Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials.We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the “5 Sense Score (5SS),” a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians’ choice of therapeutic intervention and the patient outcome.The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction . The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information.Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery. An important publication by Astner-Rohracher et al. recently suggested the need to compare new methods for guiding therapy against clinical predictions based upon the pre-implant data alone20. The group’s “5-Sense Score” was able to predict seizure focality in patients prior to invasive electrode implantation with an AUC of 0.67. This modest but important result validates the need to proceed with IEEG recording in these patients, is easy to apply across centers, and provides a floor of accuracy (null model) against which additional methods should be benchmarked to demonstrate value.Standard practice is to answer the above questions at a multidisciplinary surgical conference, where IEEG, brain imaging, and supportive metadata are reviewed manually. Unfortunately, the outcomes of these discussion vary from center to center, making it difficult to aggregate data across institutions for retrospective analysis and prospective clinical trials. A number of groups, including ours, are working on quantitative methods to guide therapy, but to our knowledge, none have yet performed strongly enough or been validated in prospective, large-scale trials to be used in routine clinical practice19. As quantitative methods are typically compared to clinical experts, we chose to compare our results to expert determinations of seizure focality, choice of therapy, and patient outcome.In emphasizing quantitative measures, our group and others hope to give clinicians rigorous, reliable tools to aid in clinical decision making, to improve our understanding of human epileptogenic networks, and to improve standardization across centers that will facilitate large-scale, multi-center clinical trials of existing and new invasive therapies as they arise25 Additionally, exclusively using ictal data for localization in the acute inpatient setting may be misleading.27 While there have been several attempts to use quantitative interictal IEEG biomarkers to predict outcome following epilepsy surgery, using these measures to look at the simpler question of whether these networks are focal or distributed remains unexplored. Addressing this question may obviate the need for ictal recording if the decision is between focal intervention or more central neuromodulation.Clinicians localize epileptic networks with IEEG by inducing seizures to measure their onset and spread patterns . Although interictal or seizure-free IEEG data are not routinely used to classify epilepsy during surgical evaluation, quantitative analysis of interictal segments has proven valuable for localization.28 To test this hypothesis, we classified patients into either focal or non-focal groups based on clinical assessments of IEEG focality. The focal group comprised patients with a focal seizure-onset zone on IEEG, while the non-focal group included those with bilateral, multifocal, broad, or non-localized seizure onset zones. We incorporated the 5-SENSE Score, which summarizes noninvasive clinical variables to predict focality,29 and implemented a measure quantifying the spatial density of both the implanted IEEG electrodes as well as their associated abnormalities. We then used our calculated measures to predict ultimate therapy and surgical outcome, hypothesizing that poor outcomes and palliative therapies are more common in patients with non-focal epileptic networks.In this study, we aimed to determine whether a quantitative analysis of interictal IEEG data could predict the focality of epileptic networks on IEEG better than pre-implant estimates. We hypothesized that the spatial dispersion of abnormalities, quantified through interictal IEEG using a normative atlas, would correlate with the focality of epileptic networks.We analyzed 101 drug-resistant epilepsy patients from The Hospital of the University of Pennsylvania who underwent pre-surgical evaluation and IEEG. Patients were enrolled serially between 2011 and 2021 after providing written informed consent for IEEG data analysis, in line with the University of Pennsylvania’s IRB-approved protocol (reference number 821778). Patient characteristics are shown in 29 We then summarized these variables using the recently proposed 5-SENSE score29, which combines five pre-implant clinical variables that were found to predict SEEG focality: a) extent of the lesion on magnetic resonance imaging, b) extent of the ictal discharge, c) extent of interictal epileptiform discharges (IEDs), d) strength of localizing semiology, and e) localization of neuropsychological deficit. More details on 5-SENSE score are available elsewhere29.We curated information from each patient’s written clinical notes on: (1) scalp EEG seizure laterality and localization, (2) scalp EEG spike laterality and localization, (3) MRI lesion status, laterality, localization, and type (4) neurophysiological testing for language dysfunction lateralization, (5) semiology lateralization and localization. These non-invasive clinical variables aided in formulating hypotheses about the localization and lateralization of epileptic networks.Following the previous non-invasive phase, IEEG electrodes were implanted to target the epileptic network. Patients were admitted to EMU for IEEG implantation, and seizures were induced to determine the laterality and localization of seizure focus. From discharge summaries and multidisciplinary conference notes, we determined whether the IEEG-defined seizure onset zone was classified as focal, bilateral, multifocal, broad, non-localized, or missed. Based on this data, 65 patients were focal and 36 were non-focal. The non-focal group included those with bilateral, multifocal (2 or more discrete onset zones), broad (lobar or multi-lobar), non-localized, or missed seizure onset zones.The choice of therapy—resection, ablation, or stimulation—was determined by weighing the risk-benefit ratio between achieving seizure freedom and potential neurological or cognitive deficits. Generally, patients found to have focal seizure onset on IEEG received surgery, and patients categorized as non-focal received neuromodulatory devices, but exceptions were seen: patients with suspicion for multifocal seizures underwent surgery if a key node was thought to be mediating, and focal patients underwent device implantation if seizure onset occurred in the eloquent cortex. Post-surgical ILAE outcomes were derived at 2 years. 30 This tool enables automatic labeling, registration, and reconstruction of iEEG electrode coordinates on brain images. In brief, each electrode contact was semi-automatically labeled on CT images, which were then registered to pre-implant T1-weighted MRI. Brain segmentation and parcellation were conducted in each subject’s native space using Freesurfer.30 Electrodes were classified as being in grey matter, white matter, or outside the brain. We excluded all electrodes located in white matter and outside the brain. For all grey matter electrodes, we determined their corresponding regions based on the Desikan-Killiany parcellation scheme in the patient’s native-space.We implemented iEEG-recon, a modular software tool, to reconstruct IEEG electrode contacts on pre-implant T1-weighted MRI images.32 We obtained these clips from IEEG.org and applied bipolar referencing. The data was processed using a 3rd order Butterworth bandpass filter between 0.5 and 80Hz, a 60Hz notch filter, and down sampled to 200Hz. We calculated relative band power  and magnitude squared coherence (IEEG connectivity) in 5 canonical bands , as well as total broadband (0.5–80Hz) power and coherence, using a 2s Hamming window with a 1s overlap. These preprocessing steps are identical to those in our previous work21, with the only exception being that we selected 20 interictal IEEG clips and performed the analysis on all 20 clips to ensure temporal robustness of our quantitative methods.We selected 20 one-minute interictal IEEG clips for each patient’s stay in the Epilepsy Monitoring Unit.31 These clips were randomly chosen, excluding three days post-implantation and two hours from any seizure annotation to minimize implant effects and peri-ictal changes during awake periods. To detect awake periods in iEEG, we applied an alpha/delta power ratio  detector, previously described for identifying the highest probability of wakefulness.21Normative modeling is an innovative case-control approach that quantifies abnormalities in a patient’s IEEG signals by determining how deviant they are from the normal range expected in controls. As IEEG is rarely implanted in patients without epilepsy, we created a normative IEEG atlas by concatenating 2304 electrodes implanted outside epileptogenic tissues, which were presumed healthy, across 144 patients. This normative IEEG atlas has been described in our previous work and is publicly available.21We quantified interictal IEEG abnormalities from both IEEG spectral activity and connectivity. Briefly, for each IEEG contact’s relative band power in each canonical frequency band, we calculated the Z-score from the electrodes in the same parcellated ROI in the normative IEEG atlas. Similarly, for iEEG coherence connectivity between two ROIs in each frequency band, we computed the Z-score of equivalent connections between the same ROIs in the normative iEEG atlas. Z-score represents the deviation from normal IEEG spectral activity and coherence. We repeated these steps for all 20 one-minute interictal clips, computing a distribution of Z-scores for iEEG activity and connectivity. These steps are identical to those in our previous work and are explained in detail there.The pre-implant clinical hypothesis regarding the focality of the epileptic network influences the spatial coverage of the IEEG implant. In cases where epileptic networks are likely focal, the density of IEEG may be more concentrated in areas believed to be involved in seizure generation and propagation. Conversely, if clinicians suspect a non-focal epileptic network, the IEEG coverage is likely to be broader.33 Mathematically, if an IEEG contact i has coordinates  and there are n contacts in a patient, the standard distance can be computed as follows:To quantify this clinical intuition about the focality of the epileptic network, we computed standard distance between IEEG contacts. Standard distance (SD) represents the 3-D standard deviation of each patient’s IEEG electrode coverage (Equation 1).A high SD value indicates a wider coverage, while a smaller SD value represents a more compact coverage. We refer to the standard distance between IEEG contacts as the “implant distance”.i with coordinates  is w, and there are n contacts in a patient, the weighed standard distance can be computed as follows:To compute the spatial dispersion of IEEG abnormalities, we implemented weighted standard distance (WSD). Weighted standard distance weights the SD with the abnormality values of each iEEG contact. Mathematically, if the abnormality of an IEEG contact In simpler terms, the weighted standard distance (WSD) takes into account the abnormality value at each IEEG contact and measures the spatial distribution of abnormality. A high WSD value indicates that abnormalities on IEEG are spatially widespread, while a low WSD value suggests that the abnormalities are located spatially closer together. We refer to the weighted standard distance of IEEG abnormalities