Our aim was to assess the impact of combined orthodontic–surgical treatment on patients’ oral health-related quality of life (OHRQoL) according to type of dentofacial deformities, by synthesizing the available evidence. Methods: Search was conducted in the PubMed, Embase/MEDLINE, Scopus, and Cochrane databases. The eligibility criteria were studies that measured OHRQoL before–after orthognathic surgery, with results disaggregated by Class II and III. Two researchers independently performed the selection process, data extraction, and methodological quality assessment. Meta-analysis of the standard mean differences (SMD) was performed using random effect models. Results: The search identified 1047 references. Thirteen studies met the inclusion criteria, and four were included in the meta-analysis. The SMD of OHRQL global score showed large improvement 4–7 months after surgery in Class II and III patients . The sensitivity analyses, excluding studies with weak methodological quality, showed that Class III patients’ improvement in functional limitation was significantly higher than in Class II patients . Conclusions: There is not enough evidence to support differences between Class II and III patients in the OHRQoL impact after orthognathic surgery, but findings suggest lower improvement of some domains in Class II patients. Dentofacial deformities refer to significant deviations from normal proportions of the maxillo-mandibular complex, being one of the oral health problems most perceived by the population. This condition affects the quality of social relationships, self-esteem ,2, and oThe combination of orthodontic and orthognathic surgery is the most established treatment to correct Class II and Class III dentofacial deformities ,5,6,7. TThe first systematic review  about quThe aim of this study was to assess the impact of combined orthodontic–surgical treatment on OHRQoL in patients with dentofacial deformities of Class II and Class III by synthesizing the available evidence through a systematic review with meta-analysis.www.crd.york.ac.uk/prospero) (accessed on 17 September 2021) with registration number CRD42019116092.A systematic review was conducted in accordance with the Cochrane Handbook for the Systematic Review of Interventions  and repoFollowing the PICO  framework, our research question was: In patients with dentofacial deformities of Class II and Class III (P), does the combined orthodontic–surgical treatment (I) have an impact (C) on their oral health-related quality of life (O)? Impact here refers to the comparison between before and after treatment, with or without control group.Inclusion criteria: randomized and nonrandomized clinical trials with or without control group, in patients with dentofacial deformities submitted to combined orthodontic–surgical treatment, that measured OHRQoL before and after surgery; including patients over 15 years old; using validated OHRQoL instruments; and presenting results disaggregated by dentofacial deformity of Class II and Class III. Exclusion criteria: patients undergoing a surgery-first approach or sleep apnea surgical treatment; studies related to patients with congenital abnormalities, such as craniofacial syndrome or cleft lip and palate, and sequels due to maxillofacial trauma; using only generic instruments to assess HRQoL, such as SF36 or EQ5D, not those specific for oral health; assessing psychometric properties; case reports or cases series or studies that were not primary; and not published in English, Spanish, German, or Portuguese.Searches for eligible articles were undertaken in four databases—PubMed, Embase/MEDLINE, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL)—from their inception to October 2021. The following terms were used in the search: “dentofacial deformities”, “orthognathic surgery”, and “quality of life”. No limits of date or languages were added to the searches since the first orthognathic surgery was described in 1849. The details of the search strategy used in each database are listed in the www.covidence.org) (accessed on 21 November 2021): (1) title- and abstract-screening; (2) full-text review with data extraction; and (3) review of references listed in articles. Title- and abstract-screening were performed independently by two reviewers of the study team (V.D. and M.D.), based on the inclusion and exclusion criteria previously established; disagreement was resolved by consensus or by a third reviewer (C.Z.), who acted as an arbitrator. Subsequently, all the selected articles were independently full-text reviewed by two reviewers (V.D. and M.A.).The systematic review followed three stages using COVIDENCE online software  (Data extraction of the studies was conducted independently by two investigators (V.D. and M.A.) using a standardized, predefined collection form that was piloted prior to its use. In order to obtain data which were not provided in the articles of interest, the authors of these studies were contacted.The information extracted from the included studies was publication data, study design, country in which the study was conducted, sample size, patient characteristics, type of dentofacial deformity, OHRQoL instrument used, follow-up data collection times, and results obtained from each group evaluated . We did not consider missing data as a reason to exclude any of the trials from the review. We did not carry out data imputation, as we assumed all missing data to be at random.The methodological quality was assessed with the Effective Public Health Practice Project (EPHPP) quality assessment tool ,29 for qA narrative description was carried out using the characteristics and main results of all studies that fulfilled inclusion criteria. Since most studies assessed OHRQoL immediately prior to surgery  and 4–7 months after surgery, change between these time assessments was selected as the main outcome of interest for quantitative synthesis. When mean and SD of change were not reported, mean and SD at each evaluation were collected to calculate the standardized mean difference (SMD) between both evaluations, and SD was estimated with the formula : (1)SDchThe magnitude of SMD was considered small for 0.2, moderate for 0.5, and large for 0.8 .2 statistic, categorized as follows: <30% not important; 30–50% moderate; 50–75% substantial; and 75–100% considerable [Forest plots were constructed showing the summary and 95% CI estimated in