Funktionelles Outcome nach perkutaner Achillessehnennaht

Hintergrund: Nach einer Achillessehnenruptur (ASR) verändern sich die Eigenschaften der Sehne, was sich langfristig auf die Kinematik und Kraftentwicklung im Unterschenkel und Sprunggelenk auswirken kann. Hypothese: Das Ziel der vorliegenden Studie war es, die strukturellen Veränderungen der Sehnen-Muskel-Einheit nach minimalinvasiver Behandlung der ASR zu untersuchen und ihre Auswirkungen auf die Patientenzufriedenheit sowie objektiven funktionellen Ergebnissen zu evaluieren. Methodik: Im Zeitraum von 2003 bis 2010 wurden insgesamt 190 Patienten mittels perkutaner Achillessehnennaht versorgt. Hiervon wählten wir zufällig 20 Patienten mit einem Durchschnittsalter von 41,3 Jahre aus. Nach einem mittleren Nachuntersuchungszeitraum von 43,1 Monaten (Bereich, 2 bis 6 Jahre) wurden die Sehnensteifigkeit, Elongation und Dehnbarkeit mittels Ultraschall und Dynamometrie evaluiert. Dreidimensionale Bewegungen in den Sprunggelenken und die bei der Bewegung entstandenen Drehmomente wurden mittels computergestützter Ganganalyse bestimmt. Die subjektiven Parameter und die klinische Untersuchung wurden standardisiert mittels Patient related outcome measurements (PROMs) erfasst. Ergebnisse: Die verletzte Achillessehne zeigte insgesamt eine erhöhte Steifigkeit (335,7 ± 132,6 N/mm vs. 198,6 ± 34,0 N / mm; p <0,001), Länge (213,3 ± 29,4 mm vs. 198,5 ± 21,8 mm, p = 0,009) und eine veränderte Kinematik (Dorsalextension: 10,9 ± 2,4 zu 9,7 ± 3,2°, p= 0,015; Plantarflexion: 19,3 ± 7,0 zu 22,9 ±5,5°, p=0,002). Trotz hoher Zufriedenheit der Patienten nach bis zu 6 Jahren zeigte sich eine signifikante Muskelatrophie der Wadenmuskulatur (36,5 ± 3,0 cm vs. 38,3 ± 2,4 cm, p <0,001), die sich ab einer Umfangsdifferenz von 2cm auch auf die PROMs auswirkte. Schlussfolgerung: Nach der operativen Versorgung von Achillessehnenrupturen mittels perkutaner Naht zeigten sich, trotz hoher Patientenzufriedenheit, funktionelle Defizite, die u.a. auf eine Veränderung der Sehnenstruktur zurückzuführen waren.Background: After an Achilles tendon rupture (ASR), the characteristics of the tendon change, which in the long term can affect the kinematics and force development in the lower leg and ankle joints. Hypothesis: The aim of the present study was to investigate the structural changes in the tendon-muscle unit after minimally invasive treatment of ASR and to evaluate their effects on patient satisfaction and objective functional outcomes. Methodology: In the period from 2003 to 2010, a total of 190 patients were treated with percutaneous Achilles tendon suture. Of these, we randomly selected 20 patients with a mean age of 41.3 years. After a mean follow-up of 43.1 months (range, 2 to 6 years), tendon stiffness, elongation and strain were evaluated by ultrasound and dynamometry. Three-dimensional movements in the hocks and the torques created during the movement were determined by means of computer aided gait analysis. The subjective parameters and clinical examination were standardized using patient-related outcome measurements (PROMs). Results: Overall, the injured Achilles tendon showed increased stiffness (335.7 ± 132.6 N / mm vs. 198.6 ± 34.0 N / mm, p <0.001), length (213.3 ± 29.4 mm vs. 198 , 5 ± 21.8 mm, p = 0.009) and altered kinematics (dorsiflexion: 10.9 ± 2.4 to 9.7 ± 3.2 °, p = 0.015, plantarflexion: 19.3 ± 7.0 to 22.9 ± 5.5 °, p = 0.002). Despite high satisfaction of the patients after up to 6 years, significant muscle atrophy of the calf muscles (36.5 ± 3.0 cm vs. 38.3 ± 2.4 cm, p <0.001) was found, which also differed from a circumference difference of 2 cm impacted on the PROM's. Conclusion: After the surgical treatment of Achilles tendon ruptures by percutaneous suture, despite high patient satisfaction, functional deficits, which were due to a change in the tendon structure

Retrospective analysis of treatment decisions and clinical outcome of Lisfranc injuries: operative vs. conservative treatment