as the “abnormality distance”. The concepts described above are illustrated schematically in the overview presented in We conducted univariate analysis to test how each metric discriminated focal from non-focal iEEG-seizure onset. In these univariate tests, we calculated effect sizes using the Cohen’s d score, non-parametric effect sizes using the area under the receiver operating characteristic curve (AUC), and non-parametric two-tailed p-values from the Mann- Whitney U test. We combined these quantitative metrics using multivariate logistic regression with lasso regularization, to mitigate the impact of correlated features and reduce the number of features. We applied leave-one-out cross-validation to predict IEEG focality in unseen (test) patients. To compare different predictive models, we applied the DeLong’s test. We performed all analyses with Python 3.10, and default regularization parameters for logistic regression  in sklearn.https://www.ieeg.org/. The normative iEEG atlas can be accessed at: https://discover.pennsieve.io/datasets/179. The iEEG-recon software is available at https://ieeg-recon.readthedocs.io. Documented codes and the 5-SENSE score for all patients included in our analysis can be found at: [GitHub link].All IEEG data used in this study are publicly available at 101 patients met the inclusion criteria. Clinicians determined that seizure generators were focal in 65 patients and non-focal in 36 patients. Among the 36 non-focal patients, 11 underwent surgery and 15 received stimulation therapy. Out of the 65 focal patients, 52 had surgery and 7 were treated with stimulation therapy. We conducted univariate analyses on: a) 5-SENSE score, b) spatial coverage of IEEG (implant distance), and c) spatial dispersion of abnormalities quantified from interictal IEEG activity and connectivity features . We investigated the association of these variables to determine IEEG focality. As depicted in Although these variables could independently distinguish between focal and non-focal patients, they exhibited a weak correlation to the 5-SENSE, as shown in To predict IEEG focality, we conducted cross-validated logistic regression classification using three distinct models: a) model incorporating only the 5-SENSE scores, b) model combining features from 5-SENSE scores and implant distance, and c) model combining features from 5-SENSE scores and IEEG abnormality distances.We next examined whether the output of our model, trained to detect focality from interictal iEEG data, would also vary by surgical outcome, implantation type, or subtypes of non-focal epilepsy.Figure S1 shows consistent equivalent results as in In this study we present a quantitative method to categorize the focality of epileptic networks for individual patients based upon their IEEG, by comparing their data to an atlas of prior patients. The method combines a) pre-implant clinical variables, b) spatial coverage of IEEG implant, and c) spatial dispersion of abnormalities quantified on interictal IEEG segments. Our findings suggest that we can combine these variables to predict whether a patient has a focal or a distributed epileptic network. These findings have significant clinical implications. Patients with a high probability of having a focal epileptic network might be better candidates for focal surgical intervention, such as laser ablation or surgical resection, and require more complex analyses, such as from ictal recordings. Conversely, patients with distributed or multifocal epileptic networks, and currently a lower likelihood of seizure-free outcome, might benefit more from palliative neurostimulation therapies that reduce seizure frequency and/or severity, but with a much lower chance of rendering them seizure-free. In these cases, our method might suggest that clinicians consider regional or central neurostimulation therapy earlier, rather than “chasing” poorly localized ictal onset patterns. Since our method does not rely on ictal recording, it has the potential to reduce length of stay during implantation, reduce morbidity from seizures associated with medication withdrawal, and reduce cost in patients found unlikely to have a clear focal onset.Of interest, our computation of the 5-Sense Score replicated the findings of the original study. This reinforces that study’s generalizability to other tertiary care centers. In an interesting confirmatory result, we found that a quantitative measure of the spatial dispersion of implanted IEEG electrodes predicted network focality with similar precision as the 5SS, indicating that in our center the implant strategy accurately translated the preimplant data into the next phase of presurgical evaluation. We found that a model incorporating preimplant data with the spatial dispersion of IEEG interictal abnormality improved significantly upon estimates of whether a given patient’s network demonstrates a focal or non-focal seizure onset pattern.34 In addition, patients with less localized seizures may have received surgery if key nodes were thought to be most implicated, as inferred from seizure spread or for other reasons.13 While our model does not include these more advanced considerations, it does provide a framework for including other quantitative measures that could, and it also provides one benchmark for assessing whether these more subjective decisions improved outcome more than quantitative measures of focality alone.Perhaps unsurprisingly, given the relationship between the clinical definition of focality and the decision to recommend focal surgery vs. neuromodulation via an implantable device , we foun36 Interestingly, abnormality distances both in relative power/coherence bands and in absolute broadband power were found to be significant predictors  in a logistic regression model. Nonlinear interactions across frequency bands may play a role in the focality of seizure onset zones,39 which would likely require larger datasets to disentangle with more complex models.In addition, we observed that quantitative models of focality could differentiate between favorable and unfavorable surgical outcomes . All mod40 We observed that all models performed better in discriminating focal from nonfocal networks in patients implanted with subdural ECoG electrodes compared to patients implanted with SEEG, including the 5-SENSE Score, which was developed on an entirely SEEG population. This phenomenon may reflect selection bias surrounding which patients were chosen for subdural ECoG implants vs SEEG implants: Subdural ECoG implants are often used to delineate seizure onset regions from eloquent cortex, often around focal lesions, whereas patients undergoing SEEG often receive broad cortical and subcortical sampling, potentially reflecting a more diffuse pre-implant hypothesis.The practice of our center over the time course of this study reflects wider trends in North America toward more SEEG implantation and less ECoG.41. The literature is less clear for seizures that spread around focal lesions and to other structures with strong connectivity, for example seizures that spread rapidly from mesial temporal lobe to insula. The additional degrees of freedom in these types of analyses will require a much larger number of patients in an atlas of ictal recordings, interventions, and known outcomes in order to quantify and understand this process.The need to localize seizure onset and spread, beyond the baseline clinical hypothesis or our analysis of background interictal abnormality, warrants further study and rigorous quantification to incorporate these measures other biomarkers of epileptogenicity with our interictal and implant spatial measures. The literature here is more limited, relating onset region and time of spread to other regions, and its impact on eventual outcome are best documented for medial temporal lobe epilepsy. For example, a study by Andrew et al. demonstrates that seizures that spread rapidly outside the resection margin associated with a poorer outcome after temporal lobectomy43 and perturbing networks with stimulation46 may lead intracranial studies to rely less on eliciting spontaneous seizures in the future to identify the major areas of dysfunction in epileptic networks amenable to treatment. It is likely that some combination of these approaches, with quantitative metrics of seizure dynamics, incorporating data on brain regions of interest and spatial distance, will likely be needed to improve on the present model. Central to this improvement is the need to aggregate and collaboratively analyze data from many patients in many centers using standardized protocols. We hope that using large numbers of patients can compensate for sparse electrode sampling in each patient.An advantage of the interictal method presented in the current study is its much more limited application and use. The method requires only 20 minutes of interictal IEEG data to map focality. Should a non-focal network be predicted, this could obviate the need for prolonged ictal recording and facilitate more expeditious neuromodulation treatment. Increasing literature measuring interictal brain abnormalitiesUltimately, predictive computational models of epileptogenicity may help guide surgical decision-making. In this study, we related the IEEG activity and connectivity of each patient to a corpus of prior patients. We show spatial coverage of electrodes, their associated IEEG abnormalities, and the data used in determining that coverage relates to seizure onset extent and surgical outcomes. By this framework, future studies may elucidate the cost-benefit decision analysis of implanting each additional electrode to identify seizure generators, or perhaps obviate the need to move forward with ictal recording in cases where more diffuse network topology is likely.50This study has important limitations. As a single-center, retrospective cohort study at a tertiary care institution, generalizability to other centers has not yet been determined. We used cross-validated lasso logistic regression to assess out-of-sample performance. There is considerable heterogeneity across epilepsy patients, and while a cohort of 101 patients is relatively large for such studies of IEEG, studies across multiple centers with greater numbers of patients are likely necessary to capture the true variability in ‘non-focal’ onset. The use of normative IEEG by identifying uninvolved epileptic electrodes is a nascent field. The openly-available atlas we employed likely requires substantially more data to improve the accuracy and generalizability of the models. We do make assumptions that unaffected electrodes in patients with epilepsy reflect true ‘normal’ activity and connectivity. This assumption is likely incorrect, as they are derived from epileptic brains, which likely skews the definition of ‘normal.’ However, the results of this study and others in normative IEEG modeling show promise in providing measures of epileptogenicity and support the continued use of this approach, for now, and contribution to a central collaborative corpus of IEEG data. Finally, it will be important for future studies of interictal IEEG to incorporate other biomarkers of epileptogenicity besides band power and connectivity, such as interictal spikes and high frequency oscillations.In conclusion, in this study we propose rigorous, data-driven quantitative measures to assess the spatial extent of epileptic networks in the brain. The quantitative methods we tested can complement presurgical evaluations to decrease lengthy hospital stays and optimize patient and therapy selection in drug-resistant epilepsy. Ultimately, these tools aim to standardize clinical decisions in ways that can be deployed in multi-center studies to advance and optimize care.


