18 years). A systematic search used PubMed, Embase, and Cochrane Library databases to identify pertinent articles published from their inception to 13 February 2023. For each SI and SIPA, the pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (AUC) with the corresponding 95% confidence intervals were calculated. We planned a priori meta-regression analyses to explore heterogeneity using the following covariates: country, clinical setting, type of center, data source, and cutoff value. Twelve studies were included based on the inclusion criteria. Among them, nine studies with 195,469 patients were included for the SIPA at the hospital, four studies with 4,970 patients were included for the pre-hospital SIPA, and seven studies with 606,445 patients were included to assess the ability of the SI in predicting mortality. The pooled sensitivity and specificity with 95% confidence interval for predicting mortality were as follows: 0.58 (0.44-0.70) and 0.72 (0.60-0.82), respectively, for the SIPA at the hospital; 0.61 (0.47-0.74) and 0.67 (0.61-0.73), respectively, for the pre-hospital SIPA; and 0.71 (0.59-0.81) and 0.45 (0.31-0.59), respectively for the SI. The DOR were 3.80, 3.28, and 2.06 for the SIPA at the hospital, pre-hospital SIPA, and SI, respectively. The AUC were 0.693, 0.689, and 0.618 for the SIPA at the hospital, pre-hospital SIPA, and SI, respectively. The SI and SIPA are simple predictive tools with sufficient accuracy that can be readily applied to pediatric patients with trauma, but SIPA and SI should be utilized cautiously due to their limited sensitivity and specificity, respectively.

An Assessment of Clinical Accuracy of Vital Sign-based Triage Tools Among U.S. and Coalition Forces

INTRODUCTION

Early appropriate allocation of resources for critically injured combat casualties is essential. This is especially important when inundated with an overwhelming number of casualties where limited resources must be efficiently allocated, such as during mass casualty events. There are multiple scoring systems utilized in the prehospital combat setting, including the shock index (SI), modified shock index (MSI), simple triage and rapid treatment (START), revised trauma score (RTS), new trauma score (NTS), Glasgow Coma Scale + age + pressure (GAP), and the mechanism + GAP (MGAP) score. The optimal score for application to the combat trauma population remains unclear.

MATERIALS AND METHODS

This is a secondary analysis of a previously described dataset from the Department of Defense Trauma Registry from January 1, 2007 through March 17, 2020. We constructed univariable analyses to determine the area under the receiving operator characteristic (AUROC) for the scoring systems of interest. Our primary outcomes were early death (within 24 hours) or early massive transfusion, as defined by ≥3 units.

RESULTS

There were 12,268 casualties that met inclusion criteria. There were 168 (1%) who died within the first 24 hours and 2082 (17%) that underwent significant transfusion within the first 24 hours. When assessing the predictive capabilities for death within 24 hours, the AUROCs were 0.72 (SI), 0.69 (MSI), 0.89 (START), 0.90 (RTS), 0.83 (NTS), 0.90 (GAP), and 0.91 (MGAP). The AUROCs for massive transfusion were 0.89 (SI), 0.89 (MSI), 0.82 (START), 0.81 (RTS), 0.83 (NTS), 0.85 (MGAP), and 0.86 (GAP).

CONCLUSIONS

This study retrospectively applied seven triage tools to a database of 12,268 cases from the Department of Defense Trauma Registry to evaluate their performance in predicting early death or massive transfusion in combat. All scoring systems performed well with an AUROC >0.8 for both outcomes. Although the SI and MSI performed best for predicting massive transfusion (both had an AUROC of 0.89), they ranked last for assessment of mortality within 24 hours, with the other tools performing well. START, RTS, NTS, MGAP and GAP reliably identified early death and need for massive transfusion, with MGAP and GAP performing the best overall. These findings highlight the importance of assessing triage tools to best manage resources and ultimately preserve lives of traumatically wounded warfighters. Further studies are needed to explain the surprising performance discrepancy of the SI and MSI in predicting early death and massive transfusion.

Prehospital Shock Index Multiplied by the Alert/Verbal/Painful/Unresponsive Score as a Predictor of Clinical Outcomes in Traumatic Injury

OBJECTIVE

Various prediction scores have been developed to predict mortality in trauma patients, such as the shock index (SI), modified SI (mSI), age-adjusted SI (aSI), and the shock index (SI) multiplied by the alert/verbal/painful/unresponsive (AVPU) score (SIAVPU). The SIAVPU is a novel scoring system but its prediction accuracy for trauma outcomes remains in need of further validation. Therefore, we investigated the accuracy of four scoring systems, including SI, mSI, aSI, and SIAVPU, in predicting mortality, admission to the intensive care unit (ICU), and prolonged hospital length of stay ≥ 30 days (LOS).

METHODS

This retrospective multicenter study used data from the Tzu Chi Hospital trauma database. The area under the receiver operating characteristic curve (AUROC) was determined for each outcome to assess their discrimination capabilities and comparing by Delong's test. Subgroup analyses were conducted to investigate the prediction accuracy of the SIAVPU in different patient populations.

RESULTS

In total, 5355 patients were included in the analysis. The median of SIAVPU were significantly higher among patients at those with major injury (1.47 vs 0.63), those admitted to the ICU (0.73 vs 0.62), those with prolonged hospital LOS≥ 30 days (0.83 vs 0.64), and those with mortality (1.08 vs 0.64). The AUROC of the SIAVPU was significantly higher than that of the SI, mSI, and aSI for 24-h mortality (AUROC: 0.845 vs 0.533, 0.540, and 0.678), 3-day mortality (AUROC: 0.803 vs 0.513, 0.524, and 0.688), 7-day mortality (AUROC: 0.755 vs 0.494, 0.505, and 0.648), in-hospital mortality (AUROC: 0.722 vs 0.510, 0.524, and 0.667), ICU admission (AUROC: 0.635 vs 0.547, 0.551, and 0.563). At the optimal cutoff value of 0.9, the SIAVPU had an accuracy of 82.2% for predicting 24-h mortality, 82.8% for predicting 3-day mortality, of 82.8% for predicting 7-day mortality, of 82.5% for predicting in-hospital mortality, of 73.9% for predicting Intensive Care Unit (ICU) admission, and of 81.7% for predicting prolonged hospital LOS ≥30 days.

CONCLUSIONS

Our results reveal that SIAVPU has better accuracy than the SI, mSI, and aSI for predicting 24-h, 3-day, 7-day, and in-hospital mortality; ICU admission; and prolonged hospital LOS ≥30 days among patients with traumatic injury.

Evaluation and treatment of gastrointestinal bleeding in patients taking anticoagulants presenting to the emergency department

This manuscript is a consensus document of an expert panel on the Evaluation and Treatment of Gastrointestinal Bleeding in Patients Taking Anticoagulants Presenting to the Emergency Department, sponsored by the American College of Emergency Physicians.

Shock index to predict outcomes in patients with trauma following traffic collisions: a retrospective cohort study

PURPOSE

Taiwan, which has a rate of high vehicle ownership, faces significant challenges in managing trauma caused by traffic collisions. In Taiwan, traffic collisions contribute significantly to morbidity and mortality, with a high incidence of severe bleeding trauma. The shock index (SI) and the modified shock index (MSI) have been proposed as early indicators of hemodynamic instability. In this study, we aimed to assess the efficacy of SI and MSI in predicting adverse outcomes in patients with trauma following traffic collisions.

METHODS

This retrospective cohort study was conducted at Chi Mei Hospital from January 2015 to December 2020. The comprehensive analysis included 662 patients, with data collected on vital signs and outcomes such as mortality, blood transfusion, emergent surgical intervention (ESI), transarterial embolization (TAE), and intensive care unit (ICU) admission. Optimal cutoff points for SI and MSI were identified by calculating the Youden index. Logistic regression analysis was used to assess outcomes, adjusting for demographic and injury severity variables.

RESULTS

An SI threshold of 1.11 was associated with an increased risk of mortality, while an SI of 0.84 predicted the need for blood transfusion in the context of traffic collisions. Both SI and MSI demonstrated high predictive power for mortality and blood transfusion, with acceptable accuracy for TAE, ESI, and ICU admission. Logistic regression analyses confirmed the independence of SI and MSI as risk factors for adverse outcomes, thus, providing valuable insights into their clinical utility.

CONCLUSIONS

SI and MSI are valuable tools for predicting mortality and blood transfusion needs in patients with trauma due to traffic collisions. These findings advance the quality of care for patients with trauma during their transition from the emergency room to the ICU, facilitating prompt and reliable decision-making processes and improving the care of patients with trauma.

