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result(s) for
"Spiegel, Lena"
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Evaluation of modified and newly applied patella height indices in primary total knee arthroplasty
by
Schreiner, Anna Janine
,
Spiegel, Lena
,
Schmidutz, Florian
in
Arthroplasty (knee)
,
Classification
,
Correlation coefficients
2023
ObjectiveThe aim of this radiological study was to compare several relevant modified and newly applied patella height indices (PHI) in navigated primary total knee arthroplasty (TKA) to determine intra- and interobserver reliability in order to give a recommendation for clinical application in measuring patella height (PH) in primary TKA.Materials and methodsA retrospective data analysis assessing different PHI (modified Insall-Salvati index (mISI), Caton-Deschamps index (mCDI), Blackburne-Peel index (mBPI), Plateau-Patella Angle (mPPA); Miura-Kawaramura index (MKI), Knee-Triangular index (KTI)) on lateral knee radiographs was performed by two blinded observers using the same software three months pre- and postoperatively. Concordance correlation coefficient and Pearson’s correlation respectively were determined for intra- and interobserver rating as well as a categorization according to Landis and Koch and Cohen.ResultsA total of 337/291 patients of a 5-year period could be analyzed pre-/postoperatively. Excellent postoperative interrater results according to the categorization of Landis and Koch were achieved for the mBPI (Pearson 0.98) > mPPA (0.90) > KTI (0.86), good results for the MKI (0.79) and the mCDI (0.69), and moderate results for the mISI (0.52) with a predominantly strong Cohen correlation in almost all cases. Preoperatively, the mBPI and the KTI were the best interrated PHI. No PH changes could be found postoperatively for the mISI, KTI, MKI, and mPPA.ConclusionThe mBPI, the mPPA, and the KTI can be recommended for PH assessment in TKA. The mPPA might be the easiest one to use in a daily clinical set-up.
Journal Article
Prehabilitation of elderly frail or pre-frail patients prior to elective surgery (PRAEP-GO): study protocol for a randomized, controlled, outcome assessor-blinded trial
2022
Background
Frailty is expressed by a reduction in physical capacity, mobility, muscle strength, and endurance. (Pre-)frailty is present in up to 42% of the older surgical population, with an increased risk for peri- and postoperative complications. Consequently, these patients often suffer from a delayed or limited recovery, loss of autonomy and quality of life, and a decrease in functional and cognitive capacities. Since frailty is modifiable, prehabilitation may improve the physiological reserves of patients and reduce the care dependency 12 months after surgery.
Methods
Patients ≥ 70 years old scheduled for elective surgery or intervention will be recruited in this multicenter, randomized controlled study, with a target of 1400 participants with an allocation ratio of 1:1. The intervention consists of (1) a shared decision-making process with the patient, relatives, and an interdisciplinary and interprofessional team and (2) a 3-week multimodal, individualized prehabilitation program including exercise therapy, nutritional intervention, mobility or balance training, and psychosocial interventions and medical assessment. The frequency of the supervised prehabilitation is 5 times/week for 3 weeks. The primary endpoint is defined as the level of care dependency 12 months after surgery or intervention.
Discussion
Prehabilitation has been proven to be effective for different populations, including colorectal, transplant, and cardiac surgery patients. In contrast, evidence for prehabilitation in older, frail patients has not been clearly established. To the best of our knowledge, this is currently the largest prehabilitation study on older people with frailty undergoing general elective surgery.
Trial registration
ClinicalTrials.gov
NCT04418271
. Registered on 5 June 2020. Universal Trial Number (UTN): U1111-1253-4820
Journal Article
The language of exoplanet ranking metrics needs to change
2017
We have found many Earth-sized worlds but we have no way of determining if their surfaces are Earth-like. This makes it impossible to quantitatively compare habitability, and pretending we can risks damaging the field.
Journal Article
Utilizing Machine Learning to Optimize Metal-Organic Framework-Derived Polymer Membranes for Gas Separation
2023
Metal-organic frameworks (MOFs) have gained substantial attention as promising materials for gas separation membranes due to their exceptional porosity, tailorability, and functionalizability. In this study, we present a novel approach to further enhance the properties of porous polymer membranes emerging from MOFs through crosslinking of the organic linker molecules and subsequent metal-atom removal. To ensure reproducibility of the multi-step synthesis process and high quality of the resulting polymeric membranes, we automated the process and followed a machine learning optimization approach. The high-quality MOF-thin films (SURMOFs) were prepared in a layer-by-layer fashion directly on gold-coated porous alumina substrates. This direct synthesis proved crucial to preserve the structural integrity of the membranes and thus avoiding defect formation caused by a substrate-transfer process, which is usually required when advanced materials are used to fabricate a membrane. The initial SURMOF membrane exhibits moderate gas separation performance, once crosslinked, its gas selectivity could be significantly enhanced although with the compromise of lower gas permeance. Interestingly, once we removed the metal centers and thereby converted the SURMOF into a purely organic polymeric membrane, the membrane gas permeance could be restored almost to its initial condition while preserving the enhanced selectivities. In particular, the resulting polymeric membrane outperforms most commercially available polymer membranes for H2 /CO2 gas separation. This research outlines a promising approach to employ MOFs as template in the generation of advanced polymer membranes for various gas and liquid phase separation applications.
The language of exoplanet ranking metrics needs to change
2017
We have found many Earth-sized worlds but we have no way of determining if their surfaces are Earth-like. This makes it impossible to quantitatively compare habitability, and pretending we can risks damaging the field.