Healing of the rotator cuff after repair constitutes a major clinical challenge with reported high failure rates. Identifying structural musculotendinous predictors for failed rotator cuff repair could enable improved diagnosis and management of patients with rotator cuff disease.To investigate structural predictors of the musculotendinous unit for failed tendon healing after rotator cuff repair.Cohort study; Level of evidence, 2.Included were 116 shoulders of 115 consecutive patients with supraspinatus (SSP) tear documented on magnetic resonance imaging (MRI) who were treated with an arthroscopic rotator cuff repair. Preoperative assessment included standardized clinical and imaging (MRI) examinations. Intraoperatively, biopsies of the joint capsule, the SSP tendon, and muscle were harvested for histological assessment. At 3 and 12 months postoperatively, patients were re-examined clinically and with MRI. Structural and clinical predictors of healing were evaluated using logistic and linear regression models.P = .03), shorter SSP tendon length , and increased proportion of slow myosin heavy chain (MHC)–I/fast MHC-II hybrid muscle fibers . Primary clinical outcome (12-month postoperative Constant score) was significantly less favorable for shoulders with fatty infiltration of the infraspinatus muscle . Conversely, a high content of fast MHC-II muscle fibers  was associated with better clinical outcome.Structural failure of tendon repair, which was significantly associated with poorer clinical outcome, was associated with older age .NCT02123784 ( Surgical reconstruction of rotator cuff tears has shown reliable improvements in pain and function. However, healing after rotator cuff repair remains a major clinical challenge with reported failure rates of 13% to 94%. These failures are associated with inferior clinical outcomes and progression of musculotendinous degenerative changes.52 Despite ongoing advances in surgical treatment and fixation strength, rehabilitation, and patient education, the failure rate remains high, and there may be limitations in intrinsic healing potential of some rotator cuff tears.Rotator cuff tears are frequent and constitute the most common cause of shoulder dysfunction and pain.36 As the sensitivity of the different muscle fiber subtypes  to atrophy signals is dependent on physiological and metabolic stimuli, muscle atrophy is associated with change in muscle fiber type composition. As loss of elasticity of the musculotendinous unit is associated with more difficult anatomical reduction to the insertion site and increased tension of the repair, we hypothesized that muscle with increased proportion of hybrid-type muscle fibers is more prone to failure of rotator cuff repair.Chronic retraction of the musculotendinous unit is associated with structural muscular changes, including muscle atrophy and fatty infiltration, which have been shown to be independent predictors for failure of rotator cuff repair. Previous research indicated that retraction of the musculotendinous unit involved nonsynchronous shortening of the tendon and muscle. Furthermore, the combination of tendon shortening and fatty infiltration of the muscle substantially improved the preoperative predictive value for rotator cuff reconstruction failure. However, the evidence is still limited, and it remains unconfirmed that tendon length is an independent predictor for retear.In addition to structural changes of the muscle, structural changes of the tendon – including tear size and tendon length – have been associated with failure of rotator cuff repair. Although these studies indicate a strong influence of intrinsic parameters of the musculotendinous unit, the validity of the measurement methods can be improved. Most studies assess fatty infiltration based on magnetic resonance imaging (MRI) adaptation of the Goutallier classification.23 However, since this classification is influenced by retraction of the musculotendinous unit and has not shown a better than moderate interrater reliability,38 it may not represent an accurate quantification of muscular fatty infiltration. Advances in MRI technology allow us to reliably quantify muscle fat fraction using Dixon sequences.52Despite previous research efforts, systematic multivariate analyses of factors associated with repair failure are sparse. In a meta-analysis that included 108 studies with evidence levels from 1 to 4, fatty infiltration, tear size, advanced age, and double-row repair were found to be associated with morphological retear.In the present study, we investigated the histological and radiographic musculotendinous predictors for retear after rotator cuff repair using Dixon MRI and histology of intraoperative muscle biopsies. We hypothesized that muscle fiber type composition would be significantly associated with failure of rotator cuff repair. Included in that study were consecutive patients who were undergoing arthroscopic rotator cuff repair at a single institution. All patients had a full-thickness supraspinatus (SSP) tear with fatty infiltration of the SSP muscle of not more than Goutallier stage 2. Excluded were patients with previous surgery on the shoulder, osteoarthritis of the glenohumeral joint, inflammatory joint diseases, or use of oral steroids or immunosuppressive drugs. All included patients provided written informed consent.Between May 2014 and March 2017, a total of 115 patients (116 shoulders) were enrolled in this institutional review board–approved study. Since the homogeneity of the study population could not be predicted, the study size was based on a previous study of 84 patients that investigated the histopathological parameters of the rotator cuff.Tendon, capsular, muscular, synovial fluid, and blood samples for the histological analyses were obtained intraoperatively. Arthroscopic rotator cuff repair was performed under regional or general anesthesia with the patient in the beach-chair position. Based on intraoperative evaluation, a tenotomy or tenodesis of the long head of the biceps was performed. Subacromial debridement was performed routinely with or without acromioplasty based on intraoperatively objectified bony prominence of the acromion. A biopsy of the SSP muscle was performed via a standardized method using a 5 mm–diameter Duckbill biopsy needle  medial to the myotendinous junction under visual control. Subsequently, the rotator cuff tendon-to-bone repair was performed using double-loaded 6.5-mm titanium screw-in anchors (Karl Storz SE & Co KG). Based on the intraoperative tear morphology, a single- or double-row repair was performed.Postoperatively, the shoulders were protected in a brace at 30° of abduction for 6 weeks and passively mobilized under the control of a physical therapist. Between weeks 7 and 12, active full range of motion (ROM) exercises were allowed without strengthening. Incremental strengthening of the repaired rotator cuff muscles was started from week 13 onward.24 MRI analysis was performed by a fellowship-trained musculoskeletal radiologist (L.F.) who was blinded to clinical data  but not to the imaging at each time point.All patients underwent MRI including Dixon sequences of the shoulder  with a dedicated 16-channel phased-array shoulder coil. An identical protocol was used for all at the 3 different time points. The protocol consisted of 4 standard imaging planes  and sagittal oblique 6-point Dixon sequence. To quantify intramuscular fat, fat signal fraction maps were generated on the scanner's console using the Dixon sequence.: small (<1 cm), medium (1-3 cm), large (>3-5 cm), and massive (>5 cm). SSP tendon length was measured from the myotendinous junction to tendon stump in the center of the tendon as a compromise to account for potential differences between articular-sided and bursal-sided tendon length. To measure fatty muscle infiltration, qualitative and quantitative analyses were performed. Whereas qualitative assessment involved scoring of fatty infiltration according to the Goutallier classification,23 quantitative assessment included placing freehand regions of interest on fat signal fraction maps on the most lateral slice where the scapular Y was still visible, as described previously.54 To evaluate SSP muscle atrophy, the tangent sign was employed.The tear size was assessed according to the Cofield classification: type 1 , type 2 , type 3 (insufficient thickness without discontinuity), type 4 , and type 5 . The MRI examination at 12 months postoperatively determined structural integrity  or failure of structural healing .Tendon continuity was assessed at 3 and 12 months postoperatively according to the Sugaya classification (both absolute and relative [adjusted for age and sex]), the Subjective Shoulder Value (SSV), and a shoulder satisfaction score on a scale from 1 to 4  were performed preoperatively as well as at 3 months (without strength measurements) and 12 months postoperatively by a trained research nurse not otherwise involved in the patients’ treatment. Given that age and sex were incorporated into the multivariate analysis, the absolute Constant score and subscores were employed as the primary clinical outcome parameter.To evaluate clinical outcomes, the Constant score and subscores Pain, Activities of Daily Living (ADL), ROM, and StrengthAfter harvesting, the biopsies were immediately embedded in Cryomolds  in Tissue-Tek OCT compound  and frozen in –80°C 2-methylbutane (Merck) using a Snapfrost device (Excilone). The biopsies were kept in airtight 2-mL cryovials  and stored at –80°C until used for further analysis.To analyze muscle fiber composition and lipid content, 12-µm cryosections were performed perpendicular to the major fiber axes of most fiber profiles using a cryostat , whereafter the sections were mounted on cryoslides and stored at –80°C until use. Briefly, fixed sections were first incubated with goat serum and subsequently incubated with both primary antibodies  in a bovine serum albumin–phosphate-buffered saline buffer. After thorough washing, the samples were incubated with the secondary antibodies Alexa Fluor 555–coupled anti-mouse and Alexa Fluor 488–coupled goat anti-rabbit antibody . Subsequently, the nuclei were counterstained with Hoechst 33342 , after which the sections were embedded in fluorescent mounting medium . The immunofluorescent signal was assessed by recording microscopic fields at 20-fold magnification covering the entire section in a nonoverlapping manner using an Olympus IX50 microscope with a DP72 digital camera operated by Cell Sens Dimension software . To analyze the different fiber types , the images were imported in Photoshop CC (Adobe Systems Inc) for semiquantitative assessment. Fibers with >0.6 circularity were selected using manually-directed identification of the stained areas with the lasso tool fibers, as this indicates that they were sectioned in a perpendicular fashion. The number of slow, fast, and slow/fast hybrid fibers from the different microscopic fields were summed to reveal the total fiber population and calculate the respective mean percentages for the 3 fiber types over the entire cryosection. Per biopsy, a mean of 373 ± 189 muscle fibers were analyzed from 7 to 8 microscopic fields at 20-fold magnification using midsample sections.The proportion of slow (MHC-I), fast (MHC-II), and hybrid-type (MHC-I/MHC-II) muscle fibers was assessed using double immunofluorescent staining for the 2 main MHC types according to a previously described