Shock indices are associated with in-hospital mortality among patients with septic shock and normal left ventricular ejection fraction

BACKGROUND

The understanding of shock indices in patients with septic shock is limited, and their values may vary depending on cardiac function.

METHODS

This prospective cohort study was conducted across 20 university-affiliated hospitals (21 intensive care units [ICUs]). Adult patients (≥19 years) with septic shock admitted to the ICUs during a 29-month period were included. The shock index (SI), diastolic shock index (DSI), modified shock index (MSI), and age shock index (Age-SI) were calculated at sepsis recognition (time zero) and ICU admission. Left ventricular (LV) function was categorized as either normal LV ejection fraction (LVEF ≥ 50%) or decreased LVEF (<50%).

RESULTS

Among the 1,194 patients with septic shock, 392 (32.8%) who underwent echocardiography within 24 h of time zero were included in the final analysis (normal LVEF: n = 246; decreased LVEF: n = 146). In patients with normal LVEF, only survivors demonstrated significant improvement in SI, DSI, MSI, and Age-SI values from time zero to ICU admission; however, no notable improvements were found in all patients with decreased LVEF. The completion of vasopressor or fluid bundle components was significantly associated with improved indices in patients with normal LVEF, but not in those with decreased LVEF. In multivariable analysis, each of the four indices at ICU admission was significantly associated with in-hospital mortality (P < 0.05) among patients with normal LVEF; however, discrimination power was better in the indices for patients with lower lactate levels (≤ 4.0 mmol/L), compared to those with higher lactate levels.

CONCLUSIONS

The SI, DSI, MSI, and Age-SI at ICU admission were significantly associated with in-hospital mortality in patients with septic shock and normal LVEF, which was not found in those with decreased LVEF. Our study emphasizes the importance of interpreting shock indices in the context of LV function in septic shock.

Comparison of Modified Shock Index and Shock Index for Predicting Massive Transfusion in Women with Primary Postpartum Hemorrhage: A Retrospective Study

BACKGROUND The modified shock index (MSI) is calculated as the ratio of heart rate (HR) to mean arterial pressure (MAP) and has been used to predict the need for massive transfusion (MT) in trauma patients. This retrospective study from a single center aimed to compare the MSI with the traditional shock index (SI) to predict the need for MT in 612 women diagnosed with primary postpartum hemorrhage (PPH) at the Emergency Department (ED) between January 2004 and August 2023. MATERIAL AND METHODS The patients were divided into the MT group and the non-MT group. The predictive power of MSI and SI was compared using the areas under the receiver operating characteristic curve (AUC). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated. RESULTS Out of 612 patients, 105 (17.2%) required MT. The MT group had higher median values than the non-MT group for MSI (1.58 vs 1.07, P<0.001) and SI (1.22 vs 0.80, P<0.001). The AUC for MSI, with a value of 0.811 (95% confidence interval [CI], 0.778-0.841), did not demonstrate a significant difference compared to the AUC for SI, which was 0.829 (95% CI, 0.797-0.858) (P=0.066). The optimal cutoff values for MSI and SI were 1.34 and 1.07, respectively. The specificity and PPV for MT were 77.1% and 40.2% for MSI, and 83.2% and 45.9% for SI. CONCLUSIONS Both MSI and SI were effective in predicting MT in patients with primary PPH. However, MSI did not demonstrate superior performance to SI.

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.

RELATIONSHIP BETWEEN SHOCK INDEX, MODIFIED SHOCK INDEX, AND AGE SHOCK INDEX AND 28-DAY MORTALITY AMONG PATIENTS WITH PREHOSPITAL SEPTIC SHOCK

BACKGROUND

A relative hypovolemia occurs during septic shock (SS); the early phase is clinically reflected by tachycardia and low blood pressure. In the prehospital setting, simple objective tools to assess hypovolemia severity are needed to optimize triaging.

OBJECTIVE

The aim of this study was to evaluate the relationship between shock index (SI), diastolic SI (DSI), modified SI (MSI), and age SI (ASI) and 28-day mortality of patients with SS initially cared for in a prehospital setting of a mobile intensive care unit (MICU).

METHODS

From April 6, 2016 through December 31, 2021, 530 patients with SS cared for at a prehospital MICU were analyzed retrospectively. Initial SI, MSI, DSI, and ASI values, that is, first measurement after MICU arrival to the scene were calculated. A propensity score analysis with inverse probability of treatment weighting (IPTW) method was used to assess the relationship between SI, DSI, MSI, and ASI and 28-day mortality.

RESULTS

SS resulted mainly from pulmonary, digestive, and urinary infections in 44%, 25%, and 17% of patients. The 28-day overall mortality was 31%. IPTW propensity score analysis indicated a significant relationship between 28-day mortality and SI (adjusted odds ratio [aOR] 1.13; 95% CI 1.01-1.26; p = 0.04), DSI (aOR 1.16; 95% CI 1.06-1.34; p = 0.03), MSI (aOR 1.03; 95% CI 1.01-1.17; p = 0.03), and ASI (aOR 3.62; 95% CI 2.63-5.38; p < 10-6).

CONCLUSIONS

SI, DSI, MSI, and ASI were significantly associated with 28-day mortality among patients with SS cared for at a prehospital MICU. Further studies are needed to confirm the usefulness of SI and SI derivates for prehospital SS optimal triaging.

Head-to-head comparison of 19 prediction models for short-term outcome in medical patients in the emergency department: a retrospective study

INTRODUCTION

Prediction models for identifying emergency department (ED) patients at high risk of poor outcome are often not externally validated. We aimed to perform a head-to-head comparison of the discriminatory performance of several prediction models in a large cohort of ED patients.

METHODS

In this retrospective study, we selected prediction models that aim to predict poor outcome and we included adult medical ED patients. Primary outcome was 31-day mortality, secondary outcomes were 1-day mortality, 7-day mortality, and a composite endpoint of 31-day mortality and admission to intensive care unit (ICU).The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC). Finally, the prediction models with the highest performance to predict 31-day mortality were selected to further examine calibration and appropriate clinical cut-off points.

RESULTS

We included 19 prediction models and applied these to 2185 ED patients. Thirty-one-day mortality was 10.6% (231 patients), 1-day mortality was 1.4%, 7-day mortality was 4.4%, and 331 patients (15.1%) met the composite endpoint. The RISE UP and COPE score showed similar and very good discriminatory performance for 31-day mortality (AUC 0.86), 1-day mortality (AUC 0.87), 7-day mortality (AUC 0.86) and for the composite endpoint (AUC 0.81). Both scores were well calibrated. Almost no patients with RISE UP and COPE scores below 5% had an adverse outcome, while those with scores above 20% were at high risk of adverse outcome. Some of the other prediction models (i.e. APACHE II, NEWS, WPSS, MEWS, EWS and SOFA) showed significantly higher discriminatory performance for 1-day and 7-day mortality than for 31-day mortality.

CONCLUSIONS

Head-to-head validation of 19 prediction models in medical ED patients showed that the RISE UP and COPE score outperformed other models regarding 31-day mortality.

Factors Associated With Hospital Mortality in Acute Myocardial Infarction

Aim    To determine clinical and laboratory parameters associated with in-hospital mortality in patients with acute myocardial infarction and to develop a multifactorial prognostic model of in-hospital mortality.Material and methods    This was a study based on the 2019-2020 Registry of acute coronary syndrome of the Tyumen Cardiology Research Center, a branch of the Tomsk National Research Medical Center. The study included 477 patients with ST-segment elevation acute myocardial infarction (AMI), 617 patients with non-ST segment elevation AMI, and 26 patients with unspecified AMI. In-hospital mortality was 6.0 % (n=67). Clinical and laboratory parameters were assessed on the day of admission. The separation power of indicators associated with in-hospital mortality was determined using a ROC analysis. The data array of each quantitative parameter was converted into a binary variable according to the obtained cut-off thresholds, followed by creation of a multifactorial model for predicting in-hospital mortality using a stepwise analysis with backward inclusion (Wald). The null hypothesis was rejected at p<0.05.Results    The multivariate model for prediction of in-hospital mortality included age (cut-off, 72 years), OR 3.0 (95 % CI: 1.5-5.6); modified shock index (cut-off threshold, 0.87), OR 1.5 (95 % CI: 1.1-2.0); creatine phosphokinase-MB (cut-off threshold, 32.8 U / L), OR 4.1 (95 % CI: 2.2-7.7); hemoglobin (121.5 g / l), OR 1.7 (95 % CI: 1.2-2.3); leukocytes (11.5×109 / l), OR 1.9 (95 % CI: 1.3-2.6); glomerular filtration rate (60.9 ml / min), OR 1.7 (95 % CI: 1.2-2.2); left ventricular ejection fraction (42.5 %), OR 4.1 (95 % CI: 2.0-8.3); and size of myocardial asynergy (32.5 %), OR 2.6 (95 % CI: 1.4-5.0).Conclusions    Independent predictors of in-hospital mortality in AMI are age, modified shock index, creatine phosphokinase-MB, peripheral blood leukocyte count, hemoglobin concentration, left ventricular ejection fraction, size of myocardial asynergy, and glomerular filtration rate. The in-hospital mortality model had a high predictive potential: AUC 0.930 (95 % CI: 0.905-0.954; p <0.001) with a cutoff threshold of 0.15; sensitivity 0.851, and specificity 0.850.

