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Background <p>Thoracic trauma accounts for approximately 10–15% of trauma admissions and contributes substantially to trauma-related morbidity and mortality. Readmission rates for thoracic trauma have not been investigated thus far; thus, the purpose of this retrospective study is to reduce patient morbidity associated with thoracic trauma by defining readmission rates and predictors of readmission.</p> Methods <p>Patients admitted between 2019 and 2023 for predominant thoracic trauma were included and followed up for 2 months. Univariate analysis was performed to identify factors associated with readmission. Variables with <i>p</i> &lt; 0.20 were entered into a multivariable logistic regression model and used to derive the weighted READ score.</p> Results <p>A total of 634 patients were included; the mean age was 62.0 ± 19.2 years; the mean in-hospital stay was 6.5 ± 3.9 days; surgical procedures were needed in 3.8% of the patients, while 29.3% required chest tube placement. The overall mortality was 2.4%. Eighteen (2.8%) patients were readmitted to the hospital at the latest follow-up. The multivariate analysis revealed that a preoperative age &gt; 60 years, low falls, pneumothorax, and pulmonary embolism were independent predictors of readmission. The ability of the derived READ score to predict readmission was tested (AUC: 0.842). The discriminative capacity for the prediction of readmission was compared with that of the Thoracic Trauma Severity and Chest Trauma scores (0.651 and 0.637, respectively; <i>p</i> = 0.0004).</p> Conclusions <p>Unplanned readmission after thoracic trauma represents a clinically relevant outcome; the proposed prediction model may provide preliminary risk stratification and should be considered exploratory pending external validation for thoracic trauma patients and identify those who may benefit from closer follow-up and improved medical treatment.</p>

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Readmission to hospital after thoracic trauma: better safe than sorry! the predictive read score

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月2日

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  • Debora Brascia,
  • Doroty Sampietro,
  • Graziana Carleo,
  • Mirko Girolamo Cantatore,
  • Maria Luisa Zhurda,
  • Loredana D’Aucelli,
  • Naomi Savarelli,
  • Ondina Pizzuto,
  • Giuseppe Marulli,
  • Angela De Palma

摘要

Background

Thoracic trauma accounts for approximately 10–15% of trauma admissions and contributes substantially to trauma-related morbidity and mortality. Readmission rates for thoracic trauma have not been investigated thus far; thus, the purpose of this retrospective study is to reduce patient morbidity associated with thoracic trauma by defining readmission rates and predictors of readmission.

Methods

Patients admitted between 2019 and 2023 for predominant thoracic trauma were included and followed up for 2 months. Univariate analysis was performed to identify factors associated with readmission. Variables with p < 0.20 were entered into a multivariable logistic regression model and used to derive the weighted READ score.

Results

A total of 634 patients were included; the mean age was 62.0 ± 19.2 years; the mean in-hospital stay was 6.5 ± 3.9 days; surgical procedures were needed in 3.8% of the patients, while 29.3% required chest tube placement. The overall mortality was 2.4%. Eighteen (2.8%) patients were readmitted to the hospital at the latest follow-up. The multivariate analysis revealed that a preoperative age > 60 years, low falls, pneumothorax, and pulmonary embolism were independent predictors of readmission. The ability of the derived READ score to predict readmission was tested (AUC: 0.842). The discriminative capacity for the prediction of readmission was compared with that of the Thoracic Trauma Severity and Chest Trauma scores (0.651 and 0.637, respectively; p = 0.0004).

Conclusions

Unplanned readmission after thoracic trauma represents a clinically relevant outcome; the proposed prediction model may provide preliminary risk stratification and should be considered exploratory pending external validation for thoracic trauma patients and identify those who may benefit from closer follow-up and improved medical treatment.