the meta-analyses, together with results from individual studies. We used a random effect model (the DerSimonian–Laird method), as we expected variation in effects due to differences in study populations, questionnaires, and methods. First, we estimated the SMD of global scores separately for Class II and Class III patients and performed subgroup analysis according to the OHRQoL instrument, as a potential source of heterogeneity. Second, we estimated the SMD of dimension scores, performing subgroup analysis according to Class II and Class III patients, to examine differences between them. Third, we also estimated the difference between SMD in Class II and Class III. Finally, sensitivity analyses were carried out by excluding studies with weak methodological quality. Heterogeneity among studies was evaluated using the Iiderable . Funnel The software used was Review Manager 5.4 .http://gdt.guidelinedevelopment.org) (accessed on 18 November 2021). The GRADE approach appraises the quality of a body of evidence based on the extent to which one can be confident that an estimate of effect or association reflects the outcome being assessed. We assessed the quality of the body of evidence with reference to the overall risk of bias of the included studies, directness of the evidence, inconsistency of the results, precision of the estimates, risk of publication bias, and magnitude of the effect. The quality of the evidence can be downgraded by one or two levels for each of these factors, reducing the confidence in the estimate of the effect. There are three factors that can increase the quality of evidence: large magnitude of an effect, dose–response gradient, and effect of plausible residual confounding. We categorized the quality of the body of evidence for each of the primary outcomes as high, moderate, low, or very low.The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used to assess the overall quality of evidence per comparison and outcome . We consThe search identified 1047 references ; after tAmong the 53 full-text articles reviewed, 39 were excluded for the following reasons: 26 studies had no analysis by type of deformity, 5 were not before–after studies, 6 were congress abstracts, and 2 included a pediatric population (participants under 15 years of age). Finally, 13 studies (14 articles) were included in our qualitative synthesis, and 4 in our quantitative synthesis .n = 14) [n = 96) [n = 24) [Details of the included studies are summarized in n = 14) , volunte[n = 96) ; and hea[n = 24) . The fin[n = 24) ,35,36,37[n = 24) , two use[n = 24) ,38, and [n = 24) ,39. Pre-The reasons why certain studies could not be included in the meta-analysis were: pre-surgery assessment carried out prior to orthodontic appliance installation ,34, or aAll the included studies showed an improvement in the OHRQoL, regardless of the questionnaire used. The single study providing information on the OQLQ domains  reportedTwo studies reported no difference between Class II and III patients ,35, whilBaherimoghaddam et al.  reportedOf the four studies that provided data before surgery and 4–7 months after surgery to be included in the meta-analysis, two used the OHIP-14 ,25, one I2 = 89%; very low quality of evidence) and Class III patients . No differences were observed between the estimators from the two questionnaires, OQLQ and OHIP-14 . Regarding the study of Sun et al., OQLQ data was selected for these forest plots because it was designed specifically to measure the impact of orthognathic surgery, while the OHIP-14 is an OHRQL generic instrument.I2 = 68%) in functional limitation to 0.01  in physical disability. The SMD between Class II and Class III patients on the OQLQ and OHIP-14 total score was −0.03 (95% CI—0.61 to 0.54).p = 0.02). In fact, Class II patients did not improve significantly , while those in Class III did . This pattern was also observed in the domain of physical disability (SMD 0.17 and 0.77) although the test for subgroups was not statistically significant.Consistently, the Funnel plots to explore possible publication biases were not constructed, as we did not have more than 10 studies to pool in any meta-analysis.All studies included were of observational design; therefore, the quality of evidence starts out low . In addiDue to concerns regarding blinding and withdrawals/dropouts, serious inconsistency downgraded certainty one level due to considerable heterogeneity and imprecision in one outcome. Indirectness of results was considered not serious since the studies included appropriately answer the question in terms of population, intervention, comparison, and results studied. Publication bias was also rated as not serious.The OHRQoL of patients with dentofacial deformities of Class II and III improved after orthognathic surgery. Improvement was of large magnitude in the global scores of both OHRQoL instruments applied in the studies, OQLQ and OHIP-14, and also in all OHIP-14 domains. No statistically significant differences by type of dentofacial deformity were found, but the sensitivity analyses  showed that Class III patients’ improvement in the functional limitation domain was significantly higher than that of Class II patients. However, there was uncertainty in determining whether the type of dentofacial deformity affects the impact of orthognathic surgery on OHRQoL.Findings obtained through the meta-analysis show improvement of large magnitude in all domains for both types of dentofacial deformities, but in Class II patients, only psychological domains (discomfort and disability), social disability, and handicap were statistically significant . Few studies incorporating Patient-Reported Outcomes (PROs) to measure the impact of orthognathic surgery on OHRQoL provided data for each type of dentofacial deformity, and sample sizes of Class II patients are smaller than those of Class III. Therefore, confidence intervals of the summary estimators obtained in our meta-analysis are very wide, especially for Class II patients.On the other hand, the studies included in our meta-analysis used mostly the OHIP-14 ,24,25, wPrevious systematic reviews consistently showed a positive impact of orthognathic surgery on OHRQoL in general ,20,21,22In accordance with previous research , our finThe sensitivity analysis performed to take into account the methodological quality of primary studies is especially relevant in this context. After