method. Briefly, cryosections were thawed and fixed in 4% paraformaldehyde, stained with a working solution of oil red O  per 100 mL isopropanol (Merck) and counterstained with hematoxylin (Artechemis). Similar to the fiber type analysis, the entire stained section was recorded for analysis. The percentage of cross-sectional area representing red signal was assessed using a macro with ImageJ software .The muscle lipid percentage was determined using an oil red O staining as described previously.t test or Mann-Whitney U test for continuous variables  and the chi-square test or Fisher exact test for categorical variables. Correlations between variables were analyzed using Pearson product-moment correlation coefficient (PCC) between 2 continuous variables, Kendall tau-b (KTB) correlation between ordinal and continuous variables, or point-biserial correlation (PBC) between continuous and binominal variables.Differences between healed and unhealed rotator cuff groups were analyzed using the independent P value <.05 was considered statistically significant.Multivariate regression analysis was used to determine the independent demographic, surgical, and structural predictors for morphological retears, as well as primary clinical outcome (12-month postoperative Constant score) and clinical improvement (change in Constant score from preoperatively to 12 months postoperatively). We input the structural parameters of the musculotendinous unit together with known independent predictors from previous research. Forward-conditional binomial multivariate logistic regression  and stepwise multivariate linear regression  were performed to analyze the independent predictors. Receiver operating characteristic (ROC) analysis with a calculation of area under the ROC curve (AUC) was performed to determine the cutoff value of SSP tendon length for structural tendon healing, Statistical analysis was performed using SPSS Statistics 25 (IBM). All statistical tests were 2-tailed, and a P < .001), a moderate correlation for the infraspinatus , and a weak correlation for the subscapularis . Histological lipid content of the SSP showed a significant weak correlation with Goutallier stage  and Dixon MRI fat fraction .From the initially enrolled cohort (116 shoulders), 97 shoulders met the inclusion criteria for further analysis . A total of 76 (78.4%) rotator cuff reconstructions were healed 1 year postoperatively. Most retears occurred in the first 3 months postoperatively, showing 17 (17.5%) MRI-confirmed retears after 3 months and 21 (21.7%) after 12 months. To include all documented early and late retears, the 12-month time point is used for further analysis. R2; of 0.26. Older age , shorter SSP tendon length  and increased content of hybrid muscle fibers  showed a significant association with failed tendon healing in the multivariate analysis  were put into the logistic multivariate model together with known independent demographic and surgical predictors or potential confounders such as sex. The model showed a high effect size, with a Cox and Snell analysis . FurtherP = .76) interaction between tendon length and Goutallier stage for the SSP, infraspinatus, or subscapularis muscles. Furthermore, correlation analysis showed no significant (P = .67) correlation between age and hybrid MHC-I/MHC-II.To analyze the interaction between tendon length and Goutallier stage of fatty infiltration on retears, the tendon length, Goutallier stage, and tendon length × Goutallier stage were put into the multivariate regression analysis. This analysis showed no significant (P = .05).Finally, in a subgroup analysis investigating the correlation of single-row repair with structural parameters of the musculotendinous unit, only SSP fatty infiltration (Dixon MRI) showed a weak significant correlation . Regarding all clinical scores and Constant subscores, only improvement of the SSV at 12 months postoperatively showed a significant negative correlation with retear .The 12-month postoperative Constant, SSV, and shoulder satisfaction scores showed a significant weak negative association with retear  showed a significant negative association with postoperative Constant score , and fast MHC-II showed a significant positive association with postoperative Constant score   showed a low effect size, with an  of 0.10 .8 Infr = .028) .P = .022), postoperative Constant Pain  and postoperative Constant ADL . Furthermore, a significant positive correlation was observed between fast MHC-II and postoperative overall Constant score  and postoperative Constant ROM .The interactions of Goutallier fatty infiltration of the infraspinatus and fast MHC-II with clinical parameters were further analyzed. Subgroup analysis showed a significant negative correlation of infraspinatus Goutallier fatty infiltration and postoperative overall Constant score . These findings correspond with previous research, which shows improvement of both healed and unhealed tendons with slightly better clinical scores in healed patients.44 Furthermore, a stronger clinical difference between the 2 groups might be expected with longer follow-up.Patients with structural healing of the repair showed significantly better clinical scores  compared with those with nonhealing. However, the difference in Constant score was interpreted as not clinically relevant, as the minimal clinically important difference (MCID) of 10.4 points was higher than the observed difference of 8.6 points.This study shows the association of structural musculotendinous parameters with failed tendon healing after rotator cuff reconstruction in an arthroscopic rotator cuff reconstruction population with of Goutallier stage ≤2. Both the structural (retear) and the primary clinical outcome (Constant score) were shown to be influenced by intrinsic parameters of the musculotendinous unit. However, different predictors were observed for the structural and clinical outcome. Previous research indicates that successful repair is closely related to the elasticity of the musculotendinous unit and the ability to lateralize the unit to its intended healing site with low tension. As musculotendinous retraction is characterized by more retraction of the tendon compared with the muscle, and reduction of the defect is for 50% accounted for relengthening of the tendon, decreased tendon length may be an important parameter for increased tension of the repaired musculotendinous unit. In addition to increased tension of the musculotendinous unit, tendon shortening could be an indicator of a diminished physiological state of the tendon. Although it is widely known that tendon unloading is associated with rapid cellular, molecular, and structural changes resulting in diminished mechanical strength, the correlation of tendon length and its physiological state is unknown.50 Further investigation of the tendon length and its associated physiological state could therefore elucidate the contribution of the different components of the musculotendinous unit to healing of the rotator cuff after repair.Decreased SSP tendon length was shown to be an independent predictor for structural rotator cuff repair failure. This corresponds with previously observed inverse correlation of tendon length and retear rate. Similar to previous research, a significant correlation was observed between Goutallier stage and Dixon MRI fat fraction. Also, the low histological lipid content for Goutallier stage ≤2 measured in this study was comparable with a previous study investigating SSP histological morphology. A weak significant correlation  was observed between histological fat fraction and MRI-assessed fatty infiltration . This weak correlation might be explained by the small range of measured fat fraction in a population with Goutallier stage ≤2. A previous study showed similar small differences between histological fat fraction of patients with Goutallier stage ≤2. With respect to muscle fiber type composition, a human cadaveric SSP histological study with no macroscopic tendon pathology showed more slow-type MHC-I fibers and fewer fast-type MHC-II fibers compared with the torn SSP muscles presented in this study. An experimental study using a preclinical model has shown a similar distribution with significantly fewer slow-type MHC-I fibers in muscles with rotator cuff tears compared with intact rotator cuff muscles.The fat fraction of the rotator cuff , measured by Dixon MRI, was comparable with the literature.43 This shift toward another muscle type is frequently associated with an increase in hybrid-type fibers that have altered MHC isoform expression profiles. Preclinical studies in rats showed that spinal cord transection is associated with a transition from slow MHC-I to fast MHC-IIa and MHC-IIx with a dramatic increase in slow/fast  hybrid muscle fibers.48 Similar results were observed in microgravity models in rats and humans with a shift from slow (MHC-I) to fast type  and an associated substantial increase in hybrid slow/fast muscle fibers when exposed to unloading by microgravity.45 Muscle unloading by bedrest showed a significant decrease in slow MHC-I, increase in fast MHC-IIx, and an increase in overall hybrid fibers  after 35 and 84 days of bedrest in humans.19In addition to tendon characteristics, increased content of hybrid muscle fibers represented an independent predictor for retear. This underlines muscular change as an important parameter for healing of the musculotendinous unit after repair. Muscular disuse is associated with various types of muscle transformation. In an experimental preclinical model, decrease in MHC-I and MHC-IIa fibers and increase in MHC-IIb fibers was associated with a reduction in muscle fiber force production and an induction of fibrogenic, adipogenic, and autophagocytic mRNA and miRNA molecules. As this study highlights hybrid muscle fiber type content as an important independent predictor for healing of the musculotendinous unit after rotator cuff repair, further research of the associated muscle physiological state could enlighten the pathomechanism of retear. Clinically, this could have both a diagnostic and a therapeutic value. Biomarkers associated with the muscle fiber type morphology obtained by minimally invasive procedures such as synovial fluid or blood could serve as tools for a personalized surgical treatment. Furthermore, a better understanding of the pathomechanism of failure of repair could reveal potential targets for pharmacological therapies.All in all, increase in slow/fast hybrid fibers (MHC-I/MHC-II) seems to be associated with muscular disuse atrophy and may indicate a shift from slow muscle fibers to fast muscle fibers. Previous research indicates that MHC isoforms are significantly correlated with other aspects of the muscle cell physiology, including myofibrillar proteins, metabolic enzymes, sarcoplasmic reticular proteins, and structural parameters.P = .05) correlated with single-row repair. We are therefore tempted to hypothesize that the surgical technique could be further optimized based on the biological profile of the musculotendinous unit. For example, if decreased tendon length and associated poor tendon quality prohibit the surgeon from performing a double-row repair, other techniques such as patch augmentation might be explored to reinforce the repair. A biomechanical study showed that weakened tendon structures could be fortified to nearly their original strength using patch augmentation.Although single-row repair was observed significantly more (>80%) in the retear group compared with the healed group, this parameter did not represent an independent predictor for retear. It seems that single-row repair is correlated with nonhealing of the musculotendinous unit, but underlying biological characteristics  seem to influence the quality of the repair. Subgroup correlation analysis showed that from all structural parameters of the musculotendinous unit, only SSP fatty infiltration (Dixon) is significantly (PBC, 0.22;  Apart from infraspinatus fatty infiltration, a positive association with low effect size was observed between fast MHC-II muscle fiber content and Constant score at 12 months postoperatively. Subgroup analysis correlated preoperative MHC-II muscle fiber content with increased ROM 12 months postoperatively. The association between fast MHC-II muscle fibers and muscle function and strength was also observed in previous research. For example, in elderly men it was shown that fast MHC-II–specific atrophy is predictive of muscle weakness.Linear regression showed a negative association with low effect size of infraspinatus Goutallier fatty infiltration with Constant score after 12 months. A previous study showed a similar association of preoperative infraspinatus fatty infiltration and worse clinical outcome.28 Also, tears were repaired according to the tear pattern and anatomy. However, to control for this potential bias, the parameter “fixation type” was included in the multivariate analysis. This parameter was demonstrated to not be an independent predictor for retear in this cohort. Furthermore, although a standardized method was performed, spatial distribution could have influenced the biopsy analysis. However, with respect to muscle fiber type analysis, previous research showed robust results of fiber type characterization despite biopsy location site. Also, since the fat fraction of fatty atrophy has a known heterogeneous mediolateral distribution, the biopsies were consequently performed medial from the musculotendinous junction under visual control.Although a cohort study design was used, study limitations should be reported. For example, the moderate sample size meant that only a limited number of predictors could be selected based on previous multivariate and meta-analyses. However, although this creates a potential bias and limited effect size for clinical outcome, we preferred this method over selecting parameters based on univariate analysis, as methodological studies showed that the latter method is associated with a high bias.The study findings confirmed that failed repairs are associated with poorer clinical outcome than healed repairs. Repair failure is more likely with older age, a shorter SSP tendon, and an increased proportion of hybrid fibers. Different intrinsic parameters showed a relevant effect on both the structural and the clinical outcome of repair. Further investigation of the relationship between the biological, structural, and functional characteristics of the musculotendinous unit might result in a more detailed understanding of the risk factors for retear and change the surgical management to increase the success rate of rotator cuff repairs.


Polymer mechanochemistry offers attractive opportunitiesfor usingmacroscopic forces to drive molecular-scale chemical transformations,but achieving efficient activation in bulk polymeric materials hasremained challenging. Understanding how the structure and topologyof polymer networks impact molecular-scale force distributions iscritical for addressing this problem. Here we show that in block copolymerelastomers the molecular-scale force distributions and mechanochemicalactivation yields are strongly impacted by the molecular weight distributionof the polymers. We prepare bidisperse triblock copolymer elastomerswith spiropyran mechanophores placed in either the short chains, thelong chains, or both and show that the overall mechanochemical activationof the materials is dominated by the short chains. Molecular dynamicssimulations reveal that this preferential activation occurs becausepinning of the ends of the elastically effective midblocks to theglassy/rubbery interface forces early extension of the short chains.These results suggest that microphase segregation and network stranddispersity play a critical role in determining molecular-scale forcedistributions and suggest that selective placement of mechanophoresin microphase-segregated polymers is a promising design strategy forefficient mechanochemical activation in bulk materials. However, yieldsof force-driven reactions in elastomeric polymer networks are typicallylow, even for mechanophores that exhibit high activation yields insolution sonication experiments.23 By changing which component of the blend contains mechanophores, we are effectively able to “label”and probe the activation of chains with different elastic strand lengthswithin otherwise equivalent networks. We find that activation occursprimarily in the short chains, which molecular dynamics (MD) simulationsreveal is driven in large part by pinning of the elastically effectivemidblock ends to the glassy/rubbery interface. These results suggestthat controlling both microphase segregation and network strand lengthdistributions is an important design strategy for directing molecular-scaleforce distributions and enabling efficient mechanochemical activationin bulk materials.Here, we use a combination of experimentsand computer simulationsto investigate how network strand dispersity impacts molecular-scaleforce distributions and mechanochemical activation in self-assembledtriblock copolymers. As illustrated in n-butyl acrylate) (PnBA) midblocks, as depicted in fPMMA ≈ 0.45) and narrow dispersities (Đ ≈ 1.2), but differed in overall molecular weight (Mn ≈ 60 or 150 kg/mol) and whether theycontained a spiropyran mechanophore in the center of the PnBA midblock.These parent polymers were then blended to prepare bidisperse sampleswith equal weight fractions of short and long chains, but with spiropyranmechanophores in different subpopulations of the chains. Samples labeledW-Sl contained mechanophores only in the short (S) chains; sampleslabeled W-sL contained mechanophores only in the long (L) chains;and samples labeled W-SL contained mechanophores in both the shortand the long (SL) chains. Here, the “W-” prefix is usedto indicate that the samples contained equal weight fractions of shortand long chains; complementary experiments on samples with equal numberfractions of short and long chains (“N-”) are reportedin the Supporting Information. Size exclusionchromatography confirmed that all three blended samples had similarnumber-average molecular weights and molecular weight distributions.Scanning transmission electron microscopy (STEM) images and small-angleX-ray scattering (SAXS) patterns of the self-assembled samples revealedthat all three polymer blends self-assembled into disordered, microphase-segregated materials with domain spacings onthe order of 30 nm, consistent with the disordered, bicontinuous morphologiesobserved in other polydisperse block copolymer systems.26We first synthesized four triblock copolymers withglassy poly(methylmethacrylate) (PMMA) end blocks and rubbery poly activated relativelyearly, with the onset of activation observed around ϵ ≈0.67 and σ ≈ 6 MPa. The W-sL samples, on the other hand,which only contained mechanophores in the long strands, activatedmuch later, with the onset of activation not observed until ϵ≈ 2.25 and σ ≈ 9 MPa. The total activation ofthe W-SL sample, which contained mechanophores in both the short andthe long chains, was also almost identical with that of the W-Sl sample,which contained mechanophores in only the short chains. Similar trendswere observed in samples containing equal number fractions of shortand long chains (see Supporting Information). Together, these results reveal that in block copolymer elastomersmechanochemical activation is almost entirely dominated by the shortchains (even when both populations of chains contain mechanophores),suggesting that the molecular-scale forces on these chains are muchhigher than those on their longer counterparts.The mechanical properties and mechanochemical activation profilesof the materials were then characterized by measuring changes in theiroptical absorption between 550 and 630 nm during uniaxial tensiledeformation.28 The PMMA and PnBAblock fractions were chosen to yield well-defined cylindrical morphologies,as shown in 30 and activationof the mechanophores in both the long and the short chains was quantifiedby monitoring changes in the bond length of a double-well unit inthe center of the chains. The resulting activation profiles for eachsubset of chains are shown in true ≈ 0.75) than the longchains did (ϵtrue ≈ 0.95). The overall activationalso closely tracked that of the short chains alone until relativelyhigh strains (ϵtrue > 1). While the simulationswererun on perfectly ordered, anisotropic morphologies and thus likelyoverestimate the overall response of more disordered and/or isotropicsamples, the close qualitative agreement of the simulation data withthe experimental results validates the simulation model and reinforcesthe conclusion that mechanochemical activation is much more efficientin the shorter chains.To understand the molecular-scale origins of thisresult, we carriedout coarse-grained molecular dynamics simulations on triblock copolymerswith bimodal molecular weight distributions designed to mimic theexperimental system.Supporting Information) additionallyreveals that activation is higher in chains that are well-alignedwith the pulling direction and that the short tie chains align moreeasily than the long tie chains do. As in the experimental systems,similar trends were also observed in samples containing equal numberfractions of short and long chains.Detailed analysis of the MD simulations providesinsights intothe molecular-scale features that promote this preferential activationof the short chains. As shown in Supporting Information). From a fundamental perspective, since the mechanophores act asmolecular-scale force probes, these results provide detailed new insightsinto how force is distributed in block copolymer elastomers. In particular,short tie chains carry much of the load, even when they constitutea minority of the tie chains in the material. Interestingly, thisresult is in contrast to the behavior observed in linear homopolymers,where activation is typically more pronounced in longer chains,32 and in both rubbery and glassy cross-linked networks, where it hasbeen shown that activation levels are essentially independent of thecross-linker length as long as the probe strands are shorter thanthe average strand length of the material.33 This suggests that pinning of the midblock ends to the hard/softinterface may be critical for directing force to the shorter strands.While similar effects might be expected to occur in covalently cross-linkedrubbers, relaxation of the junction points in these materials mayalso reduce the preferential stretching of the short chains,33 and further investigation will be needed tounderstand how network topology and strand dispersity affect mechanochemicalactivation in those materials. We note, however, that the absoluteactivation in the block copolymer samples appears to be higher thanin most elastomers reported to date.18 While thereis a small amount of uncertainty in the absolute activation arisingfrom the measurement of the extinction coefficient of the activatedmechanophores (see Supporting Information), this result suggests that pinning of the midblocks to the glassy/rubberyinterface may facilitate a more efficient force transfer overall.The observation that activation only occurs after the yield pointof the materials further highlights the importance of the glassy phase,with rearrangement of the glassy phase (which is not captured in thesimulations) necessary prior to stretching and mechanophore activationin the rubbery midblock strands.27Both the experimental and computational resultsreported in thiswork show that mechanochemical activation preferentially occurs inthe short tie chains in bidisperse triblock elastomers. Preferentialactivation of the short tie chains is so pronounced that the shortchains dominate the overall activation profile of the material, eventhough the short chains have a lower probability of forming tie chainsthan the long chains do (see From an applied perspective, this work also suggests that microphasesegregation, control of elastic strand dispersity, and carefully consideredplacement of mechanophores in different populations of the networkstrands can be used to optimize both the overall mechanochemical activationefficiencies in polymeric materials and the point at which activationoccurs during a macroscopic deformation. To facilitate early activation,mechanophores should be placed in the short strands of a triblockelastomer, while materials displaying delayed activation can be preparedby instead placing mechanophores in the long strands. Additionally,because the mechanophores in the long strands display a much loweroverall activation and are in some sense “wasted” mechanophores,the overall activation yield per mechanophore can be improved by placingthe mechanophores primarily in the short strands. Regardless of thetargeted activation profile, however, the formation of microphase-segregatedmorphologies and pinning of the elastic chain ends to the block interfaceappear to be critical for forcing early extension of the short midblocks,and we anticipate that controlling microphase segregation should bea powerful design parameter for enhancing mechanochemical activationin elastomeric networks.In summary, we showed that in microphase-segregatedtriblock elastomerswith bidisperse molecular weight distributions, mechanochemical activationoccurs primarily in the short chains. These results suggest that networkstrand dispersity plays an important role in determining molecular-scaleforce distributions in these materials and that selective placementof mechanophores in the highest-force or highest-extension strandscan be used to both control the onset of activation and improve overallactivation yields. Further investigation of how microphase segregation,network topology, dispersity, and defect content influence molecular-scaleforce distributions and mechanochemical activation yields promisesto be a fruitful avenue for achieving efficient mechanochemical activationin bulk polymer materials.


Axillary lymphadenopathy is a common side effect of COVID-19 vaccination, leading to increased imaging-detected asymptomatic and symptomatic unilateral axillary lymphadenopathy. This has threatened to negatively impact the workflow of breast imaging services, leading to the release of ten recommendations by the European Society of Breast Imaging (EUSOBI) in August 2021. Considering the rapidly changing scenario and data scarcity, these initial recommendations kept a highly conservative approach. As of 2023, according to newly acquired evidence, EUSOBI proposes the following updates, in order to reduce unnecessary examinations and avoid delaying necessary examinations. First, recommendation n. 3 has been revised to state that breast examinations should not be delayed or rescheduled because of COVID-19 vaccination, as evidence from the first pandemic waves highlights how delayed or missed screening tests have a negative effect on breast cancer morbidity and mortality, and that there is a near-zero risk of subsequent malignant findings in asymptomatic patients who have unilateral lymphadenopathy and no suspicious breast findings. Second, recommendation n. 7 has been revised to simplify follow-up strategies: in patients without breast cancer history and no imaging findings suspicious for cancer, symptomatic and asymptomatic imaging-detected unilateral lymphadenopathy on the same side of recent COVID-19 vaccination (within 12 weeks) should be classified as a benign finding (BI-RADS 2) and no further work-up should be pursued. All other recommendations issued by EUSOBI in 2021 remain valid. Worldwide COVID-19 vaccination campaigns have become commonplace.Post-vaccination COVID-19 lymphadenopathy has been reported in up to 44% of cases in at least one follow-up examination.Breast examinations should not be delayed because of COVID-19 vaccination.In average-risk patients without suspicious breast findings, ipsilateral imaging-detected axillary lymphadenopathy within 12 weeks after vaccination should be classified as BI-RADS 2. Since the start of the COVID-19 vaccination campaigns in late December 2020, axillary lymphadenopathy quickly emerged as a common side effect . MoreoveConsidering the far-reaching impact of vaccination campaigns  and the boosting recommendations that have been issued, this sudden and marked increase of a previously rare differential diagnosis in the management of unilateral axillary lymphadenopathy threatened to negatively impact the workflow of breast imaging services, especially in light of potential unnecessary additional imaging and invasive procedures. Thus, the need to quickly provide a solid consensus framework on the management of post-vaccination lymphadenopathy prompted the release, in August 2021, of ten recommendations by the European Society of Breast Imaging (EUSOBI) [In acknowledgement of the rapidly changing scenario and the lack of data concerning some aspects , these 2021 recommendations, as those published by the Society of Breast Imaging (SBI) , kept anLikewise, sparse information on temporal changes and the eventual persistence of asymptomatic lymphadenopathy justified more stringent follow-up approaches among the first published recommendations and guidelines , 12, 13.Moreover, potential further persistence of lymphadenopathy could be enhanced by the simultaneous or staggered application of other vaccines such as influenza or shingles.Therefore, as already done by the SBI , the purIn patients with previous history of breast cancer, vaccine injection (both doses for two-doses vaccines) should be performed in the contralateral arm or in the anterolateral thigh.Eight of the ten recommendations provided in August 2021 are still valid today, while two (recommendations n. 3 and n. 7) need to be revised according to new information. All recommendations are again presented below, and a brief discussion is proposed for those that have been revised.This recommendation has not been revised.2.COVID-19 vaccination data  of all patients presenting for breast imaging with any modality should be collected and made available to radiologists, including the cases of breast imaging performed for cancer staging and of follow-up imaging examinations.This recommendation has not been revised.3.Revised as:Breast examinations should not be delayed because of COVID-19 vaccination.The previous recommendation was in favour of rescheduling breast examinations (before the vaccination or at least 12 weeks after the last injection). However, current evidence points towards a near-zero risk of subsequent malignant findings in asymptomatic patients who have unilateral lymphadenopathy and no suspicious breast findings (no cancer cases in the largest series published to date [). Moreover, predictive models developed based on data from the first pandemic waves revealed that delayed or missed screening tests have a negative effect on morbidity and mortality [. Therefore, the potential temporal overlap of COVID-19 vaccinations in combination or staggered with other vaccines known to cause transient lymphadenopathy should no longer be considered a reason to reschedule periodic breast examinations, either in spontaneous or organized screening programs.4.In patients newly diagnosed with breast cancer, all necessary breast imaging examinations with any modality must be performed without any delay due to vaccination, taking into consideration the risk of false positive lymph node findings. to date ). Moreovortality –11. TherThis recommendation has not been revised.5.The contralateral axilla and both breasts should be clinically examined using appropriate imaging to exclude malignancy in all patients with axillary symptoms and in all cases of imaging-detected unilateral axillary lymphadenopathy before vaccination or at least 12 weeks after.Aside from isolated reports of vaccine-associated lymphadenopathy up to 43 weeks after vaccination [, the available literature shows that most cases of vaccine-associated lymphadenopathy arise within 50 days from vaccination [. Thus, the 12-week follow-up threshold after vaccination—after which axillary lymphadenopathy should also prompt the examination of both breasts and of the contralateral axilla—is still considered appropriate and the recommendation has not been revised.6.In patients with or without previous breast cancer history, imaging-detected suspicious axillary lymphadenopathy contralateral to the vaccination side should be managed according to standard work-up protocols, including, when necessary, tissue sampling.This recommendation has not been revised.7.Revised as:In patients without breast cancer history and no suspicious breast imaging findings, imaging-detected unilateral axillary lymphadenopathy on the same side of recent COVID-19 vaccination (i.e. within 12 weeks) should be classified as a benign finding (BI-RADS 2) and no further work-up should be pursued.In the previous version, the conservative approach adopted in the absence of sufficient available evidence led to different recommendations for patients with and without axillary symptoms. Today, this type of attitude is hardly justified and recommendation 7 has been simplified.8.In patients without breast cancer history, incidental unilateral axillary lymphadenopathy after COVID-19 vaccination coupled with ipsilateral suspicious findings in the breast at any imaging modality should be managed according to clinical practice, including biopsy when appropriate .This recommendation has not been revised.9.In patients with personal breast cancer history, lymphadenopathy after vaccination should be interpreted considering the time since vaccination and overall nodal metastatic risk  . For patThis recommendation has not been revised.10.All complex or unclear cases  should follow a personalized management, considering the risk of malignant lymphadenopathy, opting for tissue sampling when appropriate after multidisciplinary team discussion.This recommendation has not been revised.This update of the EUSOBI recommendations published in August 2021 aims at reducing unnecessary additional imaging and invasive procedures but, above all, at avoiding potential delays in breast cancer screening examinations. Future updates of these recommendations will be considered if the evolving boosting recommendations or the development and commercialization of new vaccines and of adapted versions of already approved ones will engender substantial changes in the clinical scenario.


