Objective To compare the prognostic value of different types of simplified Pulmonary Embolism Severity Index (sPESI) in patients with acute pulmonary embolism (APE), so as to select the best scoring system for clinical application. Methods We retrospectively collected the data of consecutive patients with APE in the Fourth People’s Hospital of Zigong City from January 1st, 2014 to January 1st, 2019. The endpoint was 1-month all-cause mortality. We tried to modify sPESI by replacing arterial oxyhaemoglobin saturation with arterial partial pressure of oxygen / fraction of inspired oxygen (new scoring system named psPESI), and modify sPESI by replacing arterial oxyhaemoglobin saturation with saturation of pulse oxygen / fraction of inspired oxygen (new scoring system named ssPESI), and analyzed the area under the receiver-operating characteristic curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration and decision curve. Results A total of 280 patients (109 with low-risk APE, 155 with intermediate-risk APE, and 16 with high-risk APE) were enrolled in the study. Of these patients, 165 (58.93%) were male, and the 1-month all-cause mortality rate was 10.71% (30/280). The AUCs of sPESI, psPESI and ssPESI were 0.756, 0.822 and 0.807, respectively, and the AUC of ssPESI was higher than that of sPESI (P=0.038) but not lower than that of psPESI (P=0.388). Comparing ssPESI with sPESI, the NRI was 0.928 (P<0.001) and the IDI was 0.084 (P<0.001); comparing ssPESI with psPESI, the NRI was 0.041 (P=0.227) and the IDI was –0.028 (P=0.060). The psPESI (Hosmer-Lemeshow test χ2=12.591, P=0.182) and ssPESI (Hosmer-Lemeshow test χ2=4.204, P=0.897) were well-calibrated in the internal validation cohort and obtained more net benefits within wide threshold probabilities than sPESI. Conclusion Since the saturation of pulse oxygen is non-invasive and easy to obtain, and the predictive ability of ssPESI is similar to that of psPESI, it is recommended that ssPESI be used as a new scoring system to evaluate the prognosis of APE.
Objective To construct a nomogram model for predicting delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in emergency departments. Methods All patients with acute carbon monoxide poisoning who visited the Department of Emergency of Zigong Fourth People’s Hospital between June 1st, 2011 and May 31st, 2023 were retrospectively enrolled and randomly divided into a training set and a testing set in a 6∶4 ratio. LASSO regression was used to screen variables in the training set to establish a nomogram model for predicting DEACMP. The discrimination, calibration, and clinical practicality were compared between the nomogram and Glasgow Coma Scale (GCS) in the training and testing sets. Results A total of 475 patients with acute carbon monoxide poisoning were included, of whom 41 patients had DEACMP. Age, GCS and aspartate aminotransferase were selected as risk factors through LASSO regression, and a nomogram model was constructed based on these factors. The areas under the receiver operating characteristic curves for nomogram and GCS to predict DEACMP in the training set were 0.897 [95% confidence interval (CI) (0.829, 0.966)] and 0.877 [95%CI (0.797, 0.957)], respectively; and those for nomogram and GCS to predict DEACMP in the testing set were 0.925 [95%CI (0.865, 0.985)] and 0.858 [95%CI (0.752, 0.965)], respectively. Compared with GCS, the performance of nomogram in the training set (net reclassification index=0.495, P=0.014; integrated discrimination improvement=0.070, P=0.011) and testing set (net reclassification index=0.721, P=0.004; integrated discrimination improvement=0.138, P=0.009) were both positively improved. The calibration of nomogram in the training set and testing set was higher than that of GCS. The decision curves in the training set and testing set showed that the nomogram had better clinical net benefits than GCS. Conclusion The age, GCS and aspartate aminotransferase are risk factors for DEACMP, and the nomogram model established based on these factors has better discrimination, calibration, and clinical practicality compared to GCS.