excluding the methodologically weak quality studies, improvement differences between Class III and Class II patients were greater in the functional limitations, physical pain, and physical disability domains of OHIP-14. In these domains, improvement was of large magnitude and statistically significant in Class III patients, but small or moderate and not statistically significant in Class II patients. These findings support the need for further research to clarify the impact of orthognathic surgery considering the type of dentofacial deformities.There is high variability among the studies regarding the time assessment, especially before surgery. Some studies considered the baseline as the stage prior to any intervention , other studies just before surgery, and a few in at undetermined timepoint of the pre-surgical period. Between the evaluation before pre-surgical orthodontic treatment and the preoperative phase, just before surgery, studies reported a significant worsening in OHRQoL ,39,41 duAlthough the real impact of orthodontic–surgical treatment should be obtained by comparing the baseline measurement before the installation of pre-surgical orthodontic appliances with the end of the treatment, when the postsurgical orthodontics have been removed, only one study had this design . This stThe time point when the follow-up assessment was performed in the studies included in our meta-analysis ranges from 4 to 7 months after surgery. Changes in functional and facial aesthetics resulting from orthognathic surgery are dependent on the stability of surgical procedures . The autThe present study was strictly conducted in accordance within the guidelines of the Cochrane Handbook for the Systematic Review of Interventions . Even thThe variability among studies on the assessment times before and after surgery limited their inclusion in the meta-analysis. In addition, clinical diversity due to variability in the participants according to age, gender, or degree of severity of dentofacial deformity introduced considerable heterogeneity. However, in order to minimize this, we used a random-effects model in the analysis.Finally, our findings should be interpreted with caution due to the very low certainty of the evidence, which translates into a significant uncertainty of the real magnitude of the impact of dentofacial deformities on the OHRQoL.The quantitative synthesis of results obtained in studies with moderate methodological quality suggests differences according to types of dentofacial deformities in the magnitude of the OHRQoL improvement experienced by patients.Future research comparing types of dentofacial deformities, measuring OHRQoL with condition-specific instruments such as the OQLQ, and with robust methods are needed to clarify this issue. It is relevant to incorporate PROs as a measure of the patient’s perspective, and not only to evaluate the results of the treatment from the aesthetic and functional points of view. Sociocultural conditions and severity of the dentofacial deformity could influence the motivation for treatment and its impact on the OHRQoL.There is not enough evidence to support differences between Class II and III patients in the OHRQoL impact at 4–7 months follow-up after orthognathic surgery. However, sensitive analyses excluding those studies with weak methodological quality suggest differences according to these types of dentofacial deformities in the domains of functional limitation, physical pain, and physical disability.


ThyPRO is the standard thyroid patient-reported outcome (PRO). The change in scores that patients perceive as important remains to be ascertained. The purpose of this study was to determine values for minimal important change (MIC) for ThyPRO.A total of 435 patients treated for benign thyroid diseases completed ThyPRO at baseline and 6 weeks following treatment initiation. At 6 weeks follow-up, patients also completed Global Rating of Change items. For each 0–100 scale, two MIC values were identified: An MIC for groups, using the receiver operating characteristic (ROC) curve method and an MIC for individual patients, using the Reliable Change Index.ROC analyses provided group-MIC estimates of 6.3–14.3 (score range 0–100). Evaluation of area under the curve (AUC) supported the robustness for 9 of 14 scales (AUC > 0.7). Reliable Change Index estimates of individual-MIC were 8.0–21.1. For all scales but two, the individual-MIC values were larger than the group-MIC values.Interpretability of ThyPRO was improved by the establishment of MIC values, which was 6.3–14.3 for groups and 8.0–21.1 for individuals. Thus, estimates of which changes are clinically relevant, are now available for future studies. We recommend using MIC values found by ROC analyses to evaluate changes in groups of patients, whereas MIC values identified by a dual criterion, including the reliability of changes, should be used for individual patients, for example, to identify individual responders in clinical studies or practice. During the last decades, the importance of assessing health-related quality of life (QoL) has been widely acknowledged, and QoL assessments are used both in comparative effectiveness research, and in patient-centered healthcare , 2, 3. TA general challenge for interpretation of patient-reported outcomes is to define whether an observed change in numerical scale score is large enough to be clinically relevant. Consequently, the term minimal important change (MIC) has been proposed . An MIC et al.  curve methods for estimation of MIC values, as recommended by Vet et al. . In claset al. .s.e.m.) for the score of each patient, which is derived from the standard deviation and reliability. This method may be applied in order to support results from the ROC method, since the Reliable Change Index takes the measurement error of the change scores into account, which is not the case for the ROC method , were invited to complete ThyPRO prior to and 6 weeks after treatment initiation. At follow-up, patients also rated their change since baseline; both overall and for each of 13 specific domains measured by ThyPRO. Aiming at samples around 100 (based on previous experience) in each of the major thyroid disease groups, the inclusion criteria were: age above 18; ability to complete paper-and-pencil questionnaires in Danish; and referral to and prescription of clinically relevant treatment or change in treatment of