Marius Drysch

Posttraumatic lymphedema is a frequent yet underrecognized complication of severe limb trauma and fractures. Although chronic inflammation is known to impair bone repair, it is entirely unknown whether lymphatic dysfunction itself affects skeletal regeneration. To date, no clinical or experimental data exist that directly link lymphedema to impaired bone healing. Using a validated rat model including both male and female animals, tibial bone defects were created with or without concomitant lymphatic vessel disruption. Bone regeneration was assessed by histology (aniline blue), Osteocalcin immunohistochemistry, and high-resolution micro-computed tomography (μCT). Mechanistic analyses included markers of osteoblast differentiation (RUNX2), remodeling-associated signaling (RANKL), endothelial/angiogenesis-associated signaling (PECAM-1), and cellular proliferation (PCNA), and multiplex Luminex-based cytokine and chemokine profiling. Posttraumatic lymphedema significantly impaired bone regeneration, evidenced by reduced osteoid formation, diminished Osteocalcin expression, and lower bone volume fraction on μCT (p = 0.0246). The PTL phenotype was associated with reduced osteoblast differentiation (RUNX2↓, p = 0.0038), reduced RANKL expression, consistent with altered remodeling-associated signaling (p = 0.0002), and decreased PECAM-1 expression (p = 0.0026), while PCNA expression remained unchanged. Luminex analysis revealed a distinct proinflammatory and chemotactic signature characterized by elevated TNF-α, IL-6, IL-12p70, MIP-1α, RANTES, MCP-1, and MIP-2.. This cytokine and chemokine upregulation occurred in both lymphedema groups – regardless of whether a bone defect was present – whereas animals with isolated bone defects showed only minimal inflammatory activation. This study provides experimental evidence that posttraumatic lymphedema is associated with impaired bone regeneration. The PTL phenotype was accompanied by a sustained proinflammatory and chemotactic microenvironment, reduced osteoblast differentiation, altered remodeling-associated signaling, and reduced PECAM-1 expression. These findings identify a previously unrecognized association between posttraumatic lymphatic dysfunction and skeletal repair and provide a basis for further mechanistic investigation.

Anastomotic angle and flow allocation change together in end-to-side junctions, complicating interpretation of angle-dependent wall shear. We used MITOS Flow Lab, a two-dimensional D2Q9 two-relaxation-time lattice-Boltzmann environment, to examine this coupling in steady, rigid-walled, Newtonian models at Re ≈ 91. Angles of 30–120° were compared under equal outlet pressures and at approximately matched branch-flow fractions of 0.25 and 0.21, achieved with angle-specific static outlet-pressure offsets. Under equal outlet pressures, the branch-flow fraction decreased from 0.356 to 0.151 across this angle range, while the minimum normalized signed recipient-floor shear increased from 0.140 to 0.450. Matching flow allocation substantially reduced angle-associated variation in this endpoint and in the sub-toe response, whereas sub-heel and sub-ostial responses remained angle dependent under the adjusted boundary conditions. This qualitative contrast persisted when the lumen resolution was increased from 32 to 64 nodes for the 0.25 target, although minimum-shear attenuation changed from approximately 83% to 74%. The 0.21 target was examined only on the production grid. These experiments demonstrate that the interpretation of angle-associated shear depends on the flow-allocation condition used for comparison. They do not identify a boundary-independent geometric effect or a causal mediation fraction. Absolute values and attenuation magnitudes remain sensitive to discretization and have not been independently validated. These controlled comparisons provide a framework for interpreting angle-associated shear together with achieved flow allocation and the specified outlet conditions.