Urinary tract infections (UTIs) caused by antimicrobial-resistant pathogens have been increasingly reported. Aminoglycosides are known to be effective therapy for UTIs, however their use is not common due to a fear of nephrotoxicity. Overuse of broad-spectrum antimicrobial agents, particularly carbapenems can lead to colonization with carbapenem-resistant pathogens resulting in more difficult-to-treat infections. We aim to evaluate the use of aminoglycosides for UTI therapy in pediatric patients to assess the clinical outcome.A retrospective chart review was performed to evaluate all orders of aminoglycosides for the indication of UTI from 2020-2022 at Children’s Hospital Los Angeles. Demographic data, bacterial pathogen, kidney function before and during treatment, and clinical outcomes were collected and analyzed. We also evaluated the resistance patterns of bacterial pathogens, and whether they met our institutional criteria of a multi-drug resistant organism (MDRO). Patients were excluded if they received ≤ 48hrs of treatment with an aminoglycoside or if they did not have a gram-negative pathogen identified on urine culture.A total of 61 patient encounters included an aminoglycoside order for treatment of UTI during the review period. 45 out of 61 encounters had a positive urinary culture that met our institutional criteria for an MDRO. Among patients receiving aminoglycosides, we observed 4 cases of elevated sCr that met our definition of AKI. The 2 cases with the greatest creatine increase (3-4 x baseline), were also currently receiving empiric vancomycin treatment. No patients had a documented treatment failure requiring change or escalation in therapy, or lack of resolution of fever. Four cases had a recurrence within 30 days after discharge. Three out of the four patients with recurrence had pre-existing anatomical abnormalities of the urinary tract that put them at increased risk for recurrent infection.Overall, extended interval aminoglycoside therapy was effective and well-tolerated for the treatment of urinary tract infections in our pediatric patient population. For cases of multi-drug resistant urinary pathogens, aminoglycosides represent a reasonable alternative to broader spectrum options such as carbapenems.All Authors: No reported disclosures


Older inpatients are at high risk of hospital-associated complications, particularly delirium and functional decline. These can be mitigated by consistent attention to age-friendly care practices such as early mobility, adequate nutrition and hydration, and meaningful cognitive and social activities. Eat Walk Engage is a ward-based improvement programme theoretically informed by the i-PARIHS framework which significantly reduced delirium in a four-hospital cluster trial. The objective of this process evaluation was to understand how Eat Walk Engage worked across trial sites.Prospective multi-method implementation evaluation on medical and surgical wards in four hospitals implementing Eat Walk Engage January 2016-May 2017. Using UK Medical Research Council guidance, this process evaluation assessed context, implementation  and mechanisms of impact  at each site.The four wards had varied contextual barriers which altered dynamically with time. One ward with complex outer organisational barriers showed poorer implementation and fewer practice changes. Two experienced facilitators supported four novice site facilitators through interactive training and structured reflection as well as data management, networking and organisational influence. Novice site facilitators used many implementation strategies to facilitate 45 discrete improvements at individual, team and system level. Patient interviews (42 before and 38 after implementation) showed better communication about program goals in three sites. Observations of 283 meals before and 297 after implementation showed improvements in mealtime positioning and assistance in all sites. Activity mapping in 85 patients before and 111 patients after implementation showed improvements in cognitive and social engagement in three sites, but inconsistent changes in mobility. The improvements in mealtime care and cognitive and social engagement are plausible mediators of reduced delirium observed in the trial. The lack of consistent mobility improvements may explain why the trial did not show reduction in functional decline.A multi-level enabling facilitation approach supported adaptive implementation to varied contexts to support mechanisms of impact which partly achieved the programme goals. Contexts changed over time, suggesting the need for adequate time and continued facilitation to embed, enhance and sustain age-friendly practices on acute care wards and optimise outcomes.http://www.anzctr.org.au): ACTRN12615000879561.The CHERISH trial was prospectively registered with the ANZCTR (The online version contains supplementary material available at 10.1186/s12913-023-09659-2. Almost half of older people admitted to hospital for acute illnesses, injuries or surgery will experience hospital-associated complications of delirium, functional decline, new incontinence, falls or pressure injuries . These cfacilitation is the central activating mechanism for getting innovation  into practice within the context (acute care wards) by engaging with the recipients (older patients and the multidisciplinary staff caring for them). The core components of Eat Walk Engage are a trained novice site facilitator, a local multidisciplinary work group, structured measures including older patient interviews and structured observations of care practices related to programme goals, and a trained multi-professional assistant. Informed by the i-PARIHS Facilitation Guide and facilitator’s toolkit [Eat Walk Engage is a ward-based programme developed to improve multidisciplinary team delivery of age-friendly care principles  to reduce hospital-associated complications in older inpatients . It was  toolkit  and supp toolkit . ImproveThe Collaborative for Hospitalized Elders: Reducing the Impact of Stays in Hospital (CHERISH) trial  was a hydescribing context, implementation and improvements in each site;describing and analysing changes in process measures that are postulated mechanisms of impact leading to the observed patient outcomes;describing how facilitation supported tailored implementation as hypothesised by the underpinning i-PARIHS implementation framework; andproposing how key contextual features of different sites may have contributed to implementation success or failure . This wiThe aim of this implementation evaluation informed by the UK Medical Research Council guidance for evaluating complex interventions in healthcare , 13 and This study was initiated by hospital-based clinician researchers through a collaborative partnership with the Queensland Government, Queensland University of Technology, geriatric and health services research academics, and two Hospital and Health Services (HHS) in Queensland, Australia. The Queensland government funds universal free hospital care through public hospitals organised into 16 HHS. Senior executive leaders from one metropolitan and two regional HHS were invited as industry funding partners. One metropolitan and one regional HHS supported participation of four hospitals . Each hospital nominated two acute care wards where more than half of inpatients were aged over 65 years, the program was aligned with hospital priorities, and there was nurse unit manager agreement. One ward at each hospital was randomised to implement Eat Walk Engage, providing four intervention wards. Implementation commenced in January 2016.Participants for the implementation evaluation included inpatients on the four intervention wards before (October -December 2015) and after (March–May 2017) implementation, and multidisciplinary work group members and facilitators.Implementation drew on facilitation as experiential learning, led by two experienced facilitators who recruited, trained and mentored novice site facilitators using concepts and tools outlined in the i-PARIHS Facilitation Guide , 22. TheSite facilitators engaged with the nurse unit manager and key staff on each intervention ward to form a work group focussed on improving care of older people. The work group included champions, opinion leaders and/or key roles for improving care of older people . Site facilitators scheduled monthly meetings and helped work group members reflect on evidence, tacit knowledge, older patient interviews and structured observations of care practices (see below). They supported the work group to identify and prioritise areas for improvement, clarify roles and relationships, and trial cycles of improvement aligned with programme goals, agreed team priorities and available resources.Multi-professional assistants were allied health or nursing assistants selected by interview who received two weeks of training in care of older people, including a work instruction manual, face-to-face training with local allied health professionals  and work shadowing with an experienced assistant. Any clinician could delegate tasks aligned with programme goals . Assistants could also assist with ward-level tasks related to environment and resources (e.g. updating orientation boards).The implementation evaluation was a prospective, multi-site evaluation using a theory-based research perspective to describe the context, implementation and mechanisms at each site . The evaContext was assessed by each site facilitator using a spreadsheet tool based on the i-PARIHS facilitation checklist [hecklist , focussihecklist . Scores Implementation described adherence to the core intervention components ; the implementation strategies used by facilitators to enable change; and the resulting individual, team and system-level improvements addressing programme goals. Data were obtained from minutes and field notes maintained by the experienced facilitators during regular group face-to-face meetings with the site facilitators and electronic minutes maintained by site facilitators during their local work group meetings. The two experienced facilitators independently extracted and analysed information using directed content analysis [analysis , immersianalysis . ImproveMechanisms of impact were evaluated by process measures before and after the intervention was implemented, including older patient interviews and structured observations of care practices aligned with the programme logic model  at three mealtimes  during a 1–2 week period. The observer noted whether each patient was sitting up when the meal arrived, had the tray table in reach, and was interrupted during