thyroid disease. Exclusion criteria were: pregnancy; patients undergoing minor adjustments of treatment or referred for second opinion or diagnostic procedures; major comorbidity considered to have substantial influence on QoL; or thyroid malignancy. Eligible patients were identified through screening of all patients referred with a diagnosis of thyroid disease. Eligible patients received a booklet containing ThyPRO and sociodemographic questions by mail, followed by a reminder in case of nonresponse. Clinical data were obtained by medical chart review. A subset of the data has previously been used for a methodological evaluation of the responsiveness of the ThyPRO questionnaire .The ThyPRO measures a range of aspects of QoL relevant to patients with benign thyroid disease. It covers not only physical symptoms specifically relevant to thyroid diseases, for example, symptoms of hyperthyroidism and goiter, but also nonspecific aspects of high importance to the patients, for example, depressive symptoms and impaired social life, identified by the patients themselves and clinical experts .The ThyPRO consists of 85 items, summarized in 13 domain-specific multi-item scales, and one single-item overall QoL scale 2) was smallest. The change in scale score corresponding to the cut-off value was chosen as the group-level MIC. For simplicity, we report the absolute values for MIC, although a score improvement is indicated by a negative change score. To assess the strength of our findings, the area under the curve (AUC) of each ROC curve was calculated. In accordance with previous studies/recommendations ndations , an AUC ndations . An AUC ndations .et al.  and conducted in accordance with the Declarations of Helsinki.Of the 779 patients invited to participate in the study, baseline evaluations were completed by 544 patients undergoing clinically relevant treatment, of whom 435 completed the follow-up survey, yielding a completion rate of 56% for the invited patients, and 80% for the patients completing baseline evaluations. Demographic and basic clinical characteristics are shown in At baseline, the mean scale scores ranged between 14 and 58, with the highest (i.e. worst) score on the Tiredness scale and the lowest score on the Impaired Social Life scale. For most of the remaining scales, mean baseline scores ranged between 20 and 30 points. The frequency of patients perceiving themselves as importantly improved were highest for the Goiter Symptoms scale with 45% perceiving themselves improved, and lowest for the Cosmetic Complaints and Impaired Sex Life scales with 13 and 14%, respectively. For the remaining scales, the frequency was between 21 and 39%. Mean change in scores varied between −1.1 for the depressivity scale and −12.0 for the Anxiety scale  are minimized for these 12 scales.et al.  being of a magnitude that would be trivial for an individual, whereas a mean change of the same magnitude in a large population may translate into a large number of reduced strokes in that population . The same would apply to analyses evaluating proportions of treatment-responders in a group, rather than change in group means. The change in score for each of these responding individuals should exceed the highest value of anchor-based and Reliable Change Index-based MIC, to ensure that the changes in scores are reliable. This distinction between group evaluations and individual assessments has previously been described by Guyatt et al. , denominpulation . The twoet al. . Applying the alternative approach, based on individual responses, sample size calculations could be based on the proportion of responders presented in i =12.5) on the Impaired Daily Life scale. An RCT attempting to improve that proportion by for example, 30% should be dimensioned to identify a change to 40% .The MIC values can be used to compare treatment effects in longitudinal studies and for power calculations prior to future clinical trials. For example, in the sub-sample of patients with autoimmune hypothyroidism in the study by Winther et al. , the meaphysical symptoms of hypothyroidism) had the lowest AUC, the highest Reliable Change Index and the lowest specificity. Additionally, the MIC value was equal to the smallest possible change in scale score. It has been suggested, that the physical symptoms assessed by the Hypothyroid Symptoms scale (primarily hair and skin changes) persist for a longer time than other symptoms, despite treatment , since even a small change in only 6 weeks was considered important. It is a strength that a large group of patients with different benign thyroid diseases participated and completed follow-up. The 6 weeks follow-up was deliberately chosen in order for the patients to better remember their baseline status. In future studies, it would be interesting evaluate and compare with longer time periods, for example, 6 months follow-up.In conclusion, we recommend employing the scale-specific MIC values for ThyPRO to assess change in quality of life in patients with thyroid disease. For group-level comparisons, we recommend that the anchor-based MIC values are chosen, whereas on the level of the individual, we recommend that the highest value of the Reliable Change Index and the anchor-based MIC are applied (for illustration and future application presented in a separate The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.The project was supported by grants from the Mørk and the Wedell-Wedellsborg foundations, and the research salary of UFR was supported by a grant from NovoNordisk Foundation.Selma Flora Nordqvist: Data analyses, drafting and approving the final manuscript; Victor Brun Boesen: Data analyses, drafting and approving final manuscript; Åse Krogh Rasmussen: Study design, data acquisition, revising and approving final manuscript; Ulla Feldt-Rasmussen: Study design, data acquisition, revising and approving final manuscript; Laszlo Hegedüs: Study design, data acquisition, revising and approving final manuscript; Steen Joop Bonnema: Study design, data acquisition, revising and approving final manuscript; Per Karkov Cramon: Data acquisition, analyses, drafting and approving final manuscript; Torquil Watt: Study design, data acquisition, revising and approving final manuscript; Mogens Groenvold: Study design, revising and approving final manuscript; Jakob Bue Bjorner: Study design, data analyses, drafting and approving the final manuscript.