Background: Timely re‐exploration is critical when free flaps show vascular compromise. However, the relative contribution of modifiable pre‐incision delays after surgery registration and opportunities to shorten time to re‐exploration within the recognition‐to‐incision pathway after flap ischaemia recognition remain uncertain. This study aimed to evaluate whether pre‐incision delays are associated with free‐flap salvage failure and to identify potential workflow targets for quality improvement. Methods: We conducted a retrospective, single‐center analysis of 113 free‐flap revision surgeries performed over the past 6 years. Time from registration to incision was partitioned into arrival latency (ward to operating room (OR)), anesthesia lead time, operating‐room preparation, and surgery lead time. Operative duration was assessed separately. The primary outcome was salvage versus failure (total loss). Results: Total flap loss occurred in 14.2% of re‐explorations. Median registration‐to‐incision time was similar between salvage and failure (78 min vs. 77 min, ±30 min, p = 0.89). Arrival latency (19 min vs. 20 min, ±17 min, p = 0.89), operating‐room preparation (25 min vs. 22 min, ±12 min, p = 0.66) and door to incision (52 min vs. 53 min, ±23.5 min, p = 0.5) showed no difference. Failures trended toward longer anesthesia lead time (28 vs. 38 min, ±16.7 min, p = 0.48) and operative duration (83 vs. 109 min, ±75 min, p = 0.12). Night‐time operations were not associated with failure, but weekend cases showed a higher proportion of failure (25% vs. 12%, p = 0.06, trend only). Conclusions: In this cohort, pre‐incision delays (arrival and OR preparation (prep)) were not associated with failure. Signals instead pointed toward patient and anesthetic complexity and technically challenging salvage procedures. Thus, quality improvement attempts should prioritize rapid recognition/decision pathways and anesthesia‐surgery coordination rather than focusing solely on logistics between ward and incision.

BACKGROUND Operative opportunity is the central but finite resource of surgical education, and departments must serve junior residents, senior residents, fellows, reduced-FTE trainees and clinician-scientists from the same theater time. Whether scheduling can expand education rather than ration it has rarely been tested in practice. OBJECTIVE To determine whether clinician-led hierarchical AI-informed operating room scheduling could scale surgical education while preserving resident access, equitable proportionality and departmental capacity. METHODS We studied 150 matched calendar weeks in a single academic plastic surgery department, 75 before and 75 after a hierarchical educational scheduling strategy took effect in January 2025. The strategy integrated trainee role, training year, contractual full-time equivalent (FTE), recent exposure and weekly capacity, and deliberately paired fellows with residents in complex procedures; final rosters were constructed and approved by the senior surgical leadership. Residents and fellows formed the educational population with time-varying postgraduate year and eligible FTE person-time as the denominator. Analyses used generalized estimating equations clustered by trainee with sensitivity analyses across alternative eligibility thresholds. RESULTS Total trainee operating days rose from 807 to 962 (+19.2%) while total departmental volume remained essentially stable (1503 and 1543 surgeon-days). The educational conversion rate, the share of departmental operative activity carrying a trainee, rose from 54% to 62%. Fellow operating days increased from 283 to 431 (52.3%) and absolute resident operating days were preserved at 524 and 531, giving a fellow-to-resident exposure ratio of 1.36 (95% CI 1.09-1.69) before and 1.71 (1.42-2.07) after implementation. Temporal regularity (residual variance ratio 0.93, 0.83-1.05) and weekly capacity (ratio 1.03, 0.97-1.10) were maintained. Operative exposure among trainees recorded as women remained closely proportional to their eligible FTE share, at 0.97 and 0.95, despite women holding the reduced-FTE trainee position in both periods and two of three reduced-FTE contracts departmentwide. As the cohort grew from 14 to 17, eligible person-time expanded faster than opportunity, so exposure per eligible resident week fell (adjusted rate ratio 0.81, 0.69-0.96; 0.90, 0.77-1.06 after standardization for training-year composition) and progression across resident training years attenuated from 1.17 (1.11-1.22) to 1.10 (0.99-1.23) per year, partly reflecting transition of senior trainees into fellowship. CONCLUSIONS Clinician-led hierarchical AI-informed scheduling scaled operative education without sacrificing its principal equity and capacity safeguards. Advanced fellow exposure increased by more than 50% while absolute resident operating volume was maintained, and operative access among women remained proportional to eligible FTE despite their greater representation in reduced-FTE employment. Deliberate fellow-resident pairing in complex surgery provides a scalable multilevel training model. Future iterations should ensure that operative opportunity grows proportionally with an expanding resident workforce and should protect progressive exposure across training years.

Background: Surgical residency training faces mounting pressure from expanding subspecialty knowledge requirements alongside compressed learning opportunities. Microlearning, defined as brief, focused educational episodes, offers a pedagogically sound approach suited to fragmented clinical schedules, while large language models present capabilities for scalable content generation. However, the feasibility, quality, and educational value of large language model–generated microlearning in surgical training remain unexplored. Objective: This study aimed to assess the feasibility and acceptability of artificial intelligence (AI)-generated microlearning modules among plastic surgery residents, evaluate content quality through systematic faculty evaluation, and generate preliminary effect size estimates for self-perceived knowledge and confidence changes. Methods: A single-arm pilot feasibility study with a pre-post design was conducted at an academic plastic surgery residency program (N=11 residents) over 12 weeks. Six modules covering core subspecialties were developed using Google Gemini 2.5 Pro. From 60 AI-generated multiple-choice questions, 42 were selected following independent evaluation by 2 board-certified plastic surgeons using a 5-dimension rubric (accuracy, relevance, clarity, pedagogical value, and safety). Modules were released biweekly via Google Forms. Outcomes included retention, acceptability (7-point Likert scales), faculty evaluation ratings, item-level psychometrics, and pre-post changes in self-perceived knowledge and confidence. Composite scores were calculated as the mean change across all 6 subspecialty topics. Wilcoxon signed-rank tests served as the primary analysis for matched pairs (n=9). Analyses were conducted using Python 3.11. Results: All 11 residents completed postassessments. Acceptability was high across all 6 subitems (all medians ≥5 out of 7). Faculty evaluation confirmed high content quality (mean quality index 4.68/5); interrater reliability was poor (intraclass correlation coefficient (3,1)=0.231). Among 9 matched pairs, composite confidence improved significantly (median change 0.33; d=0.65; P=.047), while composite knowledge showed a medium effect (d=0.71; P=.09). Topic-specific gains were largest where baseline was lowest: hand surgery knowledge (d=1.48; P=.02) and confidence (d=1.41; P=.02). Resource use and sense-of-community measures remained stable. Conclusions: AI-generated microlearning modules are feasible and acceptable for plastic surgery residency education. Faculty-evaluated content achieved high quality ratings (mean 4.68/5), and residents showed strong engagement with preliminary improvements in self-perceived confidence. The intervention was integrated into existing learning ecosystems without disrupting traditional resources or peer dynamics. These findings provide effect size estimates to support the design of adequately powered randomized trials.

Background: Expenditures for physiotherapy and extended outpatient physiotherapy (EAP) are increasing within Germany’s statutory accident insurance system (Berufsgenossenschaften), placing growing pressure on rehabilitation capacity and timely access to care. Digital health applications (DiGAs) are reimbursable nationwide and represent a novel component of routine rehabilitation pathways. However, their real-world system-level and economic effects in occupational rehabilitation remain insufficiently understood. Objective: This study aimed to evaluate how the integration of DiGAs into occupational rehabilitation pathways may influence costs, service capacity, and waiting times within routine care delivered by 5 German statutory accident insurance funds that cover 25.9 million insured individuals. Methods: Aggregated administrative data from 5 Berufsgenossenschaften (fiscal years 2023‐2024) were analyzed using a multilevel simulation framework combining (1) probabilistic cost-consequence modeling with Monte Carlo simulation (10,000 iterations), (2) an adherence-based adoption funnel distinguishing long-term engaged users (15%) and short-term users (85%) based on German claims data, and (3) a calibrated M/M/1 queuing model validated through discrete event simulation to estimate the effects on waiting times and system capacity. Primary outcomes included net financial impact, break-even thresholds, and changes in access-related performance metrics. Results: Combined physiotherapy and EAP expenditures reached €404 million (€1=US $1.18) in 2024, increasing by 10.1% year-over-year. The primary simulation (N=10,000 iterations) indicated mean annual net savings of €18.4 million (median €17.9 million) with a 90.7% probability of cost savings (95% uncertainty range: net cost of €8 million to net savings of €47.7 million). After incorporating adherence dynamics, the projected mean net savings were €16.2 million (95% CI €5-€29.8 million), corresponding to a 100% probability of positive financial impact within the modeled parameter space. Cost neutrality was maintained for DiGA prices up to €617.8 per prescription, nearly 40% above the base-case assumption of €450, indicating substantial economic robustness. Queuing analyses demonstrated that modest reductions in therapeutic demand decreased mean waiting times from 17.3 to 12.8 days (−26%), equivalent to approximately 120,000 cumulative patient waiting days saved annually across 26,705 EAP patients. The validation of discrete event simulation confirmed the magnitude and direction of analytic estimates. Conclusions: Under conservative assumptions, integrating digital therapeutics into occupational rehabilitation pathways is likely to generate both economic benefits and substantial system-level capacity gains. The break-even threshold of €617.80 per prescription provides a wide margin for pricing policy. Beyond cost effects, DiGAs may function as scalable capacity tools that alleviate systemic bottlenecks and improve timely access to rehabilitation services in capacity-constrained systems.

Background: Atrophic nonunion is a challenging complication of fracture healing with few noninvasive therapeutic options. Given that sphingosine-1-phosphate (S1P) regulates bone remodeling and angiogenesis, systemic S1P modulation may offer a regenerative strategy; however, its efficacy in nonunion has not been established. Questions/purposes: We therefore asked whether S1P lyase inhibition (1) enhances osteogenesis and consolidation in a murine critical-size bone defect model of atrophic nonunion, (2) modulates bone remodeling (osteoblast differentiation and osteoclast activity), and (3) augments cellular proliferation and endothelial activity, and (4) whether quantitative micro-CT corroborates histologically observed improvements. Methods: In a validated murine critical-size bone defect model of atrophic nonunion, 12-week-old male and female C57BL/6J mice were treated by continuous systemic administration of the S1P lyase inhibitor 4-deoxypyridoxine (DOP) for 5 weeks, while a reference group remained untreated after nonunion induction. Bone regeneration was assessed by histology and immunohistochemistry to evaluate osteoblast differentiation, osteoclast activity, cellular proliferation, and angiogenesis (n = 7 per group) and by high-resolution micro-CT to quantify newly formed bone within the defect region (n = 6 per group). Results: DOP treatment resulted in increased mineralized tissue and defect bridging on overview histology (aniline blue staining) compared with untreated controls (mean ± SD histologic bone formation score [pixels] DOP 80,000 ± 20,000 versus controls 52,000 ± 22,000, mean difference 28,000 [95% confidence interval (CI) 4200 to 53,000]; p = 0.03). Osteoblast differentiation was higher in DOP-treated animals (RUNX2 6200 ± 3200 versus 2200 ± 1400, mean difference 4000 [95% CI 1200 to 6900]; p = 0.01 and osteocalcin 60,000 ± 24,000 versus 28,000 ± 12,000, mean difference 32,000 [95% CI 9400 to 54,000]; p = 0.009), while osteoclast activity was also higher, indicating more active bone remodeling (TRAP 43,000 ± 15,400 versus 23,000 ± 7400, mean difference 20,000 [95% CI 6600 to 35,000]; p = 0.008). Cellular proliferation (PCNA 22,000 ± 7500 versus 14,000 ± 5700, mean difference 8000 [95% CI 470 to 16,000]; p = 0.04) and endothelial marker expression (PECAM-1 23,000 ± 6100 versus 13,700 ± 5500, mean difference 9300 [95% CI 2900 to 16,400]; p = 0.009) were both higher in the DOP group than in controls. Quantitative micro-CT confirmed greater newly formed bone volume within the defect region in DOP-treated mice compared with untreated controls (bone volume [%] 20.6 ± 8.2 versus 8.8 ± 3.3, mean difference 11.8 [95% CI 4.5 to 19.0]; p = 0.004). Conclusion: These results suggest that pharmacologic modulation of the S1P axis could represent a novel, noninvasive adjunct to surgical management of nonunions and delayed unions. Clinical Relevance: Key unanswered questions include optimal dosing, treatment duration, and safety of systemic S1P modulation beyond murine models. Addressing these questions in translational large-animal studies and early clinical trials will be essential to advance this approach toward clinical application.

