# External validation of the CARDOT score for predicting respiratory complications after thoracic surgery

## TL;DR

This study validates a score called CARDOT for predicting respiratory complications after thoracic surgery and finds that adding a blood test (NLR) improves its accuracy.

## Contribution

The study externally validates the CARDOT score and demonstrates that adding preoperative neutrophil-to-lymphocyte ratio improves its predictive performance.

## Key findings

- The CARDOT score showed good discrimination (AuROC 0.758) in predicting respiratory complications in an external validation dataset.
- Adding a high neutrophil-to-lymphocyte ratio (NLR ≥ 4.5) improved the predictive performance of the CARDOT score (AuROC 0.775).
- The CARDOT score with NLR provides better prediction than the score alone, especially in settings without pulmonary function testing.

## Abstract

The CARDOT scores have been developed for prediction of respiratory complications after thoracic surgery. This study aimed to externally validate the CARDOT score and assess the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR) for postoperative respiratory complication.

A retrospective cohort study of consecutive thoracic surgical patients at a single tertiary hospital in northern Thailand was conducted. The development and validation datasets were collected between 2006 and 2012 and from 2015 to 2021, respectively. Six prespecified predictive factors were identified, and formed a predictive score, the CARDOT score (chronic obstructive pulmonary disease, American Society of Anesthesiologists physical status, right-sided operation, duration of surgery, preoperative oxygen saturation on room air, thoracotomy), was calculated. The performance of the CARDOT score was evaluated in terms of discrimination by using the area under the receiver operating characteristic (AuROC) curve and calibration.

There were 1086 and 1645 patients included in the development and validation datasets. The incidence of respiratory complications was 15.7% (171 of 1086) and 22.5% (370 of 1645) in the development and validation datasets, respectively. The CARDOT score had good discriminative ability for both the development and validation datasets (AuROC 0.789 (95% CI 0.753–0.827) and 0.758 (95% CI 0.730–0.787), respectively). The CARDOT score showed good calibration in both datasets. A high NLR (≥ 4.5) significantly increased the risk of respiratory complications after thoracic surgery (P < 0.001). The AuROC curve of the validation cohort increased to 0.775 (95% CI 0.750–0.800) when the score was combined with a high NLR. The AuROC of the CARDOT score with the NLR showed significantly greater discrimination power than that of the CARDOT score alone (P = 0.008).

The CARDOT score showed a good discriminative performance in the external validation dataset. An addition of a high NLR significantly increases the predictive performance of CARDOT score. The utility of this score is valuable in settings with limited access to preoperative pulmonary function testing.

The online version contains supplementary material available at 10.1186/s12871-024-02685-5.