Cement augmentation is a technique used to increase the stability and purchase of pedicle screws in poor quality bone. Various methods can be applied for cement delivery, such as cement injection before screw placement and the use of fenestrated screws. However, potential problems can arise with the use of cement augmentation.2‐5), with minimal comorbidities, was referred to our unit 9 months after surgery. Pain and progressive kyphosis were investigated clinically and radiographically with computed tomography (CT) scans to assess the status of the hardware and fusion. CT imaging revealed that cement was present only at the distal tip of the fenestrated screws at the L4 vertebral level. A non‐union was present along with loosening and a halo around the body of the pedicle screws, and there was evidence of pullout of inferior screws.A 66‐year‐old man with a lower trunk deformity, severe kyphosis, and sagittal imbalance following fusion (LSingle‐level cement augmentation of pedicle screw in a posterior construct and distal tip cement augmentation of the screw results in a fixed pivot point. Micromotion in cranio‐caudal loading during flexion and extension may result in screw toggling with the single‐level cement‐augmented tip as a fulcrum. This may cause screw loosening, which can lead to pullout and loss of construct stability. The halo around the screw suggests bone loss and/or a fibrous tissue interface, which further complicates revision surgery. Stress shielding and polymethylmethacrylate cement present additional difficulties.The findings of this technical note question the risks and benefits of cement‐augmented fenestrated pedicle screw fixation for spinal fusion. Although incidences of such cases are uncommon, surgeons should perform this technique with caution. Accurate restoration of lumbar lordosis during index procedures is important to minimize the risk of construct failure. The use of vertebral screws for spinal fixation dates back to the 1940s and has since evolved into pedicle screw fixation for stabilization to encourage intervertebral arthrodesisHowever, potential problems can arise with cement augmentation. Intraoperative mis‐positioning of screw holesAlthough clinical studies discussing the potential toggling of pedicle screws have been carried out, to the authors’ knowledge there is no formal publication reporting the outcomes of screw toggling in patients. This technical note will discuss the outcomes of distal cement augmented pedicle screw which serves as a pivot point for proximal screw toggling and loosening.2‐L5) with postero‐lateral grafting, without inter‐body implants from a different institute. He experienced significant pain due to L4 and L5 motor / sensory radiculopathy. Reflexes were absent in both lower limbs with a bilateral foot drop. Oswestry Disability Index was 74%, with Visual Analog Scale pain score of 10 in the standing position, 8 on lying flat.We report a case of a 66‐year‐old male with minimal co‐morbidities who presents with lower trunk flat back deformity, severe iatrogenic kyphosis and sagittal imbalance following 9 months postoperative lumbar decompression and fusion  scan revealed loosening and non‐union of the inferior aspect of the fusion construct. There is pull‐out of the inferior screws Fig. A with haThe haloing effect demonstrated by the pedicle screws is consistent with hardware failure, and also seen in the “PEEK‐Halo” effect when PolyEther‐Ether‐Ketone (PEEK) is being used as an intervertebral implant which results in poor osseointegration3/4 and L4/5 levels) and Posterior Smith‐Peterson osteotomy at L3/4. Focal lordosis of approximately 22o was corrected resulting in a total correction of over 65 degrees at L3/4. The patient was able to stand up‐right which enabled him to maintain his view on horizon when his spine was in a neutral position. Figure A revision procedure utilizing both anterior and posterior approach was carried out Fig. . LordosiTo the authors’ knowledge, there is currently no literature reporting such an adverse event, however the use of fenestrated cement fixation is relatively recent. A cadaveric study by Bostelmann et al. studying the effect of cranio‐caudal cyclic loading on non‐augmented and cement‐augmented pedicle screws concluded the superiority of augmentation compared to standard pedicle screwsIn the case of fenestrated screws were only the tip is strongly fixated by cement in the vertebral body, the tip can act as a fulcrum in which micro‐movements and torsion can cause toggling of the screw body within the pedicle, resulting in proximal loosening, and non‐union of the fusion construct. As time passes, cranio‐caudal loading during lumbar flexion and extension, accumulates into a significant amount of force which eventually results in minute motions turning into significant toggling upon the cemented fulcrum. Further loading result in more proximal toggling. The loss of bone structure around the screw appears as a haloing effect seen on imaging Fig. . The togThe reduced forces withstood by the spine may be a potential risk factor for stress shielding to occur. As seen in the hip, stress reduction in an implanted bone can lead to bone lossThe end result of such an effect can be disastrous to the patient. Revision of the loose pedicle screws presents a significant problem, as removal of these screws may lead to further damage of the surrounding bone or fracture of the vertebral body and the pedicles. The patient may require further levels of fusion as well as other invasive surgeries  to correct the kyphosis. Blattert et al. argued that removal of cement‐augmented fenestrated screws was possible even in severe osteoporosis. They concluded that the cement screw connection was fragile enough to break off during extractionDifferent methods have been proposed and used for the revision of non‐augmented pedicle screws. These include the use of a larger and longer pedicle screwsIn addition to extending the posterior construct for re‐establishing sagittal balance, the authors agree that the use of interbody fusion techniques may further benefit the patient for anterior column support. In terms of correcting sagittal alignment, the use of ALIF as in the current case has been shown to compliment other realignment techniquesFurther studies and data are required to study the long‐term efficacy of cement‐augmented pedicle screw fixation, associated risks and complications. Long‐term outcomes of pedicle screw fixation comparing different screws should be carried out to compare the pros and cons of different screw designs. Recently, expandable pedicle screws have gained an interest amongst spine surgeonsThe use of single‐level cement augmentation has resulted in a fulcrum for screw toggling when load was applied along the construct. Accurate restoration of sagittal alignment with ideal lumbar lordosis at the index procedure while using cement augmentation techniques would have reduced the risk of such a complication. Separately, the use of cement‐augmented fenestrated pedicle screws is a recent technique. Although there is currently an adequate body of literature on the pull‐out strength and stability of cement‐augmented fenestrated pedicle screws, there are no reports on non‐union biomechanics and the effect of cranio‐caudal toggling. Haloing around pedicle screw due to toggling is a major complication especially if cement‐augmentation was used. This phenomenon adds significant difficulty and potential morbidity to the revision procedure. Anterior or lateral interbody cages may aid with sagittal realignment. The appearance of such phenomenon potentially questions the role of such fixation technique. The use of intra‐operative on table CT scan may be beneficial to access the accuracy of screw placement in order to limit post‐operative toggling due to abnormal stress loading.All authors contributed significantly and met the authorship criteria according to the latest guidelines of the International Committee of Medical Journal Editors. All authors agree to the final submitted manuscript.


MDA) and clinically inactive disease (CID). We undertook this study to compare short‐ and long‐term outcomes following achievement of MDA and CID on the 10‐joint clinical Juvenile Arthritis Disease Activity Score (cJADAS10) and following achievement of CID on Wallace et al's preliminary criteria.Potential targets for treat‐to‐target strategies in juvenile idiopathic arthritis are minimal disease activity . At 1 year, 21% had achieved CID on the cJADAS10 may be preferable as a treatment target to CID on Wallace et al's preliminary criteria in terms of both feasibility of application and long‐term outcomes. Despite the licensing of biologic therapies for juvenile idiopathic arthritis (JIA) Defining disease states such as CID in clinical practice can be challenging and currently relies on composite criteria Therefore, the aims of this study were 1) to describe the impact of early achievement of CID on functional ability, joint limitations, and psychosocial health over the first 5 years following initial presentation to a pediatric rheumatology clinic, 2) to assess whether the applied definition of CID at 1 year is associated with different long‐term outcomes, and 3) to assess whether achieving CID is beneficial beyond MDA in terms of pain in addition to these outcomes according to the 10‐joint cJADAS (cJADAS10).Study population. This analysis included children recruited to the Childhood Arthritis Prospective Study (CAPS), a prospective inception cohort recruiting from 8 UK pediatric and adolescent rheumatology centers since 2001. Details of this cohort have been described previously For this study, children were included if they had a physician's diagnosis of JIA (oligoarticular and either rheumatoid factor [RF]–negative or –positive polyarticular categories) and had been recruited to the CAPS prior to January 1, 2011 to allow for at least 5 years of follow‐up. Children were included in each analysis if outcome data were available for at least one of the time points studied. Those who had not returned study forms after initial presentation were excluded.Data collection. CAPS data were collected from the medical case notes at first presentation to a pediatric rheumatology clinic (baseline date) and annually thereafter for 5 years using a predefined study schedule. These include demographic and disease features, International League of Associations for Rheumatology (ILAR) category At each follow‐up visit, proxies (or the children themselves where possible if they were age >11 years) were asked to complete a series of patient‐reported outcome measures, including the Childhood Health Assessment Questionnaire (C‐HAQ) and the Child Health Questionnaire (CHQ) States of CID and MDA. Using data from 1 year following initial presentation, children were categorized according to their CID status on Wallace et al's preliminary criteria Outcome assessment. The following outcomes were selected: functional ability on the C‐HAQ, no joints with limited range of motion, psychosocial health on the CHQ, and pain. These