The value of shock index, modified shock index and age shock index to predict mortality and hospitalisation in a district level emergency centre

Introduction

Triage is the most important step in patients' journey through an Emergency Centre (EC) and directly impacts time to critical actions. Triage tools, like the South African Triage Scale, are however not designed to predict patient outcomes. The shock index (SI), modified shock index (MSI) and age shock index (ASI) are clinical markers derived from vital signs and correlate with tissue perfusion in critically ill patients. This study aimed to assess the value of SI, MSI and ASI to predict mortality and the need for hospitalisation in all adult patients presenting to a district level emergency centre in South Africa.

Methods

This diagnostic study was performed as a retrospective observational study, using data from an existing electronic registry at a district level hospital emergency centre over a period of 24 months. All adult patients who presented to Mitchells Plain Hospital were eligible for inclusion. Sensitivity, specificity and likelihood ratios were calculated for each variable as a predictor of mortality and hospitalisation with pre-determined thresholds.

Results

During the study period of 24 months, a total of 61 329 patients ≥ 18 years old presented to the EC with 60 599 included in the final sample. A red SATS triage category (+LR = 7.2) and SI ≥1.3 (+LR = 4.9) were the only two predictors with any significant clinical value. The same two markers performed well for both patients with and without trauma and specifically for patients who died while under the care of the emergency centre.

Discussion

The study demonstrated that patients with a SI≥1.3 at triage have a significantly higher likelihood to die or require hospitalisation, whether the presenting complaint is trauma related or not, especially to predict mortality while under the care of the EC. Incorporating this marker as a triage alert could expedite the identification of patients requiring time critical interventions and improve patient throughput in the emergency centre.

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.

The usefulness of the shock index and the modified shock index in predicting patient outcomes in a tertiary emergency department in India

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Complementary value of the Shock Index v. the Modified Shock Index in the prediction of in-hospital intensive care unit admission and mortality: A single-centre experience

Background

Shock is a state of circulatory insufficiency that creates an imbalance between tissue oxygen supply and demand, resulting in end-organ dysfunction and hypodynamic circulatory failure. Most patients with infectious and trauma-related illnesses present to the emergency department (ED) in shock.

Objectives

To study the usefulness of the shock index (SI) and modified shock index (MSI) in identifying and triaging patients in shock presenting to the ED.

Methods

This was a year-long observational, cross-sectional study of 290 patients presenting to the ED of a tertiary hospital in compensated or overt shock. The SI and MSI were calculated at the time of first contact, and then hourly for the initial 3 hours. Relevant background investigations targeting the cause of shock and prognostic markers were done. The outcome measures of mortality and intensive care unit admission were documented for each participant.

Results

The mean age of the participants was 49 years, and 67% of them were men. In consensus with local and national data, the major medical comorbidities were hypertension (20%) and diabetes mellitus (16%). An SI ≥0.9 and an MSI ≥1.3 predicted in-hospital mortality (p<0.05) and ICU admission (p<0.05) with no significant superiority of the MSI over the SI in terms of mortality, although the MSI was a better surrogate marker for critical care admission.

Conclusion

The study showed the complementary value of the SI and MSI in triage in a busy tertiary hospital ED, surpassing their components such as blood pressure, heart rate and pulse pressure. We determined useful cut-offs for these tools for early risk assessment in the ED, and larger multicentre studies are needed to support our findings.

Study synopsis

What the study adds. The study highlights the usefulness of clinical bedside tools such as the shock index (SI) and modified shock index (MSI) in triaging patients in the emergency department, and their role in predicting morbidity and mortality.Implications of the findings. Compared with systolic blood pressure, diastolic blood pressure and mean arterial pressure, alone or in combination, the SI and MSI had higher sensitivity and specificity in terms of outcome prediction. While both an elevated SI and an elevated MSI predicted in-hospital mortality, the MSI was a better surrogate marker for ICU admission.

Discriminant ability of the shock index, modified shock index, and reverse shock index multiplied by the Glasgow coma scale on mortality in adult trauma patients: a PATOS retrospective cohort study

BACKGROUND

The shock index (SI) predicts short-term mortality in trauma patients. Other shock indices have been developed to improve discriminant accuracy. The authors examined the discriminant ability of the SI, modified SI (MSI), and reverse SI multiplied by the Glasgow Coma Scale (rSIG) on short-term mortality and functional outcomes.

METHODS

The authors evaluated a cohort of adult trauma patients transported to emergency departments. The first vital signs were used to calculate the SI, MSI, and rSIG. The areas under the receiver operating characteristic curves and test results were used to compare the discriminant performance of the indices on short-term mortality and poor functional outcomes. A subgroup analysis of geriatric patients with traumatic brain injury, penetrating injury, and nonpenetrating injury was performed.

RESULTS

A total of 105 641 patients (49±20 years, 62% male) met the inclusion criteria. The rSIG had the highest areas under the receiver operating characteristic curve for short-term mortality (0.800, CI: 0.791-0.809) and poor functional outcome (0.596, CI: 0.590-0.602). The cutoff for rSIG was 18 for short-term mortality and poor functional outcomes with sensitivities of 0.668 and 0.371 and specificities of 0.805 and 0.813, respectively. The positive predictive values were 9.57% and 22.31%, and the negative predictive values were 98.74% and 89.97%. rSIG also had better discriminant ability in geriatrics, traumatic brain injury, and nonpenetrating injury.

CONCLUSION

The rSIG with a cutoff of 18 was accurate for short-term mortality in Asian adult trauma patients. Moreover, rSIG discriminates poor functional outcomes better than the commonly used SI and MSI.

Modified Shock Index as a Predictor of Admission and In-hospital Mortality in Emergency Departments; an Analysis of a US National Database

Introduction

The modified shock index (MSI) is the ratio of heart rate to mean arterial pressure. It is used as a predictive and prognostic marker in a variety of disease states. This study aimed to derive the optimal MSI cut-off that is associated with increased likelihood (likelihood ratio, LR) of admission and in-hospital mortality in patients presenting to emergency department (ED).

Methods

We retrospectively reviewed data from the National Hospital Ambulatory Medical Care Survey between 2005 and 2010. Adults>18 years of age were included regardless of chief complaint. Basic patient demographics, initial vital signs, and outcomes were recorded for each patient. Then the optimal MSI cut-off for prediction of admission and in-hospital mortality in ED was calculated. LR ≥ 5 was considered clinically significant.

Results

567,994,402 distinct weighted adult ED patient visits were included in the analysis. 15.7% and 2.4% resulted in admissions and in-hospital mortality, respectively. MSI > 1.7 was associated with a moderate increase in the likelihood of both admission (Positive LR (+LR) = 6.29) and in-hospital mortality (+LR = 5.12). +LR for hospital admission at MSI >1.7 was higher for men (7.13; 95% CI 7.11-7.15) compared to women (5.49; 95% CI 5.47-5.50) and for non-white (7.92; 95% CI 7.88-7.95) compared to white patients (5.85; 95% CI 5.84-5.86). For MSI <0.7, the +LRs were not clinically significant for admission (+LR = 1.07) or in-hospital mortality (LR = 0.75).

Conclusion

In this largest retrospective study, to date, on MSI in the undifferentiated ED population, we demonstrated that an MSI >1.7 on presentation is predictive of admission and in-hospital mortality. The use of MSI could help guide accurate acuity designation, resource allocation, and disposition.

The incidence of cardiovascular instability in patients receiving various vasopressor strategies for peri-intubation hypotension

INTRODUCTION

Patients frequently experience hypotension in the peri-intubation period. This can be due to the underlying disease process, physiologic response to the intervention, or adverse effect from medications. With the heterogeneity in cause for hypotension, the duration can also be short or prolonged. Initiation of vasopressors for peri-intubation hypotension includes various strategies using continuous infusion norepinephrine (NE) or push-dose phenylephrine (PDPE) to obtain goal mean arterial pressure. There is a paucity of data describing cardiovascular stability outcomes in patients receiving vasopressors for peri-intubation hypotension.

