The reverse shock index multiplied by the Glasgow Coma Scale score can predict the need for initial resuscitation in patients suspected of sepsis

Reverse Shock Index multiplied by Glasgow Coma Scale score as a point-of-care severity assessment for initial trauma management: A nationwide cohort study

BACKGROUND

Severe trauma patients often require emergent interventions, such as massive transfusion, resuscitative procedures, and surgical procedures, and consume considerable human and medical resources. However, few practical indices can be easily used for emergent interventions. In recent years, it has become clear that rSIG (Reverse Shock Index multiplied by Glasgow Coma Scale [GCS] score), which can be easily calculated from vital signs, is a promising predictor of mortality. However, it is unclear whether rSIG is useful for emergent interventions.

METHODS

Data collected by the Japan Trauma Data Bank for adult patients admitted directly from the scene of trauma between April 2019 and December 2020 were analysed. The outcomes were massive transfusion, resuscitative procedures, surgical procedures and emergent interventions. Emergent interventions were defined as the composite outcome of massive transfusion, resuscitative procedures, and surgical procedures. The ability of rSIG to predict massive transfusion was compared with that of the ABC score and FASILA score by receiver-operating characteristic curve analysis. The ability of rSIG to predict resuscitative and surgical procedures was compared with that of the Shock Index (SI), GCS, Triage Revised Trauma score (T-RTS), and Previous Simple Prediction (PSP) score. The ability of rSIG to predict emergent interventions was compared with that of T-RTS, PSP, ABC, and FASILA. In addition to rSIG, rSIM (Reverse Shock Index multiplied by best motor response score) was also analysed as a supplement.

RESULTS

The study included 32,201 patients, 6,371 of whom required emergent interventions. The area under the receiver-operating characteristic curve (AUROC) for massive transfusion was highest for rSIG (0.846 [95 % confidence interval 0.832-0.859]) and significantly higher for rSIG than for rSIM, ABC and FASILA (all p < 0.0001). AUROCs for resuscitative and surgical procedures were highest for rSIG (0.777 [0.769-0.785] and 0.731 [0.720-0.741], respectively) and significantly higher than those for rSIM, SI, GCS, T-RTS, and PSP (all p < 0.0001). The AUROC for emergent interventions was highest for rSIG (0.760 [0.753-0.768]) and significantly higher for rSIG than for rSIM, T-RTS, PSP, ABC, or FASILA (all p < 0.0001).

CONCLUSIONS

rSIG is a simple and effective point-of-care predictor of emergent interventions during initial management of trauma.

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.