outcomes were selected to avoid circular reasoning. For example, the cJADAS10 includes the proxy global assessment of well‐being and Wallace et al's preliminary criteria do not. It would therefore be expected that CID on the cJADAS10 would be more strongly associated with better longitudinal proxy‐assessed well‐being than would CID on Wallace et al's preliminary criteria. To avoid this circular reasoning, all outcomes selected for the current study must not have formed one of the components of either CID/MDA criteria set. All outcomes were assessed annually from baseline to 5 years following initial presentation to a pediatric rheumatology clinic.Statistical analysis. First, associations were tested between 1‐year CID/MDA states cross‐sectionally with the outcomes at 1 year. Second, associations between these 1‐year states and outcomes annually from 1 to 5 years following initial presentation were analyzed via multilevel, multivariable regression analyses. All children with outcomes available for at least one time point were included. Depending on the outcome, the following regression analyses were applied: logistic  and linear  regressions. The known floor effect of the C‐HAQ, whereby scores cluster at the “high functional ability” end of the scale Data were analyzed following multiple imputation under assumptions detailed in previous work Random effects were included at the patient level for longitudinal models. The zero‐inflated longitudinal models instead incorporated robust clusters at the patient level. Multivariable models were adjusted for hospital, age, symptom duration and year of presentation, sex, and ILAR category, and models at 1 year were also adjusted for respective outcome at baseline. Covariate multicollinearity was assessed via Spearman's correlations, and zero‐inflated negative binomial models were deemed preferable to Poisson models if dispersion parameter 95% confidence intervals (95% CIs) did not contain zero. All analyses were completed using Stata software, version 14.Patient cohort. A total of 1,106 patients had been recruited to the CAPS by January 1, 2011. Of these, 274 were excluded . This left 832 patients for the current analyses, including 649 for whom we had available data on the CHQ psychosocial score at any time point (601 from 1 year onward). By the end of the 5‐year follow‐up period, 510 children (61%) remained under care of pediatric rheumatologists and had not been lost to follow‐up or discharged . The numbers of children with available data for each outcome across time points are shown in Supplementary Table http://onlinelibrary.wiley.com/doi/10.1002/art.40519/abstract.Within the cohort, median age at initial presentation to a pediatric rheumatology clinic was 6.9 years (interquartile range [IQR] 3.1–11 years), and median symptom duration at presentation was 5.5 months (IQR 2.9–11 months). Seventy percent of the cohort were females, and 68%, 28%, and 5% were diagnosed as having oligoarticular JIA, RF‐negative polyarticular JIA, and RF‐positive polyarticular JIA, respectively . Twenty‐one percent had achieved both CID states, and an additional 23% had achieved only one state of CID . On the cJADAS10, 48% of patients had achieved MDA. Of those patients, 79% had also achieved CID (38% of the entire cohort).Association between early achievement of CID and outcomes measured at 1 year. All estimates from complete case analyses were similar to those following multiple imputation (see Supplementary Tables http://onlinelibrary.wiley.com/doi/10.1002/art.40519/abstract). The following results relate to imputed data, except for CHQ psychosocial scores. All models met the tested assumptions.At 1 year, achievement of any state of CID was associated with significantly increased odds of having no joints with limited range of motion . However, children who had achieved CID only on Wallace et al's preliminary criteria but not on the cJADAS10 had no better CHQ psychosocial scores or C‐HAQ scores than those with active disease at 1 year. In contrast, those children who had achieved CID on at least the cJADAS10 scored at least 5 points better on CHQ psychosocial health  than did children with active disease. Those children also had at least 4 times the odds of having no disability recorded using the C‐HAQ  than did those with active disease. When assessing nonzero C‐HAQ scores, children who had achieved CID on the cJADAS10 had 50% lower scores   and lower VAS pain scores  at 1 year. However, there were no significant differences between these 2 groups of children in any of the C‐HAQ or CHQ psychosocial outcomes  anAssociations between disease activity state at 1 year and long‐term outcomes. Early achievement of CID on either criteria set was associated with between 2.0 times  and 3.0 times  the odds of no joints with limited range of motion for each additional year through 5 years compared with children who had active disease at 1 year  and −5.5 mm better pain scores  through 5 years. There was no difference between these patient groups in C‐HAQ or CHQ scores (Table The success of treat‐to‐target strategies in adult rheumatology, such as aiming for a low Disease Activity Score in 28 joints The results of this analysis show that children who achieve CID at 1 year according to either measure have lower counts of joints with limited range of motion both at 1 year and over the next 4 years of follow‐up. However, children who achieved CID according to Wallace et al's preliminary criteria but not according to the cJADAS10 were consistently found to have high levels of disability and poorer psychosocial function. Previous analysis has shown that this difference is driven by lower levels of patient well‐being, despite the absence of joints with active disease or other inflammatory manifestations of disease This study benefitted from a large sample of patients with JIA in all 3 ILAR categories assessed, all of whom were treated within a single health care service. The scale of the data collected meant that 5‐year outcomes could be assessed following early achievement of different CID states. In addition, robust methods, including imputation methods under clinically plausible assumptions, were implemented to deal with the inevitable missing data associated with observational cohorts. In particular, a large proportion of patients were lost to follow‐up. Informative dropout in the majority of cases informed the imputation methods for CID/MDA states. In turn, this information was used to impute missing outcome values. Thus, although precision of model estimates is affected by missing data, the point estimates should be relatively unbiased.A challenge is in understanding how best to apply these results in the clinical setting. As achievement of CID according to the cJADAS10 was associated with outcomes equivalent or superior to those for CID achieved according to Wallace et al's preliminary criteria, and since the cJADAS10 is more feasible to complete in clinical practice because it contains only 3 routinely collected components As the 2 scores differ in their components, one could argue that they are not capturing the same construct. Wallace et al's preliminary criteria capture more objective measures of inflammation, while the cJADAS10, through inclusion of a measure of patient well‐being, may also capture other noninflammatory components of the disease, such as chronic pain and fatigue not captured by Wallace et al's preliminary criteria. However, in addition to a single score/cutoff, the value of the individual components of the cJADAS10 would be required to guide individual treatment decisions. Although it is well recognized that functional ability, HRQoL, and pain do improve following treatment with both methotrexate and biologic therapies At the outset of this analysis, it was also unknown whether achievement of CID is associated with better outcomes than those for patients who achieve MDA but not CID. The present study found that achieving CID on the cJADAS10 is associated with fewer joints with limited range of motion compared with achieving MDA. However, achieving CID above MDA was not associated with greater improvements in C‐HAQ or CHQ scores, either between baseline and 1 year or from 1 to 5 years. Therefore, MDA on the cJADAS10 may be an appropriate target when disease activity parameters are low but patient well‐being is poor. The risk of adverse effects with treatment intensification should be considered, particularly if the attainment of CID is deemed unlikely A limitation of this study was that, to avoid circular reasoning, important disease activity variables such as counts of joints with active disease could not be used as outcomes. Since the variables differentially form the CID states, any state including said variable would be intrinsically more likely to associate with the outcome. The outcomes selected for the study did, however, comprise multiple physician‐ and patient‐important outcomes. However, these conclusions can only relate to oligoarticular and polyarticular JIA. The CID definitions have only been validated in these categories, and it is likely that additional components will need to be added to these criteria sets in order to fully capture low and inactive disease in less common JIA categories. In addition, due to a lack of data on morning stiffness, we were not able to compare outcomes following the achievement of the 2011 ACR CID criteria with the other CID states. Finally, although it has been suggested that treat‐to‐target strategies will result in better long‐term outcomes, during the period of data collection for this study there was no formal treat‐to‐target strategy in place in the UK. Therefore, although the findings support the notion that early achievement of CID is associated with better outcomes, the data cannot be used to show that active treatment toward these targets currently results in better long‐term outcomes. Further work will need to assess long‐term outcomes following the implementation of these guidelines.In conclusion, early achievement of CID according to the cJADAS10 is associated with long‐term outcomes equivalent or superior to those associated with early achievement of CID according to Wallace et al's preliminary criteria. Differences in the components of these 2 definitions and the implications for clinical practice through implementation of a single score suggest that the optimal definition of CID for application in a clinical setting remains unclear. Further work, ideally involving consumers, clinicians, and researchers, is needed to best define treatment targets and treatment strategies for use in JIA. The results do, however, highlight the importance of addressing all aspects of JIA and not just the underlying inflammation, in terms of best outcomes for the child.All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Hyrich had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Shoop‐Worrall, Verstappen, Thomson, Hyrich.Baildam, Chieng, Davidson, Foster, Ioannou, McErlane, Wedderburn, Thomson, Hyrich.Shoop‐Worrall, Verstappen, McDonagh, Hyrich. Click here for additional data file.


DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption that DOY accurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno‐climatic models (PCMs) designed to predict the effects of climate on flowering date.Herbarium specimens have been used to detect climate‐induced shifts in flowering time by using the day of year of collection (PI), which we use in PCMs to control for phenological variation among specimens of Streptanthus tortuosus (Brassicaceeae) when testing for the effects of climate on DOY. We demonstrate that including PI as an independent variable improves model fit.Here we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI in PCMs increased the model R2 relative to PCMs that excluded PI; regression coefficients for climatic parameters, however, remained constant.Including PI in PCMs increases R2 and enables predictions of the DOY of any phenophase under any specified climatic conditions.Our protocol provides a simple, quantitative phenological metric for any observed plant. Including  Studies of phenology—the timing of life cycle events—have provided some of the strongest evidence that many organisms have been or will be affected by global changes in climate  of specimens that were collected in flower. In these studies, DOY is considered to be a proxy for first flowering date (FFD) or the date of peak flower (DPF)  but likely included specimens that were collected both pre– and post–peak flowering. Data recorded from field‐based observations, by contrast, represented the true dates of peak flower. When the flowering date derived from each data set was regressed (separately) on temperature, both data sets showed a negative relationship between flowering date and temperature, but temperature explained four times more variation in flowering date in the field data–based model than the herbarium data–based model , presumably because it did not conflate variation in actual DPF with variation caused by sample collection that occurred before or after DPF. High variation among the phenological status of herbarium sheets is one potential reason for the low explanatory power of models constructed with herbarium‐derived data. Another potential factor includes the possibility that herbarium‐derived data, which are often distributed across broader spatial extents than field‐based data, may therefore also differ from many field‐based data with respect to the range of climatic conditions represented.Figure Reducing—or controlling statistically for—variation among herbarium or living specimens in their phenological status could help to improve models and to clarify relationships between climate and flowering or collection date. This could be done by either (1) restricting data sets to include only those specimens collected at a specific phenological stage or (2) incorporating into statistical models a quantitative metric that estimates the phenological status of individual specimens or plants. Given that herbarium specimens are rarely collected precisely at first flower or at peak flowering, the first approach would drastically reduce the sample size used to estimate relationships between phenology and climate. This reduction in sample size might preclude the analysis of species represented by relatively few specimens . In addition, because herbarium specimens represent an instantaneous snapshot of an individual's phenological status, it is nearly impossible to determine whether an individual specimen was collected at peak flower. However, we can easily quantify a specimen's phenological status by determining the numbers of the different classes of reproductive organs  present on each sheet, and then converting those counts into a proportional weighted mean.Streptanthus tortuosus Kellogg, Brassicaceae) specimens; and (4) to discuss how parameterized models that include the PI as an independent variable can be used as a predictive model and as a means to quantify the length of the reproductive period.Here, our objectives are (1) to present a protocol designed to score and to record the numbers of reproductive structures representing successive developmental stages on imaged herbarium specimens using a plugin (Cell Counter) developed for the image analysis software ImageJ; (2) to introduce a new integrated metric of a specimen's phenological status—the phenological index (PI)—which is calculated using the counts derived from Cell Counter and allows us to control for the variation in the phenological status of collected specimens when testing statistical models for the effect of climatic conditions on the DOY of specimen collection; (3) to demonstrate how the PI can be used to construct and improve pheno‐climatic models using a herbarium‐derived data set composed of mountain jewelflower  induces individual plants or populations to flower earlier  present on a preserved plant on a herbarium sheet. The proportion of a given class is then weighted by an index representing the degree of phenological advancement of that class . The following equation can be used to calculate the PI for each plant:S. tortuosus (Brassicaceae) herbarium specimens from the California Academy of Sciences (CAS) and the University of California, Santa Barbara (UCSB), were imaged using an ORTECH Photo e‐Box Plus 1419 imaging station  at the Cheadle Center for Biodiversity and Ecological Restoration at UCSB. Each plant on the imaged sheets was scored with ImageJ using the plugin Cell Counter by counting the number of buds, flowers, immature fruits, and mature fruits present on each plant , which is a database that contains location information for many California herbarium records  during the year and previous year that each herbarium specimen was collected. Specifically, we extracted total winter precipitation  and the spring  mean maximum temperature (Tmax). Winter precipitation was selected because the California Floristic Province, where S. tortuosus occurs, receives the majority of annual rainfall during winter months. Maximum temperature was selected instead of mean or minimum temperatures because this parameter has been shown to have a higher predictive power (R2) than other temperature parameters in large‐scale phenological models  of all S. tortuosus specimens available from the CCH for which the exact collection date  was recorded  and multiple regressions using 10‐fold cross‐validation were performed using Python version 2.7.11 , we were able to capture a wide variety of collection dates and phenological progressions in our sample  and has a lower overall corrected Akaike information criterion  includes temperature and precipitation parameters as main effects, whereas the second model Model 2) includes the same climatic parameters in addition to the PI as main effects. Model 2 explains 31% more variation in DOY than Model 1 , whereas Model 2 parameters indicate that flowering time advances 4.14 ± 0.48 days/°C , whereas Model 2 detected that DOY is delayed by one day for every 50‐mm increase in winter precipitation  every 17.08 ± 3.37 days  at a given location with a given set of climatic parameters, in this case winter precipitation (winter PPT) and maximum spring temperature (spring Tmax), from the following equation:Including the PI allows us to use the parameterized pheno‐climatic model to predict the day of year of peak flowering of S. tortuosus specimens. We found that while including the PI as an independent variable in a pheno‐climatic model does not appear to dramatically alter the resulting model coefficients, it does provide a substantial improvement to the model's predictive power by accounting for variation in DOY caused by collection of specimens at different phenological stages. Third, we tested a series of predictions concerning the phenological response of S. tortuosus to local climate. We found that warmer spring maximum temperatures and drier winters during the year of specimen collection advance the reproductive phenology of S. tortuosus across its range. Finally, we demonstrated how pheno‐climatic models constructed with the PI as an independent variable can be used to estimate the length of the reproductive period as well as forecast the day of year of onset of any reproductive phase for any given set of climatic conditions.The work presented here was motivated by four primary objectives. First, we developed a protocol to score the phenological status of imaged herbarium specimens by first counting the number of reproductive organs representing different developmental stages . This process was facilitated by the use of Cell Counter, a plugin available through the free image processing and analysis software ImageJ. This protocol provides users a fast and easy way to reliably score imaged herbarium specimens. Second, we used these counts to develop a new quantitative metric of a specimen's phenological status: the phenological index. We then demonstrated how it can be used to construct and improve pheno‐climatic models in our analysis of a herbarium‐derived data set composed of S. tortuosus. The DOY of sampled herbarium specimens advances with increased temperature and is delayed with increased precipitation, which corroborates our predictions concerning the relationship between flowering date and climate. The sensitivity of DOY to temperature observed in S. tortuosus is consistent with that observed in other herbarium‐based studies of intraspecific variation in phenology in relation to climate. For example, Matthews and Mazer . Both of these studies detected similar sensitivities to temperature to that detected in S. tortuosus  will facilitate the testing of more complex models and the detection of more subtle relationships between climate and the timing of distinct phenophases  and Global Biodiversity Information Facility .Here, we provide a simple and readily available method to score imaged herbarium specimens using the free image analysis software program, ImageJ, and the available plugin, Cell Counter. Cell Counter allows its user to use point‐and‐click movements to accurately count the numbers of reproductive organs representing each of any number of distinct phenological phases, as specified by the user. Because of the ease and simplicity of this protocol, it could be easily incorporated into workflows that include scoring by citizen scientists, especially with the forthcoming widespread availability of imaged herbarium specimens through data aggregators such as Integrated Digitized Biocollections , this variable accounted for 11.5% of the variance in flowering date among ens Fig.  and Ellwens Fig.  both fouS. tortuosus. By including only two climatic parameters, we were able to construct a model that predicts the day of year of peak flowering among our sampled herbarium specimens with 47% accuracy  for cy Table . With a cy Table .Rhododendron species was sensitive to changes in annual average temperature (−2.27 days/°C); therefore, they expected that because mean temperature had increased during the study period (1952–2009), they would detect a temporal advance in flowering date. However, they failed to detect a statistically significant phenological shift. The variation in phenological stage among specimens may have obscured the true relationship across the sampled decades. Including the PI may be especially useful in models designed to detect shifts in flowering date through time because such shifts are likely to be small and difficult to detect. Consequently, reducing the error variance in the model due to variation among specimens in their phenological status will likely improve our ability to detect temporal shifts in flowering date while also helping to improve the fit and accuracy of pheno‐climatic models.One of the main goals of herbarium‐based studies is to investigate long‐term shifts in flowering date through time to determine whether the seasonal cycles of plants have been affected by recent temperature increases. Some of these studies have successfully detected advances in flowering date through time  and to improve pheno‐climatic models (Lorieul et al., S. tortuosus, the inclusion of PI as an independent variable reduced the resulting error variance in the DOY among specimens while increasing the model's predictive power and decreasing the AICc. The PI also provides a way to quantify the reproductive period of plants from herbarium specimens and allows us to estimate not only how climate affects flowering dates but also how climate may affect the length of the reproductive period. Moreover, pheno‐climatic models constructed with the PI can be used to forecast the day of year of a specific phenophase, given any specified set of climatic parameters.In our multivariate models for APPENDIX S1. Ten‐fold cross‐validation for pheno‐climatic Models 1 and 2.Click here for additional data file.