METHODS

This is a retrospective cohort study including emergency department patients across three academic medical centers and smaller health system sites who received vasopressors for hypotension within 30 min of intubation. Patients were matched based on factors likely to influence vasopressor selection and were divided into groups if they received PDPE alone, continuous infusion NE alone, or PDPE followed by continuous infusion NE. The primary outcome was a composite of the incidence of hypotension (systolic blood pressure < 90 mmHg), bradycardia (HR < 60 beats per minute), and cardiac arrest within 2 h following initiation of vasopressors.

RESULTS

Screening occurred for 2518 patients, with 105 patients undergoing matching. Mean time to vasopressor initiation was 10 min following intubation. The composite primary outcome was not statistically different between groups and occurred 88.6%, 80.0%, and 88.6% in the NE, PDPE, and PDPE+NE groups, respectively. A subgroup analysis of patients with an ED diagnosis of sepsis or septic shock were more likely to receive PDPE before starting continuous infusion NE (41.3% vs. 27.1%, p = 0.075) and more frequently experienced the primary composite outcome (p = 0.045) but was not correlated with vasopressor strategy (p = 0.55).

DISCUSSION

Cardiovascular instability following vasopressor initiation for peri-intubation hypotension was no different depending on the selected vasopressor strategy. This held true in patients with a sepsis or septic shock diagnosis. Selection of vasopressors should continue to include patient specific factors and product availability.

A Comparative Study on Predictive Validity of Modified Shock Index, Shock Index, and Age Shock Index in Predicting the Need for Mechanical Ventilation among Sepsis Patients in a Tertiary Care Hospital

Introduction

The shock index (SI), modified shock index (MSI), and age multiplied by SI (ASI) are used to assess the severity of shock. They are also used to predict the mortality of trauma patients, but their validity for sepsis patients is controversial. The aim of this study is to assess the predictive value of the SI, MSI, and ASI in predicting the need for mechanical ventilation after 24 h of admission among sepsis patients.

Methods

A prospective observational study was conducted in a tertiary care teaching hospital. Patients with sepsis (235) diagnosed based on systemic inflammatory response syndrome criteria and quick sequential organ failure assessment were included in the study. The need for mechanical ventilation after 24 h is the outcome variables MSI, SI, and ASI were considered as predictor variables. The utility of MSI, SI, and ASI in predicting mechanical ventilation was assessed by receiver operative curve analysis. Data were analyzed using coGuide.

Results

Among the study population, the mean age was 56.12 ± 17.28 years. MSI value at the time of disposition from the emergency room had good predictive validity in predicting mechanical ventilation after 24 h, as indicated by the area under the curve (AUC) of 0.81 (P < 0.001), SI and ASI had fair predictive validity for mechanical ventilation as indicated by AUC (0.78, P < 0.001) and (0.802, P < 0.001), respectively.

Conclusion

SI had better sensitivity (78.57%) and specificity (77.07%) compared to ASI and MSI in predicting the need for mechanical ventilation after 24 h in sepsis patients admitted to intensive care units.

Early Mortality Risk in Acute Trauma Patients: Predictive Value of Injury Severity Score, Trauma Index, and Different Types of Shock Indices

Objective: This study aimed to explore the predictive value of the Injury Severity Score (ISS), Trauma Index (TI) and different types of shock indices (SI) on the early mortality risk of acute trauma patients. Methods: Clinical data of acute trauma patients who met the inclusion and exclusion criteria of this study and were treated in the hospital from January 2020 to December 2020 were retrospectively collected, including gender, age, trauma mechanism, severe injury site, ISS, TI, admission vital signs, different types of shock indices (SI), death within 7 days, length of hospital stay, and Glasgow Outcome Score (GOS). The predictive value of the Injury Severity Score, Trauma Index, and different types of shock indices on the risk of early mortality in patients with acute trauma were compared using relevant statistical methods. Results: A total of 283 acute trauma patients (mean age 54.0 ± 17.9 years, 30.74% female) were included, and 43 (15.19%) of the patients died during 7 days of hospitalization. The admission ISS, TI, SI, MSI, and ASI in the survival group were significantly lower than those in the death group, and the difference was statistically significant (p < 0.05). Meanwhile, different trauma assessment tools included in the study have certain predictive value for early mortality risk of trauma patients. Conclusions: The TI indicates a better capability to predict the risk of early death in patients with acute trauma. As the most sensitive predictor, the SI has the greatest reference value in predicting the risk of early death in patients with traumatic shock.

Shock index and modified shock index are predictors of long-term mortality not only in STEMI but also in NSTEMI patients

BACKGROUND

Shock index (SI) and modified shock index (mSI) are useful instruments for early risk stratification in acute myocardial infarction (AMI) patients. They are strong predictors for short-term mortality. Nevertheless, the association between SI or mSI and long-term mortality in AMI patients has not yet been sufficiently examined.

MATERIAL AND METHODS

For this study, a total of 10,174 patients with AMI was included. All cases were prospectively recorded by the population-based Augsburg Myocardial Infarction Registry from 2000 until 2017. Endpoint was all-cause mortality with a median observational time of 6.5 years [IQR: 3.5-7.4]. Using ROC analysis and calculating Youden-Index, the sample was dichotomized into a low and a high SI and mSI group, respectively. Moreover, multivariable adjusted COX regression models were calculated. All analyses were performed for the total sample as well as for STEMI and NSTEMI cases separately.

RESULTS

Optimal cut-off values were 0.580 for SI and 0.852 for mSI (total sample). AUC values were 0.6382 (95% CI: 0.6223-0.6549) for SI and 0.6552 (95% CI: 0.6397-0.6713) for mSI. Fully adjusted COX regression models revealed significantly higher long-term mortality for patients with high SI and high mSI compared to patients with low indices (high SI HR: 1.42 [1.32-1.52], high mSI HR: 1.46 [1.36-1.57]). Furthermore, the predictive ability was slightly better for mSI compared to SI and more reliable in NSTEMI cases compared to STEMI cases (for SI and mSI).

CONCLUSION

High SI and mSI are useful tools for early risk stratification including long-term outcome especially in NSTEMI cases, which can help physicians to make decision on therapy. NSTEMI patients with high SI and mSI might especially benefit from immediate invasive therapy.Key messagesShock index and modified shock index are predictors of long-term mortality after acute myocardial infarction.Both indices predict long-term mortality not only for STEMI cases, but even more so for NSTEMI cases.

PREHOSPITAL SHOCK INDEX MULTIPLIED BY AVPU SCALE AS A PREDICTOR OF CLINICAL OUTCOMES IN TRAUMATIC INJURY

ABSTRACT

Objectives: Many prehospital trauma triage scores have been proposed, but none has emerged as a criterion standard. Therefore, a rapid and accurate tool is necessary for field triage. The shock index (SI) multiplied by the AVPU (Alert, responds to Voice, responds to Pain, Unresponsive) score (SIAVPU) reflected the hemodynamic and neurological conditions through a combination of the SI and AVPU. This study aimed to investigate the prediction performance of SI multiplied by the AVPU and to compare the prediction performance of other prehospital trauma triage scores in a population with traumatic injury. Patients and Methods: This study included 6,156 patients with trauma injury from the Taipei Tzu Chi trauma database. We investigated the accuracy of four scoring systems in predicting mortality, intensive care unit (ICU) admission, and prolonged hospital stay (defined as a duration of hospitalization >14 days). In the subgroup analysis, we also analyzed the effects of age, injury mechanism and severity, underlying diseases, and traumatic brain injury. Results: The predictive accuracy of SIAVPU for mortality, ICU admission, and prolonged hospital stay was significantly higher than that of SI, modified SI, and SI multiplied by age in the traumatic injury population, with an area under the receiver operating characteristic curve of 0.738 for mortality, 0.641 for ICU admission, and 0.606 for prolonged hospital stay. In the subgroup analysis, the prediction accuracy of mortality, ICU admission, and prolonged hospital stay of SIAVPU was also better in patients with younger age, older age, major trauma (Injury Severity Score ≥16), motor vehicle collisions, fall injury, healthy, cardiovascular disease, mixed traumatic brain injury, and isolated traumatic brain injury. The best cutoff levels of SIAVPU score to predict mortality, ICU admission, and total length of stay ≥14 days in trauma injury patients were 0.90, 0.82, and 0.80, with accuracies of 88.56%, 79.84%, and 78.62%, respectively. Conclusions: In conclusion, SIAVPU is a rapid and accurate field triage score with better prediction accuracy for mortality, ICU admission, and prolonged hospital stay than SI, modified SI, and SI multiplied by age in patients with trauma. Patients with SIAVPU ≥0.9 should be considered for the highest-level trauma center available within the geographic constraints of regional trauma systems.

Shock index, modified shock index, age shock index score, and reverse shock index multiplied by Glasgow Coma Scale predicting clinical outcomes in traumatic brain injury: Evidence from a 10-year analysis in a single center

OBJECTIVES

Early identification of traumatic brain injury (TBI) patients at a high risk of mortality is very important. This study aimed to compare the predictive accuracy of four scoring systems in TBI, including shock index (SI), modified shock index (MSI), age-adjusted shock index (ASI), and reverse shock index multiplied by the Glasgow Coma Scale (rSIG).

PATIENTS AND METHODS

This is a retrospective analysis of a registry from the Taipei Tzu Chi trauma database. Totally, 1,791 patients with TBI were included. We investigated the accuracy of four major shock indices for TBI mortality. In the subgroup analysis, we also analyzed the effects of age, injury mechanism, underlying diseases, TBI severity, and injury severity.

RESULTS

The predictive accuracy of rSIG was significantly higher than those of SI, MSI, and ASI in all the patients [area under the receiver operating characteristic curve (AUROC), 0.710 vs. 0.495 vs. 0.527 vs. 0.598], especially in the moderate/severe TBI (AUROC, 0.625 vs. 0.450 vs. 0.476 vs. 0.529) and isolated head injury populations (AUROC 0.689 vs. 0.472 vs. 0.504 vs. 0.587). In the subgroup analysis, the prediction accuracy of mortality of rSIG was better in TBI with major trauma [Injury Severity Score (ISS) ≥ 16], motor vehicle collisions, fall injury, and healthy and cardiovascular disease population. rSIG also had a better prediction effect, as compared to SI, MSI, and ASI, both in the non-geriatric (age < 65 years) and geriatric (age ≥ 65 years).

CONCLUSION

rSIG had a better prediction accuracy for mortality in the overall TBI population than SI, MSI, and ASI. Although rSIG have better accuracy than other indices (ROC values indicate poor to moderate accuracy), the further clinical studies are necessary to validate our results.

Evaluation of SI, MSI and DSI for very early (3-day) mortality in patients with septic shock

BACKGROUND

Septic shock is associated with increased mortality. Predicting mortality, including early prediction for septic shock patients in intensive care units (ICUs), remains an important challenge.

METHOD

We searched the Medical Information Mart for Intensive Care IV database. Odds ratios (ORs) with 95% confidence intervals (CIs) of the relationships between shock index (SI), modified SI (MSI), and diastolic SI (DSI) of patients with septic shock requiring vasopressors and 3-day/in-hospital mortality were calculated using logistic regression models. The time-course changes of these parameters were compared between survivors and non-survivors. The performance of the different parameters was described by the area under the receiver operating characteristic (ROC) curve (AUC) and compared with DeLong analysis.

RESULTS

A total of 1266 patients with septic shock requiring vasopressors were identified. The 3-day mortality rate and in-hospital mortality rate were 8.7% and 23.5%, respectively. Multivariable logistic regression analysis showed significant associations between pre-vasopressor SI/MSI/DSI and 3-day mortality in patients with septic shock requiring vasopressors in fully adjusted models (Ps for trend < 0.01). The AUCs of pre-vasopressor SI, MSI, and DSI were 0.746, 0.710, and 0.732 for 3-day mortality, respectively. There were significant differences in the time-course of SI, MSI, and DSI between survivors and non-survivors at 3-day/in-hospital mortality among patients with septic shock requiring vasopressors (repeated-measures ANOVA, inter-subjects difference P < 0.001).

CONCLUSION

Pre-vasopressor SI, MSI, and DSI values identified patients with septic shock requiring vasopressors who are at increased risk of early death. Of these easy-to-acquire values, SI and MSI show a comparatively better performance.

Clinical Validation of the Shock Index, Modified Shock Index, Delta Shock Index, and Shock Index-C for Emergency Department ST-Segment Elevation Myocardial Infarction

Background: ST-segment elevation myocardial infarction (STEMI) is a leading cause of death worldwide. A shock index (SI), modified SI (MSI), delta-SI, and shock index-C (SIC) are known predictors of STEMI. This retrospective cohort study was designed to compare the predictive value of the SI, MSI, delta-SI, and SIC with thrombolysis in myocardial infarction (TIMI) risk scales. Method: Patients > 20 years old with STEMI who underwent percutaneous coronary intervention (PCI) were included. Receiver operating characteristic (ROC) curve analysis with the Youden index was performed to calculate the optimal cutoff values for these predictors. Results: Overall, 1552 adult STEMI cases were analyzed. The thresholds for the emergency department (ED) SI, MSI, SIC, and TIMI risk scales for in-hospital mortality were 0.75, 0.97, 21.00, and 5.5, respectively. Accordingly, ED SIC had better predictive power than the ED SI and ED MSI. The predictive power was relatively higher than TIMI risk scales, but the difference did not achieve statistical significance. After adjusting for confounding factors, the ED SI > 0.75, MSI > 0.97, SIC > 21.0, and TIMI risk scales > 5.5 were statistically and significantly associated with in-hospital mortality of STEMI. Compared with the ED SI and MSI, SIC (>21.0) had better sensitivity (67.2%, 95% CI, 58.6−75.9%), specificity (83.5%, 95% CI, 81.6−85.4%), PPV (24.8%, 95% CI, 20.2−29.6%), and NPV (96.9%, 95% CI, 96.0−97.9%) for in-hospital mortality of STEMI. Conclusions: SIC had better discrimination ability than the SI, MSI, and delta-SI. Compared with the TIMI risk scales, the ACU value of SIC was still higher. Therefore, SIC might be a convenient and rapid tool for predicting the outcome of STEMI.

Shock Index and Characteristics of "Bounce-Back" Patients in the Emergency Department of King Abdullah Medical City (KAMC): A Retrospective Analysis

Background "Bounce back" patients is a term used to refer to patients returning to the emergency department within 72 hours after the first visit. This can be attributed to various factors related to diagnosis, management, or the health care system. Objective This study sought to evaluate the extent of bounce-back patients in the emergency department of King Abdullah Medical City (KAMC), Makkah, Saudi Arabia, and then explore the possible relationship between shock index (SI) and bounce-back patients. Methods This is a retrospective chart review of the electronic system among patients who have returned to the emergency department within 72 hours from the index visit. All records were reviewed from May 2019 to May 2021. Vital signs were collected to calculate the shock index (heart rate/systolic blood pressure). The data were analyzed by SPSS Statistics v.27.0 (IBM Corp., Armonk, NY).  Results A total of (506) responses were analyzed. The median age was 56 years with an IQR of 40-67, and males represented 55.3%. Around three-quarters of the second complaints (76.9%) were related to the index visit. The durations between the visits were as follows: 51.8% within 24 hours, 30.2% within 25-48 hours, and 18% within 49-72 hours. The median and IQR for shock index were 0.67 and 0.59-0.80 respectively, while the median and IQR for reverse shock index were 1.49 and 1.25-1.71 respectively. Diabetes and the duration between the two visits were associated with the complaints (p-value=0.005, p-value=0.011) respectively. Conclusion The majority of bounce-back cases occurred within the first 24 hours in our sample. Hypertension, diabetes, and ischemic heart diseases were the most prevalent comorbidities among the bounce-back patients. The majority of bounce-back patients (76.9%) presented with complaints related to the index visit.

Evaluation of Intravascular Volume Using the Internal Jugular Vein Cardiac Collapse Index in the Emergency Department: A Preliminary Prospective Observational Study

A non-invasive method for assessment of intravascular volume for optimal fluid administration is needed. We here conducted a preliminary study to confirm whether cardiac variation in the internal jugular vein (IJV), evaluated by ultrasound, predicts fluid responsiveness in patients in the emergency department. Patients who presented to the emergency department between August 2019 and March 2020 and required infusions were enrolled. We recorded a short-axis video of the IJV, respiratory variability in the inferior vena cava and stroke volume variations using the ClearSight System (Edwards Lifesciences, Irvine, CA, USA) before infusion of 500 mL of crystalloid fluid. Cardiac variations in the cross-sectional area of the IJV were measured by speckle tracking. Among the 148 patients enrolled, 105 were included in the final analysis. Fluid responsiveness did not correlate with the cardiac collapse index (13.6% vs. 16.8%, p = 0.24), but correlated with stroke volume variations (12.5% vs. 15.6%, p = 0.026). Although it is a simple correction, the cardiac collapse index correlated with stroke volume corrected by age (r = 0.25, p = 0.01), body surface area (r = 0.33, p = 0.002) and both (r = 0.35, p = 0.001). Cardiac variations in the IJV did not predict fluid responsiveness in the emergency department, but may reflect stroke volume.