the meal. They recorded whether patients required assistance with meal set-up or eating, and whether they received this assistance within 10 minutes. We evaluated the percentage of mealtimes where patients were sitting in a chair and received timely assistance, as these factors are associated with increased nutritional intake .Structured observations of patients’ physical, cognitive and social activities were conducted using activity mapping , 30, sysContext measures were summarised for each ward and over time in a table to allow visual comparison. Implementation strategies were summarised in a table using the ERIC taxonomy  and descThe four intervention wards were a general surgical, respiratory medicine, general medicine, and orthopaedic surgery ward. Each ward had 26–38 beds in combinations of multi-bed bays and single rooms. Patients were cared for by junior medical officers supervised by consultant physicians or surgeons, registered and enrolled nurses with daytime ratios of 4–6 patients per nurse, and allied health professionals  with varying team communication structures. Figure Site facilitators were an occupational therapist, two dietitians and a registered nurse, all with four or more years of clinical experience and previous quality improvement experience. Each was working within the site in a clinical capacity which provided some tacit knowledge of the local and organisational context. One had previous experience working in Eat Walk Engage at the pilot site. All attended four half-day group training sessions, and 10–12 group mentoring sessions, and all remained in the position until the end of the evaluation. Multidisciplinary work groups were convened in all sites by February 2016. During the following 15 months, Site A held 11 work group meetings, Site B held 16, Site C held 9 and Site D held 5. Median attendance was 6–8 staff per meeting at all sites. Assistants were recruited at three sites by October 2016, and included a physiotherapy assistant, an occupational therapy assistant and a nursing assistant. All completed the introductory training and work shadowing; the nursing assistant required additional mobility training with the local physiotherapist. No assistant was recruited at site D.Facilitators employed multiple implementation strategies to facilitate change  as outliUsing these strategies, the site facilitators facilitated 45 discrete improvements summarised in Table Interviews were conducted with 42 older inpatients pre-intervention and 38 post-intervention (Site D only achieved 7 post-intervention interviews). Most agreed that the key principles were very important to recovery  may have meant that they were more confident or comfortable supporting nutrition or engagement interventions, or the well-recognised multi-level barriers to in-hospital mobility , 33 may The study supports the i-PARIHS implementation theory, illustrating how experienced facilitators supported novices to consciously adapt implementation strategies and improvements within varied and dynamic contexts. Facilitation is both a role and a set of activities . The stuOur longitudinal observations also illustrate how context influenced and was influenced by implementation . An adveStrengths of this study are a clear logic model and prospective use of an appropriate implementation theory. Implementation was guided by older patients’ experience and local context as well as published evidence, and ward-level observations provided meaningful measurement of programme goals both as an opportunity for improvement and a measure of progress. Rich evaluation using multiple data sources captured critical concepts of context, implementation and mechanisms; an accompanying in-depth qualitative evaluation of the facilitator’s journey will augment the evaluation further. We acknowledge potential limitations, including the challenges inherent in program developers and facilitators being involved as investigators . The evaThe Eat Walk Engage programme was implemented with reasonable success across four wards with varied and dynamic contexts using an experienced-novice facilitation model. The facilitators used a wide range of implementation strategies to support diverse improvements aligned with program goals, and these were associated with improvements in several key processes of age-friendly care which likely mediated the observed reduction in delirium. The limited impact on functional decline and length of stay might be explained by inconsistent improvements in mobility, perhaps because insufficient improvements were implemented within the project time frame to address this care practice. Spread and sustainability of this complex intervention will require continued investment in skilled multi-level facilitation to support clinician-led improvement in dynamic and varied ward contexts.Additional file 1: Supplementary Table 1. Summary of patient interview data regarding perceived importance of the key principles, and their recollections of staff recommendations related to these principles. Supplementary Table 2. Summary of key process of care measures before and after implementation, by site.


CYP1A2 and AHR genes via the two-sample Mendelian randomization (MR) framework to estimate the association of genetically predicted plasma caffeine and caffeine intake on kidney traits. Genetic association summary statistics on plasma caffeine levels and caffeine intake were taken from genome-wide association study (GWAS) meta-analyses of 9876 and of >47,000 European ancestry individuals, respectively. Genetically predicted plasma caffeine levels were associated with a decrease in estimated glomerular filtration rate (eGFR) measured using either creatinine or cystatin C. In contrast, genetically predicted caffeine intake was associated with an increase in eGFR and a low risk of chronic kidney disease. The discrepancy is likely attributable to faster metabolizers of caffeine consuming more caffeine-containing beverages to achieve the same pharmacological effect. Further research is needed to distinguish whether the observed effects on kidney function are driven by the harmful effects of higher plasma caffeine levels or the protective effects of greater intake of caffeine-containing beverages, particularly given the widespread use of drinks containing caffeine and the increasing burden of kidney disease.Caffeine is a psychoactive substance widely consumed worldwide, mainly via sources such as coffee and tea. The effects of caffeine on kidney function remain unclear. We leveraged the genetic variants in the  Caffeine, a central nervous system stimulant, is present in coffee beans, tea leaves, and cacao beans and is commonly added to energy and carbonated drinks as well as analgesic drugs . By inhiIncreasing evidence has indicated that caffeine may have detrimental effects on kidney function, although the literature remains controversial. Animals’ investigations have shown an increase in proteinuria and renal vascular resistance, leading to marked renal failure ,4. In paCYP1A2 and AHR genes via the two-sample Mendelian randomization (MR) framework to estimate the association of genetically predicted plasma caffeine level and caffeine intake on kidney traits, which comprised glomerular filtration rate estimated from creatinine (eGFRcrea) and glomerular filtration rate estimated from cystatin-c (eGFRcyst), urinary sodium, urinary, blood urea nitrogen (BUN), albumin-creatinine ratio (UACR), and risk of CKD. With this study, we aimed to overcome the limitations of traditional observational methods, including environmental confounding and reverse causation, by employing the MR paradigm. In particular, because the genetic variants used as instrumental variables in MR are randomly allocated at conception, their associations are not typically affected by environmental confounding factors. Additionally, their allocation precedes the exposure and outcome, protecting against reverse causation bias. Further, we consider both caffeine intake and plasma caffeine levels, respectively, as the relevant exposures of interest.Here, we leveraged the genetic variants in the Genetic association summary statistics for plasma caffeine level were retrieved from a meta-analysis of six genome-wide association studies (GWAS) on caffeine metabolites: the Prospective Study of the Vasculature in Uppsala Seniors (PIVUS), the Study of Health in Pomerania TREND (SHIP-TREND), the Swiss Kidney Project on Genes in Hypertension (SKIPOGH), TwinGene, TwinsUK and the Uppsala Longitudinal Study of Adult Men (ULSAM), including a total of 9876 European ancestry individuals . Plasma Caffeine intake summary statistics were derived from a GWAS meta-analysis including >47,000 individuals of European descent from 5 studies (Atherosclerosis Risk in Communities (ARIC), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), the Nurses’ Health Study (NHS), the Health Professionals Follow-Up Study (HPFS), Women’s Genome Health Study (WGHS)) . In each2 and log transformed ; p = 1.6 × 10−6 for log(eGFRcyst)), and log(UACR) . Genetically predicted plasma caffeine levels were also associated with higher urinary sodium levels  and BUN .The MR analysis identified that a 1-SD increase in genetically predicted plasma caffeine level was associated with a decrease in eGFR  and 0.013 ; p = 0.01, for log(eGFRcyst)), and log(UACR) . A 1-SD increase in genetically predicted caffeine intake was also associated with a lower risk of CKD , lower urinary sodium , and BUN . A graphical summary of the results is shown in In contrast, higher genetically predicted caffeine intake associated with an increase in both eGFR measures , which was minimized in this study by selecting genetic instruments with effects that plausibly act directly on the trait in question  by the regulation of CYP1A2 expression. A limitation of this study is that our findings might not be generalizable to a population of non-European ancestry because all genetic summary statistics are from European ancestry. Nevertheless, a previous study confirmed that ividuals . AnotherThis MR analysis provides evidence that there is an effect of coffee consumption and genetic predisposition to caffeine metabolism on kidney function. It suggests a detrimental effect of genetically predicted higher plasma caffeine levels and a protective effect of a genetically predicted higher amount of caffeine intake on kidney function. Further research is needed to distinguish whether the observed effects on kidney traits are driven by the harmful effects of plasma caffeine in slower metabolizers or the protective effects of greater caffeine intake in faster metabolizers.