Header

UZH-Logo

Maintenance Infos

Zur Prognose der Schenkelhalsfraktur


Smektala, R; Ohmann, C; Paech, S; Neuhaus, E; Rieger, M; Schwabe, W; Debold, P; Deimling, A; Jonas, M; Hupe, K; Bücker-Nott, H J; Giani, G; Szucs, T D; Pientka, L (2005). Zur Prognose der Schenkelhalsfraktur. Der Unfallchirurg, 108(11):927-937.

Abstract

BACKGROUND: Data on the treatment of hip fractures in acute care settings have been collected in a report card system for quality assurance in Germany since the beginning of the 1990s. However, there are no data on the long-term outcome and long-term quality of care. MATERIAL AND METHOD: In a retrospective study, data on 1393 patients from 1999 were collected from different sources: from the department of quality assurance at the medical association of Westfalia-Lippe, the Statutory Health Insurance Funds (AOK), and the Medical Review Board of the Statutory Health Insurance Funds (Medizinischer Dienst der Krankenkasse, MDK). Statistical analyses were performed by the Center for Clinical Studies of the University of Düsseldorf. RESULTS: Uni- and multivariate analyses reveal the following prognostic parameters for survival after hip fracture: sex, age, nursing care dependency, living in a nursing home, risk stratification according to ASA, and postoperative complications. Timing of the operation had no affect on survival. CONCLUSIONS: Prognostic factors for the outcome after hip fracture can only be obtained by analyzing data from the hospital stay and the post-hospital setting as well. Chances of survival can be significantly improved by rehabilitative care.

Abstract

BACKGROUND: Data on the treatment of hip fractures in acute care settings have been collected in a report card system for quality assurance in Germany since the beginning of the 1990s. However, there are no data on the long-term outcome and long-term quality of care. MATERIAL AND METHOD: In a retrospective study, data on 1393 patients from 1999 were collected from different sources: from the department of quality assurance at the medical association of Westfalia-Lippe, the Statutory Health Insurance Funds (AOK), and the Medical Review Board of the Statutory Health Insurance Funds (Medizinischer Dienst der Krankenkasse, MDK). Statistical analyses were performed by the Center for Clinical Studies of the University of Düsseldorf. RESULTS: Uni- and multivariate analyses reveal the following prognostic parameters for survival after hip fracture: sex, age, nursing care dependency, living in a nursing home, risk stratification according to ASA, and postoperative complications. Timing of the operation had no affect on survival. CONCLUSIONS: Prognostic factors for the outcome after hip fracture can only be obtained by analyzing data from the hospital stay and the post-hospital setting as well. Chances of survival can be significantly improved by rehabilitative care.

Statistics

Citations

8 citations in Web of Science®
11 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

1 download since deposited on 10 Jun 2009
0 downloads since 12 months
Detailed statistics

Additional indexing

Other titles:On the prognosis of hip fractures. Assessment of mortality after hip fractures by analyzing overlapping segments of longitudinal data
Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:German
Date:21 July 2005
Deposited On:10 Jun 2009 11:48
Last Modified:05 Apr 2016 13:15
Publisher:Springer
ISSN:0177-5537
Additional Information:The original publication is available at www.springerlink.com
Publisher DOI:https://doi.org/10.1007/s00113-005-0972-6
PubMed ID:16034636

Download

Preview Icon on Download
Filetype: PDF - Registered users only
Size: 2MB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations