There is a paucity of literature examining the effect of Ventral Intermediate Nucleus (VIM) deep brain stimulation (DBS) on voice in patients with vocal tremor (VT).Investigate the effect of unilateral and bilateral VIM DBS on voice in patients with Essential Tremor (ET) and VT.All patients receiving VIM DBS surgery underwent voice evaluation pre- and six-months post-operatively. We collected patient-reported quality-of-life outcome measures and acoustic voice measures of sustained phonation and connected speech. Acoustic measures specific to VT included amplitude tremor intensity index (ATRI), frequency tremor intensity index (FTRI), rate and extent of F0 modulation, and rate and extent of intensity modulation.Five patients, age 72.8 ± 2.6 years, 4 female, 1 male with mean disease duration of 29 ± 26.2 years met the inclusion criteria and were included. Two subjects had bilateral procedure and three had unilateral. We observed significant improvements in measures of vocal tremor including ATRI, FTRI, rate of F0 modulation, rate of intensity modulation, and extent of intensity modulation, as well as patient reported voice-related quality of life measured by VHI-10. Bilateral VIM DBS cases showed greater improvement in VT than unilateral cases.Both unilateral and bilateral VIM DBS resulted in significant improvement of VT, with more improvement demonstrated in patients having bilateral as compared to unilateral VIM DBS. In addition, patients also reported significant improvements in voice-related quality of life. If larger studies confirm our results, VIM DBS has the potential to become a treatment specifically for disabling VT. Essential tremor (ET) is an isolated tremor syndrome of bilateral upper limb action tremor of at least 3 years’ duration with or without tremor in other locations  and absence of other neurological signs, such as dystonia, ataxia, or parkinsonism . The preTraditional treatments for VT including pharmacologic management and chemodenervation using laryngeal botulinum toxin (BTX) injections offer limited success in reliable symptom management. Systemic medications such as propranolol and primidone for VT yield variable outcomes and patients may experience disabling adverse side effects or require polytherapy for improvement 7. BotuliFor patients who are intolerant and/or refractory to the pharmaceutical and medical treatments for VT, deep brain stimulation (DBS) is arguably one of the most promising treatment alternatives. DBS of the thalamic ventral intermediate nucleus (VIM) and the posterior subthalamic area/caudal zona incerta are being explored as potential treatments for VT 8910111214151617.141516910111213141516While vocal tremor is most prominent during a sustained phonation task , voice pThis study was approved by the Institution Review Board at Atrium Health Wake Forest Baptist.As standard of care, patients underwent a voice evaluation with a voice-specialized speech-language pathologist (SLP) pre- and six-months post-VIM DBS. Data were collected retrospectively from patients presenting to the Atrium Health Wake Forest Baptist Voice and Swallowing Center pre- and six-months post-VIM DBS. Inclusion criteria were patients aged 18 years or older receiving VIM DBS for medically refractory ET and concomitant VT who underwent both pre- and post-operative voice evaluations between August 2018 and January 2022. All patients were diagnosed with medically refractory ET by fellowship-trained movement disorder neurologists and elected to undergo VIM DBS for the treatment of their medically refractory ET as per standard of care following a multidisciplinary team evaluation. Tremor was measured with Modified Fahn-Tolosa-Marin Tremor Rating Scale [The neurosurgeon performed the DBS procedure using a stereotactic approach. Targets were refined with microelectrode recording and intra-operative stimulation. Patients were unilaterally or bilaterally implanted with electrodes in the VIM of the thalamus. The decision for unilateral or bilateral implantation was based on severity of tremor on the contralateral side and benefits versus risks were weighed for each lead. Programming parameters for ET symptoms were optimized post-implantation to target limb tremor as per standard of care in which each electrode contact was interrogated to check for efficacy and thresholds for side effects. The electrode stimulation parameters were chosen to provide the best efficacy to side-effects ratio while focusing on reaching therapeutic benefit for tremor .Patients underwent a comprehensive voice evaluation with a voice-specialized SLP pre-VIM DBS and 6 months post-VIM DBS. The voice evaluation included instrumental acoustic voice assessment, perceptual speech evaluation, and completion of a validated voice-specific patient-reported quality of life measure. No patients had received laryngeal BTX injections within at least one year prior to the pre- or post-operative voice recordings and there were no changes in anti-tremor medications (primidone or propranolol) between the pre- and post-operative recordings. Patients wore an AKG C420 head-mounted microphone  positioned approximately 45° from the mouth during the recording of all speech samples. The audio samples were recorded using Real Time Pitch (RTP), Multi-Dimensional Voice Program (MDVP), and Analysis of Dysphonia in Speech and Voice (ADSV) programs from the Computerized Speech Lab . Patients were asked to produce a sustained /a/ vowel and a set of standard sentences from the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V) protocol  to obtaiFor analysis of vocal tremor in sustained vowel phonation, the SLP prompted patients to “Take a breath and say the vowel /a/ at a comfortable pitch and loudness for approximately 5 seconds.” MDVP from the Computerized Speech Lab was used to collect Amplitude Tremor Intensity Index (ATRI) and Frequency Tremor Intensity Index (FTRI) to quantify the magnitude of long-term periodic frequency and amplitude modulations of the acoustic signal in sustained /a/ vowel production. The rate and average extent of fundamental frequency (F0) and intensity modulations were also calculated from the central 2-seconds of the sustained vowel recording using Praat speech analysis program . The SLP calculated the average rate of F0 and intensity modulations by counting the total number of cycles of modulation per one second. Extent of F0 and intensity modulations were calculated by measuring the minimum and maximum F0 and intensity for each cycle of modulation in the central 2-seconds of the vowel production. These values were used to calculate range of modulation in F0 and intensity, which were then divided by the sum of minimum and maximum F0 and intensity and then multiplied by 100 to obtain percent modulation. For all intensity measures, the minimum and maximum intensity values in dB SPL were converted from the logarithmic decibel scale to a linear scale of sound pressure, Pascals .For the acoustic analysis of voice in connected speech, the SLP prompted patients to “read the sentences aloud at a comfortable pitch and loudness.” The ADSV program was used to collect cepstral and spectral measures from the all-voiced sentence “We were away a year ago” in addition to the central one second of the sustained /a/. Cepstral and spectral measures collected included the Cepstral Spectral Index of Dysphonia (CSID) and cepstral peak prominence (CPP). These voicing tasks and subsequently collected cepstral measures were selected as they reflect the global relationship of periodic versus aperiodic energy in a voice signal, are more reliable predictors of dysphonia 252627, a2526Patients also completed the Voice Handicap Index-10 (VHI-10) questionnaire to self-report their perceived vocal handicap pre- and 6-months post VIM DBS . A VHI-1One laryngologist and one voice-specialized speech-language pathologist were blinded raters for the Clinical Global Impression Scale of Severity (CGI-s) assessment. Raters were separated from each other and blinded to patient information as well as the timing of the recording in terms of whether it was before or after surgery. The CGI-s is a numerical scale from 0 to 7  designed for clinicians to rate the severity of a specified symptom. This scale was used to subjectively assess the severity of perceived dysarthria pre- and post-operatively.Descriptive statistics were used to report characteristics of patients with ET and voice evaluations. Data were summarized using means and standard deviations. Percent change was calculated between all pre-operative and post-operative values. Changes between assessments were analyzed using a paired t-test.A total of 5 patients met the inclusion criteria and were included in the study . Two subjects had bilateral procedure and 3 had unilateral .Five of the 6 measures of vocal tremor in sustained vowel phonation including ATRI, FTRI, rate of F0 modulation, rate of intensity modulation, and extent of intensity modulation improved significantly 6 months post-operatively in patients who underwent unilateral or bilateral procedure. For all of these measures, bilateral participants showed a greater improvement than participants with unilateral procedure  and 2. TPatient-reported quality of life relative to voice as measured by the VHI-10 also improved significantly with all participants showing a decrease in VHI-10 score. Participants with bilateral procedure showed greater improvement than participants with unilateral procedure .In terms of global measures that were not vocal tremor or voice specific, mTRS scores were collected and analyzed for all participants, and showed a significant decrease post-operatively with participants with unilateral procedure showing greater improvement than participants with bilateral procedure . There wPatient dysarthria ratings pre- and post-DBS were also measured. All participants showed no change in dysarthria rating using CGI-s, with the exception of bilateral participant 2, who was rated as ‘normal, no dysarthria,’ pre-DBS and ‘borderline dysarthria’ post-DBS.To date, previous studies have primarily relied on perceptual voice outcome measures subject to rater bias, have examined basic acoustic measures of vocal tremor, have not included validated voice-specific patient-reported outcome measures, and/or have been limited by inconsistent follow-up duration 911121314.111213Our findings offer clinically meaningful implications as the average VHI-10 scores of our cohort improved from an abnormal to a normal range post-operatively, suggesting improvement in quality of life relative to voice and communication in patients with VT post-VIM DBS. Patient-perceived impact of voice on quality of life is critical to assess when examining the effect of VIM DBS on voice in patients with VT as we know that perceived voice handicap scores are higher in ET cases with VT, similar to voice handicap scores reported in patients with Parkinson’s disease .For the acoustic analysis portion of the voice evaluation, we evaluated acoustic features of voice in both sustained phonation and connected speech tasks. Clinical evaluation of VT is typically collected during sustained phonation tasks as VT has been shown to be more prominent during prolongation of voiced sounds 33. In thIn addition to sustained vowel phonation, instrumental analysis of voice in connected speech is recommended in standard instrumental voice evaluation protocols to provide relevant information regarding the acoustic features of a patient’s voice in tasks more representative of functional communicative contexts . TherefoIn our small cohort, we did not identify statistically significant change in cepstral or spectral measures of voice in connected speech post-DBS. There is a possibility that a lack of statistically significant results could be at least partially secondary to the variable effect of VT on connected speech and potentially increased disruption of the tremor cycle during connected speech, making VT less evident in sentence production than sustained phonation . It is aWhile previous studies have reported that 25–50% of patients with bilateral VIM DBS experience dysarthria post-operatively, only one of the participants in our cohort presented with minimal change in speech post-DBS 3536. Thi35In this study, we found that patients who underwent bilateral VIM DBS demonstrated greater improvement in voice measures compared to those who underwent unilateral procedure. We think this difference may be due to bi-hemispheric influence on axial symptoms such as voice tremor. There was a difference in disease duration between the unilateral and bilateral group, which can potentially influence the degree of improvement. Previous studies have offered inconclusive findings comparing the effect of unilateral versus bilateral DBS on the success of treating VT 13161735.131617Our study is limited by its smaller size and our preliminary results would need to be confirmed in larger studies. There are important questions which can be addressed in larger studies in the future including: effectiveness of unilateral versus bilateral VIM DBS for VT, incidence of dysarthria and balance issues in larger cohorts, impact of disease duration and severity on effectiveness of DBS for VT, effect of somatotopy of the thalamus for VT, and if the results of our study apply to isolated VT.In summary, the present study is the first to examine and compare the effects of unilateral and bilateral VIM DBS on voice and vocal tremor in not only sustained phonation tasks, but also acoustic measures of connected speech and voice-specific quality of life measures six months post-operatively. In our cohort, both unilateral and bilateral VIM DBS resulted in improvement of VT and patient-reported voice outcomes, with more improvement seen with bilateral procedures compared to unilateral procedures. If our findings are confirmed in a larger well-controlled study, VIM DBS has the potential to become a treatment specifically for disabling VT.


Alzheimer’s disease (AD) exhibits spatially heterogeneous 3R/4R tau pathology distributions across participants, making it a challenge to quantify extent of tau deposition. Utilizing Tau-PET from three independent cohorts, we trained and validated a machine learning model to identify visually positive Tau-PET scans from regional SUVR values and developed a novel summary measure, THETA, that accounts for heterogeneity in tau deposition. The model for identification of tau positivity achieved a balanced test accuracy of 95% and accuracy of ≥87% on the validation datasets. THETA captured heterogeneity of tau deposition, had better association with clinical measures, and corresponded better with visual assessments in comparison with the temporal meta-region-of-interest Tau-PET quantification methods. Our novel approach aids in identification of positive Tau-PET scans and provides a quantitative summary measure, THETA, that effectively captures the heterogeneous tau deposition seen in AD. The application of THETA for quantifying Tau-PET in AD exhibits great potential. However, evidence from pathology and imaging have shed light on the heterogeneity of tau deposition in AD, suggesting that there could be distinct patterns of tau accumulation across individuals4.Alzheimer’s disease (AD) is characterized by the accumulation of β-amyloid (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain. NFTs are composed of hyperphosphorylated tau proteins and in a majority of individuals tau progresses along predictable patterns, originating in the transentorhinal cortex and spreading to the limbic system and eventually to the neocortex. The spread of tau leads to cognitive impairment and dementia6. Positron emission tomography (PET) imaging is used to visualize and assess tau deposition using radioligands that bind specifically to the paired helical filament of NFTs and can be used to detect and track tau pathology in vivo7. Studies using PET have shown in preclinical AD, tau deposition is spread throughout several cortical regions and there follows multiple trajectories3. The most common quantification methods for Tau-PET utilize meta-regions of interest (meta-ROIs), such as the temporal meta-ROI, or the more recent medial temporal lobe (MTL) and neocortical (NEO) meta-ROIs to stage disease severity9. These methods ignore the extent of tau outside these meta-ROIs and average the Tau-PET standardized uptake value ratios (SUVR) in the entire meta-ROI, which underweights any focal depositions of tau in smaller regions within the meta-ROI. In addition to the meta-ROIs, there are less commonly used quantitative methods such as the volumes-of-interest voxel-based multiblock barycentric discriminant analysis (MUBADA)10 that have also been used to assess the clinical group separation.Current understanding of AD pathophysiology and neurodegeneration suggests that the NFT accumulation is closely correlated with clinical disease progression and precedes clinical symptoms, making tau a promising biomarker for disease diagnosis and clinical trial design18F]flortaucipir (Tauvid™) which was recently FDA-approved for AD tau pathology at B3-level (Braak stages V/VI)11. The visual assessment criteria consider the focal deposition of tau through the brain and could overcome the limitations of the meta-ROI methods. In this work we set out to test the hypothesis that a machine learning (ML) model can be developed to identify positive Tau-PET scans based on the clinically accepted multirater visual ratings, and improved quantification methods can be developed to incorporate the heterogeneity in spatial distribution of tau tracer signals throughout the brain. We further hypothesized that these ML-based tau quantification methods could outperform the currently used meta-ROI quantification methods and provide a more accurate and sensitive quantification of tau deposition that would map better to disease severity.The visual rating method followed in this study was based on the density and distribution of tau identified by the radiotracer  flortaucipir PET imaging for detecting NFT B3 corresponding to Braak stages V or IV. Hence, effectively quantifying the Tau-PET signal has important implications because it provides a more accurate and sensitive assessment of disease severity. Given that multirater visual assessment is the clinically accepted standard in the field, developing a highly accurate model using this gold standard and utilizing the model characteristics for quantification of Tau-PET signal has several advantages. This is reflected in the THETA score outperforming the current methods as observed in F flortauTHETA can be utilized with ease across multiple clinical studies. The calculation of THETA in a clinical or research setting is similar to the meta-ROI calculation. Once an ML model is trained on the regional SUVRs and is interpreted using the SHAP AI explainer, THETA scores can be generated automatically using our formula. This process can be done for a single participant or a list of participants. The training of a ML model need only be done once and the trained model can be used multiple times, and the training set can constitute cohorts of different demographics as we have demonstrated in our study. Future work will focus on validating THETA for tracking longitudinal Tau-PET changes.Supplementary Table 3 and Supplementary Figure 4. Third, the THETA score exhibits high sensitivity for a given tau-status which can be strength or a limitation. While visually accurate classification can provide a better range for tau quantification, a visually inaccurate classification (< 1% cases) could force the THETA towards zero. Future studies are planned to validate its performance on longitudinal studies. Lastly, changing of the cut-points for the meta-ROIs than ones used in this study could change the results for the meta-ROI comparisons.This study has some strengths and limitations. We developed a ML model on one dataset and validated it on two independent datasets. There were some limitations in this study. First, the visual assessment of scans is subjective and can be prone to human errors. However, the visual ratings were obtained independently from three raters, and ambiguous discordant cases were reassessed by a Neuroradiologist (CRJ). Second, as expected, the model’s performance was lower for the ADNI, and OASIS-3 validation sets due to differences between the cohorts. However, combining the cohorts and training a new model on the combined data solved this problem. The combined model achieved balanced accuracy between 94% and 96%, and ROCAUC greater than 0.99 for all datasets. This is shown in In conclusion, this study aimed to address the limitations of the current quantitative methods for quantifying the spread of tau deposition in Alzheimer’s disease by using advanced ML approaches. We also developed a novel summary measure that captures regional heterogeneity, which can be a useful clinical tool for assessing disease progression and subtypes and identifying potential therapeutic targets. Further studies are needed to test the versatility of THETA. The ML model developed in this study performed extremely well in predicting tau status on both the MAYO dataset as well as on the external datasets. The model outperformed the three meta-ROIs in classifying tau positivity on the Mayo test set and was comparable in ADNI and OASIS-3. Additionally, the novel summary measure, THETA, was able to better quantify the spatial heterogeneity of tau deposition and provide a more sensitive measure of clinical disease severity. Overall, the study provides promising results for the use of ML models in improving the detection and quantification of tau pathology in Alzheimer’s disease.4.4.1.18F]flortaucipir tracer from three studies: a combined Mayo Clinic Study of Aging (MCSA)22 and Mayo Alzheimer’s Disease Research Center (ADRC) data set , Alzheimer’s Disease Neuroimaging Initiative phase 2 or 3 (ADNI) (N = 831), and Open Access Series of Imaging Studies phase 3 OASIS-3 (N = 430)23. Individuals with frontotemporal dementia were excluded. The Mayo cohort is a population-based study of cognitive aging among residents of Olmsted County, Minnesota, while the ADRC is a longitudinal research study of individuals recruited from clinical practice, and all participants provided written informed consent. Both studies have been approved by the Mayo Clinic and Olmsted Medical Center Institutional Review Boards. The ADNI cohort initiative was as launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). The ADNI data was obtained from adni.loni.usc.edu database and for up-to-date information, see www.adni-info.org. The OASIS-3 cohort is a longitudinal study through WUSTL Knight ADRC’s ongoing projects including cognitively normal adults and individuals at various stages of cognitive decline, with MR and PET scans available. The data was obtained through request at https://www.oasis-brains.org/.We included participants who had undergone a Tau-PET scan with [4.2.24. Tau-PET scans were rigidly coregistered to corresponding MRI and median values were taken for each region. Cortical and subcortical regions were referenced to the median of the cerebellar crus to form SUVR units. These regional SUVR values were used both to form the meta-ROIs and as inputs to our machine learning models  or negative  AD pattern status using a previously published visual interpretation method25 .We followed the FDA-approved official criteria for visual assessment to classify the scans in the study4.4.8. A cutoff point of 1.23 SUVR was used to assess tau positivity for the temporal meta-ROI. The MTL was an unweighted average of medial Tau-PET uptake in bilateral entorhinal cortex and amygdala while the NEO meta-ROI was a voxel-weighted average of bilateral middle temporal and inferior temporal gyri9. Meta-ROI values above 1.30 SUVR for MTL and above 1.73 for NEO were considered abnormal.The temporal meta-ROI was a voxel-weighted average of median uptake in the entorhinal, amygdala, parahippocampal, fusiform, inferior temporal, and middle temporal regions with the cerebral crus gray median as a reference region4.5.Supplementary Fig. 1). To account for class (tau-positive vs tau-negative) and group imbalance (discordant vs concordant) we implemented a semi-random iterative stratified data splitting technique .The inputs to the ML model were 41 cortical region SUVR values calculated as mean of the right and left hemispheres values. The final model was trained on the Mayo dataset (n = 1290) split into 80% training (n = 1038) and 20% testing (n = 252) and was evaluated on the external datasets ADNI (n = 831) and OASIS-3 (n = 430). To validate the effect of the data splitting on the model performance, we split the data using 200 random seeds and ran the models on the different partitions ic THETA , we made4.6.Tau Heterogeneity Evaluation in Alzheimer’s Disease). This score is calculated as a linear combination of two components: the model outputs based on the contributions of tau SUVRs across the entire brain, and the weighted contribution of the SUVRs that fall within the 1st and the 99th percentile of SHAP values  to the model’s prediction. The second component xi) are multiplied to reflect their scaled impact. By combining these two components, the THETA score provides a comprehensive assessment of tau accumulation over the whole brain.We have developed a novel summary measure which we termed as the THETA score .To assess the repeatability of the THETA scores, we calculated the intra-class correlation coefficient (ICC) of the top models. We found the smallest ICC was 0.97 and the largest ICC was 1.00 . The predicted probabilities and the raw SUVRs were used to plot the ROC AUC curve for the model and meta-ROIs, respectively. To compare the visual assessments to the meta-ROIs or to the ML model’s predictions, we used the true positive rate (TPR = TP / (TP + FN)), which is also known as sensitivity, true negative rate (TNR = TN / (TN + FP)), also known as specificity, rate of tau-positive mismatch (1-TPR), and rate of tau negative mismatch (1-TNR). In addition, we evaluated the performance of THETA on the clinical disease severity measures by calculating correlation using Spearman


However, pre-analytical variables including reagent effects on the CWA parameters are poorly understood and must be standardized as a potential diagnostic assay. (2) Methods: CWA was first analysed with patient samples to understand reagent lot variation in three common APTT reagents: Pathromtin SL, Actin FS, and Actin FSL. A total of 1055 healthy volunteers were also recruited from seven institutions across the Asia-Pacific region and CWA data were collected with the Sysmex CS analysers. (3) Results: CWA parameters varied less than 10% between lots and the linear mixed model analysis showed few site-specific effects within the same reagent group. However, the CWA parameters were significantly different amongst all reagent groups and thus reagent-specific 95% reference intervals could be calculated using the nonparametric method. Post-hoc analysis showed some degree of influence by age and gender with weak correlation to the CWA (r < 0.3). (4) Conclusions: Reagent type significantly affects APTT-based CWA with minimal inter-laboratory variations with the same coagulometer series that allow for data pooling across laboratories with more evidence required for age- and gender-partitioning. The activated partial thromboplastin time (APTT) is a routine coagulation assay widely performed with automated coagulometers using the optical detection method. Changes to the optical transmittance through platelet-poor plasma (PPP) is detected as the fibrin clot forms upon addition of phospholipids, contact activator, and calcium. The clot time is extracted from the transmittance change, of which the clot kinetics can be represented graphically. APTT-based clot waveform analysis (CWA) is an extended quantitative analysis of this optical transmittance graph that quantifies the waveform characteristics through its derivatives . The firAt present, CWA has demonstrated its potential clinical utility in the assessment of haemophilia and hypercoagulable states ,3,4,5,6.We therefore set about to investigate the reagent effects on the APTT-based CWA obtained from the Sysmex CS series analyzers across different laboratories in the South-east Asia region. We aim to understand the extent of reagent lot change on the CWA. We also hypothesize that reagent types will affect the CWA and that this assay is likely to be robust to inter-laboratory variation with peer groups within 15% of each parameter mean . Our effr and percent difference between the lots.Two different reagent lot numbers were obtained for Pathromtin SL, Actin FS, and Actin FSL. At least 40 patient samples with results across the measuring range were run on the same Sysmex CS2500  analyzer at the Singapore General Hospital using two different lots of the same reagent in succession. The analyser was rinsed and primed when changing between lots to ensure no carryover. The inter-lot variation of individual CWA parameter is compared by Passing-Bablok regression and expressed as correlation coefficient Seven institutions from across Southeast Asia  particip9/liter. The PPP samples were all analysed for APTT within 24 h of collection. Any sample with hematocrit exceeding 55%, or obviously hemolysed when inspected visually, was not included in the analysis.Blood sampling and processing to obtain the PPP were carried out as per local practices  such thaCWA data were collected from participating sites using the Sysmex CS series of analyzers. The Sysmex CS 5100 is a high-volume standalone coagulometer while the CS 2100i and CS 2500 analyzers are intermediate-volume desktop analyzers that utilize the same optical detection methods. Individual models differ in terms of throughput and pre-analytical check functions, but the multi-wavelength detection technology and measuring algorithms were the same for the CS series analyzers. Published data have indicated a good correlation between the Sysmex CS 5100 and CS 2000 analyzers with an r = 0.991 . An inte4 M ellagic acid and purified soy phosphatides [4 M and a mixture of soy and rabbit brain phosphatides [APTT was measured by the Sysmex CS analyzers in the individual sites using specific reagents as outlined in phatides . Actin Fphatides . Data cop < 0.05 was taken as significant. The reagent-specific reference intervals were subsequently calculated using the non-parametric determination recommended by the Clinical & Laboratory Standards Institute (CLSI) guidelines EP28-A3c [Initial data analysis was done by the Analyse-It for Microsoft Excel software (Version 5.30.1) to check for normality and identify outliers using the Tukey’s method. All outliers were deemed as sporadic analytical errors and were omitted from further analysis. Reagent lot comparability was also performed using Passing-Bablok analysis and Kruskal-Wallis comparison by the Analyse-It software (Version 5.40.2). Subsequent statistical analysis was carried out using SPSS Version 23 . Site-specific or reagent-specific means were eventually compared taking into account the age and gender effects using a linear mixed model analysis with LSD correction. A EP28-A3c  with theThe inter-lot analysis for the three commonly used APTT reagents  showed good correlation of all CWA parameters between two reagent lots across the normal and pathological result ranges. The correlation coefficients for the CWA parameters were all greater than 0.95 and the percent inter-lot differences were within 10% , suggestA total of 1055 healthy individuals were recruited at the seven participating sites. Although some sites did not submit age and gender details, the CWA data were used in the analysis without exclusion. The data collected were first analysed for outliers for each individual parameter. Outliers identified were investigated for sample collection and processing errors at each site, but none were found. The number of outliers eliminated from the final analysis for each parameter at each site was not more than 10% of the numbers collected, and they were subsequently removed for the final analysis. The total numbers of data points included for the APTT-based CWA reference distribution parameters at each site are shown in p = 0.043).Age and gender details were available from 757 subjects ranging from 18 to 72 years. There were 273 males  10.20 years) and 484 females . There were disproportionately more females than males, but the mean ages were minimally different , suggesting little site-specific variation within the same reagent group  and 97.5th (upper limit) percentile values . Since tIn post-hoc analysis to elucidate how the CWA parameters were affected by different reagents, age and gender were used as independent variables in a mixed model analysis of the parameter (dependent variable). Both variables significantly affected all the CWA parameters but did not show any site-specific differences .The clot times for each reagent were not significantly influenced by age or gender. In comparison, the CWA parameters and the corresponding times at which they occurred were all significantly influenced by age . The CWAThe possibility of separating reference intervals for the age and gender subclasses were considered given that these factors significantly affected the CWA parameters. The CLSI guidelines suggested several methods to partition reference intervals for various subclasses, but partitioning should not be estimated unless the differences between the subclass means are at least 25% as large as the 95% reference interval estimated from the combined sample of reference subjects. Each subclass should have at least 120 subjects for such comparisons to be valid. Although we did not recruit 120 subjects in each 10-year subclass, the observed means of the age and gender subclasses were nonetheless compared. The differences in means were within 25% of the 95% reference interval, except for some subclasses aged greater than 50. In such subclasses, the numbers of subjects were very small and might not truly estimate the observed means.In this multi-centre regional study conducted on the Sysmex CS platform, the three commonly-used reagents differed in their activator type  and phospholipid content, with Actin FS having lower phospholipids compared to Actin FSL. Our results showed that the APTT-based CWA, like the APTT, is sensitive to the activator rather than the phospholipid content of the reagent. This is evident as CWA parameters obtained from the Pathromtin SL varied quite significantly compared to those obtained from Actin FS and Actin FSL, while little variability was observed between CWA results for Actin FS and Actin FSL.Despite the inevitable differences in local laboratory practices, our data showed that there was very little inter-laboratory variability for results obtained within each reagent type and lot change. The current recommended laboratory processes for obtaining the CWA appears robust in ensuring consistency of results and was only susceptible to the type of reagent employed. This has enabled the pooling of data to calculate universal reagent-specific reference intervals that could be shared amongst users of the same reagent-analyzer combinations after local validation procedures.12. Furthermore, the small number of recruited subjects in these extreme age groups would have limited the accuracy of individual subclass RIs. Currently, the clinical significance of age and gender differences on the RI is uncertain. It is plausible that proven age-dependent fluctuations in coagulation factors and other contributing physiological changes could lead to parallel fluctuations in the CWA. Until more data emerge on the clinical impact of age or gender stratification, we are of the view that a common RI for the CWA parameters best serves its purpose in clinical and research practices.The reference intervals (RIs) of the CWA parameters for the study population were calculated from a wide spread of individuals across several countries, and we believe these can be applied to the general adult population regardless of age or gender. Although noticeable differences in the CWA parameters exist between specific age subclasses such as the youngest and oldest strata, the outlier numbers in these subclasses were only a small fraction of the total recruited population. This negates the value of partitioned RIs according to either age or genderOur study has benefitted from the collaborative efforts of participating laboratories in different countries, which has allowed us to investigate the robustness of the platform against varied operating environments. Consistent results for the same reagent–analyzer combination means that CWA data collection can be expanded across different sites and combined to accelerate collaborative efforts in clinical and research protocols. Our results, however, cannot be generalized to CWA obtained with other optical detection analyzers. We also did not study the effect of different reagent combinations on PT-based CWA, which has less defined clinical utility. Our assessment of the effects of age and gender would also have benefitted from a larger study population with a better spread of subjects across different age sub-classes.We have demonstrated that the type of reagent used significantly affects APTT-based CWA, but there are minimal inter-laboratory and inter-lot variations between laboratories employing the same reagent-analyzer set-up. A common set of reference intervals established for individual reagents can hence be used for cross-referencing in quality assurance programs and provide confidence for combining data in multi-centre clinical and research protocols to further simplify and spur greater utilization of CWA in daily practice.


Interprofessional communication is needed to enhance the early recognition and management of patients with sepsis. Preparing medical and nursing students using virtual reality simulation has been shown to be an effective learning approach for sepsis team training. However, its scalability is constrained by unequal cohort sizes between medical and nursing students. An artificial intelligence (AI) medical team member can be implemented in a virtual reality simulation to engage nursing students in sepsis team training.This study aimed to evaluate the effectiveness of an AI-powered doctor versus a human-controlled doctor in training nursing students for sepsis care and interprofessional communication.A randomized controlled trial study was conducted with 64 nursing students who were randomly assigned to undertake sepsis team training with an AI-powered doctor (AI-powered group) or with medical students using virtual reality simulation (human-controlled group). Participants from both groups were tested on their sepsis and communication performance through simulation-based assessments (posttest). Participants’ sepsis knowledge and self-efficacy in interprofessional communication were also evaluated before and after the study interventions.P=.001) and self-efficacy in interprofessional communication (P<.001) in posttest scores. For sepsis care knowledge, a significant improvement in sepsis care knowledge from the baseline was observed in the AI-powered group (P<.001) but not in the human-controlled group (P=.16). Although no significant differences were found in sepsis care performance between the groups , the AI-powered group  had statistically significantly higher sepsis posttest knowledge scores (P=.009) than the human-controlled group . No significant differences were found in interprofessional communication performance between the 2 groups . However, the human-controlled group  reported a significantly higher level of self-efficacy in interprofessional communication (P=.008) than the AI-powered group .A total of 32 nursing students from each group completed the simulation-based assessment, sepsis and communication knowledge test, and self-efficacy questionnaire. Compared with the baseline scores, both the AI-powered and human-controlled groups demonstrated significant improvements in communication knowledge (Our study suggested that AI-powered doctors are not inferior to human-controlled virtual reality simulations with respect to sepsis care and interprofessional communication performance, which supports the viability of implementing AI-powered doctors to achieve scalability in sepsis team training. Our findings also suggested that future innovations should focus on the sociability of AI-powered doctors to enhance users’ interprofessional communication training. Perhaps in the nearer term, future studies should examine how to best blend AI-powered training with human-controlled virtual reality simulation to optimize clinical performance in sepsis care and interprofessional communication.ClinicalTrials.gov NCT05953441; https://clinicaltrials.gov/study/NCT05953441 Delays in sepsis recognition and slow initiation of diagnostic work and treatment are associated with poor patient outcomes, including death -3. It isIn addition to knowledge on sepsis recognition and management, nurses need to possess effective communication skills. Upon recognizing a patient with or at risk of sepsis, a nurse must be able to communicate patient concerns effectively to the medical team, for example, the junior doctors or attending doctors, as part of a process known as care escalation . HoweverAlthough conventional simulation  has traditionally been a popular method for delivering team-based training in IPE, its implementation is often plagued by logistical issues, such as the availability of simulation facilities and facilitators, conflicting schedules among students from different health care professions and high costs involved . This haSpecifically, a recent sepsis IPE program using VRS for undergraduate medical and nursing students has reported favorably on the use of VRS for interprofessional sepsis team training . In the Harnessing the power of artificial intelligence (AI)—a branch of computer science that builds intelligent computer systems capable of performing tasks that typically require human intelligence —we develWe conducted a prospective 2-arm randomized controlled trial with a pretest-posttest study design. Social media platforms were used to recruit participants who were undertaking year 3 of their nursing courses in a local university. We used the rule of thumb for a pilot 2-arm trial sample size involving at least 55 participants . AccountThis study was approved by the National University of Singapore institutional review board (ref no. NUS-IRB-2022-202). Before the study intervention, both groups met the research team through a Zoom videoconference to receive information about the study and provide their written consent. They were assured that participation was entirely voluntary, and withdrawal would not affect their academic performance.Participants in both the AI-powered and human-controlled groups were scheduled to participate in a 2-hour VRS on sepsis team training remotely. The participants in the AI-powered group were scheduled to undertake the VRS individually while being supported by the research team via Zoom chat for any enquiries. Participants in the human-controlled group were assigned to groups of 4 to 6 team players to engage in the VRS with medical students and facilitators. The design and development of both forms of VRS, which were grounded in experiential learning theory, has been described and evaluated in previous studies ,22.In both study interventions, participants were involved in 2 simulation scenarios. The first scenario simulated a morning medical round, involving a postoperative patient with early manifestations of sepsis, which required early goal-directed management of sepsis. The second scenario involved the same patient whose condition had deteriorated into septic shock and required airway management and fluid resuscitation. The participants were given time to read the case history before commencing each scenario. Both scenarios began with a nursing participant performing nursing assessment and management of the virtual patient using the ABCDE  approach, followed by communicating with an AI virtual doctor or a doctor avatar controlled by the medical student. A voice chatbot learning system was built using Google Cloud’s Dialogflow engine to train the AI doctor, which operates through deep neural networks to recognize and predict human-agent conversation patterns . The AI Each simulation scenario lasted 15 to 20 minutes and was followed by a debriefing to enable participants to receive feedback on their performance regarding the assessment and management of sepsis and septic shock and their interprofessional communication. As illustrated in We administered the knowledge tests and self-efficacy scale before (baseline) and immediately after (posttest) interventions for both groups. The 8-item communication knowledge and 18-item sepsis knowledge tests were developed and content validated by a multidisciplinary team comprising a medical doctor, an advanced practice nurse, and nursing academics. This study reported a high Cronbach α of .81. The Patient Clinical Information Exchange and Interprofessional Communication Self-Efficacy Scale, a 6-item questionnaire using a 0-100 Likert scale developed by Hernández-Padilla et al , was useParticipants from both groups were scheduled to undertake simulation-based assessment within 2 weeks of postintervention to determine their sepsis care and interprofessional communication performance. Participants were given a case history to read and an orientation of the simulation room with a manikin setup. The simulation-based assessment involved the participants performing the nursing assessment and management of the manikin, which displayed signs and symptoms of deterioration, and communicating with the doctor to provide team care. Each simulation assessment lasted approximately 15 minutes, and the entire process was recorded. The recorded videos were sent for rating by 2 assessors, who were blinded to the groupings. The assessors rated the communication and sepsis care performances independently using a validated team communication scale and the RAPIDS (Rescuing A Patient In Deteriorating Situation) tool. The team communication scale comprising a 9-item checklist was developed by the research team based on observable nurse-doctor communication using the TeamSTEPPS communication strategies. The scale was content validated by an interprofessional team of 5 nursing academics and clinicians. The RAPIDS tool was adopted from a previous study to measure nurses’ simulation performance in assessing and managing a deteriorating patient . Interrat tests, to analyze the demographic characteristics of the study population. We computed the paired sample t test to examine significant changes between the baseline and posttest performance scores and used ANOVA to determine differences in the posttest scores between the groups. The level of statistical significance was set at P<.05.We applied descriptive statistics, chi-square tests and P=.49), gender (P=.55), and ethnicity (P=.54) between the AI doctor and human doctor groups (see Table 1). This supported the homogeneity of participants between the 2 groups.Sixty-four nursing students were recruited in the study. The majority were women  and Chinese  and had a mean age of 22.2 (SD 2.20) years. No significant differences were observed in the baseline characteristics, including age , though a higher mean score was observed in the AI-powered group . As shown in 31=−5.21, P<.001) but not the human-controlled  group.The simulation-based assessment revealed no significant differences in the sepsis care performance scores between the AI-powered and human-controlled groups  and communication performance scores , the human-controlled group reported higher communication self-efficacy mean scores  than the AI-powered group .As presented in To the best of our knowledge, this is one of the first studies to evaluate the effectiveness of AI-powered VRS by comparing it with human-controlled VRS. This randomized controlled trial study did not demonstrate any significant differences in sepsis performance and interprofessional communication performance between participants in the AI-powered and human-controlled groups. However, we found significant differences in sepsis care knowledge and communication self-efficacy between the 2 groups. Although the AI-powered group obtained significantly higher sepsis care knowledge scores than the human-controlled group, the human-controlled group reported significantly higher self-efficacy in interprofessional communication than in the AI-powered group. The underlying learning principles and theories that guided the use of AI and human-controlled VRS could be applied to explain these findings.The simulation-based assessment performance outcomes did not reveal inferiority of AI-powered VRS regarding either sepsis care or communication skills performance when compared with human-controlled VRS. Despite the different medical team virtual player agents, both VRS approaches offered experiential learning and cognitive tools that allowed the nursing students to practice the assessment and management of sepsis and team communication skills through role playing and reflection. An earlier study demonstrated the need for both cognitive tools and experiential learning modalities to support the development of a shared mental model and optimal teamwork delivery . The appInterestingly, our findings demonstrated that the AI-powered group had significantly higher sepsis knowledge scores than the human-controlled group. This finding supported our earlier qualitative data in which the AI-powered doctor was perceived by the nursing students as a more knowledgeable agent than the doctor agent controlled by medical students . AlthougAlthough no significant difference was noted regarding interprofessional communication performance, the human-controlled group reported a significantly higher level of self-efficacy for interprofessional communication than in the AI-powered group. Unlike AI-powered groups, participants in the human-controlled group were given the opportunity to engage in social interactions among learners through role playing and debriefing. The theory of social constructivism has emphasized the importance of learning from social interaction , which hThe lack of substantial differences in performance between AI and human-controlled VRS highlighted the potential role of AI-powered VRS in supporting nursing students with interprofessional training, particularly in circumstances when the accessibility and availability of medical students are lacking. In addition, variations in learning outcomes between the groups suggested the benefits of combining the different simulation modalities to provide an optimal learning approach. Our previous study recommended the use of scaffolding for the instructional sequence of interprofessional learning activities within blended learning environments . Thus, aThe limitations that warrant attention are few. First, we acknowledged the variations in experiential learning approach between the 2 simulation modalities as confounding variables. However, the performance outcome measurements used in this study were closely aligned with the learning objectives. Second, despite evaluating participants’ performance using simulation-based assessment and a validated tool, this was limited by an immediate posttest performance in the simulation setting. Third, similar to the performance test, we did not measure the long-term retention of knowledge and level of self-efficacy. Thus, future studies could evaluate learning outcomes over a longer period and measure the impact in the clinical setting. Finally, the effectiveness of AI-powered VRS was not optimized by allowing participants to have more than one exposure as the intent was to enable deliberate practice opportunities.An AI virtual doctor agent was embedded in a virtual environment to engage interprofessional team training of nursing students on sepsis care. The performance outcomes from simulation-based assessment did not suggest that the AI-powered VRS provided inferior sepsis care and interprofessional communication training when compared with a human-controlled VRS. This shed light on the effectiveness of AI-powered medical team players in supporting nursing students with interprofessional learning where the opportunity to form interprofessional teams with medical students is lacking. Our findings suggested the need for further innovative development in AI-powered VRS to promote social connectedness with learners and support AI-driven learning analytics for assessment. Given the varied learning outcomes between AI-powered and human-controlled VRS approaches, our study recommended blending them along with face-to-face simulation to optimize students’ performance in sepsis care and interprofessional communication.


Student well-being is an area of increasing interest for schools around the world. However, the extent to which school-based well-being and mental health interventions are currently being delivered by different schools has not previously been explored in many countries, including New Zealand.This survey of a nationally-representative sample of schools was undertaken to identify: what well-being and mental health interventions were being used by primary (elementary) and secondary (high) schools and what gaps exist between current practice and the evidence-base.Forty staff from 37  schools across New Zealand participated in semi-structured interviews. Data was analysed for key themes and subthemes using Braun and Clarke’s method.Seven key themes were identified: 1) staff awareness and enthusiasm about student well-being and mental health; 2) existence of specific interventions to support student well-being and mental health; 3) support for government-sponsored programmes; 4) limitations of existing programmes; 5) drivers of new interventions; 6) barriers to implementation; and 7) suggestions for future interventions and their implementation.Despite enthusiasm from educators for interventions with which to improve student well-being, there is a gap between intention and activity. Students are receiving primarily non-evidence based interventions in a variable manner due to staff and cost-related barriers. We suggest ways for health and education providers in New Zealand and elsewhere to address these issues, as well as avenues for further research.None Declared


Parental education and childhood adversities are associated with long-term work disability but their contribution to sickness absence is largely unknown. We aimed to examine the associations between parental education, childhood adversities and self-certified and medically-certified sickness absence among midlife employees.The Helsinki Health Study baseline survey data (2000–2002) of 40-to-60-year-old municipal employees were linked with sickness absence data from the employer’s register. Self-certified (1–3 days) and medically-certified (>3 days) sickness absence spells were followed from 2003 until the end of 2008. The study included 5728 employees. The analyses were made by Poisson regression and the results are presented as rate ratios (RRs) and their 95% confidence intervals (CIs).Low maternal education was associated with self-certified sickness absence  among women only whereas both low maternal  and low paternal education  were associated with medically-certified sickness absence. Adjustment for own occupational class mainly abolished these associations. Having experienced any childhood adversity was associated with self-certified  and medically-certified  sickness absence. In addition, childhood economic difficulties, childhood illness, parental divorce, parental mental illness, parental alcohol problems and bullying were each associated both with self-certified and with medically-certified sickness absence. The associations mainly remained after adjustments for occupational class, marital status, working condition, body mass index and health behaviours.Low parental education and childhood adversities contributed to midlife sickness absence. Promoting well-being of families with children might help sustain adult work ability and prevent sickness absence still in midlife. There is increasing evidence that childhood socioeconomic circumstances and childhood adversities have long-term influences on adult health . Such in38Most previous studies have focused on childhood socioeconomic position. A Norwegian study on young adults found that risk of sickness absence due to musculoskeletal diseases increased with decreasing parental educational level . A SwediIn addition to childhood socioeconomic position some other childhood adversities have been examined. A Finnish study found that childhood adversity was associated with work disability due to any cause, due to mental disorders and due to musculoskeletal diseases . Each inPrevious studies have often addressed the question of whether adult socioeconomic position mediates between childhood factors and sickness absence. Both Norwegian and Swedish studies suggested that the contribution of childhood factors to sickness absence was partly mediated through own education ,9 and soPrevious research leaves some gaps regarding childhood factors and subsequent sickness absence. First, many studies have been conducted among rather young employees, neglecting older ones. Second, previous studies have not distinguished between self-certified and medically confirmed sickness absence. Medically-certified sickness absence is considered as a valid measure of health  whereas The first aim of this study was to examine whether parental education and childhood adversities contribute to self-certified and medically confirmed sickness absence among midlife employees. The second aim was to examine whether adult socioeconomic position, marital status, working conditions and body mass index (BMI) and health behaviours contribute to the associations.n=424) the data consisted of 5728 employees, of whom 4636 were women and 1092 were men. Item non-response concerning the questions on parental education and childhood adversities varied from 1% to 10% in the linked data and partially overlapped with other drop-out. The final number of participants in each analysis can be seen in This study is part of the Helsinki Health Study (HHS) on employees of the City of Helsinki , which wAccording to the non-response analysis younger employees, employees in lower socioeconomic classes and employees with longer sickness absence during the study year were somewhat less likely to participate. Men in lower occupational classes and employees with medically-certified sickness absence were somewhat overrepresented among the non-consenters to data linkage. The differences were small and not fully consistent .The Ethics Committee of the Department of Public Health at the University of Helsinki and the health authorities at the City of Helsinki approved the study.Maternal and paternal education were inquired by questions with six response alternatives and divided into three classes: ‘low’ (elementary school or part of it or intermediate school), ‘mid-level’  and ‘high’ (polytechnic or university degree). In the analyses examining joint associations of parental education and adult occupational class maternal and paternal education were dichotomized by combining ‘mid-level’ and ‘high’ education. Childhood adversities before the age of 16 years were asked by six questions with response alternatives ‘yes’ and ‘no’. The questions inquired whether the respondent had had serious or long-term illness during childhood, whether parents divorced or one of the parents died, whether one of the parents had mental health problems, whether parental alcohol drinking caused problems at home, whether the family had significant economic difficulties and whether the respondent had been bullied at school or by peers. Similar questions on childhood adversities have been used in previous studies by us and others ,16.The data on sickness absence spells, their dates and duration were derived from the employer’s personnel register. The follow-up started from the beginning of 2003 and continued until the end of 2008 or when the employee quit working for the City of Helsinki. The average follow-up time was 5.1 years. Self-certified (1–3 days) and medically-certified (>3 days) sickness absence spells were analysed separately as the City of Helsinki requires a medical certificate of sickness absence spells exceeding three days. Medical certification means that the employee must provide the employer with a medical certificate