Purpose: Lisfranc injuries are rare and often pose a challenge for surgeons, particularly in initially missed or neglected cases. The evidence on which subtypes of Lisfranc injuries are suitable for conservative treatment or should undergo surgery is low. The aim of this study was to retrospectively analyze treatment decisions of Lisfranc injuries and the clinical outcome of these patients within the last ten years. Methods: All patients treated due to a Lisfranc injury in a German level I trauma centre from January 2011 until December 2020 were included in this study. Radiologic images and medical data from the patient files were analyzed concerning the classification of injury, specific radiologic variables, such as the Buehren criteria, patient baseline characteristics, and patient outcome reported with the Foot Function Index (FFI). Results: Ninety-nine patients were included in this study (conservative = 20, operative = 79). The overall clinical outcome assessed by the FFI was good (FFI sum 23.93, SD 24.93); patients that were identified as suitable for conservative treatment did not show inferior functional results. Qualitative radiological factors like the grade of displacement and the trauma mechanism were more strongly associated with the decision for surgical treatment than quantitative radiologic factors such as the distance from the first to the second metatarsal bone. Conclusion: If the indication for conservative or operative treatment of Lisfranc injuries is determined correctly, the clinical outcome can be comparable. These decisions should be based on several factors including quantitative and qualitative radiologic criteria, as well as the trauma mechanism

Muscle Fascicles Exhibit Limited Passive Elongation Throughout the Rehabilitation of Achilles Tendon Rupture After Percutaneous Repair

Achilles tendon rupture (ATR) results in long-term functional and structural deficits, characterized by reduced ankle mobility and plantarflexor muscle atrophy. However, it remains unclear how such functional impairments develop after surgical repair. While it is known that this injury negatively affects the tendon's function, to date, limited work has focused on the short-term effect of ATR on the structure of the muscles in series. The aim of this study was to characterize changes in medial gastrocnemius architecture and its response to passive lengthening during the post-surgical rehabilitative period following ATR. Both injured and contralateral limbs from 10 subjects (1 female, BMI: 27.2 ± 3.9 kg/m2; age: 46 ± 10 years) with acute, unilateral ATR were assessed at 8, 12, and 16 weeks after percutaneous surgical repair. To characterize the component tissues of the muscle-tendon unit, resting medial gastrocnemius muscle thickness, fascicle length, and pennation angle were determined from ultrasound images with the ankle in both maximal plantarflexion and dorsiflexion. The ankle range of motion (ROM) was determined using motion capture; combined ultrasound and motion capture determined the relative displacement of the musculotendinous junction (MTJ) of the AT with the medial gastrocnemius. The ATR-injured gastrocnemius muscle consistently exhibited lower thickness, regardless of time point and ankle angle. Maximal ankle plantarflexion angles and corresponding fascicle lengths were lower on the injured ankle compared to the contralateral throughout rehabilitation. When normalized to the overall ankle ROM, both injured fascicles and MTJ displacement exhibited a comparably lower change in length when the ankle was passively rotated. These results indicate that when both ankles are passively exposed to the same ROM following ATR surgery, both ipsilateral Achilles tendon and gastrocnemius muscle fascicles exhibit limited lengthening compared to the contralateral MTU tissues. This appears to be consistent throughout the rehabilitation of gait, suggesting that current post-operative rehabilitative exercises do not appear to induce muscle adaptations in the affected MTU

Use of artificial intelligence in sports medicine: a report of 5 fictional cases

Background Artificial intelligence (AI) is one of the most promising areas in medicine with many possibilities for improving health and wellness. Already today, diagnostic decision support systems may help patients to estimate the severity of their complaints. This fictional case study aimed to test the diagnostic potential of an AI algorithm for common sports injuries and pathologies. Methods Based on a literature review and clinical expert experience, five fictional “common” cases of acute, and subacute injuries or chronic sport-related pathologies were created: Concussion, ankle sprain, muscle pain, chronic knee instability (after ACL rupture) and tennis elbow. The symptoms of these cases were entered into a freely available chatbot-guided AI app and its diagnoses were compared to the pre-defined injuries and pathologies. Results A mean of 25–36 questions were asked by the app per patient, with optional explanations of certain questions or illustrative photos on demand. It was stressed, that the symptom analysis would not replace a doctor’s consultation. A 23-yr-old male patient case with a mild concussion was correctly diagnosed. An ankle sprain of a 27-yr-old female without ligament or bony lesions was also detected and an ER visit was suggested. Muscle pain in the thigh of a 19-yr-old male was correctly diagnosed. In the case of a 26-yr-old male with chronic ACL instability, the algorithm did not sufficiently cover the chronic aspect of the pathology, but the given recommendation of seeing a doctor would have helped the patient. Finally, the condition of the chronic epicondylitis in a 41-yr-old male was correctly detected. Conclusions All chosen injuries and pathologies were either correctly diagnosed or at least tagged with the right advice of when it is urgent for seeking a medical specialist. However, the quality of AI-based results could presumably depend on the data-driven experience of these programs as well as on the understanding of their users. Further studies should compare existing AI programs and their diagnostic accuracy for medical injuries and pathologies.Peer Reviewe

Decision support by machine learning systems for acute management of severely injured patients: A systematic review