Permanent Ocean, Land, Permanent Ice, and Transient Sea Ice—is used to investigate the influence of surface type on low‐level Arctic cloud liquid water path (LWP) seasonality. The results show significant variations in the Arctic low‐level cloud LWP by surface type linked to differences in thermodynamic state. Subdividing the Transient Ice region  by melt/freeze season onset dates reveals a complex influence of sea ice variations on low cloud LWP seasonality. We find that lower tropospheric stability is the primary factor affecting the seasonality of cloud LWP. Our results suggest that variations in sea ice melt/freeze onset have a significant influence on the seasonality of low‐level cloud LWP by modulating the lower tropospheric thermal structure and not by modifying the surface evaporation rate in late spring and midsummer. We find no significant dependence of the May low‐level cloud LWP peak on the melt/freeze onset dates, whereas and September/October low‐level cloud LWP maximum shifts later in the season for earlier melt/later freeze onset regions. The Arctic low cloud LWP seasonality is controlled by several surface‐atmosphere interaction processes; the importance of each varies seasonally due to the thermodynamic properties of sea ice. Our results demonstrate that when analyzing Arctic cloud‐sea ice interactions, a seasonal perspective is critical.Using CALIPSO‐CloudSat‐Clouds and the Earth's Radiant Energy System‐Moderate Resolution Imaging Spectrometer data set, this study documents the seasonal variation of sea ice, cloud, and atmospheric properties in the Arctic (70°N–82°N) for 2007–2010. A surface‐type stratification—consisting  The Arctic low cloud liquid water path seasonal cycle exhibits a surface‐type dependenceSea ice affects liquid water path seasonality by modulating lower tropospheric stabilityRegions of earlier sea ice melt and later freeze onset show a larger cloud liquid water path variance Note that the sum of area percentage of ocean and sea ice  for a grid box can vary because of the limited sampling. Each 2° Land, which is consistent with the terrain boundary  A Transient Ice grid points possess a pronounced seasonal variation in SIC. Next, we consider spatial patterns of the onset date of sea ice melt and freeze to characterize the differences in the seasonal variations of Arctic sea ice coverage and their potential relationship with Arctic low‐level clouds. We define the onset date of sea ice melt at a grid point as the day after which its SIC shows a negative daily tendency for more than 80% of the time with a total decrease of SIC exceeding 15% within a 1‐month period. This condition guarantees a significant change in sea ice cover around the melt onset dates and also eliminates the influence of sea ice regrowth after a short‐lived melting event or due to divergence/convergence of the ice pack. Similarly, the onset date of sea ice freeze is defined as the day after which SIC shows an increasing daily tendency for more than 80% of the time with the total increase of SIC exceeding 15% within a 1‐month period.By definition, only Note that the melt and freeze onset dates defined in this study differ slightly from previous studies  of the SIC within a target region. Figures Transient Ice grid points. It is seen that regardless of an early or late sea ice melt onset date, most regions have high values of SIC (above 80%) before melt onset and gradually evolve toward a nearly ice‐free state (below 15%) after onset, confirming the effectiveness of our onset date detection methods. It can also been seen that the temporal evolution from sea ice freeze onset to an ice‐covered state is faster (~1–2 months) than that from sea ice melt onset to the minimum sea ice state (~2–3 months), consistent with results shown in Figure We calculated the probability density function (PDF) of 4‐year SIC data over aster ~1– months t4Transient Ice region  but larger than Land (0.15 kg/m2) and Permanent Ice (0.16 kg/m2). In cold months (November through April), low‐level cloud LWP varies little across surface types; Land, Permanent Ice, and Transient Ice surfaces all show a small LWP and weak spatial variability (a narrow width in the PDF). Similar findings have been reported using ground observed and satellite passive radiometer retrieval data  mean greater than 0.2 kg/m2 and a noticeable spatial variability. The temporal evolution of the low‐level cloud LWP over Permanent Ocean shows a continuous increase in the first half of the year (January‐June) and a decrease in the remainder of the year. Other surface types exhibit a strong increase in low‐level cloud LWP during warm months (May through September) and a gradual decrease in LWP after September‐October. It is noted that the Permanent Ice and Transient Ice surfaces show a unique midsummer evolution of LWP, i.e., decreasing from mid‐May to the end of June and then increasing again through mid‐August. This local minimum in the LWP around July is weaker over Transient Ice than over Permanent Ice.Table Transient Ice regions with different sea ice melt  indicate a higher likelihood of the specific LWP values relative to the LWP PDF of all Transient Ice grid points  play a dominant role in the seasonal cycle of LWP? Are these factors modified by the nature of underlying surface?According to previous studies  yet substantial moisture above Permanent Ocean (about 3 cm). Permanent Ocean exhibits the strongest evaporation rate in winter, whereas the other surface types have an evaporation rate close‐to‐zero  and air temperature at 700 hPa (T700hPa), over different surface types. LTS is defined as the difference between the potential temperature at 700 hPa and the surface  and resembles Permanent Ocean in warm months (May‐September). These LTS seasonal variations agree well with the annual cycle of LTS over the Beaufort‐Chukchi Seas seasonal ice zone reported by Liu and Schweiger  and from fall to winter (during freeze season), making them distinctly different from Land or Permanent Ocean. In light of the aforementioned discussions, we expect the seasonal variations of LTS over different surface types to be influenced mainly by the thermodynamic properties of the surface.To assess which temperature, surface skin or atmospheric, controls the seasonal variation of LTS over different surface types, we examine the seasonal evolution of Ts Figure  and T700a Figure . It is ePermanent Ocean surface above freezing  correspond to the seasonal maxima in LWP. The time shift of the autumn LWP decreases toward an earlier/later time over regions where sea ice freeze earlier/later is consistent with the time shift of autumn LTS increase. The inverse relationship between LTS and LWP over Permanent Ice and most of the Transient Ice regions and the correspondence between the seasonal LTS minima and LWP maximum suggest that LTS plays an important role in controlling the seasonality of LWP. Low‐level Arctic clouds in Permanent Ice and Transient Ice regions tend to be decoupled from the surface during the warm season  Land, (iii) Permanent Ice where is covered by sea ice pack all the year round, and (iv) Transient Ice where there is a significant seasonal change in sea ice coverage, namely, covered by sea ice in winter but open water in summer. In addition, we further subdivide the Transient Ice region into four subregions according to sea ice melt/freeze onset dates to explore the influence of sea ice on the Arctic low cloud LWP.This study documents the seasonal variation of sea ice, clouds, and the related atmospheric properties in the Arctic region (70–82°N) for the period 2007–2010. We use a surface‐type stratification to investigate the influence of surface type on the seasonality of Arctic low‐level cloud LWP. Four surface types are defined: (i) Permanent Ocean due to cold temperatures and a lack of water vapor.The annual mean and seasonality of low‐level cloud LWP shows a strong dependence on surface type. Regions with smaller sea ice coverage have a higher surface skin temperature in warm months, stronger evaporation, more lower tropospheric moisture, and weaker LTS; conditions that promote larger low‐level cloud LWP. Regional differences in the annual mean cloud LWP are also affected by other factors, such as air and surface temperature and atmospheric advection from lower latitudes. The seasonal variation of LWP shows a large contrast among different surface types in warm months, whereas in cold months, LWP is close to zero over all surface types except Permanent Ice and Transient Ice regions exhibit a low‐level cloud LWP seasonal cycle with several distinguishing characteristics: (1) small LWP values during cold months, (2) a primary and secondary peak in May and September/October, and (3) a midsummer local minimum value. Stratifying the Transient Ice regions by sea ice melt and freeze onset dates provides several key results: (1) The timing of the May peak in the seasonal variation of low‐level cloud LWP is independent of sea ice melt onset timing; (2) the mid‐summer low‐level areal‐mean cloud LWP values and the width of the PDF are sensitive to melt onset where earlier sea ice melt regions possess larger low‐level cloud LWP with larger spatial variance; and (3) the timing of the autumn LWP peak is sensitive to sea ice freeze onset. Our analysis indicates a complex but close relationship between the sea ice and the seasonality of low‐level cloud LWP.The Permanent Ice and Transient Ice region, and (3) variations in LTS explain the warm season differences in the variation of LWP with respect to sea ice melt onset and freeze. Variations in evaporation rate have a smaller contribution than LTS because evaporation rate differences do not contribute to the May LWP maximum and evaporation rate does not explain the midsummer differences in LWP over the regions stratified by sea ice melt onset. Enhanced evaporation rate shows some correspondence to the Autumn LWP maximum in regions except Permanent Ocean. However, the evaporation changes linked to variations in underlying surface makes a minor contribution to the seasonal cycle of the water vapor in the lower troposphere. The seasonal structure of the lower tropospheric water vapor shows little contrast by surface type and does not align with the seasonality of low‐level cloud LWP and thus cannot be a primary controlling factor to its evolution.Variations in LTS is found to be the primary factor controlling the seasonality of cloud LWP and timing of the key turning points of the annual cycle of low‐level cloud LWP. The three primary pieces of evidence include (1) the significant correlation between LTS and LWP across all Arctic regions, (2) the correspondence between the seasonality of LWP and LTS such that the seasonal minima in LTS (May and October) correspond to the seasonal maxima in LWP over 700hPa is much weaker.Despite ruling out the influence of sea ice cover via modifying the surface evaporation, surface characteristics and sea ice melt/freeze onset influence the seasonality of low‐level cloud LWP by modulating the seasonality of LTS and the lower tropospheric thermal structure. The large contrast in the thermal inertia between ocean, sea ice, and land leads to differences in the seasonal variations of surface temperature, especially for the transient ice regions in the transitions between winter to summer (during melt season) and from fall to winter (during freeze season), while the contrast in TPermanent Ice and Transient Ice are explained by the thermodynamic characteristics of the surface and its changes. The May LTS minimum results from the rapid surface skin temperature increase in response to increased solar insolation that results from the low thermal inertia of the ice surface, outpacing the warming in the lower troposphere. The midsummer increase in LTS (which corresponds to a decrease in LWP across Permanent Ice and Transient Ice regions) occurs because the surface temperature becomes constant at 0 °C due to sea ice melt while the air temperature continues to warm. The LTS decrease from late summer to early autumn results from the rapid cooling of the lower troposphere while the high thermal inertia of the water surface maintains a warmer surface skin temperature. The LTS increase in autumn is closely tied to the surface thermal inertia decrease caused by the sea ice freezing. The timing of the LTS increase is highly dependent on the sea ice variation, which explains the significant time shift of autumn LWP decrease over regions with different sea ice freeze onset dates. Therefore, the seasonality of low‐level cloud LWP follows these variations in LTS and is attributed to the thermodynamic characteristics of the surface.The primary features in the seasonality of LTS over The influence of sea ice cover on the probability distribution of cloud LWP, to the best of our knowledge, has not been previously demonstrated. We speculate that the apparent enhancement in the variance in low‐level cloud LWP in midsummer may stem from the conditional availability of surface moisture whereby under specific conditions, the cloud layer can access surface moisture resulting in larger LWP values. Additionally, a surface‐type dependent modulation of surface temperature affecting the thermodynamic structure of the lower troposphere may also play a role.In closing, our results argue that the primary factor controlling the seasonality of low‐level cloud LWP in warm months at different surface types is the variation in lower tropospheric stability controlled by the surface thermodynamic characteristics. The Arctic low cloud LWP seasonality is complex with different processes and atmospheric conditions operating in different months. Taking a seasonal perspective when analyzing Arctic cloud‐sea ice interactions is critical. This refined understanding serves as a useful constraint to assess and improve the representation of the Arctic cloud annual cycle in climate models and increase the fidelity of Arctic climate change projections.Supporting Information S1Click here for additional data file.