The relationship between age shock index, and severity of stroke and in-hospital mortality in patients with acute ischemic stroke

BACKGROUND

Shock index (SI) has been reported to help us predict adverse prognosis in patients with acute ischemic stroke (AIS). However, the prognostic value of age SI and age modified shock index (MSI) in acute ischemic stroke is unknown. In our study, we aimed to examine the association between the severity of the stroke and in-hospital mortality, age SI and age MSI in patients with AIS.

METHODS

A total of 256 patients were enrolled in this study. The National Institutes of Health Stroke Scale (NIHSS) was used to determine the severity of stroke. Patients were divided into two groups according to the NIHSS score calculated during hospitalization (NIHSS>14: severe disability group, NIHSS<15: moderate and mild disability group). Shock indexes were calculated using the blood pressure and heart rate values measured as a result of the cardiovascular examinations of the patients. We looked for correlations between increased NIHSS and in-hospital mortality with age shock index and age modified shock index.

RESULTS

Age SI and age MSI values were higher in the severe disability group than those without severe disability, and the results were statistically significant (p<0.001, p<0.001, respectively). Also, a positive correlation was determined between the height of NIHSS and the age SI and the age MSI (p=0.002, r=0.197, p=0.001, r=0.215, respectively). Thirty-two (12.5%) of 256 patients included in the study died during hospitalization. Patients who died were older (77.1±11.0 vs. 67.5±13.5, respectively; p<0.001). According to Point-Biserial correlation analysis, there was a positive correlation between mortality and age SI, and age MSI (p<0.001, r=0.258 ve p<0.001, r=0.274, respectively).

CONCLUSIONS

As a result of our study, the relationship between stroke severity and increasing age SI and age MSI was significant and there was a positive correlation. In addition, there was a significant and positive relationship between in-hospital mortality and age SI and age MSI.

Modified Shock Index as Simple Clinical Independent Predictor of In-Hospital Mortality in Acute Coronary Syndrome Patients: A Retrospective Cohort Study

Introduction

Despite being the current most accurate risk scoring system for predicting in-hospital mortality for patients with acute coronary syndrome (ACS), the Global Registry of Acute Coronary Events (GRACE) risk score is time consuming due to the requirement for electrocardiography and laboratory examinations. This study is aimed to evaluate the association between modified shock index (MSI), as a simple and convenient index, with in-hospital mortality and revascularization in hospitalized patients with ACS.

Methods

A single-centered, retrospective cohort study, involving 1,393 patients with ACS aged ≥ 18 years old, was conducted between January 2018 and January 2022. Study subjects were allocated into two cohorts: high MSI ≥ 1 (n = 423) and low MSI < 1 group (n = 970). The outcome was in-hospital mortality and revascularization. The association between MSI score and interest outcomes was evaluated using binary logistic regression analysis. The area under the curve (AUC) between MSI and GRACE score was compared using De Long’s method.

Results

Modified shock index ≥ 1 had 61.1% sensitivity and 73.7% specificity. A high MSI score was significantly and independently associated with in-hospital mortality in patients with ACS [odds ratio (OR) = 2.72(1.6–4.58), p < 0.001]. However, ST-segment elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI) patients with high MSI did not significantly increase the probability of revascularization procedures. Receiver operating characteristic (ROC) analysis demonstrated that although MSI and GRACE scores were both good predictors of in-hospital mortality with the AUC values of 0.715 (0.666–0.764) and 0.815 (0.775–0.855), respectively, MSI was still inferior as compared to GRACE scores in predicting mortality risk in patients with ACS (p < 0.001).

Conclusion

Modified shock index, particularly with a score ≥ 1, was a useful and simple parameter for predicting in-hospital mortality in patients presenting with ACS.

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.

Modified Shock Index as a Predictor for Mortality and Hospitalization Among Patients With Dementia

BACKGROUND

One in four older adults in the Emergency Department (ED) suffers from severe cognitive impairment, creating great difficulty for the emergency physicians who determine the urgency of their patients' condition, which informs decisions regarding discharge or hospitalization.

OBJECTIVE

Our objective was to determine whether modified shock index (MSI) can be a clinical mortality and hospitalization predictor when applied to older patients with dementia in the ED.

METHODS

Included in the research were all patients with dementia, > 65 years old, who arrived at the Soroka University Medical Center ED during 2014-2017. The population was divided into three groups according to their MSI score, calculated as heart rate/mean arterial pressure: MSI < 0.7; 0.7 > MSI < 1.3; and MSI > 1.3. We performed multivariable logistic regression as a predictor of death within 30 days, Cox analysis for number of days to death, and a negative binominal regression for predicting the number of admission days.

RESULTS

Included were 1437 patients diagnosed with dementia. Patients with an MSI > 1.3 vs. those with MSI < 0.7 had an odds ratio of 8.23 (95% confidence interval [CI] 4.64-4.54) for mortality within 30 days, increased mortality risk within 180 days (hazard ratio 4.42; 95% CI 2.64-7.41), and longer hospitalization duration (incidence rate ratio 1.8; 95% CI 1.32-2.45).

CONCLUSIONS

High MSI scores were associated with high mortality rates and longer hospitalization duration for patients diagnosed with dementia who were > 65 years old. We suggest performing prospective studies utilizing the MSI score as an indicator in ED triage settings to classify patients with dementia by their severity of risk, to determine if this benefits health, minimizes expenses, and prevents unnecessary hospitalizations.

A Comprehensive Appraisal of Risk Prediction Models for Cardiogenic Shock

ABSTRACT

Despite advances in early revascularization, percutaneous hemodynamic support platforms, and systems of care, cardiogenic shock (CS) remains associated with a mortality rate higher than 50%. Several risk stratification models have been derived since the 1990 s to identify patients at high risk of adverse outcomes. Still, limited information is available on the differences between scoring systems and their relative applicability to both acute myocardial infarction and advanced decompensated heart failure CS. Thus, we reviewed the similarities, differences, and limitations of published CS risk prediction models and herein discuss their suitability to the contemporary management of CS care.

Detection of Hemodynamic Status Using an Analytic Based on an Electrocardiogram Lead Waveform

OBJECTIVES

Delayed identification of hemodynamic deterioration remains a persistent issue for in-hospital patient care. Clinicians continue to rely on vital signs associated with tachycardia and hypotension to identify hemodynamically unstable patients. A novel, noninvasive technology, the Analytic for Hemodynamic Instability (AHI), uses only the continuous electrocardiogram (ECG) signal from a typical hospital multiparameter telemetry monitor to monitor hemodynamics. The intent of this study was to determine if AHI is able to predict hemodynamic instability without the need for continuous direct measurement of blood pressure.

DESIGN

Retrospective cohort study.

SETTING

Single quaternary care academic health system in Michigan.

PATIENTS

Hospitalized adult patients between November 2019 and February 2020 undergoing continuous ECG and intra-arterial blood pressure monitoring in an intensive care setting.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

One million two hundred fifty-two thousand seven hundred forty-two 5-minute windows of the analytic output were analyzed from 597 consecutive adult patients. AHI outputs were compared with vital sign indications of hemodynamic instability (heart rate > 100 beats/min, systolic blood pressure < 90 mm Hg, and shock index of > 1) in the same window. The observed sensitivity and specificity of AHI were 96.9% and 79.0%, respectively, with an area under the curve (AUC) of 0.90 for heart rate and systolic blood pressure. For the shock index analysis, AHI's sensitivity was 72.0% and specificity was 80.3% with an AUC of 0.81.

CONCLUSIONS

The AHI-derived hemodynamic status appropriately detected the various gold standard indications of hemodynamic instability (hypotension, tachycardia and hypotension, and shock index > 1). AHI may provide continuous dynamic hemodynamic monitoring capabilities in patients who traditionally have intermittent static vital sign measurements.

Validation of the Shock Index, Modified Shock Index, and Shock Index-Paediatric age-Adjusted (SIPA) for predicting length of stay and outcome in children admitted to a paediatric intensive care unit

Background

Maintaining hemodynamic stability requires constant complex interaction between multiple vascular and extravascular factors. There are varieties of parameters that determine the same and few of them are used to predict the hemodynamic instability at earliest. Shock Index (SI), Modified Shock Index (MSI) and Shock Index-Pediatric age-Adjusted (SIPA) have been studied constantly in different clinical settings. They are best non-invasive measures for early prediction in resource poor setting or at community referral centers. We would like to compare the predictive value of each parameter in our tertiary care center.