including a diagnosis and assessment of work ability done by a medical professional.2). Leisure-time physical activity was measured using four questions from which metabolic equivalent tasks (METs) were calculated. Problem drinking was measured by the CAGE-scale  . A synergy index above 1 suggests that the joint association is synergistic, a synergy index equal to 1 suggests an additive association and a synergy index below 1 an antagonistic association.p<0.1), and significant interactions concerned maternal education and self-certified sickness absence (p=0.0286), occupational class and self-certified sickness absence (p=0.0317), occupational class and medically certified sickness absence (0.0587) and the joint association of occupational class and maternal education and self-certified sickness absence (p=0.0184). These analyses were performed separately for men and women. Otherwise women and men were pooled.Interactions for gender were tested  and low  maternal education were associated with an increased risk of self-certified sickness absence after adjustments for age and for marital status . AdjustmMid-level  and low  paternal education were associated with an increased risk of medically-certified sickness absence compared with high paternal education . Mid-levHaving experienced any childhood adversity increased the risk of both self-certified  and medically-certified  sickness absence . The assLow adult occupational class was associated with self-certified and medically certified sickness absence among both women  and men  . Adult oThis study sought to examine the associations between parental education, childhood adversities and self-certified and medically-certified sickness absence among midlife municipal employees.Both paternal and maternal low education increased the risk of medically-certified sickness absence whereas only maternal low education among women increased that of self-certified sickness absence. Our results are in line with previous studies –10, alth8We examined both self-certified and medically-certified sickness absence as their determinants partly differ. In addition to health various factors at work and outside work such as motivational factors , working8The strengths of the study include a large data set, register-based data on sickness absence, the possibility to differentiate between self-certified and medically-certified sickness absence spells, prospectively followed disability sickness absence after reporting parental education and childhood adversities, and the fact that we were able to control for several covariates. The major limitation was the retrospective and self-reported data of parental education and childhood adversities. Clear-cut questions such as parental divorce and death might be less biased whereas questions such as being bullied might be affected by mood and other conditions during the time of the survey. A review on adult recall of childhood adversities reported that false negative reports are common . The facIn conclusion, this study showed that low parental education and childhood adversities contribute to both self-certified and medically-certified sickness absence still in midlife. Previous studies have shown that there are effective ways to promote well-being of families with children. For example, anti-bullying programmes effectively reduce school bullying , high-qu


This meta-analysis was designed to assess if pre-operative low skeletal muscle mass impacts mortality rates of patients undergoing abdominal aortic aneurysm (AAA) repair.st January 1980 to 15th December 2021 for studies assessing the role of low skeletal muscle mass on mortality rates of AAA repair. Studies measuring skeletal muscle mass on computed tomography scans and reporting long-term mortality (>1 year) were included. Multivariable adjusted ratios were combined in a random-effects model.Datasets of PubMed, CENTRAL, ScienceDirect, Embase, and Google Scholar were searched from 1Fifteen studies with 3776 patients were included. Meta-analysis showed a statistically significant increased risk of all-cause mortality in patients with low skeletal muscle mass (HR: 2.07 95% CI: 1.56, 2.74 ILow skeletal muscle mass in AAA patients undergoing surgical repair is associated with increased risk of long-term mortality. Current evidence is limited by the retrospective nature of data and variability in defining and measuring low skeletal muscle mass. There is a need for future prospective studies defining the optimal cut-off of low skeletal muscle mass in different populations. Abdominal aortic aneurysms (AAA) are an important cause of mortality in the elderly and are usually associated with risk factors like family history, hypertension, tobacco use, and male gender.4However, since the majority of patients with AAA are aged and frail, vascular surgeons need to stratify patients based on the presence of comorbidities and other risk factors which may worsen postoperative outcomes.8Research has shown that reduced skeletal muscle mass is closely related to adverse outcomes in patients with a variety of diseases ranging from cardiac ailments to malignancies.The protocol of this meta-analysis was prospectively on the online database PROSPERO (CRD42022295885). The reporting guidelines of the PRISMA statement  were adhered.21st January 1980 to 15th December 2021. We utilized both free-text and MeSH keywords for the literature search, namely, “sarcopenia”, “psoas muscle”, “skeletal muscle” and “abdominal aortic aneurysm” in various combinations .Studies were to assess the role of low skeletal muscle mass on survival of AAA patients.Skeletal muscle mass was to be measured on CT scans that were no older than 12 months from AAA repair. Psoas and adjacent muscles measured at the level of lumbar vertebrae were acceptable for inclusion.Studies were to define low skeletal muscle mass and compare mortality between low vs non-low muscle mass. No restriction was placed on this criterion and all definitions of low skeletal muscle mass by the included studies were acceptable.Mortality data was reported as adjusted ratio with 95% confidence intervals (CI).Duration of the follow-up was >1 year.Studies on mixed AAA and thoracoabdominal aneurysm patients.Studies not using CT to measure low skeletal muscle mass.Studies not reporting adjusted data.Non-English language studies.Studies combining skeletal muscle mass and attenuation.The following data was noted: author details, type of study and its database, sample size, patients with low skeletal muscle mass, demographic details, type of AAA repair (open or endovascular), the cut-off for defining low skeletal muscle mass, method and level of measurement, and follow-up.The included studies either defined low skeletal muscle based on a cut-off value derived from receiver operating curve (ROC) analysis or from the literature, which was then used to group low and normal skeletal muscle mass, or the study authors classified skeletal muscle mass into different tertiles  in which case the lowest tertile was considered to be low skeletal muscle mass for our meta-analysis. This methodology for data analysis is similar to the prior published meta-analysis.The Newcastle-Ottawa scale (NOS)The meta-analysis was performed using “Review Manager” . Adjusted ratios of mortality was pooled to calculate hazard ratios (HR) with 95% CI using the random-effects model. Heterogeneity was judged by the I13-16,18-20,23-30 The majority of the studies were retrospective cohort in nature (One thousand five hundred two (1502) articles were searched in total , in whicn nature . A totalThere was wide variation in the studies in defining low skeletal muscle mass. All studies measured defined skeletal muscle area by measuring the bilateral psoas muscles with or without additional muscular structures. Measurements were made on CT at the level of L3 or L4 vertebrae using manual or software-based tracing tools. The follow-up duration was also variable amongst the included studies. The NOS score of the included studies was eight indicating a moderate risk of bias.On pooled analysis of all 15 studies, we noted a statistically significant increased risk of all-cause mortality in patients with low skeletal muscle mass . In contrast in the subgroup of mixed studies (open and endovascular), the overall effect size was just 1.39 which, however, still indicated poor survival amongst low skeletal muscle mass patients. This difference in the two groups is difficult to explain since there was just one study that included only open repair patients and it is unclear if the prognostic role of low skeletal muscle mass is altered based on the type of repair.The results of our study concur with the previous review of Antoniou et alA major limitation in the interpretation and clinical application of our results is the variability of definition and technique to measure low skeletal muscle mass. The included studies divided their samples either into two groups based on a singular cut-off value or into different tertiles with the lowest tertile being considered as low skeletal muscle mass. The cut-off value was widely different across studies with some studies adjusting it for gender and height while others did not. The level of measurement, the area of measurement, and the technique of measurement  also differed across studies. Defining sarcopenia has indeed been a challenge since the recognition of this disease.37The most recent European consensus on definition and diagnosis of sarcopenia (EWGSOP2) has a three-step, cut-off defined structure for diagnosing sarcopenia: first, screening by the SARC-F questionnaire; second, diagnosis by low muscle mass and strength; and third, severity grading by physical performance.They have recommended using normative data from the study population till future research identifies specific validated cut-off points in the global population.Firstly, the majority data in the meta-analysis was retrospective in nature. Retrospective studies are prone to selection bias, errors in record keeping, and data entry. Secondly, our meta-analysis could only assess the impact of low skeletal muscle mass on mortality. Lack of data on other important outcomes like complications precluded a meta-analysis. Thirdly, long-term patient survival after AAA repair depends on several confounding factors. While our meta-analysis only pooled adjusted data, it is plausible that some known and unknown confounders could have been missed by the included studies and skewed the study results.Nevertheless, the strength of the meta-analysis lies in the large number of studies included in the analysis. By including several recent studies, our study presents the most comprehensive and updated evidence on the topic. Our findings have important implications for clinical practice. Since CT scans are routinely ordered for AAA patients, psoas muscle cross-sectional area can be easily measured in all patients undergoing surgical intervention. Such data would help in risk stratification and taking informed clinical decisions.Results of our meta-analysis suggest that low skeletal muscle mass is a significant predictor of long-term mortality in AAA patients undergoing surgical repair. Current evidence is limited by retrospective nature of data and variability in defining and measuring low skeletal muscle mass. There is a need for future prospective studies defining the optimal cut-off of low skeletal muscle mass in different populations.JC conceived and designed the study.YX, YL and HZ collected the data and performed the analysis.JC was involved in the writing of the manuscript and is responsible for the integrity of the study.All authors have read and approved the final manuscript.


