Turkish
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
HPB 2019-Apr

Nomogram for predicting postoperative pancreatic fistula.

Sadece kayıtlı kullanıcılar makaleleri çevirebilir
Giriş yapmak kayıt olmak
Bağlantı panoya kaydedilir
Yunghun You
In Han
Dong Choi
Jin Heo
Youngju Ryu
Dae Park
Seong Choi
Sunjong Han

Anahtar kelimeler

Öz

Previous studies analyzed risk factors for postoperative pancreatic fistula (POPF) and developed risk prediction tool using scoring system. However, no study has built a nomogram based on individual risk factors. This study aimed to evaluate individual risks of POPF and propose a nomogram for predicting POPF.From 2007 to 2016, medical records of 1771 patients undergoing pancreaticoduodenctomy were reviewed retrospectively. Variables with p < 0.05 in multivariate logistic regression analysis were included in the nomogram. Internal performance validation was executed using a repeated cross validation method.Of 1771 patients, 222 (12.5%) experienced POPF. In multivariable analysis, sex (p = 0.004), body mass index (BMI) (p < 0.001), ASA score (p = 0.039), preoperative albumin (p = 0.035), pancreatic duct diameter (p = 0.002), and location of tumor (p < 0.001) were identified as independent predictors for POPF. Based on these six variables, a POPF nomogram was developed. The area under the curve (AUC) estimated from the receiver operating characteristic (ROC) graph was 0.709 in the train set and 0.652 in the test set.A POPF nomogram was developed. This nomogram may be useful for selecting patients who need more intensified therapy and establishing customized treatment strategy.

Facebook sayfamıza katılın

Bilim tarafından desteklenen en eksiksiz şifalı otlar veritabanı

  • 55 dilde çalışır
  • Bilim destekli bitkisel kürler
  • Görüntüye göre bitki tanıma
  • Etkileşimli GPS haritası - bölgedeki bitkileri etiketleyin (yakında)
  • Aramanızla ilgili bilimsel yayınları okuyun
  • Şifalı bitkileri etkilerine göre arayın
  • İlgi alanlarınızı düzenleyin ve haber araştırmaları, klinik denemeler ve patentlerle güncel kalın

Bir belirti veya hastalık yazın ve yardımcı olabilecek bitkiler hakkında bilgi edinin, bir bitki yazın ve karşı kullanıldığı hastalıkları ve semptomları görün.
* Tüm bilgiler yayınlanmış bilimsel araştırmalara dayanmaktadır

Google Play badgeApp Store badge