Literature DB >> 31823148

A novel id-iri score: development and internal validation of the multivariable community acquired sepsis clinical risk prediction model.

Husrev Diktas1, Serhat Uysal2, Hakan Erdem3, Yasemin Cag4, Egidia Miftode5, Gul Durmus6, Ayşegul Ulu-Kilic7, Selma Alabay7, Balint Gergely Szabo8, Botond Lakatos8, Ricardo Fernandez9, Pinar Korkmaz10, Michael Cruz Caliz9, Xavier Argemi11, Sholpan Kulzhanova12, Fatime Kormaz13, Fatma Yilmaz-Karadag4, Pinar Ergen4, Aynur Atilla14, Edmond Puca15, Mustafa Dogan16, Francesca Mangani17, Suzan Sahin18, Svjetlana Grgić19, Krsto Grozdanovski20, Gul Ruhsar Yilmaz21, Rosa Fontana Del-Vecchio22, Aslihan Demirel23, Fatma Sirmatel24, Alper Şener25, Suzan Sacar25, Emsal Aydin26, Ayşe Batirel18, Gorana Dragovac27, Rehab El-Sokkary28, Crişan Alexandru29, Selcan Arslan-Ozel30, Sibel Bolukcu31, H Deniz Ozkaya32, Saygin Nayman-Alpat33, Asuman Inan34, Fahad Al-Majid35, Berna Kaya-Ugur36, Jordi Rello37.   

Abstract

We aimed to develop a scoring system for predicting in-hospital mortality of community-acquired (CA) sepsis patients. This was a prospective, observational multicenter study performed to analyze CA sepsis among adult patients through ID-IRI (Infectious Diseases International Research Initiative) at 32 centers in 10 countries between December 1, 2015, and May 15, 2016. After baseline evaluation, we used univariate analysis at the second and logistic regression analysis at the third phase. In this prospective observational study, data of 373 cases with CA sepsis or septic shock were submitted from 32 referral centers in 10 countries. The median age was 68 (51-77) years, and 174 (46,6%) of the patients were females. The median hospitalization time of the patients was 15 (10-21) days. Overall mortality rate due to CA sepsis was 17.7% (n = 66). The possible predictors which have strong correlation and the variables that cause collinearity are acute oliguria, altered consciousness, persistent hypotension, fever, serum creatinine, age, and serum total protein. CAS (%) is a new scoring system and works in accordance with the parameters in third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). The system has yielded successful results in terms of predicting mortality in CA sepsis patients.

Entities:  

Keywords:  Community acquired; Scoring system; Sepsis; Sepsis-3; mortality

Year:  2019        PMID: 31823148     DOI: 10.1007/s10096-019-03781-y

Source DB:  PubMed          Journal:  Eur J Clin Microbiol Infect Dis        ISSN: 0934-9723            Impact factor:   3.267


  43 in total

1.  Early peak temperature and mortality in critically ill patients with or without infection.

Authors:  Paul Jeffrey Young; Manoj Saxena; Richard Beasley; Rinaldo Bellomo; Michael Bailey; David Pilcher; Simon Finfer; David Harrison; John Myburgh; Kathryn Rowan
Journal:  Intensive Care Med       Date:  2012-01-31       Impact factor: 17.440

2.  Application of the Third International Consensus Definitions for Sepsis (Sepsis-3) Classification: a retrospective population-based cohort study.

Authors:  John P Donnelly; Monika M Safford; Nathan I Shapiro; John W Baddley; Henry E Wang
Journal:  Lancet Infect Dis       Date:  2017-03-04       Impact factor: 25.071

3.  The meaning and use of the area under a receiver operating characteristic (ROC) curve.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1982-04       Impact factor: 11.105

4.  Community acquired infections among refugees leading to Intensive Care Unit admissions in Turkey.

Authors:  Mediha Turktan; Oznur Ak; Hakan Erdem; Dilek Ozcengiz; Sally Hargreaves; Safak Kaya; Emre Karakoc; Ozlem Ozkan-Kuscu; Gunay Tuncer-Ertem; Recep Tekin; Handan Birbicer; Gul Durmus; Canan Yilmaz; Funda Kocak; Edmond Puca; Jordi Rello
Journal:  Int J Infect Dis       Date:  2017-04-15       Impact factor: 3.623

5.  [A model based on random forests in prediction of 28-day prognosis in patients with severe sepsis/septic shock].

