Rana dijagnoza i optimizacija intraoperativnih strategija lečenja za uklještenje zadnje tibijalne tetive nakon preloma skočnog zgloba kod starijih osoba
Sažetak
Uvod/Cilj. Uklještenje zadnje tibijalne tetive (posterior tibial tendon – PTT) predstavlja retku, često nedovoljno prepoznatu, ali ozbiljnu komplikaciju složenih preloma skočnog zgloba. Cilj rada bio je da se utvrde karakteristike uklještenja PTT kod starijih pacijenata sa prelomima skočnog zgloba i da se uspostavi prediktivni model zasnovan na preoperativno dostupnim kliničkim i podacima medicinskih snimanja. Metode. U studiju je bilo uključeno ukupno 130 starijih pacijenata lečenih u periodu između 2019. i 2024. godine. Podaci su retrospektivno analizirani, a svi pacijenti su praćeni u minimalno 12 meseci. Koristeći intraoperativnu potvrdu kao zlatni standard, osnovni model logističke regresije (LR) zasnovan na kliničkim podacima upoređen je sa LR modelom unapređenim podacima medicinskih snimanja (koji uključuje broj fragmenata preloma i zahvaćenost omotača PTT), modelom „slučajne šume“ (random forest – RF) i algoritmima support vector machine (SVM). Učinak je validiran pomoću petostruke unakrsne validacije, površine ispod krive receiver operating characteristic (ROC) – AUC, kalibracije i analize krive odlučivanja (decision curve analysis – DCA). Rezultati. Uklještenje PTT registrovano je kod 29,2% (38/130) pacijenata, primarno lokalizovano u zadnjem delu preloma (68,4%) ili u medijalnom maleolusu (31,6%). Morfološki nalazi uključivali su jednostavno mehaničko uklještenje (50,0%), adheziju mekog tkiva (36,8%) i oštećenje površine tetive (13,1%). Model LR unapređen podacima medicinskih snimanja značajno je nadmašio osnovni model (AUC 0,89 vs. 0,72) i premašio modele RF (0,85) i SVM (0,88). DCA je pokazala visoku neto korist kroz različite nivoe rizika, a intraoperativni nalazi bili su u velikoj meri usklađeni sa predikcijama zasnovanim na medicinskim snimcima. Zaključak. Uklještenje PTT je česta pojava kod preloma skočnog zgloba kod starijih osoba. Prediktivni model unapređen podacima medicinskog snimanja, zasnovan na preoperativnoj morfologiji preloma dobijenoj kompjuterizovanom tomografijom i lokalnoj anatomiji, omogućava efikasnu procenu rizika, pružajući pouzdanu osnovu za ciljano intraoperativno istraživanje i strategije hirurškog lečenja.
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