Quiscalus mexicanus) hasexpanded its range northward from Texas to Nebraska in the past 40 years, whileits closest relative, the boattailed grackle ,has remained tied to the coasts of the Atlantic Ocean and the Gulf of Mexico aswell as the interior of Florida. We created species distribution andconnectivity models trained on citizen science data from 1970–1979 and2010–2019 to determine how the availability of habitat, the types ofhabitat occupied, and range-wide connectivity have changed for both species. Wefound that the two species occupy distinct habitats and that the great-tailedgrackle has shifted to occupy a larger breadth of urban, arid environmentsfarther from natural water sources. Meanwhile, the boattailed grackle hasremained limited to warm, wet, coastal environments. We found no evidence thatchanges in habitat connectivity affected the ranges of either species. Overall,our results suggest that the great-tailed grackle has shifted its realized nicheas part of its rapid range expansion, while the range dynamics of theboat-tailed grackle may be shaped more by climate change. The expansion inhabitats occupied by the great-tailed grackle is consistent with observationsthat species with high behavioral flexibility can rapidly expand theirgeographic range by using human-altered habitat. This investigation identifieshow opposite responses to anthropogenic change could drive divergent rangedynamics, elucidating the factors that have and will continue to shape speciesranges.Species ranges are set by limitations in factors including climatetolerances, habitat use, and dispersal abilities. Understanding the factorsgoverning species range dynamics remains a challenge that is ever more importantin our rapidly changing world. Species ranges can shift if environmental changesaffect available habitat, or if the niche or habitat connectivity of a specieschanges. We tested how changes in habitat availability, niche, or habitatconnectivity could contribute to divergent range dynamics in a sister-speciespair. The great-tailed grackle ( Species ranges determine the patterns of biodiversity across the world,shaping the environments different species encounter and the other species they caninteract with .We are A species expanding into new areas is assumed to have overcome some of thetrade-offs or limitations that shape a species’ realized niche. Niche shiftscan occur via physiological or behavioral changes, as well as interactions betweenthese factors .PhysiolHowever, range dynamics are also influenced by factors beyond changes in therealized niche: environmental change leading to a recent increase in the amount ofavailable habitat representing the current niche can facilitate a geographic rangeexpansion , and chaQuiscalusmexicanus) and boat-tailed grackle .These species offer an opportunity for simultaneous investigation of the roles ofbehavior and increased habitat availability in a rapidly increasing geographic rangeexpansion. The great-tailed grackle has rapidly expanded its range northward overthe course of the 20th century : Other species traits, such as demographicdynamics or dispersal physiology, limited the historic species range, resulting inno apparent environmental difference between the newly occupied and historicallyoccupied ranges. Given this hypothesis, there are no changes in habitatavailability, but both species have suitable but unoccupied habitat available tothem. Only the great-tailed grackle is able to occupy additional habitat due tochanges in the other traits or conditions that previously limited the species range,with the ongoing expansion reflecting the time-lag to reach new areas. This outcomewould be consistent with the hypothesis that the original behavior of thegreat-tailed grackle, determined by inherent species traits, was already welladapted to facilitate a range expansion while the behavior of the boat-tailedgrackle restricts it to its current range.The range expansion in the great-tailed grackle and range stability in theboat-tailed grackle could be due to differences in realized niche change betweenthese two closely related species. We characterized the historic (1970–1979)and current (2010–2019) realized niches of the great-tailed grackle and theboat-tailed grackle using species distribution models (SDMs) to test threehypotheses on the causes of range expansion in the great-tailed grackle and rangestability in the boat-tailed grackle .HypotheWe used ecological niche modeling to examine temporal habitat changes overthese past four decades using observation data for both grackle species fromexisting citizen science databases. We determined the change in habitat availabilityusing predictions produced by both our current and historic models for each speciesbased on environmental data from 1979 and 2019  that passed pre-study peer review at Peer Community in Ecology in 2020. Thehypotheses, predictions, and methods in this manuscript come from thepreregistration, and we detail all changes to the methods below.This article is the first of three articles that will be produced from apreregistration  - we chosethese land cover types because they represent the habitat types in whichboth species exist, as well as habitat types  they are notexpected to exist in  (e (NLCD)  andhiste (NLCD) . We inite (NLCD) , share texist in . If the Elevation - Climate  -the great-tailed grackle was originally from the tropics  as thebasis for water bodies instead of the USGS NationalHydrography database. The USGS National Hydrography databasedoes not differentiate between minor and major bodies ofwater, resulting in near-complete coverage of the contiguousUS map with bodies of water. The Natural Earth databaseincorporates data on rivers and lakes from the NorthAmerican Environmental Atlas at a 1:10 million scale. Thelower resolution data allowed for the computation ofdistances between the more than 1 million sample points andall water bodies. Natural Earth shapefiles have also beenused in other SDMs to calculate distances to water bodies to the nearest uninhabited suitablehabitat patch in 1970 and again in ~2018. Given that great-tailedgrackles are not found in forests or beyond certain elevations  and a set for model validation(20% of checklists). We used a balanced random forest approach, in which absencepoints are selected at an equal frequency as presence points, thus addressingthe imbalance in the ratio of presence and absence points . RandomWe predicted habitat suitability across the contiguous United Statesusing environmental data from 1979 and 2019. We produced three types ofpredictions  depending onwhether the time period of the SDM matched the time period of the environmentaldata . When thDeviations from the preregistered plan: We used arandom forest model to estimate habitat suitability in place of Maxentdue to the advantages offered by using presence-absence data instead ofpresence-background data. Presence-background data can only determinethe habitat suitability of points relative to the background environment resolution . We thenplanned to take these variables and identify which locations in the Americasfall within the grackle-suitable ranges in 1970 and in 2018. We would thenbe able to compare the maps (1970 and 2018) to determine whether the amountof suitable habitat has increased or decreased. If we would be able to finddata for these variables before 1970 across the Americas, we wouldadditionally run models using the oldest available data to estimate therange of suitable habitat earlier in the great-tailed grackle rangeexpansion period.Final analysis: We used the discriminationability of our SDMs as metrics for how accurately our models predictgrackle-suitable habitat and whether one model could be used topredict suitable habitat in both the historic and current timeperiods for each species. We tested discrimination ability using the20% of data excluded from the training set of each model. Wemeasured Cohen’s Kappa and AUC for each model. We also usedthese metrics to quantify model transferability, the ability of amodel to perform accurately using datasets independent of thetraining dataset. Model transferability has been used to measure theconsistency of habitat associations over time  for each species.Final analysis: We compared the proportion ofobservations located on each land cover class in addition to thenumber of different land cover classes that each species wasobserved on. Changes in the number of land cover classes eitherspecies was observed on would indicate that the species occupiesnovel habitat.ecospat.niche.similarity.test function within the Rpackage ecospat , and for model 2 the species . If we were be able to find data for these variables before 1970across the Americas, we would additionally run models using the oldestavailable data to estimate the range of connected habitat earlier in theirrange expansion.Final analysis: We used Circuitscape version4.0.5 . Wevalidated these predictions using presence-absence data set aside from thecurrent and historic datasets. If habitat availability was an important factorin determining the range dynamics of either species, then the current modelsshould be sufficient to predict the expected range dynamics, the current andhistoric models should agree on the locations of suitable habitat, and thecurrent models should be transferable to the historic dataset. Alternatively, ifchanges in habitat associations or connectivity were important for the speciesrange dynamics, the current and historic models should disagree and be mutuallynon-transferrable.2 to 199,912 km2 in the historic model, and from111,218 km2 to 163,243 km2 in the current model . We also quantified how frequentlyeach species was observed on different land cover classes between the currentand historic datasets to test for changes in the breadth of land cover classesused by either species. Finally, we