The best average accuracy of the proposed detection algorithm in classifying the PD severity stage classification was 96.52% using ResNet-50 with vGRF data from the PhysioNet database. The proposed detection algorithm can effectively differentiate gait patterns based on time–frequency spectrograms of vGRF signals associated with different PD severity levels.Conventional approaches to diagnosing Parkinson’s disease (PD) and rating its severity level are based on medical specialists’ clinical assessment of symptoms, which are subjective and can be inaccurate. These techniques are not very reliable, particularly in the early stages of the disease. A novel detection and severity classification algorithm using deep learning approaches was developed in this research to classify the PD severity level based on vertical ground reaction force (vGRF) signals. Different variations in force patterns generated by the irregularity in vGRF signals due to the gait abnormalities of PD patients can indicate their severity. The main purpose of this research is to aid physicians in detecting early stages of PD, planning efficient treatment, and monitoring disease progression. The detection algorithm comprises preprocessing, feature transformation, and classification processes. In preprocessing, the vGRF signal is divided into 10, 15, and 30 s successive time windows. In the feature transformation process, the time domain vGRF signal in windows with varying time lengths is modified into a time–frequency spectrogram using a continuous wavelet transform (CWT). Then, principal component analysis (PCA) is used for feature enhancement. Finally, different types of convolutional neural networks (CNNs) are employed as deep learning classifiers for classification. The algorithm performance was evaluated using  Parkinson’s disease (PD) is a neurodegenerative disease that belongs to a group of motor system disorders caused by the loss of dopamine-producing brain cells. PD is the second most common neurodegenerative disease ; its preGait analysis is used to assess and treat individuals with conditions affecting their ability to walk, such as poor health, advanced age, size, weight, and speed. A standard assessment is needed to clinically identify and evaluate gait characteristics and other phenomena in PD patients, such as gait count, walking speed, and step length. Pistacchi et al. analyzed temporal parameters see  in patieClassification is the process of identifying the class of a new observation using a set of categories based on a training process involving observations for which the classes are known. In PD classification, various machine learning algorithms have been implemented as classifiers and combined with sophisticated feature extraction methods for dimensionality reduction. Recently, deep learning approaches, instead of conventional machine learning algorithms, have been applied to improve PD classification performance. For example, Jane et al. presented a Q-backpropagated time delay neural network (Q-BTDNN) in a clinical decision-making system (CDMS) to diagnose patients with PD (PD vs. CO) . The Q-BAs previously mentioned, only a few studies have used the deep learning approach for the detection and severity classification of PD, and some of them have used statistical features combined with machine learning methods. The drawbacks of using machine learning are the dependence of its performance on data size and the understanding of features ,16. MachThe proposed PD severity classification algorithm attempts to extract pattern features and visualizations from vGRF signals in PD patients with severity stages of 0, 2, 2.5, and 3 on the HY rating scale by transforming one-dimensional time domain signals into two-dimensional patterns (images) using the feature transformation method from a CWT. The proposed PD severity classification algorithm consists of four main steps, as shown in The vGRF database used in this research, the Gait in Parkinson’s Disease Database (gaitpdb), is available online from PhysioNet . The datThe database contains information recorded from 93 idiopathic PD patients  and 73 CO subjects . Every subject was instructed to walk at their usual pace for about two minutes while wearing a pair of shoes with eight force sensors located under each insole. The raw vGRF signal data in this database were obtained using force-sensitive sensors  with the output proportional to the force under the foot in Newtons, collected at 100 samples per second (frequency of readings during movement was 100 Hz). The recordings also included two signals that reflect the sum of the eight sensor outputs from the left and right foot.The database also contains information about each participant, including gender, age, height, weight, walking velocity, and severity level of PD. The PD severity level was assigned according to two rating scales, HY  and the A two-minute foot force signal was acquired during data collection from subjects. The LF, RF, and CF vGRF signals of the CO and PD subjects were used as inputs to the proposed algorithm. It was difficult to interpret the foot force data directly, despite using a CWT to transform the features, due to the length of the foot force signal. To observe the foot force signal more accurately, a window function was employed. A window function is a mathematical construct that is zero-valued outside of selected intervals. In this research, 10, 15, and 30 s window sizes were used. The aim of the time-windowing process was to obtain shorter signal data. In the clinical application, this data collection is more convenient for the PD patient and, furthermore, reduces the fall risk. The possibility of patient injury rises if the data collection time is longer. Normalization and zero-mean processing were also used, to reduce the redundancy and dependency of data.In 1987, Nilsson and Thorstensson observed the adaptability in the frequency and amplitude of leg movements during human locomotion at different speeds . They reThe continuous wavelet transform (CWT) is a signal processing tool used to observe the time–frequency spectrum characteristics of non-stationary signals . As in tA CWT consists of a time series function The parameter The aim of the time–frequency transformation is to represent the vGRF signal a as a tiThe main goal of principal component analysis (PCA) is to perform dimension reduction for a dataset containing a large number of interrelated variables while, to the greatest extent possible, retaining the variations present in the dataset . This reThe PCA method is defined mathematically using the following steps. Consider a matrix The purpose of using PCA for feature enhancement was to extract fewer patterns while identifying the most important texture and pattern features. This processing was conducted in order to improve the performance of machine learning and artificial intelligence algorithms used for classifying the data points. The full PCs of each spectrogram image sample were selected to preserve the important texture and pattern features for visualization.A convolutional neural network (CNN) is composed of one or more convolutional layers, often with subsampling and pooling layers, followed by one or more fully-connected layers, as in a basic multi-layer neural network . CNN wasThe AlexNet architecture  compriseThe main idea behind a residual network (ResNet)  is the pAn average pooling layer with a A A fully connected layer with 1024 units and rectified linear activation.A dropout layer with 70% rate