Zosteriform cutaneous metastases are an unusual and rare morphological variant. We discuss the case of a 78‐year‐old gentleman with a background of end‐stage renal disease with metastatic adenocarcinoma of the lung which was diagnosed due to the development of zosteriform cutaneous metastases around his vascular catheter (vascath) site. The vascath may have acted as a traumatic nidus for lymphatic spread. Zosteriform cutaneous metastases are a rare morphological variant. We present a case of metastatic adenocarcinoma of the lung in a 78‐year‐old presenting as zosteriform cutaneous metastases around a vascular catheter site. Zosteriform cutaneous metastases are a rare morphological variant, which is infrequently described in the literature. In this paper, we report a case of a 78‐year‐old gentleman with zosteriform cutaneous metastases of lung adenocarcinoma, associated with a right internal jugular vascular catheter (vascath) site in a patient with end‐stage renal disease (ESRD).A 78‐year‐old gentleman of South‐East Asian heritage was admitted with cervical lymphadenopathy and a three‐week history of a new rash for investigation. He had a background of ESRD and was on haemodialysis via a right internal jugular vascath which had been inserted four to five months prior. His other past medical history included ischaemic heart disease with previous coronary artery bypass grafting, prior left frontal cardiovascular cerebral accident, atrial fibrillation, hypercholesterolaemia, and hypertension. He was HIV negative, was not immunosuppressed, and was not a transplant recipient. He was a reformed smoker, with a 25‐year pack history.The rash had started around the vascath site and had spread rapidly to his midline, right shoulder, and neck, as well as being associated with a similar isolated patch on his right abdomen. It was non‐pruritic and non‐painful. On examination, he had zosteriform erythematous to violaceous plaques with overlying microvesicles and dilated capillaries Figure . There wAbdominal skin and right supraclavicular lymph node biopsies were performed, and both showed metastatic non‐small cell carcinoma, with positive cytokeratin (MNF116) and Thyroid transcription factor 1 (TTF1) immunostaining favouring an adenocarcinoma of lung origin. The skin biopsy showed a lymphatic pattern of distribution of the adenocarcinoma in keeping with its metastatic nature Figure . EndotheCutaneous metastases are estimated to occur in approximately 2.1% of patients with lung cancer, and in about half of these cases are the first sign of extranodal disease Several mechanisms have been proposed to explain zosteriform metastases, including a Koebner or Koebner‐like phenomenon in skin previously affected by the varicella zoster virus (VZV), or post‐herpetic neural and immunological modulation which predisposes the previously affected skin to metastases A previous case report describes an incisional cutaneous metastasis in a patient with large cell adenocarcinoma of the lung nine months after a posterolateral thoracotomy and bilobectomy In our case, the vascath site may have functioned as a traumatic nidus for cutaneous metastasis, likely through lymphatic spread based on the histology findings and presence of lymphadenopathy. This is supported by the history of the rash, which started initially on the skin around the vascath. However, what is not known is whether this patient previously had VZV infection in the affected areas. Therefore, the possible role of VZV infection in predisposing the affected sites cannot be established with any certainty. Alternatively, haematogenous spread is also possible given the vascath is in direct communication with the inferior internal jugular vein but appears to be a less likely explanation given the associated regional lymph node spread.Appropriate written informed consent was obtained for publication of this case report and accompanying images.K. J. L. Wark is a relative of Professor Peter Wark who is on the editorial board.


Decreased plasma BDNF (pBDNF) levels have been proposed as a biomarker in illness phases of mood disorders. Serum cortisol (seC) levels are an index of energy mobilization and stress. The aim of this cross‐sectional study was to evaluate pBDNF and seC levels in workers exposed to occupational stress and suffering from Adjustment Disorders (AD) compared to healthy workers.Plasma BDNF and seC levels were measured by means of specific immunoassays in 64 AD patients and 38 healthy controls. Perceived and occupational stress was evaluated in patients and controls using the Psychological Stress Measure (PSM) and the Job Content Questionnaire (JCQ). Psychopatological symptoms in patients were assessed using specific rating scales.Plasma BDNF levels resulted significantly higher in patients than in controls, whereas no significant differences were found for seC levels. In patients but not in controls pBDNF levels showed a significant positive correlation with seC levels. Perceived stress levels were positively correlated with all psychopatological rating scales scores.BDNF could play a key role in the pathophysiology of stress‐related disorders and its peripheral levels elevation could contribute to protect neurons under stress. Further research is needed focusing on biomarkers for stress‐related disorders as a potential tool for the diagnosis and prevention of occupational diseases. A meta‐The current literature is lacking regarding BDNF levels in patients suffering from AD or in workers exposed to occupational stress. Being AD a paradigm of stress‐related disorders, it seems very crucial to investigate about neuroplasticity markers such as peripheral BDNF levels and HPA‐axis functions in AD patients. The aim of this study was, therefore, to measure pBDNF and seC levels in workers exposed to occupational stress and suffering from AD compared to healthy control subjects and to investigate about possible correlations in AD patients between the biological variables and patients' clinical characteristics.22.1SD: 47.3 ± 8.6 years) consecutively recruited at the Occupational Health Department operating in the Azienda Ospedaliero‐Universitaria Pisana and 38 healthy workers as control group  recruited from blood donors in hospitals of Tuscany and Liguria.This study has a cross‐sectional design and examines two samples consisting, respectively, of 64 AD patients . Exclusion criteria for patients were: age lower than 18 or higher than 65 years, presence of comorbid major neurological or medical illnesses, current acute or chronic inflammatory diseases in treatment with steroidal anti‐inflammatory drugs, taking psychopharmacological treatments in the last 4 weeks, pregnancy, presence of other current comorbid psychiatric disorders, presence of lifetime psychiatric comorbidity, onset of current AD symptoms as a reaction to preceding stressors different from current stressful work situations, insufficient comprehension of Italian that prevented completion of self‐report questionnaires, inability to sign informed consent.Exclusion criteria for healthy controls were as follows: age lower than 18 or higher than 65 years, history of past and/or current major medical or mental disorders, heavy cigarette smoking, current treatment with steroidal anti‐inflammatory drugs, regular medication intake and/or substance abuse.The research project was approved by the Ethics Committee of the University of Pisa according to the Declaration of Helsinki (2013) and the participation in the study was formalized with the collection of written informed consent.2.2The recruited AD patients received a general medical examination by an occupational physician and a psychiatric and psychological evaluation. The general medical examination, the collection of the medical history and the revision of clinical records of each patient allowed to exclude those with neurological or medical illnesses. Then, the patients were asked to complete questionnaires and rating scales as specified below.A self‐report form was used to collect sociodemographic and work information, including the type of contract, the number of years of work in the current workplace and in previous workplaces, the size and the sector of the firm.The clinical diagnosis of AD was confirmed by the administration of the Structured Clinical Interview for DSM‐IV axis I disorders Patient Version , a widely used self‐administered workplace environment questionnaire designed to measure social and psychological characteristics of jobs , a validated self‐report instrument designed using 49 items drawn from descriptors generated by focus groups on stress , a widely used 21‐item multiple‐choice self‐report test with two subscales (cognitive‐affective and somatic), was administered to AD patients to assess the severity of depressive symptoms , a self‐report instrument with adequate skills of sensitivity, accuracy, and reproducibility . Normal values for morning seC were 8.5–26 μg/dl.For serum extraction, a tube of whole blood was collected and then left to clot at room temperature for 30 min. The clot was removed by centrifuging at 2,000 2.4p value <0.05 was considered significant. As several correlation analyses were performed, the Benjamini–Hochberg correction for multiple testing was applied.The data were recorded in a specifically designed database and elaborated by means of the MedCalc software (version 12.7). According to the Kolmogorov–Smirnov test, all the examined continuous variables were normally (Gaussian) distributed except the PSM total score and the JCQ Job Demands and Social Support subscales scores. Therefore, the comparisons between patients' subgroups for variables of Gaussian distribution were performed by means of parametric statistical tests: in particular, the Student's test for independent samples was used. For the comparison of non‐Gaussian distributed variables the nonparametric statistical test of Mann–Whitney was performed. The Chi‐square test was used to compare the frequencies of categorical variables. Correlations between continuous variables of Gaussian distribution were examined by means of the Pearson's coefficient; for continuous non‐Gaussian distributed variables the Spearman's coefficient was used. A 33.1Sociodemographic and work characteristics, pBDNF and seC levels, stress rating scales scores of the two groups  are reported in Table p = 0.06), sex (p = 0.9) and education level having almost all patients  and all controls at least 8 years of education (p = 0.8). The majority of patients  and controls  were working for private companies. The frequency of stable job was significantly higher in the patients' group than in the controls' one . Plasma BDNF levels resulted significantly higher in patients than in controls , whereas no significant differences were found between the two groups for serum cortisol levels (p = 0.81). As for perceived psychological stress and occupational stress levels, patients presented significantly higher PSM and JCQ Job Demands scale but significantly lower JCQ Decision Latitude and Social Support scales scores than controls  did not significantly differ in terms of age . In AD patients seC levels resulted to be negatively correlated only with the SCL‐90 total score . By extending correlation analyses to both AD patients and healthy controls, pBDNF levels were also found to be positively correlated with the PSM total score  and negatively with the JCQ Social Support subscale score .As regards biological variables, in AD patients but not in healthy controls pBDNF levels showed a statistically significant positive correlation with seC levels , the SAS , the SCL‐90  and the PSQI . In AD patients but not in healthy controls they were also positively correlated with the JCQ Job Demands subscale score .As for clinical variables, in AD patients the perceived psychological stress levels expressed by the PSM total score showed significant positive correlations with the total scores of many psychopathological rating scales such as the BDI‐II , the BDI‐II total score and the other