Journal of Emergencies, Trauma, and Shock最新文献

Acute kidney injury (AKI) is a common and severe complication in severe burns. Preexisting chronic kidney disease (CKD) can make the management more challenging. We present the management strategy adopted in such a case, highlighting the adaptations in fluid resuscitation, dialysis, and septicemia prevention. The case involved the 2^nd and 3^rd degree burns covering 53% body surface, in a patient with preexisting CKD and hypertension. Despite initial fluid resuscitation, the patient developed AKI. Sustained low-efficiency dialysis (SLED) was started, along with nutritional support using buttermilk diet. Aggressive antibiotic prophylaxis was initiated based on wound swabs culture and sensitivity. Wound debridement was deferred and daily dressing with silver nitrate gel and moisture-retaining film was used. Debridement and grafting were performed on postburn days 43 and 65. The patient was discharged after 80 days, with healed wounds. Our approach included meticulous fluid and nutrition supplementation coupled with SLED and appropriate wound management coupled with aggressive antimicrobial prophylaxis to prevent septicemia.

Introduction: Acute trauma resuscitation is challenging and disorganized in low- and middle-income countries as there is lack of evidence-based transfusion practices with respect to ratio, volume, trigger, cutoff points for various triggers. This study aims to study the patterns of blood use in various mechanisms of injury, by interfacility transfer status and define triggers for transfusion of various blood components. Prospective observational study, emergency department of level 1 trauma center (August 2017-August 2018).

Methods: Demographic, injury, clinical, laboratory, transfusion characteristics, and patient outcomes were collected from electronic hospital records and transfusion service records. We used multivariate logistic regression to identify triggers of transfusion of red blood cells, plasma, platelets (PLTs), cryoprecipitate, and mortality predictors.

Results: Among 986 severely injured patients 80% were males, 92% had blunt injuries and commonest trauma was Head. The median length of intensive care unit stay and hospital stay were more in a referred group. Patients brought to center directly received more massive transfusions (56, 13.05% vs. 48, 8.62%). Railway track injuries received the most total median packed red blood cells (PRBCs) units in both groups. The triggers for various blood product transfusions include: Hematocrit < 32.08 for PRBC, PT >16.9 s for plasma, PLT count <130 lakhs for platelets, MAP <89.7 mmHg and PT >18.2 s for cryoprecipitate.

Conclusion: Railway track injuries with inferior extremity injuries required maximum transfusion requirements and were a trigger for PRBC, plasma, PLTs, and cryoprecipitate. Smartphone-based apps and transfusion prediction models can be framed based on the triggers and cut points.

Introduction: The objective of this study is to compare bed-up-head-elevated (BUHE) position with supine sniffing position (SSP) in patients undergoing rapid sequence intubation (RSI) using direct laryngoscopy in the emergency department (ED).

Methods: This single-center randomized controlled superiority trial was carried out from September 2021 to December 2022 in an academic emergency medicine department. The patients undergoing RSI in ED were grouped into two arms, namely BUHE position and SSP. The primary outcome was the time taken for endotracheal intubation. The secondary outcomes were the first-pass success rates and postintubation complications.

Results: A total of 136 patients were enrolled in the study. Time for intubation in the BUHE group was no different from SSP (32.09 s [interquartile range (IQR): 23.30-42.68] vs. 33.40 [IQR: 27.53-45.90], P = 0.17). There was a modest reduction in intubation time when performed by trained experts (22.5 s [IQR: 17.7-25.3] versus 30.3 s [IQR: 21.3-33.2], P = 0.04). The first-attempt success rate in the BUHE position was also similar to the SSP position ([91.18% vs. 90.91%] P = 0.958). Postintubation complications were lesser in BUHE compared to the SSP group ([7.4% vs. 19.7%] P = 0.04).

Conclusions: In our study, BUHE position did not improve time to intubation and first-pass success rate in ED patients compared to SSP. A modest decrease in intubation time was noted while experts used the BUHE position. The postintubation complications were slightly lesser in the BUHE group.

[This corrects the article on p. 157 in vol. 15, PMID: 36643772.].

Introduction: Full outline of unresponsiveness (FOUR) score has advantages over Glasgow Coma Scale (GCS); as it can be used in intubated patients and provides greater neurological details. It has been studied mainly in the trauma and neuroscience setting. Our primary objective was to compare the FOUR versus GCS score as predictors of mortality at 30 days and poor functional outcome at 3 months among nontrauma patients in the emergency department (ED).

Methods: This prospective observational study was conducted on adult patients presenting with altered mental status (duration <7 days) in the ED (March 2019-November 2020). Data collection included demographic and clinical features, the GCS and FOUR scores, the feasibility of acquiring and interpreting FOUR on a Likert scale, duration of hospital stay, 30-day mortality, and functional outcome at 3 months on the modified Rankin Scale. Trained emergency medicine residents managing the patient collected the data. The area under receiver's operating characteristics curve (AUROC) was used to compare the accuracy of the GCS and FOUR scores in predicting outcomes. The FOUR score equivalent of GCS cutoffs for categorizing neurological impairment (mild, moderate, and severe) was also investigated.

Results: Two hundred and ninety-one patients were included, with a mean age of 50.3 years and 67.4% males. Most patients (40.2%) had altered mental status for 1-3 days and hepatic encephalopathy was the most common ED diagnosis. The mortality at 30 days was 66.7% (194 of 291), and 88% (256 of 291) of patients had poor functional outcomes at 3 months. The AUROCs for predicting 30-day mortality were similar for both the scores (GCS: 0.70, FOUR: 0.71, and the P value for difference: 0.9). Similarly, the AUROCs for predicting 3-month poor functional outcome were 0.683 and 0.669 using GCS and FOUR, respectively, with a nonsignificant difference (P = 0.82). The FOUR score strata of 14-16, 11-13, and 0-10 were found to be equivalent to the GCS scores of 13-15 (mild), 9-12 (moderate), and 3-8 (severe). The feasibility of acquiring and interpreting GCS and FOUR scores on the Likert scale was found to be "easy."

Conclusion: The FOUR score is similar to GCS in predicting mortality at 30 days and poor neurological outcomes at 3 months among nontrauma patients of ED. Moreover, it was found that the FOUR score is "easy" to assess and interpret by the emergency residents.

Introduction: Acute liver injury (ALI) is a common complication of sepsis and is associated with adverse clinical outcomes. We aimed to develop a model to predict the risk of ALI in patients with sepsis after hospitalization.

Methods: Medical records of 3196 septic patients treated at the Lishui Central Hospital in Zhejiang Province from January 2015 to May 2023 were selected. Cohort 1 was divided into ALI and non-ALI groups for model training and internal validation. The initial laboratory test results of the study subjects were used as features for machine learning (ML), and models built using nine different ML algorithms were compared to select the best algorithm and model. The predictive performance of model stacking methods was then explored. The best model was externally validated in Cohort 2.

Results: In Cohort 1, LightGBM demonstrated good stability and predictive performance with an area under the curve (AUC) of 0.841. The top five most important variables in the model were diabetes, congestive heart failure, prothrombin time, heart rate, and platelet count. The LightGBM model showed stable and good ALI risk prediction ability in the external validation of Cohort 2 with an AUC of 0.815. Furthermore, an online prediction website was developed to assist healthcare professionals in applying this model more effectively.

Conclusions: The Light GBM model can predict the risk of ALI in patients with sepsis after hospitalization.