of dropped outputs.A linear layer with softmax loss as the classifier.GoogLeNet  is a preAlthough AlexNet, ResNet-50, ResNet-101, and GoogLeNet achieved significant performance in the PD severity detection , their architecture characteristics exhibited different influences on performance based on the benefits and drawbacks of the networks. The advantages and disadvantages of AlexNet, ResNet-50, ResNet-101, and GoogLeNet applied in the proposed method are summarized in Cross-validation is a statistical method used to assess and compare learning algorithms by dividing data into two groups: a training set used to train a model and a testing set used to test the model . The traThe experiments were carried out using MATLAB R2018a software on an NVIDIA GeForce GTX 1060 6 GB computer with 24 GB RAM. The computation time is affected by the number of input time–frequency spectrogram images  and the number of neurons in the CNN. We employed multi-class classification for the COs and PD Stages 2, 2.5, and 3. This approach is representative of real-life applications, because doctors and neurologists do not have preliminary information about whether a patient is healthy or suffers from PD and, if the latter, what the severity is.The sensitivity, specificity, accuracy, and AUC value of the proposed method were included as parameters for evaluation. The detailed definition of each evaluation parameter is provided in . When seThe gaitpdb database  containsThe proposed method covered two kinds of classifications, multi-class (CO vs. PD Stage 2 vs. PD Stage 2.5 vs. PD Stage 3) classification and two-class (CO vs. PD) classification. In the two-class classification, PD Stage 2, 2.5, and 3 datasets were combined into one PD dataset. The best classification performance was obtained using AlexNet CNN for multi-class classification and ResNet CNN for two-class classification. The best classification result of the Ga dataset has 98.15% sensitivity, 98.16% specificity, 98.16% accuracy, and an AUC value of 0.9816 on average for multi-class classification and 99.77% sensitivity, 98.80% specificity, 99.11% accuracy, and an AUC value of 0.9995 for two-class classification. The best classification result of the Ju dataset has 98.06% sensitivity, 98.38% specificity, 98.24% accuracy, and an AUC value of 0.9822 on average for multi-class classification and 98.94% sensitivity, 99.04% specificity, 99.01% accuracy, and an AUC value of 0.9993 for two-class classification. The best classification result for the Si dataset has 97.73% sensitivity, 98.76% specificity, 98.27% accuracy, and an AUC value of 0.9825 on average for multi-class classification and 98.85% sensitivity, 98.41% specificity, 98.56% accuracy, and an AUC value of 0.9964 for two-class classification. Based on these classification results, the performance of the proposed method was not influenced by different datasets in the database, even though the data collection processes varied among these datasets.For this classification, the three vGRF datasets in gaitpdb were merged and used as inputs to the proposed PD severity classification algorithm. For the 10 s, 15 s, and 30 s time windows, the input signal numbers for CO, PD Stage 2, PD Stage 2.5, and PD Stage 3 were 994, 1180, 784, and 277; 658, 781, 516, and 184; and 321, 379, 243, and 91, respectively. The best result for this classification type was obtained using the ResNet CNN, with 92.08% sensitivity, 95.60% specificity, 94.58% accuracy, and an AUC value of 0.9384 on average for multi-class classification and 94.46% sensitivity, 97.69% specificity, 96.63% accuracy, and an AUC value of 0.9949 for two-class classification. The complete classification results are shown in In this section, we discuss the gait analysis for each severity stage of PD based on the time and frequency analyses of the time–frequency spectrograms. Some key features of a signal are difficult to observe with the naked eye, but time–frequency spectrogram analysis can help to decipher important information regarding time and frequency characteristics. A CWT was used in this study to transform the signal from the time domain into the time–frequency domain. The gait phenomena could be identified using pattern visualization and recognition based on time–frequency spectrograms for CO subjects and PD patients with severity stages of 2, 2.5, and 3.This observation was only performed for the CF vGRF signal. Since this type of input signal is the additive force between the left and right foot force signals, it describes the correlations between the features of the left and right feet instead of a single feature of the left or right foot. In order to further investigate the gait phenomena, a 10 s time window spectrogram was selected because the image feature was derived from a shorter input signal, and more detail can be perceived from the texture and pattern visualization of gait phenomena. For a 15 and 30 s time window spectrogram, the texture and pattern information is more compressed, and thus, the gait phenomena are blurred and not easily observed see . The 0.1Normal gait phenomena were interpreted by observing the time–frequency spectrogram of CO subjects, as shown in the first column of In the 5–50 Hz frequency range , two frequency ranges (0.83–1.95 and 1.95–50 Hz), and three types of gait foot force signals  were selected as inputs to obtain good feature visualization. After the original signal was transformed, PCA was applied for feature enhancement, to increase between-class separability and to reduce within-class separability. Finally, CNNs were used to perform classification. To evaluate the CNNs’ classification process, 10-fold cross-validation was performed, and the accuracy, sensitivity, specificity, and the AUC value were evaluated. The proposed method was able to achieve the highest performance for more than 97.42% of the parameters being evaluated and achieved superior performance in comparison with the detection and PD severity classification performance of state-of-the-art methods found in the literature.Although the evidence indicates that the proposed method achieved good performance, there are several major drawbacks that could be improved. First, an existing database was used with the proposed method, and clinical data with a greater number of severity levels should be used to verify the performance and to resolve the limitation of the relatively small number of PD patients at certain severity levels in the current database. Clinical data collection will be carried out using a smart insole with an embedded 0.5” force sensing resistor of our own design. The precision and accuracy of force sensing resistor readings are also considered in order to obtain the correct representation of the vGRF signal. PD patients will be asked to perform some simple daily activities, such as turning around and sitting, instead of only walking down a long pathway. Second, long-term data collection to monitor PD progression is important for treatment decisions, since the gait patterns of PD patients appear to change with the long-term progression of the disease. Third, to further investigate the clinical meaning of the results, PD gait phenomena based on time–frequency spectrograms should be discussed with physicians. Fourth, other input data, such as kinetic data, temporal data, step length, and cadence, and other classifiers should be used to confirm and compare the effectiveness of pattern visualization and recognition based on the use of time–frequency spectrograms in PD detection.