Methods

It was a retrospective study carried out in PICU of a tertiary care centre and includes data collected from 15 August 2019 to 14 August 2021 over a period of 2 years. We recorded demographic data, age, gender, final diagnosis, outcome, and length of stay in PICU. We compared Outcome (Survived/Expired) and length of stay with SI ≥ 0.7 or < 0.7, MSI ≥ 1.3 or < 1.3 and SIPA > 1.22 or < 1.22 (age 4–6 years) > 1 or < 1 (7–12 years) and > 0.9 or < 0.9 (13–16 years).

Results

This study includes 235 children who were admitted to PICU during study period. The median age was 8 years the median length of stay was 5 days and mortality rate being 11.48% (27). Median SI, MSI were 0.78, 1.6 respectively. 61.70% (145) of patients had SI > 0.7. Median value of SI for septic shock patients was 0.92 on admission. The mortality of the patients with SI > 0.7 was 13.10% (19) and those with MSI > 1.3 was 14.89% (21). Mortality in accordance with SIPA for ages 4–6 years, 7–12 years, and 13–16 years were 15.25% (9), 23% (9) and 19.23% (5) respectively. Basically, SIPA was designed to monitor post trauma cases but in our study we got significant correlation with outcome and length of stay in conditions other than trauma.

Conclusions

The SI, MSI, and SIPA are simple bedside parameters may be used for prioritizing the patients who require strict monitoring on admission to PICU and intervention whenever required. These parameters were best in predicting the severity of sepsis and septic shock in comparison to other diagnosis. SIPA can be generalised for monitoring any high-risk case.

Prognostic utility of shock index and modified shock index on long-term mortality in acute decompensated heart failure; Persian Registry of cardioVascular diseasE/Heart Failure (PROVE/HF) study

BACKGROUND

Shock index (SI) and modified SI (MSI) are used for prognosis in patients with cardiovascular diseases (CVDs), especially myocardial infarction. However, the utility of these indices in heart failure(HF) is less frequently investigated. We aimed to evaluate the long-term prognostic capability of SI and MSI among Iranian HF patients.

METHODS

This retrospective cohort study was implemented in the context of the Persian Registry Of cardioVascular diseasE/HF (PROVE/HF). A total of 3896 acute decompensated HF (ADHF) patients were enrolled from March 2016 to March 2020. SI and MSI were assessed at admission. Receiver operating characteristic (ROC) and Kaplan-Meier curves were used to define optimum SI and MSI cut-off points and depict mortality during follow-up, respectively. The association of CVD death according to different SI and MSI cut-off points and quartiles was assessed through univariate and multivariate regression hazard models.

RESULTS

Mean age of participants was 70.22 ± 12.65 years (males: 62.1%). We found 0.66 (sensitivity:62%, specificity: 51%) and 0.87 (sensitivity: 61%, specificity: 51%) as optimised cut-off points for SI and MSI, respectively. Mean follow-up was 10.26 ± 7.5 months and 1110 (28.5%) deaths occurred during this time. Multivariate adjusted models revealed patients had SI ≥ 0.66 or within the third and fourth quartiles had higher likelihood of mortality compared to reference group (hazard ratio(HR): 1.58, 95%CI: 1.39-1.80, p < 0.001, HR: 1.38,95%CI:1.14-1.66, p = 0.001 and HR:2.00,95%CI:1.68-2.38, p < 0.001, respectively). MSI outcomes were similar (MSI ≥ 0.87: HR: 1.52,95%CI: 1.34-1.72, p < 0.001, third quartile (0.89 ≤ MSI < 1.00):HR:1.23,95%CI:1.009-1.50, p = 0.041, fourth quartile (MSI ≥ 1.00): HR: 1.80,95%CI: 1.53-2.13, p < 0.001). Kaplan-Meier curves showed patients with higher SI and MSI cut-off values and quartiles had lower survival rates.

CONCLUSION

Higher SI and MSI values were associated with increased mortality risk, and these two bedside indices could be appropriately considered for long-term prognosis in ADHF patients.

A New Time-Window Prediction Model For Traumatic Hemorrhagic Shock Based on Interpretable Machine Learning

ABSTRACT

Early warning prediction of traumatic hemorrhagic shock (THS) can greatly reduce patient mortality and morbidity. We aimed to develop and validate models with different stepped feature sets to predict THS in advance. From the PLA General Hospital Emergency Rescue Database and Medical Information Mart for Intensive Care III, we identified 604 and 1,614 patients, respectively. Two popular machine learning algorithms (i.e., extreme gradient boosting [XGBoost] and logistic regression) were applied. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the performance of the models. By analyzing the feature importance based on XGBoost, we found that features in vital signs (VS), routine blood (RB), and blood gas analysis (BG) were the most relevant to THS (0.292, 0.249, and 0.225, respectively). Thus, the stepped relationships existing in them were revealed. Furthermore, the three stepped feature sets (i.e., VS, VS + RB, and VS + RB + sBG) were passed to the two machine learning algorithms to predict THS in the subsequent T hours (where T = 3, 2, 1, or 0.5), respectively. Results showed that the XGBoost model performance was significantly better than the logistic regression. The model using vital signs alone achieved good performance at the half-hour time window (AUROC = 0.935), and the performance was increased when laboratory results were added, especially when the time window was 1 h (AUROC = 0.950 and 0.968, respectively). These good-performing interpretable models demonstrated acceptable generalization ability in external validation, which could flexibly and rollingly predict THS T hours (where T = 0.5, 1) prior to clinical recognition. A prospective study is necessary to determine the clinical utility of the proposed THS prediction models.

Outcomes of Trauma Patients Present to the Emergency Department with a Shock Index of ≥1.0

Introduction

The study aimed primarily to evaluate the association between the initial shock index (SI) ≥1.0 with blood transfusion requirement in the emergency department (ED) after acute trauma. The study's secondary aim was to look at the outcomes regarding patients' disposition from ED, intensive care unit (ICU) and hospital length of stay, and deaths.

Methods

It was a retrospective, cross-sectional study and utilized secondary data from the Saudi Trauma Registry (STAR) between September 2017 and August 2020. We extracted the data related to patient demographics, mechanism of injuries, the intent of injuries, mode of arrival at the hospital, characteristics on presentation to ED, length of stay, and deaths from the database and compared between two groups of SI <1.0 and SI ≥1.0. A P < 0.05 was statistically considered significant.

Results

Of 6667 patients in STAR, 908 (13.6%) had SI ≥1.0. With SI ≥1.0, there was a significantly higher incidence of blood transfusion in ED compared to SI <1.0 (8.9% vs. 2.4%, P < 0.001). Furthermore, SI ≥ 1.0 was associated with significant ICU admission (26.4% vs. 12.3%, P < 0.001), emergency surgical intervention (8.5% vs. 2.8%, P < 0.001), longer ICU stay (5.0 ± 0.36 vs. 2.2 ± 0.11days, P < 0.001), longer hospital stays (14.8 ± 0.61 vs. 13.3 ± 0.24 days, P < 0.001), and higher deaths (8.4% vs. 2.8%, P < 0.001) compared to the patient with SI <1.0.

Conclusions

In our cohort, a SI ≥ 1.0 on the presentation at the ED carried significantly worse outcomes. This simple calculation based on initial vital signs may be used as a screening tool and therefore incorporated into initial assessment protocols to manage trauma patients.

Modified Shock Index as an Indicator for Prognosis Among Sepsis Patients With and Without Comorbidities Presenting to the Emergency Department

OBJECTIVES

Modified shock index (MSI) is a simple bedside tool used in the emergency department. There are a few studies suggesting MSI as a good prognostic indicator than shock index in sepsis patients. However, there is not enough research emphasizing the role of MSI in patients with comorbidities. Hence, this study aims to assess the predictive validity of MSI in predicting the prognosis of sepsis patients with and without co-morbidities.

METHODS

From January to December 2020, a prospective observational study was conducted in a tertiary care teaching hospital. Patients with sepsis diagnosed based on systemic inflammatory response syndrome criteria and quick sequential organ failure assessment (qSOFA) were included. The need for mechanical ventilation and step down from the intensive care unit were outcome variables, MSI was considered as a predictor variable, and co-morbidities as an explanatory variable.

