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Showing posts with label score. Show all posts
Showing posts with label score. Show all posts

Tuesday, 21 May 2024

Critical Care bulletin - May 2024

 

Development and validation of the tic score for early detection of traumatic coagulopathy upon hospital admission: a cohort study

 by Louis Brac, Albrice Levrat, Charles-Hervé Vacheron, Pierre Bouzat, Tristan Delory and Jean-Stéphane David 

 Critical Care volume 28, Article number: 168, Published: 18 May 2024

 Background

Critically injured patients need rapid and appropriate hemostatic treatment, which requires prompt identification of trauma-induced coagulopathy (TIC) upon hospital admission. We developed and validated the performance of a clinical score based on prehospital resuscitation parameters and vital signs at hospital admission for early diagnosis of TIC.

Methods

The score was derived from a level-1 trauma center registry (training set). It was then validated on data from two other level-1 trauma centers: first on a trauma registry (retrospective validation set), and then on a prospective cohort (prospective validation set). TIC was defined as a PTratio > 1.2 at hospital admission. Prehospital (vital signs and resuscitation care) and admission data (vital signs and laboratory parameters) were collected. We considered parameters independently associated with TIC in the score (binomial logistic regression). We estimated the score’s performance for the prediction of TIC.

Results

A total of 3489 patients were included, and among these a TIC was observed in 22% (95% CI 21–24%) of cases. Five criteria were identified and included in the TIC Score: Glasgow coma scale < 9, Shock Index > 0.9, hemoglobin < 11 g.dL−1, prehospital fluid volume > 1000 ml, and prehospital use of norepinephrine (yes/no). The score, ranging from 0 and 9 points, had good performance for the identification of TIC (AUC: 0.82, 95% CI: 0.81–0.84) without differences between the three sets used. A score value < 2 had a negative predictive value of 93% and was selected to rule-out TIC. Conversely, a score value ≥ 6 had a positive predictive value of 92% and was selected to indicate TIC.

Conclusion

The TIC Score is quick and easy to calculate and can accurately identify patients with TIC upon hospital admission.

Wednesday, 5 January 2022

 

Predicting 90-day survival of patients with COVID-19: Survival of Severely Ill COVID (SOSIC) scores

by Matthieu Schmidt, Bertrand Guidet, Alexandre Demoule, Maharajah Ponnaiah, Muriel Fartoukh, Louis Puybasset, Alain Combes and David Hajage 

Annals of Intensive Care volume 11, Article number: 170 (2021) Published: 11 December 2021

 Background

Predicting outcomes of critically ill intensive care unit (ICU) patients with coronavirus-19 disease (COVID-19) is a major challenge to avoid futile, and prolonged ICU stays.

Methods

The objective was to develop predictive survival models for patients with COVID-19 after 1-to-2 weeks in ICU. Based on the COVID–ICU cohort, which prospectively collected characteristics, management, and outcomes of critically ill patients with COVID-19. Machine learning was used to develop dynamic, clinically useful models able to predict 90-day mortality using ICU data collected on day (D) 1, D7 or D14.

Results

Survival of Severely Ill COVID (SOSIC)-1, SOSIC-7, and SOSIC-14 scores were constructed with 4244, 2877, and 1349 patients, respectively, randomly assigned to development or test datasets. The three models selected 15 ICU-entry variables recorded on D1, D7, or D14. Cardiovascular, renal, and pulmonary functions on prediction D7 or D14 were among the most heavily weighted inputs for both models. For the test dataset, SOSIC-7’s area under the ROC curve was slightly higher (0.80 [0.74–0.86]) than those for SOSIC-1 (0.76 [0.71–0.81]) and SOSIC-14 (0.76 [0.68–0.83]). Similarly, SOSIC-1 and SOSIC-7 had excellent calibration curves, with similar Brier scores for the three models.

Conclusion

The SOSIC scores showed that entering 15 to 27 baseline and dynamic clinical parameters into an automatable XGBoost algorithm can potentially accurately predict the likely 90-day mortality post-ICU admission (sosic.shinyapps.io/shiny). Although external SOSIC-score validation is still needed, it is an additional tool to strengthen decisions about life-sustaining treatments and informing family members of likely prognosis.

 

 

 

 

Development of a new score for early mortality prediction in trauma ICU patients: RETRASCORE

 

by Luis Serviá, Juan Antonio Llompart-Pou, Mario Chico-Fernández, Neus Montserrat, Mariona Badia, Jesús Abelardo Barea-Mendoza, María Ángeles Ballesteros-Sanz and Javier Trujillano 

 

Critical Care volume 25, Article number: 420 (2021) Published: 07 December 2021

Background

Severity scores are commonly used for outcome adjustment and benchmarking of trauma care provided. No specific models performed only with critically ill patients are available. Our objective was to develop a new score for early mortality prediction in trauma ICU patients.

Methods

This is a retrospective study using the Spanish Trauma ICU registry (RETRAUCI) 2015–2019. Patients were divided and analysed into the derivation (2015–2017) and validation sets (2018–2019). We used as candidate variables to be associated with mortality those available in RETRAUCI that could be collected in the first 24 h after ICU admission. Using logistic regression methodology, a simple score (RETRASCORE) was created with points assigned to each selected variable. The performance of the model was carried out according to global measures, discrimination and calibration.

Results

The analysis included 9465 patients: derivation set 5976 and validation set 3489. Thirty-day mortality was 12.2%. The predicted probability of 30-day mortality was determined by the following equation: 1/(1 + exp (− y)), where y = 0.598 (Age 50–65) + 1.239 (Age 66–75) + 2.198 (Age > 75) + 0.349 (PRECOAG) + 0.336 (Pre-hospital intubation) + 0.662 (High-risk mechanism) + 0.950 (unilateral mydriasis) + 3.217 (bilateral mydriasis) + 0.841 (Glasgow ≤ 8) + 0.495 (MAIS-Head) − 0.271 (MAIS-Thorax) + 1.148 (Haemodynamic failure) + 0.708 (Respiratory failure) + 0.567 (Coagulopathy) + 0.580 (Mechanical ventilation) + 0.452 (Massive haemorrhage) − 5.432. The AUROC was 0.913 (0.903–0.923) in the derivation set and 0.929 (0.918–0.940) in the validation set.

Conclusions

The newly developed RETRASCORE is an early, easy-to-calculate and specific score to predict in-hospital mortality in trauma ICU patients. Although it has achieved adequate internal validation, it must be externally validated.