psychopathological rating scales scores , the SAS total score and the SCL‐90  and PSQI  total scores, the SCL‐90 total score and the PSQI total score .Finally, in AD patients significant positive correlations were found between the SAS score and the JCQ Job Demands subscale score  and (b) correlation between PSM total score and JCQ Job Demands subscale score .After adjusting by means of Benjamini–Hochberg correction for multiple testing, only two correlations lose statistical significance: (a) correlation between SAS score and JCQ Job Demands subscale score  compared to controls.In this study, AD patients' pBDNF levels resulted to be significantly higher than those of healthy workers, whereas no significant differences were found between the two groups for serum cortisol levels. To the best of our knowledge, there are not studies in literature investigating blood BDNF levels in patients suffering from AD. Conversely, it is largely demonstrated that peripheral blood (plasma and/or serum) BDNF levels are lower in patients suffering from mood disorders during manic/mixed and depressive episodes compared to matched healthy controls and that effective treatments are able to normalize them . This result is in line with our hypothesis about the homeostatic and neuroprotective role of BDNF under stress but it is in contrast with other data from literature. In particular, a negative correlation between serum BDNF levels and work‐related psychological stress levels measured by means of Stress and Arousal Check List (s‐SACL) emerged in workers in health , anxiety (SAS) and global psychopathology (SCL‐90), moderate with sleep disturbances (PSQI) and just weak with the levels of job demands detected by the JCQ. These findings are in line with many studies in literature reporting a significant association between the levels of perceived stress and symptoms of depression or anxiety in different populations (students, workers, patients; Bergdahl & Bergdahl, This study suffers from some limitations that should be acknowledged. First, the cross‐sectional design of the study and the relatively small sample size which did not allow further subgrouping, for example, for AD subtypes. Second, the psychiatric history as well as the occupational history were investigated and defined solely on the basis of what reported by the patients but no information from relatives was available. Another problem is related to the extent to which blood BDNF levels may reflect brain BDNF concentrations. However, since BDNF can cross the blood–brain barrier (Pan, Banks, Fasold, Bluth, & Kastin, In conclusion, this study demonstrates higher pBDNF levels in patients suffering from AD than in healthy controls and a positive correlation in AD patients between pBDNF levels and seC levels. As already mentioned the small sample size is an important bias of this study and affects the relevance of our findings which must be considered preliminary and need of validation in extended samples. However, the results of this study suggest that BDNF could play a key role in the pathophysiology of stress‐related disorders and that an elevation of its peripheral levels could contribute to protect neural cells under stress conditions. Since AD represent very common occupational stress diseases, research aimed at increasing the knowledge of their underlying neurobiological mechanisms and at investigating about the neuronal damage mediated by stress appears to be a real priority for preventive monitoring of workers exposed to occupational stress. Taking into account that work‐related stress represents an emerging risk in occupational medicine, the results of this study should therefore solicit further research focusing on putative biomarkers for stress‐related disorders as a potential tool for the diagnosis and prevention of occupational diseases.The authors report no conflicts of interest.


Electroglottography (EGG) is the most commonly used method of indirect visual examination of vocal fold vibration.EGG) in different functional dysphonias to develop a differential diagnosis. The second aim was to check the influence of articulation on QOQEGG values.The study was conducted with an aim of assessing EGG quasi open quotient (QOQThere were 20 people without voice problems, 20 patients with hypofunctional dysphonia and 20 patients with hyperfunctional dysphonia included in the study. Electroglottography was recorded during comfortable sustained phonation of [a], [e], [i], [o], [u].EGG observed during phonation of different vowels in the control group and patients with hyperfunctional dysphonia. In patients with hypofunctional dysphonia, significantly higher values of QOQEGG were observed during [a] and [e]. Both in the control and in studied groups vowel [i] was vocalized significantly quieter.There were no statistically significant differences in QOQEGG is a parameter differentiating hypofunctional dysphonia from hyperfunctional dysphonia. Dissimilarities in articulation of different vowels in patients with various types of dysphonia influence values of QOQEGG. EGG study protocol in cases of functional dysphonia should include a comparison of [a], [e], [i] vowels.To conclude, EGG can be useful in differential diagnosis of functional dysphonia. QOQ Electroglottography (EGG) is the most commonly used method of indirect visual examination of vocal fold vibration. The method was first described by Fabre in 1957 as high frequency glottography , [e], [i], [o], [u] Fig. . AccordiEGG. QOQEGG is a parameter describing the relative open phase duration of a glottal cycle  in the control group compared to the studied group (p = 0.11).No statistically significant differences between the control group and the hyperfunctional dysphonia group in the values of QOQEGG were observed during [a] and [e] phonation compared to other vowels (p < 0.05). The relation was also observed in comparison to healthy controls (p < 0.05). These patients phonated [a] significantly quieter than patients with hyperfunctional dysphonia and control group. Level of dB SPL during phonation of [e] was smaller in patients with hypofunction of the vocal folds in comparison to the control group.In patients with hypofunctional dysphonia, significantly higher values of QOQEGG in various types of functional dysphonias we aimed to develop a successful differential diagnosis.Through analysis of the QOQEGG values are higher during phonation of [a] and [e]. Zagólski and co-authors analysed the results of EGG obtained from 16 healthy women and 8 healthy men  and [e] between individuals with different types of functional dysphonia. Mean values of QOQEGG in patients with hyperfunctional dysphonia were smaller compared to patients with hypofunctional dysphonia. We have also observed higher values of QOQEGG during phonation of [i] in patients with hyperfunctional dysphonia, which can be explained with a widening of a glottal gap caused by the increase of vocal fold tension when voice frequency is higher. Extension of the opening phase relative to the closing phase with the increase of voice frequency had been previously described by Childers , [e], [i] should be included in the EGG study protocol.


Dryobates borealis) declined after human activities reduced their fire‐maintained pine ecosystem to <3% of its historical range in the southeastern United States and degraded remaining habitat. An estimated 1.6 million RCW cooperative breeding groups declined to about 3,500 groups with no more than 10,000 birds by 1978. Management has increased RCW population abundances since they were at their lowest in the 1990s. However, no range‐wide study has been undertaken since then to investigate the impacts of this massive bottleneck or infer the effects of conservation management and recent demographic recoveries. We used mitochondrial DNA sequences (mtDNA) and nine nuclear microsatellite loci to determine if range‐wide demographic declines resulted in changes to genetic structure and diversity in RCW by comparing samples collected before 1970 (mtDNA data only), between 1992 and 1995 (mtDNA and microsatellites), and between 2010 and 2014 (mtDNA and microsatellites). We show that genetic diversity has been lost as detected by a reduction in the number of mitochondrial haplotypes. This reduction was apparent in comparisons of pre‐1970 mtDNA data with data from the 1992–1995 and 2010–2014 time points, with no change between the latter two time points in mtDNA and microsatellite analyses. The mtDNA data also revealed increases in range‐wide genetic differentiation, with a genetically panmictic population present throughout the southeastern United States in the pre‐1970s data and subsequent development of genetic structure that has remained unchanged since the 1990s. Genetic structure was also uncovered with the microsatellite data, which like the mtDNA data showed little change between the 1992–1995 and 2010–2014 data sets. Temporal haplotype networks revealed a consistent, star‐like phylogeny, suggesting that despite the overall loss of haplotypes, no phylogenetically distinct mtDNA lineages were lost when the population declined. Our results may suggest that management during the last two decades has prevented additional losses of genetic diversity.Red‐cockaded woodpeckers (RCW;  Studies that adopt a historical perspective mainly do so using phylogenetic or phylogeographic concepts that provide insights about long‐term historical changes that may have occurred over evolutionary time scales Avise, . AdvanceDryobates borealis; Chesser et al., Picoides borealis) were widespread and abundant throughout the open, fire‐maintained Longleaf pine  ecosystem and other pine habitats in the southeastern United States prior to European settlement three centuries ago  offspring frequently stay and assist with incubation and feeding of nestlings and fledglings  a preliminary overnight incubation with proteinase K as per the buccal swab protocol, (b) a manual grinding step using plastic mortars, and (c) an additional overnight incubation after addition of 10 µl Proteinase K. DNA extractions for the museum samples were performed in a separate laboratory from the blood and buccal swab samples.DNA extraction protocols varied depending on sample type . DNA was obtained from buccal swabs using the protocol outlined in Vilstrup et al. . Blood s2.3Three mitochondrial markers  were initially screened for a subset of samples spanning the species' range. We found very low genetic diversity at the Cytochrome b and COX1 marker, and therefore, chose to only sequence part of the hypervariable region of the control region (CR) for the remaining samples. Primers were designed to amplify approximately 800 base pairs (bp) of the CR based on prior available sequences Alstad . Five ovNine microsatellite markers developed for RCW , haplotype diversity (H), and nucleotide diversity (π). Although haplotype diversity and nucleotide diversity are unbiased estimators whose values are not affected by sample size, the observed number of haplotypes is potentially correlated with sample size  by assuming sample sizes associated with the smallest group of interest in a particular comparison . Second, samples from the pre‐1970s mtDNA data set could be grouped into three distinct geographic regions based on locality information associated with the museum specimens  and the average number of alleles per locus (Amicrosat), recognizing that the latter quantity is also affected by sample sizes. Thus, rarefaction‐based analyses as described above were used to estimate Armicrosat and correct the number of microsatellite alleles for the time period with the smaller sample size in our comparisons. These diversity statistics were calculated for the complete data sets, within each of 3 post hoc groupings defined by the pre‐1970 mtDNA data , we used Arlequin 3.5  at different time points using the Analysis of Molecular Variance . As with analyses of the mtDNA data, separate estimates of differentiation were quantified for the 3 ad hoc regions, ecoregions where aggregated samples