Classification by SOFA score revealed that CFT was slower (P = 0.017) and MCF weaker (P = 0.005) in patients with more severe organ failure (SOFA ≥ 10, CFT 125 ± 76 seconds, and MCF 57 ± 11 mm) as compared with patients who had lower SOFA scores (SOFA <10, CFT 69 ± 27, and MCF 68 ± 8).
The ranking of the classifications by InfoKeep score remained virtually unchanged from the overall analysis and was similar between the two subgroups.
In fact, when we divided all patients into 10 groups based on their disease activity ranks within the cohort, as measured using the different scores, we found statistical agreement that was indicative of high clinical conformity of classifications by different scores.
Disease classification by the different scoring schemes is summarized in Table 3.
Benign/malignant classification by BI-RADS scoring of greyscale ultrasound scans and by shear wave elastography using the defined cutoff value were compared with histology to give figures for sensitivity, specificity, positive and negative predictive values (PPV and NPV) and accuracy.
First, our data demonstrate that generally the distribution of gender, tumor localization, histotype, KIT status, mitotic rate, median tumor size and risk classification by different risk scores are similar between patients younger or older than 50 years at time of diagnosis, in concordance with data of large series of GIST patients [ 10, 15].
Disease classifications by clinical scores on day 7 after challenge were: not affected (0 0.70), slightly affected (0.71 7.13), moderately affected (7.14 13.56), severely affected (>13.56).
Disease classifications by clinical scores on day 21 were: not affected (0 2.00), slightly affected (2.01-34.7), moderaffectedfected (34.71-67.3) and severely affected (>67.3).
Cumulative clinical scores were calculated for each pig as a sum of daily clinical scores from day of arrival to infection (day 0), from day 0 to 4 and from day 0 to 21. Disease classifications by clinical scores on day 0 and 4 were: not affected (0 0.70), slightly affected (0.71-7.13), moderaffectedfected (7.14-13.56) and severely affected (>13.56).
Treating these probabilities as scores, and sorting the results by score to generate rankings, enables us to consider classification systems as a scoring system that have a score function and a rank function.