The aims of this study were to 1) determine the frequency of AOC in Central Europe, and 2) investigate differences in mental health outcomes in bereaved caregivers depending on whether the decedent had experienced AOC or not.i.e., decision regret, complicated grief, depression, and anxiety. After multiple imputation of missing data, differences in mental health outcomes between AOC-caregivers and non-AOC-caregivers were analyzed in a multivariate analysis of variances.We conducted a cross-sectional study in a large tertiary comprehensive cancer care center in Germany. Bereaved caregivers provided information about (a) treatment within the last month of life of the deceased cancer patient and (b) their own mental health status, We enrolled 298 bereaved caregivers of deceased cancer patients. AOC occurred in 30.9% of all patients. In their last month of life, 20.0% of all patients started a new chemotherapy regimen, and 13.8% received ICU-treatment. We found differences in mental health outcomes between bereaved AOC- and non-AOC-caregivers. Bereaved AOC caregivers experienced significantly more decision regret compared to non-AOC caregivers .AOC occurs frequently in European health care and is associated with poorer mental health outcomes in bereaved caregivers. Future cohort studies should substantiate these findings and explore specific trajectories related to AOC. Notwithstanding, shared-decision making at end-of-life should increasingly account for both patients’ and caregivers’ preferences. While some patients benefit from innovative treatments for advanced cancer –3, an ini.e., levels of depressive symptoms and anxiety, complicated grief, and decision regret, depending on whether the decedent had experienced AOC or not.Hence, this cross-sectional study aimed first to estimate the frequency of AOC as defined above in a large, tertiary comprehensive cancer care center in Germany. In a second step, we aimed to examine differences in mental health outcomes of bereaved caregivers, We hypothesized that bereaved caregivers who had witnessed AOC showed a significantly higher mental health burden compared to caregivers who had not witnessed AOC.This cross-sectional study comprised a survey in bereaved caregivers of cancer patients who had received their treatment at the National Center for Tumor Diseases (NCT) in Heidelberg, a large, tertiary comprehensive cancer care center in Germany. The period of recruitment and data collection was between October 2015 and March 2016. The study was funded by the German Research Foundation (DFG) and approved by the Institutional Review Board of the Medical Faculty of Heidelberg University (Registration-No. S-500/2014). Prior to enrolment, all participants were able to ask questions and required to give their informed consent.th, 2012 and December 31st, 2014. The caregivers approached were listed as contact person by the patients. Inclusion criteria for caregivers were: 1) aged 18 years or older, 2) patient had passed away at least six months prior to caregiver’s study participation, and 3) patient was diagnosed with the following tumor entities: pancreatic, prostate, colon, breast, and lung cancer. Exclusion criteria were: 1) insufficient German language proficiency, 2) cognitive and/or physical impairment, which precluded adequate completion of the questionnaires, and 3) participation in an oncological trial which led to chemotherapy. In a first step, we reviewed the patient’s medical record for information about a contact person. Additionally, we checked the patient’s date of death and whether she or he was diagnosed with one of the included tumor entities. In a second step, we called the identified caregivers initially by phone and determined age, language proficiency, and capability of filling in questionnaires and asked whether the patient participated in an oncological trial in which chemotherapy had been prescribed. If caregivers refused study participation, we recorded the reason for non-participation. We mailed an invitation letter, the study information material, and the set of questionnaires comprising sociodemographic and medical data and psychometrically validated instruments to all interested caregivers and offered a telephone appointment to answer questions raised from the documents. After we clarified all the questions, caregivers filled in the set of questionnaires and mailed it back to the study center along with the signed consent form. For study participation, we chose the timepoint of at least 6 months after the patient’s death so that caregivers would be likely to be beyond a state of acute grief . To investigate differences between AOC in patients and psychological outcomes in bereaved caregivers, caregivers completed psychometrically validated instruments. We reminded not responding caregivers up to four times via telephone and mail (twice each) and recorded reasons for non-participation.For our sample we sought to contact the bereaved caregivers of cancer patients registered in the Cancer Registry of the NCT Heidelberg who had died between June 30te grief , but cloTo achieve a power of 80 at a Type I error rate of 5% when assessing small effects, we estimated that approximately 100 participants per group would be required in a two-group design applying four dependent mental health outcomes measures . To accoTo adapt the definition of AOC to the German health care system where short and medium-long hospital admissions are more common than in the US, we shortened the list of determining factors. We considered the following aspects as the key factors for the definition of AOC usage: 1) new chemotherapy regimen starting less than 30 days before death, 2) the last dose of chemotherapy within 14 days of death, and 3) more than one day ICU stay within the last month of life. If at least one of these factors had been present, we