had sample sizes of 5 or more, and sample locations where data from 5 or more individuals were available.Microsatellite data sets (1992–1994 and 2010–2014) were analyzed using the locus‐by‐locus analysis option in Arlequin, resulting in a measure of differentiation comparable to Weir and Cockerham's  unbiasedK (the assumed number of clusters) ranging from 1 to 5. Five replicate analyses were performed for each value of K using an initial burn‐in of 105 Markov‐Chain Monte Carlo steps followed by recording for 106 steps. We calculated the average likelihood associated with runs from each value of K and assumed that values of K with the highest average likelihood score reflected the true number of genetic clusters.We used two additional approaches to test for changes in differentiation patterns over time. For mtDNA data, we used the TempNet package . Our analyses suggested that mitochondrial haplotypes have been lost in RCWs over time. Across the complete data sets, no consistent changes in π or H were apparent, however, rarefied estimates of haplotype richness (ArmtDNA) that accounted for different sample sizes from each time period were lower in the 1992–1995 and 2010–2014 data sets relative to the pre‐1970 data  that were known to have been reduced to a population of ~50 individuals in 1993  identified a similar loss of microsatellite alleles  and Hawaiian Gallinules from Hawaii . While these studies illustrate that similar patterns may be revealed by mtDNA and microsatellite markers, it does not guarantee that a comparable scenario exists in RCW. Mitochondrial DNA, by virtue of being haploid and maternally inherited, has a fourfold smaller effective population size relative to diploid, biparentally inherited nuclear loci. Consequently, mtDNA is more sensitive to the effects of genetic drift and may show more rapid or dramatic changes compared to loci such as microsatellites. At this time, given the absence of microsatellite data from the pre‐1970s data set, we are unable to conclusively state that nuclear genetic diversity has been reduced.The loss of diversity was only observed in our mtDNA data set because the microsatellite loci did not reliably amplify from the museum specimens that we examined Tables  and 4, tChelonoidis nigra) between data sets based on mitochondrial gene fragments, sets of mitochondrial genes, or complete mitochondrial genomes (Jensen et al., Although our analyses indicated that mtDNA haplotypes have been lost in RCW, our analysis was based on a fragment of the mitochondrial genome. Recent work compared the apparent loss of diversity in a known population bottleneck of Giant Galapagos tortoises (Comparisons of the 1992–1995 and 2010–2014 data derived from the mtDNA and microsatellites suggested that, with a few exceptions, similar genetic diversity levels existed at these two time points Tables , 4. MoreArmtDNA from “All Data” row in Table Based on the mtDNA analysis, RCW have lost ~25%–30% of their haplotypes over the past century (Fst of 0.14 in allozyme analyses of 26 populations while Haig, Rhymer, et al. (Fst of 0.19 using RAPD markers from 14 populations. Haig et al. (Fst of 0.21 that was comparable to that detected in the earlier investigation (Haig, Rhymer, et al., FST that were identified in the pre‐1970s mtDNA data. This widespread panmictic population has transitioned more recently into a discontinuously distributed species with isolated populations and reduced gene flow based on the low, but significant, population differentiation observed at later time points in both the mtDNA and microsatellite data. This result may indicate that RCW are reluctant to move among fragmented habitat patches. Furthermore, as with the analyses of genetic diversity, the 1992–1995 and 2010–2014 data suggest that there has been little overall change in genetic differentiation patterns since that time and may indicate a secondary benefit of management interventions such as translocations beyond the demographic impacts that have been observed in monitoring studies. A more thorough understanding of this outcome may be possible through future analyses based on the complete history of the RCW translocation program and documentation of source and recipient populations used for translocation purposes.Prior analyses from the 1990s highlighted significant genetic structure among RCW populations. Stangel et al.  estimate, et al.  estimateg et al.  later reOur study is among a growing list of investigations that use historical DNA samples to identify genetic changes that have occurred in natural populations. These approaches are powerful, as they may provide insights not only about trends over time, but can also help determine if management actions are having the desired effects at the genetic level (Frankham et al., None declared.SMH and JRW conceptualized the project. SMH performed project oversight. JTV and TDM collected the data. JTV and MPM analysed the data. All authors were involved in interpretation of analysis results. All authors were involved in manuscript preparation and development of final content. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Health system strengthening is needed to improve delivery of secondary prophylaxis against rheumatic heart disease.acute rheumatic fever recurrence rates. Overall, 304 patients requiring prophylaxis were eligible. The proportion receiving ≥80% of scheduled injections during baseline was 141 of 304 (46%)—higher than anticipated. No effect attributable to the study was evident: in the intensive phase, 126 of 304 (41%) received ≥80% of scheduled injections . There was modest improvement in the maintenance phase among high‐adhering patients . Also, the proportion of days at risk in the whole cohort decreased in the maintenance phase . Acute rheumatic fever recurrence rates did not differ between study sites during the intensive phase and the whole jurisdiction .We undertook a stepped‐wedge, randomized trial in northern Australia. Five pairs of Indigenous community clinics entered the study at 3‐month steps. Study phases comprised a 12 month baseline phase, 3 month transition phase, 12 month intensive phase and a 3‐ to 12‐month maintenance phase. Clinics received a multicomponent intervention supporting activities to improve penicillin delivery, aligned with the chronic care model, with continuous quality‐improvement feedback on adherence. The primary outcome was the proportion receiving ≥80% of scheduled penicillin injections. Secondary outcomes included “days at risk” of acute rheumatic fever recurrence related to late penicillin and rheumatic heart disease secondary prophylaxis within the study time frame. Longer term primary care strengthening strategies are needed.This strategy did not improve adherence to URL: http://www.anzctr.org.au. Unique identifier: ACTRN12613000223730. This multicomponent intervention at 10 remote Australian Aboriginal clinics did not improve adherence to penicillin among people with rheumatic fever or rheumatic heart disease during a 12‐month time frame, demonstrating the substantial challenges to effective adherence support.Adherence was already improving overall in this setting; the proportion receiving the nominated target of ≥80% of scheduled injections was 46% at baseline, more than double the previously published rate.Although improvement in the primary outcome was not seen, patients who were already well engaged experienced benefit during longer term follow‐up.Longer interventions are needed, with more community linkages, to achieve better adherence in this cross‐cultural context.Secondary prophylaxis with penicillin is a highly effective strategy to reduce progression from acute rheumatic fever to rheumatic heart disease or from milder to more severe forms of rheumatic heart disease, but strategies to support adherence that are culturally appropriate and age appropriate are needed.The challenges identified in this study make a compelling case for investment in better preventive strategies at primordial and primary levels.More patient‐centered approaches within culturally competent health systems are a priority to achieve improved outcomes for individuals living with rheumatic heart disease.Rheumatic heart disease (RHD), which develops as a complication of acute rheumatic fever (ARF), is an important cause of morbidity and mortality in areas of socioeconomic deprivation globally.The most effective strategy to prevent ARF recurrences and RHD progression is secondary prevention with intramuscular long‐acting benzathine penicillin G (BPG) injections every 4 weeks for a minimum 10 years after the last ARF episode or until age 21, whichever occurs later.We hypothesized that barriers to adherence would be amenable to a health system intervention, based on elements of the chronic care model (CCM)We aimed to test whether a health systems intervention engaging staff and patients at primary care clinics and the regional RHD control program would improve delivery of secondary prophylaxis for people with ARF and/or RHD. A comprehensive mixed‐methods evaluation done in parallel is reported separately.The RHDSP (Rheumatic Heart Disease Secondary Prophylaxis) trial was a stepped‐wedge, pragmatic, community, randomized trial with an open cohort design using mixed‐methods evaluation. The study protocol was published previously.Approval was provided by the Human Research Ethics Committee of the NT Department of Health and Menzies School of Health Research (no. 2012‐1756) and the Central Australian Human Research Ethics Committee (no. 2013‐126). The trial was registered with the Australian New Zealand Clinical Trials Registry: ACTRN 12613000223730. The anonymized quantitative data and study materials will be been made available on request to the authors for purposes of reproducing the results or replicating the procedure.Indigenous includes Aboriginal and Torres Strait Islander peoples; in our study, all Indigenous people were Aboriginal Australians, reflecting the demographics of the Indigenous NT population. Consent from individuals was not required for quantitative data collection; these data were routinely collected and reported to the regional RHD Control Program. For qualitative data collection, healthcare providers at participating clinics, patients with ARF and/or RHD, and key stakeholders involved in ARF care were invited to participate in interviews. Informed consent for interviews was sought by project officers or a qualitative researcher using written and verbal materials, with information provided in an Australian Indigenous language, if appropriate. For patients aged <15 years, consent was sought from a parent or guardian and assent was requested from the interviewee.The unit of participation was healthcare centers, which were eligible if they had ≥10 patients with ARF and/or RHD requiring secondary prophylaxis and provided written informed consent from the health center manager or management board. Of note, in Australia, the term Clusters in the stepped‐wedge study comprised pairs of health centers that entered at 3‐month steps in random order. The random allocation code was computer generated centrally at the National Health and Medical Research Council Clinical Trials Center. No components of the intervention were subject to masking.Study phases comprised 1) baseline data collection (12 months), (2) transition phase with commencement of intensive phase activities but data excluded from outcome analyses (3 months); (3) intensive implementation phase (12 months), (4) maintenance implementation phase  aligned under the themes of the CCM and developed and implemented by health centers. Implementation was supported by project officers via monthly face‐to‐face meetings during the transition and intensive phase  and every 3 months during the maintenance phase. CQI activities comprised meetings between the staff of participating heath centers and project officers to review quarterly adherence rates, presented as simple graphics, and discussion of progress against action plans. If clinics were unable to be visited because of closure, such as for a funeral or flooding, project officers sought a meeting by telephone. All efforts were made to ensure that exposure to the intervention, measured as the number of clinic support visits conducted face‐to‐face or by telephone, was homogeneous across sites and in accordance with the stepped‐wedge design.The a priori primary outcome was proportion of patients receiving ≥80% of their scheduled BPG injections over the 12‐month intensive phase compared with the baseline phase. Secondary outcome measures were proportion of scheduled injections that a patient received; average number of “days at risk” of ARF due to late penicillin dosing (median number >28 days between scheduled injections)Adherence data (penicillin injection dosing with date and location of administration) were obtained from the NT RHD Control Program Register. A subset of these data was checked for accuracy against primary clinic data, and corrected if required, for the whole study period, as reported elsewhere.