performed a niche similarity test todetermine if the environments occupied by each species in the historic andcurrent time periods are more different from each other than would be expectedby chance . Changes in the environments either species was observedon would indicate that the species has novel habitat associations in the currenttime period relative to the historic time period.The most important predictors for the current boat-tailed grackle modelwere mean temperature of the wettest quarter , elevation (11.8%), precipitation of the wettest month(9.1%), and deciduous forest land cover 8.4%; . HabitatThe historic model for the boat-tailed grackle disagreed on theimportance and effect of only a few predictors, supporting consistent habitatusage in the species. Both the historic and current models placed highimportance on the mean temperature in the wettest quarter 12.4%; , precipiI = 0.647;p-value = 0.446, Boat-tailed grackles were found in every land cover class exceptdeciduous forests and ice/snow in both the historic and current time periods.Boat-tailed grackles were found more often in urban areas in the current timeperiod, and less often in the land cover class that was the second most commonin the historic time period: woody wetlands . Boat-taThe most important predictors for the current great-tailed grackle modelwere maximum temperature of the warmest month 15.5%; , mean teThe historic model for the great-tailed grackle disagreed on theimportance and effect of several predictors, supporting a change in habitatassociations. The historic model agreed with the current model on the highimportance of the maximum temperature of the warmest month 9.8%,  and meanI = 0.641; p-value = 0.001, I was lower than the simulatedvalues, further supporting the hypothesis that the great-tailed grackle changedthe environments it occupies between the historic and current time periods.Great-tailed grackles were found in every land cover class exceptdeciduous forests, mixed forests, and ice/snow in the historic sample, and everyland cover class except deciduous forests and ice/snow in the current sample.There were more great-tailed grackle observations in the current sample on urbanareas, croplands, and grasslands and less observations in water, shrublands,pastures, and evergreen forests . While tTo determine whether changes in connectivity between habitat patchescaused by environmental change could explain the rapid expansion of thegreat-tailed grackle but not the boat-tailed grackle, we estimated the change inaccumulated current across the range of each species between 1979 and 2019. Accumulated current summarizes the amount of movement through acell, thus cells with higher current values are more suitable for movement andincrease connectivity. We binned current values into high or low connectivityusing the 75th percentile . Most ceConnectivity decreased for the boat-tailed grackle along the interiorportion of its range (farther from the coasts) in the southern Atlantic statesand the southern coast of Texas . HoweverConnectivity decreased for the great-tailed grackle within the state ofArizona and along the northern extreme of the cells within the 75th percentile. However, connectivity increased alongthe eastern extreme (Texas and Oklahoma) and the northern edges in Arizona andNew Mexico . Only onWe investigated how changes in habitat availability, habitat breadth, andconnectivity relate to differential range dynamics in a sister-species pair. Wefound that the rapidly-expanding great-tailed grackle has increased the variety ofoccupied habitats in the past 40 years. The current realized niche of thegreat-tailed grackle contains more arid climate conditions and is less dependent onbodies of fresh water than in the past realized niche. We did not find evidence foran increase in the connectivity of previously isolated patches of suitable habitat.Overall, our results for the great-tailed grackle are consistent with hypothesis 2,that an expansion in the realized niche of the great-tailed grackle may havecontributed to the geographic range expansion of the species . While tOur current boat-tailed grackle model is consistent with past work showingthat boat-tailed grackles are highly restricted to coastal areas, and that anexpansion into northern coastal areas could be due to climate changes. Boat-tailedgrackles rarely occur far from saltwater in the northern portion of their range, butcan nest inland across Florida .Our curThe changes in species range we found in the great-tailed grackle matchedthose predicted by previous researchers. It remains unclear why the great-tailed grackle has expanded its realizedniche while the boat-tailed grackle has not. Both the boat-tailed grackle and thegreat-tailed grackle are highly adaptable species with similar foraging habits.Human-associated species like boat-tailed grackles and great-tailed grackles thatuse urban habitats are typically more behaviorally flexible and better suited to usenew environments than other species .There cQuiscalusquiscalus)  . Evidenciscalus) . Speciesiscalus) , potentiiscalus) .IdentifThe high accuracy of our SDMs when cross validated on their own datasets andthe transferability of the current boat-tailed grackle model support the use of SDMsas tools to study how species ranges change over time. While improving modeltransferability remains a challenge for SDMs , using aCorvus ossifragus), which overlapsin range with boat-tailed grackles but not great-tailed grackles  or greattailed grackles (GTGR)from historic (1970–1979) and current (2010–2019) eBirdrecords. These locations are filtered for record qualitySupplementary Figure 2 – Predicted habitatsuitability using random forest models for boat-tailed grackles (BTGR) andgreat-tailed grackles (GTGR). Brighter colors indicate higher habitatsuitability. The presented results are the average of the 10 replicates.Supplementary Figure 3 – Partial dependencecurves for environmental predictors across all models . The curves represent how changing eachenvironmental predictor changes the encounter rate for the modeled species.The historic models are represented by the darker dashed lines and thecurrent models are represented by the lighter solid lines. Shaded regionsindicate one standard deviation. The differences between the historic andcurrent models for each species present how the species niche has changedbased on our models.Supplementary Figure 4 – Land cover classes with observations of boat-tailed grackles (BTGR) and great-tailed grackles (GTGR) in 1970–1979 and 2010–2019 compared to the change in percent land cover area between each year range. The proportion of land cover measures what percent of observations for each species were located on each land cover class in the corresponding time frame. Both species were found more often in urban environments in the current time period, which also corresponds with a slight increase in the urban background area. Both species were also found less often in their previously second most common land cover type (woody wetland for boat-tailed grackles and shrubland for great-tailed grackles).Supplementary Figure 5 – Results of the nichesimilarity test between the historic (1970–1979) and current(2010–2019) time periods for the boat-tailed grackle. (A) Speciesoccurrence points plotted along the first two principal component (PC) axesused for the niche similarity test. The percent variance captured by eachprincipal component is presented in the axis label. The black linesexpanding from the origin indicate the rotation values for the environmentalpredictors along the two principal components. The current time periodobservations were randomly subsampled to 1000 points for visual clarity. (B)Values of Warren’s I from the niche similarity testbased on the observed data (solid line) and 100 simulations (histogram).Higher values of Warren’s I indicate greater nichesimilarity. The p-value presented for the observed value is based on thenull hypothesis that the observed value presents equal or greater nichesimilarity than the simulations.Supplementary Figure 6 – Results of the nichesimilarity test between the historic (1970–1979) and current(2010–2019) time periods for the great-tailed grackle. (A) Speciesoccurrence points plotted along the first two principal component (PC) axesused for the niche similarity test. The percent variance captured by eachprincipal component is presented in the axis label. The black linesexpanding from the origin indicate the rotation values for the environmentalpredictors along the two principal components. The current time periodobservations were randomly subsampled to 1000 points for visual clarity. (B)Values of Warren’s I from the niche similarity testbased on the observed data (solid line) and 100 simulations (histogram).Higher values of Warren’s I indicate greater nichesimilarity. The p-value presented for the observed value is based on thenull hypothesis that the observed value presents equal or greater nichesimilarity than the simulations.Supplementary Figure 7 – Change in connectivitybetween 1979 and 2019 measured as change in accumulated current forboat-tailed grackles (BTGR) and great-tailed grackles (GTGR). Current valueswere divided into high and low categories based on whether the values wereabove or below the 75th percentile of current values for each map. Colorsindicate whether the current values remained low between the two time steps(gray), went from high to low (magenta), went from low to high (blue), orremained high (green). The darker gray color indicates areas outside therange where checklists were selected for each species, and were excludedfrom the connectivity analysis. The regions that have remained highlyconnected are continuous for both species, which indicates that changes inconnectivity are not responsible for range changes in either species..