RESULTS

Among people with co-morbidities, the MSI value on arrival to the emergency department had fair predictive validity in predicting the need for mechanical ventilation after 24 hours, as indicated by the area under the curve of 0.749 (95% CI: 0.600-0.897; p-value = 0.002) and a sensitivity of 68.75% in predicting mechanical ventilation after 24 hours (MSI ≥ 1.59). Among people without co-morbidities, the MSI value on arrival to the emergency department had fair predictive validity in predicting the need for mechanical ventilation after 24 hours, as indicated by the area under the curve of 0.879 (95% CI: 0.770-0.988; p-value <0.001) and a sensitivity of 83.33% in predicting the need for mechanical ventilation after 24 hours (MSI ≥ 1.67).

CONCLUSION

MSI can be used as an indicator in predicting the prognosis of sepsis patients in the emergency department. A simple bedside calculation of the MSI can indicate the need for mechanical ventilation and step down from the intensive care unit after 24 hours in patients with co-morbidities and without co-morbidities.

The Pathophysiology and Management of Hemorrhagic Shock in the Polytrauma Patient

The recognition and management of life-threatening hemorrhage in the polytrauma patient poses several challenges to prehospital rescue personnel and hospital providers. First, identification of acute blood loss and the magnitude of lost volume after torso injury may not be readily apparent in the field. Because of the expression of highly effective physiological mechanisms that compensate for a sudden decrease in circulatory volume, a polytrauma patient with a significant blood loss may appear normal during examination by first responders. Consequently, for every polytrauma victim with a significant mechanism of injury we assume substantial blood loss has occurred and life-threatening hemorrhage is progressing until we can prove the contrary. Second, a decision to begin damage control resuscitation (DCR), a costly, highly complex, and potentially dangerous intervention must often be reached with little time and without sufficient clinical information about the intended recipient. Whether to begin DCR in the prehospital phase remains controversial. Furthermore, DCR executed imperfectly has the potential to worsen serious derangements including acidosis, coagulopathy, and profound homeostatic imbalances that DCR is designed to correct. Additionally, transfusion of large amounts of homologous blood during DCR potentially disrupts immune and inflammatory systems, which may induce severe systemic autoinflammatory disease in the aftermath of DCR. Third, controversy remains over the composition of components that are transfused during DCR. For practical reasons, unmatched liquid plasma or freeze-dried plasma is transfused now more commonly than ABO-matched fresh frozen plasma. Low-titer type O whole blood may prove safer than red cell components, although maintaining an inventory of whole blood for possible massive transfusion during DCR creates significant challenges for blood banks. Lastly, as the primary principle of management of life-threatening hemorrhage is surgical or angiographic control of bleeding, DCR must not eclipse these definitive interventions.

Risk Prediction in Cardiogenic Shock: Current State of Knowledge, Challenges and Opportunities

Cardiogenic shock (CS) is a condition associated with high mortality rates in which prognostication is uncertain for a variety of reasons, including its myriad causes, its rapidly evolving clinical course and the plethora of established and emerging therapies for the condition. A number of validated risk scores are available for CS prognostication; however, many of these are tedious to use, are designed for application in a variety of populations and fail to incorporate contemporary hemodynamic parameters and contemporary mechanical circulatory support interventions that can affect outcomes. It is important to separate patients with CS who may recover with conservative pharmacological therapies from those in who may require advanced therapies to survive; it is equally important to identify quickly those who will succumb despite any therapy. An ideal risk-prediction model would balance incorporation of key hemodynamic parameters while still allowing dynamic use in multiple scenarios, from aiding with early decision making to device weaning. Herein, we discuss currently available CS risk scores, perform a detailed analysis of the variables in each of these scores that are most predictive of CS outcomes and explore a framework for the development of novel risk scores that consider emerging therapies and paradigms for this challenging clinical entity.

In-hospital mortality of acute pulmonary embolism: Predictive value of shock index, modified shock index, and age shock index scores

OBJECTIVE

The shock index (SI), modified shock index (MSI), and age shock index (ASI) have been reported to predict adverse outcomes in patients with different acute cardiovascular conditions. This study aimed to investigate the association between these indexes and in-hospital mortality in patients with acute pulmonary embolism.

METHODS

The medical records of all adult patients who were hospitalized with acute pulmonary embolism between June 2014 and June 2019, were examined. Collected data included vital signs, demographic characteristics, comorbidities, and laboratory values on presentation. The predictive value of SI, MSI, ASI, and pulmonary embolism severity index (PESI) for predicting in-hospital mortality were compared by C-statistics.

RESULTS

A total of 602 consecutive patients (mean age 66.7±13.2 years, 55% female) were included, and 62 (10.3%) of the patients died during their in-hospital course. The admission SI, MSI, ASI, and PESI were significantly higher in the deceased patients. After adjusting for other factors, the SI, MSI, PESI, and ASI were independent predictors of in-hospital mortality. The prognostic performance of ASI (C-statistics 0.74) was better than MSI (C-statistics 0.71), SI (C-statistics 0.68), and PESI (C-statistics 0.65).

CONCLUSION

The ASI may be used to identify patients at risk for in-hospital mortality following acute pulmonary embolism.

Reverse shock index multiplied by Glasgow coma scale as a predictor of massive transfusion in trauma

BACKGROUND AND PURPOSE

Previous studies have identified that the reverse shock index multiplied by the Glasgow Coma Scale score (rSIG) is a good predictor of mortality in trauma patients. However, it is unknown if rSIG has utility as a predictor for massive transfusion (MT) in trauma patients. The present study evaluated the ability of rSIG to predict MT in trauma patients.

METHODS

This was a retrospective, observational study performed at a level 1 trauma center. Consecutive patients who presented to the trauma center emergency department between January 2016 and December 2018 were included. The predictive ability of rSIG for MT was assessed as our primary outcome measure. Our secondary outcome measures were the predictive ability of rSIG for coagulopathy, in-hospital mortality, and 24-h mortality. We compared the prognostic performance of rSIG with the shock index, age shock index, and quick Sequential Organ Failure Assessment.

RESULTS

In total, 1627 patients were included and 117 (7.2%) patients received MT. rSIG showed the highest area under the receiver operating characteristic (AUROC) curve (0.842; 95% confidence interval [CI], 0.806--0.878) for predicting MT. rSIG also showed the highest AUROC for predicting coagulopathy (0.769; 95% CI, 0.728-0.809), in-hospital mortality (AUROC 0.812; 95% CI, 0.772-0.852), and 24-h mortality (AUROC 0.826; 95% CI, 0.789-0.864). The sensitivity of rSIG for MT was 0.79, and the specificity of rSIG for MT was 0.77. All tools had a high negative predictive value and low positive predictive value.

CONCLUSION

rSIG is a useful, rapid, and accurate predictor for MT, coagulopathy, in-hospital mortality, and 24- h mortality in trauma patients.

Early Maladaptive Cardiovascular Responses are Associated with Mortality in a Porcine Model of Hemorrhagic Shock

BACKGROUND

Hemorrhage is a leading cause of death on the battlefield. Current methods for predicting hemodynamic deterioration during hemorrhage are of limited accuracy and practicality. During a study of the effects of remote ischemic preconditioning in pigs that underwent hemorrhage, we noticed arrhythmias among all pigs that died before the end of the experiment but not among surviving pigs. The present study was designed to identify and characterize the early maladaptive hemodynamic responses (tachycardia in the presence of hypotension without a corresponding increase in cardiac index or mean arterial blood pressure) and their predictive power for early mortality in this experimental model.

METHODS

Controlled hemorrhagic shock was induced in 16 pigs. Hemodynamic parameters were monitored continuously for 7 h following bleeding. Changes in cardiovascular and laboratory parameters were analyzed and compared between those that had arrhythmia and those that did not.

RESULTS

All animals had similar changes in parameters until the end of the bleeding phase. Six animals developed arrhythmias and died early, while 10 had no arrhythmias and survived longer than 6 h or until euthanasia. Unlike survivors, those that died did not compensate for cardiac output (CO), diastolic blood pressure (DBP), and stroke volume (SV). Oxygen delivery (DO2) and mixed venous saturation (SvO2) remained low in animals that had arrhythmia, while achieving certain measures of recuperation in animals that did not. Serum lactate increased earlier and continued to rise in all animals that developed arrhythmias. No significant differences in hemoglobin concentrations were observed between groups.

CONCLUSIONS

Despite similar initial changes in variables, we found that low CO, DBP, SV, DO2, SvO2, and high lactate are predictive of death in this animal model. The results of this experimental study suggest that maladaptive responses across a range of cardiovascular parameters that begin early after hemorrhage may be predictive of impending death, particularly in situations where early resuscitative treatment may be delayed.