“One21Seventy” RHD auditsQualitative data collection comprised semistructured interviews with ARF/RHD patients, clinic staff, and key stakeholders and project officer reports summarizing each episode of contact with a healthcare center. A nested focused ethnographic study  was conducted at 4 sites, investigating patients’ perspectives on their condition.A program theory was developed using the 6 themes of the CCM as the framework.Using a stepped‐wedge design with a 3‐month period for each step, with enough communities to provide at least 30 participants at each step and taking into account within‐cluster correlation, 300 patients were required to provide 90% power and a 2‐sided significance level of 5% to detect an increase from 20% to 40% of participants receiving ≥80% of their scheduled penicillin injections.The intervention was implemented at the level of the community health center, but measured by its impact on ARF/RHD patients and health center staff. All patients with ARF and/or RHD whose primary clinic was participating in the study were included. In an a priori plan taking account of population mobility, analyses were restricted to those who, during the baseline and intensive phases of the study, resided in a study site for at least 75% of the time (≥9 of 12 months during each phase of quantitative data collection) and required penicillin prophylaxis for ≥12 months during each of the baseline and intensive phases of the study. To avoid potential adherence rates of >100% and counting multiple needles administered within a short time frame, adherence calculations excluded doses given within 14 days of each other; however, all doses were retained in calculations of days at risk.Analyses of adherence were based on observations for each participant in each time period and used generalized linear mixed models to account for the correlation within a person over time and between people within the same clinic. The primary analysis included only the baseline and intensive phases. When the maintenance phase was included in the analysis, the results showed the maintenance phase compared with the baseline and intensive phases, with a test for trend over the 3 time points. Binary outcomes included whether a patient received ≥80%, ≥90%, <50%, and 50% to 79% of scheduled BPG injections over the 12‐month intensive phase. Days at risk of ARF recurrence were presented in 2 ways: number of days >28 days (or >21 for those prescribed 21‐day regimens) that occurred between scheduled injections in a 12‐month period or proportion (days at risk divided by number of days that penicillin was intended). Days at risk were Poisson distributed, and proportion of days at risk was normally distributed and analyzed using a generalized linear mixed model. Results are presented as odds ratios, rate ratios, or absolute differences and 95% confidence intervals. Patients had to be included in both baseline and intensive phases to be included in the analysis. Comparison of ARF recurrence rates was undertaken using MedCalc software. All other analyses were undertaken in SAS 9.3 (SAS Institute).The impacts of the study on delivery of other services for RHD patients and on other routine clinic activities were assessed using One21Seventy and AHKPI data, respectively. For several reasons, graphical descriptions rather than statistical tests were undertaken for these outcome measures: the time frames for aggregated data sets did not exactly align with the stepped‐wedge design, not all sites undertook One21Seventy audits, and One21Seventy data are deidentified so could not be used in individual patient‐level adherence analyses.Healthcare provider interview transcripts and project officer reports were subjected to deductive coding by 3 researchers in NVivo qualitative data analysis software . Codes were determined a priori according to established criteria. Interpretation of findings was made in consultation with the project staff and other study investigators. Patient interview transcripts were analyzed using an exploratory inductive approach.The trial was funded by the Australian National Health and Medical Research Council and Wesfarmers Center for Vaccines and Infectious Diseases at Telethon Kids Institute. The funders had no role in the study design, data collection, analysis, interpretation, or writing of this report.very remote , with small populations but high numbers of individuals per household and low incomes. Four clinics were run by community‐controlled health boards and 6 by the Government Department of Health. Staff turnover was high: During the 15‐month period of data collection from start of transition to end of intensive phase, the number of healthcare providers at each study site holding the portfolio of RHD coordinator ranged from 2 to 8 . ARF recurrence rates did not differ between study sites during the intensive phase and the whole jurisdiction . There was no interaction between the prespecified subgroups  and change in adherence.Primary and secondary outcomes are presented in Table P<0.001). Differences in adherence also occurred between age groups (Table P<0.001). Adherence did not differ between male and female patients.There was a large difference between sites in adherence Table : the props Table , being bP=0.66).Recurrence rates of definite or probable ARF diagnosed using the Jones criteria during intensive phase were compared between the 10 participating sites and the whole NT during the relevant period . During the intensive phase, 9 definite or probable ARF recurrences occurred at participating sites in individuals identified as needing secondary prophylaxis (3.0 recurrences per 100 patient‐years), compared with 3.5 recurrences per 100 patient‐years in the whole jurisdiction  and 37 family members or Aboriginal key informants. Main themes are presented in summary in this article; detailed qualitative findings are presented elsewhere.NT AHKPI data from the participating sites are shown in Figure In this first rigorous randomized controlled trial to test the impact of a health systems intervention on delivery of RHD secondary prophylaxis, no significant increase in adherence was achieved. Improvement in documented adherence was already evident at the outset of this study: double (46%) the proportion of patients were receiving ≥80% of scheduled injections compared with the previous estimate (23%).Reasons for the overall increase in documented adherence in the NT may include the now‐widespread local practice (days at risk approach) of recalling patients for their 28‐day injection from day 21 onward to avoid late delivery.Age and site were significant predictors of adherence. Reassuringly, adherence was best in children, who have the highest risk of ARF recurrence. Given methodological constraints—having only 10 participating sites for comparison, but with diverse characteristics—we were unable to identify individual community, clinic, or project implementation factors in statistical analyses that significantly predicted adherence or response to the study intervention. It appeared that a complex interplay of factors at high‐performing sites contributed to their ability to deliver care more effectively. Chief among these was the presence of stable staffing provided by culturally competent individuals working within well‐functioning clinics. Previous research in our setting has identified that staff who are able to identify with patients and healthcare centers that value quality improvement initiatives and are successful in developing effective community linkages respond more effectively to CQI initiatives.A key factor that we believe impeded project success was staffing challenges, including high turnover Table —a well‐rWe used the CCM to guide and categorize the activities that clinics undertook to improve delivery of penicillin injections. Clinics found some aspects of chronic disease management easier to implement than others—the majority of implemented action items involved changing clinic‐based systems such as software‐embedded recall systems or undertaking staff training. Far more challenging was the ability to establish effective community linkages or to provide self‐management support. Among the 10 clinics, only 4 action items in the self‐management support domain were undertaken Table . Self‐maThe AHKPI data attest to the added challenges of the delivery of RHD prophylaxis compared with other routine services, which were more likely to meet or approach targets Figure . The RHDA chief limitation of the study is the short time frame. Stepped‐wedge designs have advantages over traditional cluster randomized community trials,Secondary prevention is the cornerstone of international ARF and RHD control, but effectiveness is limited by suboptimal adherence. Our findings indicate the critical importance of improving engagement between healthcare services and Aboriginal patients. The barriers to this improvement need to be addressed by engaging the highest levels of health system governance, using innovative staff education and retention measures and ensuring cultural security within healthcare environments. A wide range of other creative strategies need to be explored, such as use of social media, incentives, peer‐support groups, and consideration of community support personnel employed to assist Aboriginal people in navigating the healthcare system. The ongoing challenges in delivery of secondary prophylaxis make a compelling case to broaden the scope of ARF prevention activities, with particular emphasis on primordial and primary prevention both among individuals with existing ARF or RHD and among whole communities. Research now under way is engaging communities to address high streptococcal transmission in households and communities to provide community‐led solutions to reducing the strikingly high rates of RHD.This study was funded by the Australian National Health and Medical Research Council (NHMRC) project grant 1027040 and Center of Research Excellence 1080401, and by the Wesfarmers Center for Vaccines and Infectious Diseases at Telethon Kids Institute. Ralph and Maguire are supported by NHMRC fellowships (1142011 and 1046563 respectively).None.Table S1. TIDieR (Template for Intervention Description and Replication) ChecklistTable S2. Examples of Action Plan ItemsFigure S1. Rheumatic heart disease coordinator staff turnover during the 15‐mo period of data collection from start of transition to end of intensive phase of the study.Figure S2. Association between adherence (percentage of patients receiving ≥80% of scheduled injections during intensive phase) and clinic characteristics. No associations were found to be statistically significant at P<0.05.Figure S3. Associations between Aboriginal Health Key Performance Indicators between 2013 and 2016, and adherence as calculated for this study during the intensive phase of the study.Figure S4. Results of rheumatic heart disease audit results  in relation to adherence to secondary prophylaxis.Click here for additional data file.