Authors:  Yang Wang; Shangzhong Chen; Caibao Hu; Changqin Chen; Jing Yan; Guolong Cai
Journal:  Zhonghua Wei Zhong Bing Ji Jiu Yi Xue       Date:  2017-12

6.  Assessment of the requisites of microbiology based infectious disease training under the pressure of consultation needs.

Authors:  Hakan Erdem; Suda Tekin-Koruk; Ibrahim Koruk; Derya Tozlu-Keten; Aysegul Ulu-Kilic; Oral Oncul; Rahmet Guner; Serhat Birengel; Gurkan Mert; Saygin Nayman-Alpat; Necla Eren-Tulek; Tuna Demirdal; Nazif Elaldi; Cigdem Ataman-Hatipoglu; Emel Yilmaz; Bilgul Mete; Behice Kurtaran; Nurgul Ceran; Oguz Karabay; Dilara Inan; Melahat Cengiz; Suzan Sacar; Behiye Yucesoy-Dede; Sibel Yilmaz; Canan Agalar; Yasar Bayindir; Yesim Alpay; Selma Tosun; Hava Yilmaz; Hurrem Bodur; Huseyin A Erdem; Nebahat Dikici; Murat Dizbay; Serkan Oncu; Nurbanu Sezak; Tuba Sari; Oguz R Sipahi; Serhat Uysal; Esma Yeniiz; Selcuk Kaya; Asim Ulcay; Halil Kurt; Bulent A Besirbellioglu; Haluk Vahaboglu; Yesim Tasova; Gaye Usluer; Dilek Arman; Husrev Diktas; Sercan Ulusoy; Hakan Leblebicioglu
Journal:  Ann Clin Microbiol Antimicrob       Date:  2011-12-16       Impact factor: 3.944

Review 7.  The pathophysiological basis and consequences of fever.

Authors:  Edward James Walter; Sameer Hanna-Jumma; Mike Carraretto; Lui Forni
Journal:  Crit Care       Date:  2016-07-14       Impact factor: 9.097

8.  A study on the efficacy of APACHE-IV for predicting mortality and length of stay in an intensive care unit in Iran.

Authors:  Mohammad Ghorbani; Haleh Ghaem; Abbas Rezaianzadeh; Zahra Shayan; Farid Zand; Reza Nikandish
Journal:  F1000Res       Date:  2017-11-20

9.  Patterns and early evolution of organ failure in the intensive care unit and their relation to outcome.

Authors:  Yasser Sakr; Suzana M Lobo; Rui P Moreno; Herwig Gerlach; V Marco Ranieri; Argyris Michalopoulos; Jean-Louis Vincent
Journal:  Crit Care       Date:  2012-11-16       Impact factor: 9.097

10.  Sepsis biomarkers in unselected patients on admission to intensive or high-dependency care.

Authors:  Martin J Llewelyn; Mario Berger; Mark Gregory; Ravi Ramaiah; Amanda L Taylor; Ingo Curdt; Frédéric Lajaunias; Rolf Graf; Stuart J Blincko; Stephen Drage; Jonathan Cohen
Journal:  Crit Care       Date:  2013-03-26       Impact factor: 9.097

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  3 in total

Review 1.  Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature.

Authors:  Brian J Douthit; Rachel L Walden; Kenrick Cato; Cynthia P Coviak; Christopher Cruz; Fabio D'Agostino; Thompson Forbes; Grace Gao; Theresa A Kapetanovic; Mikyoung A Lee; Lisiane Pruinelli; Mary A Schultz; Ann Wieben; Alvin D Jeffery
Journal:  Appl Clin Inform       Date:  2022-02-09       Impact factor: 2.342

2.  Effectiveness of automated alerting system compared to usual care for the management of sepsis.

Authors:  Zhongheng Zhang; Lin Chen; Ping Xu; Qing Wang; Jianjun Zhang; Kun Chen; Casey M Clements; Leo Anthony Celi; Vitaly Herasevich; Yucai Hong
Journal:  NPJ Digit Med       Date:  2022-07-19

3.  SOFA Score, Hemodynamics and Body Temperature Allow Early Discrimination between Porcine Peritonitis-Induced Sepsis and Peritonitis-Induced Septic Shock.

Authors:  Mahmoud Al-Obeidallah; Dagmar Jarkovská; Lenka Valešová; Jan Horák; Jan Jedlička; Lukáš Nalos; Jiří Chvojka; Jitka Švíglerová; Jitka Kuncová; Jan Beneš; Martin Matějovič; Milan Štengl
Journal:  J Pers Med       Date:  2021-02-28
  3 in total

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