BACKGROUND Expenditures for physiotherapy (PT) and extended outpatient physiotherapy (EAP) are increasing within Germany’s statutory accident insurance system (Berufsgenossenschaften, BGs), placing growing pressure on rehabilitation capacity and timely access to care. Digital health applications (DiGAs) are reimbursable nationwide and represent a novel component of routine rehabilitation pathways. However, their real-world system-level and economic effects in occupational rehabilitation remain insufficiently understood. OBJECTIVE This study aimed to evaluate how integration of DiGAs into occupational rehabilitation pathways may influence costs, service capacity, and waiting times within routine care. METHODS Aggregated administrative data from five BGs covering 25.9 million insured individuals (2023–2024) were analyzed using a multi-level simulation framework. The framework combined (1) probabilistic cost–consequence modeling with Monte Carlo simulation (10,000 iterations), (2) an adherence-based adoption funnel distinguishing long-term and short-term DiGA engagement, and (3) a calibrated M/M/1 queuing model validated through discrete-event simulation to estimate effects on waiting times and system capacity. Primary outcomes included net financial impact, break-even thresholds, and changes in access-related performance metrics. RESULTS Combined PT/EAP expenditures reached €404 million in 2024, increasing by 10.1% year over year. Simulation results indicated mean annual net savings of €18.4 million with a 90.7% probability of cost savings. After incorporating adherence dynamics, projected mean net savings were €16.2 million (95% CI €5.0–29.8 million), corresponding to a 100% probability of positive financial impact. Cost neutrality was maintained for DiGA prices up to €617.80 per prescription. Queuing analyses demonstrated that modest reductions in therapeutic demand could decrease mean waiting times from 17.3 to 12.8 days (−26%), equivalent to approximately 120,000 cumulative patient waiting days saved annually. CONCLUSIONS Under conservative assumptions, integrating digital therapeutics into occupational rehabilitation pathways is likely to generate both economic benefits and substantial system-level capacity gains. Beyond cost effects, DiGAs may function as scalable implementation tools that alleviate bottlenecks and improve timely access to rehabilitation services in capacity-constrained health systems.

Background: Postoperative free flap surveillance relies on clinical inspection or hardware-dependent adjuncts. Remote photoplethysmography offers a contactless alternative, but motion, lighting variation, specular reflection, and camera autoexposure can mimic perfusion signals. AI-Enhanced Transcutaneous Hemodynamic Evaluation for Reconstructive surgery (AETHER) combines per-patch spatial phase coherence, in-image reference correction, and augmented overlay visualization. Methods: We retrospectively analyzed bedside smartphone videos of 25 consecutive anterolateral thigh (ALT) free flaps treated between November 2025 and April 2026. No patient-level demographic, comorbidity, clinical-suspicion, or bedside-examination data entered the algorithm; AETHER was evaluated as a covariate-free, video-only signal-processing proof of concept. Flap and nonperfused reference regions of interest, each divided into 100 subregions, underwent plane-orthogonal-to-skin-based pulse extraction, band-pass filtering, and sliding-window correlation with a global mean reference. The Global Coherence Score (GCS) was defined as the percentage of synchronous subregions; corrected GCS was flap GCS minus reference GCS. Compromise was defined as clinically indicated surgical take-back with intraoperative confirmation of arterial compromise. Results: Six flaps had arterial compromise, and 19 were vital. Raw flap GCS and reference GCS did not separate groups (area under the receiver operating characteristic curve 0.62 and 0.36, respectively). Corrected GCS showed strong observed in-sample case-level separation (area under the receiver operating characteristic curve 0.96, 95% confidence interval 0.87 to 1.00). At an exploratory 17% cutoff, sensitivity was 0.83 and specificity 0.89; predictive values were prevalence-dependent. Conclusions: AETHER identified a video-derived perfusion-associated signal from routine smartphone video alone. These findings support covariate-free signal extraction but not recording-level diagnostic performance, lead time, or generalizability. Prospective validation is required before clinical use.