Introduction Treating severely injured patients requires numerous critical decisions within short intervals in a highly complex situation. The coordination of a trauma team in this setting has been shown to be associated with multiple procedural errors, even of experienced care teams. Machine learning (ML) is an approach that estimates outcomes based on past experiences and data patterns using a computer-generated algorithm. This systematic review aimed to summarize the existing literature on the value of ML for the initial management of severely injured patients. Methods We conducted a systematic review of the literature with the goal of finding all articles describing the use of ML systems in the context of acute management of severely injured patients. MESH search of Pubmed/Medline and Web of Science was conducted. Studies including fewer than 10 patients were excluded. Studies were divided into the following main prediction groups: (1) injury pattern, (2) hemorrhage/need for transfusion, (3) emergency intervention, (4) ICU/length of hospital stay, and (5) mortality. Results Thirty-six articles met the inclusion criteria; among these were two prospective and thirty-four retrospective case series. Publication dates ranged from 2000 to 2020 and included 32 different first authors. A total of 18,586,929 patients were included in the prediction models. Mortality was the most represented main prediction group (n = 19). ML models used were artificial neural network ( n = 15), singular vector machine (n = 3), Bayesian network (n = 7), random forest (n = 6), natural language processing (n = 2), stacked ensemble classifier [SuperLearner (SL), n = 3], k-nearest neighbor (n = 1), belief system (n = 1), and sequential minimal optimization (n = 2) models. Thirty articles assessed results as positive, five showed moderate results, and one article described negative results to their implementation of the respective prediction model. Conclusions While the majority of articles show a generally positive result with high accuracy and precision, there are several requirements that need to be met to make the implementation of such models in daily clinical work possible. Furthermore, experience in dealing with on-site implementation and more clinical trials are necessary before the implementation of ML techniques in clinical care can become a reality

Robotic observation pipeline for small bodies in the solar system based on open-source software and commercially available telescope hardware

The observation of small bodies in the Space Environment is an ongoing important task in astronomy. While nowadays new objects are mostly detected in larger sky surveys, several follow-up observations are usually needed for each object to improve the accuracy of orbit determination. In particular objects orbiting close to Earth, so called Near-Earth Objects (NEOs) are of special concern as a small but not negligible fraction of them can have a non-zero impact probability with Earth. Additionally, the observation of manmade space debris and tracking of satellites falls in the same class measurements. Telescopes for these follow-up observations are mainly in a aperture class between 1 m down to approximately 25 cm. These telescopes are often hosted by amateur observatories or dedicated companies like 6ROADS specialized on this type of observation. With upcoming new NEO search campaigns by very wide field of view telescopes, like the Vera C. Rubin Observatory, NASA’s NEO surveyor space mission and ESA’s Flyeye telescopes, the number of NEO discoveries will increase dramatically. This will require an increasing number of useful telescopes for follow-up observations at different geographical locations. While well-equipped amateur astronomers often host instruments which might be capable of creating useful measurements, both observation planning and scheduling, and also analysis are still a major challenge for many observers. In this work we present a fully robotic planning, scheduling and observation pipeline that extends the widely used open-source cross-platform software KStars/Ekos for Instrument Neutral Distributed Interface (INDI) devices. The method consists of algorithms which automatically select NEO candidates with priority according to ESA’s Near-Earth Object Coordination Centre (NEOCC). It then analyses detectable objects (based on limiting magnitudes, geographical position, and time) with preliminary ephemeris from the Minor Planet Center (MPC). Optimal observing slots during the night are calculated and scheduled. Immediately before the measurement the accurate position of the minor body is recalculated and finally the images are taken. Besides the detailed description of all components, we will show a complete robotic hard- and software solution based on our methods.TS-R acknowledges funding from the NEO-MAPP project (H2020-EU-2-1-6/870377). This work was (partially) funded by the Spanish MICIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” by the “European Union” through grant RTI2018-095076-B-C21, and the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia “María de Maeztu”) through grant CEX2019-000918-M

Global Carbon Budget 2022

Accurate assessment of anthropogenic carbon dioxide (CO$_2$) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO$_2$ emissions (E$_{FOS}$) are based on energy statistics and cement production data, while emissions from land-use change (E$_{LUC}$), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO$_2$ concentration is measured directly, and its growth rate (G$_{ATM}$) is computed from the annual changes in concentration. The ocean CO$_2$ sink (S$_{OCEAN}$) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO$_2$ sink (S$_{LAND}$) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (B$_{IM}$), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, E$_{FOS}$ increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr$^{−1}$ (9.9 ± 0.5 GtC yr$^{−1}$ when the cement carbonation sink is included), and E$_{LUC}$ was 1.1 ± 0.7 GtC yr$^{−1}$, for a total anthropogenic CO$_2$ emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr$^{−1}$ (40.0 ± 2.9 GtCO$_2$). Also, for 2021, G$_{ATM}$ was 5.2 ± 0.2 GtC yr$^{−1}$ (2.5 ± 0.1 ppm yr$^{−1}$), S$_{OCEAN}$ was 2.9  ± 0.4 GtC yr$^{−1}$, and S$_{LAND}$ was 3.5 ± 0.9 GtC yr$^{−1}$, with a B$_{IM}$ of −0.6 GtC yr$^{−1}$ (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO$_2$ concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in E$_{FOS}$ relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO$_2$ concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr$^{−1}$ persist for the representation of annual to semi-decadal variability in CO$_2$ fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO$_2$ flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b)