defined AOC usage as present. The occurrence of AOC was considered as independent variable for all the analyses.strongly agree to strongly disagree. The participants are asked to retrospectively evaluate treatment decisions that were made at the end of the patient’s life. To determine whether the caregivers experienced potentially maladaptive aspects of grief, we used the 19-item Inventory of Complicated Grief (ICG)   . The DRSd grief) . Second,d grief) .i.e., levels of depressive symptoms, anxiety, complicated grief, and decision regret, depending on whether the decedent had experienced AOC or not, we conducted a one-way multivariate analysis of variance (MANOVA). Prior to the main analysis, we eliminated multivariate outliers using Mahalanobis distance to limit their effect on the Type I error. We then performed multiple imputation for participants who had <10% missing values (n = 35) on continuous variables (m = 8 imputed sets with 30 iterations) , the patient’s age at time of death, and the time between death and study participation as covariates (only main effects) in the MANOVA. The statistical analysis of the data was conducted using R, version 4.0.3  . We evalon 4.0.3 . For allFrom 1,138 patients who were detected in the Cancer Registry of the NCT Heidelberg and died between June 30th, 2012 and December 31st, 2014, we were able to identify 646 potentially eligible bereaved caregivers. Among the eligible caregivers, 348 non-responders could not be included due to several reasons, mostly because the caregiver could never be reached (n = 154) or was too distressed to participate (n = 94). In total, 298 caregivers completed the questionnaires (response rate: 46.1%). After removal of six outlier cases and 14 participants with missing data on all main study variables , we retained 278 observations for the multivariate analysis. Complete information on all the main study variables was available for 258 participants. For the study flow diagram see Overall, 30.9% of the caregivers (92/298) reported that their deceased family member had experienced at least one component of AOC at the-end-of-life. Specifically, the initiation of a new chemotherapy regimen within the last month of the patient’s life was the most frequently experienced component of AOC , followed by treatment on ICU , and receipt of chemotherapy in the last 14 days of the patient’s life . For a detailed display of frequencies of AOC components see vs. no AOC experience and mental health outcomes, i.e., levels of depressive symptoms and anxiety, complicated grief, and decision regret. A statistically significant MANOVA main effect of moderate size was obtained, Pillai’s criterion = .06, F  = 3.75, p = .006, η²p = .06 , the patient’s age at time of death, and the time since death and study participation as covariates (only main effects) in the MANOVA. In particular, the main effect of AOC on mental health outcomes remained significant, Pillai’s criterion = .06, F = 3.63, p = .007, η²p = .06. Except for relationship to the deceased, Pillai’s criterion = .06, F = 3.82, p = .005, η²p = .06, no significant main effects emerged . Univariate analyses of covariance showed that, as before, participants differed in decision regret between AOC groups, F = 14.5, p <.001, with individuals having experienced AOC reporting higher decision regret than those not having experienced AOC. There were no differences with respect to depressive symptoms, anxiety symptoms, and complicated grief (p’s >.29). Of the covariates, only relationship to the deceased emerged as a significant predictor of decision regret, F = 4.26, p = .040, with bereaved spouses and partners reporting moderately lower regret  than others . None of the covariates significantly predicted one of the other mental health outcomes (p’s >.067) (data not shown).The direction of the findings did not vary when we included gender of the bereaved, relationship to the deceased , the reported ranges of frequencies of chemotherapy within the last 14 days and ICU admissions  entail the point estimates we found. However, compared with numbers from other studies reporting numbers for Europe and the US, our findings are mostly higher. Generally, a consistent difference in AOC frequencies cannot be observed between Europe and the US. One study identified similar frequencies of chemotherapy use and ICU admissions in cancer patients in Europe compared to the US  on the one hand and systematic differences as insurance structures and specific health care environments  on the other hand as possible explanations.To the best of our knowledge, this is one of the first studies providing data on the frequency and impact on caregivers of AOC in Europe. The findings of our study are essentially in line with prior findings on AOC in cancer patients. The estimated frequency of AOC in our sample concurs with the frequencies of the different components of AOC reported in a recently published systematic review of 42 studies in patients with lung cancer . Althougo the US . Furthero the US , 45–47. e.g. shared-decision making featuring discussions about treatment near to death between patients and physicians) may reduce the frequency of AOC and decision regret in patients  that supports the involvement of caregivers early in the treatment trajectory.Concerning future research on AOC, there is a need for longitudinal studies which may substantiate our findings but can also explore specific trajectories related to AOC as well as potential long-term effects. Cohort studies will (a) allow for the comparison of patients for whom chemotherapy was stopped earlier compared to patients who received AOC at end-of-life and (b) further clarify how dyadic aspects play out in the development of distress both in patients and caregivers. Especially in Europe, the linkage between AOC and its effect on caregivers’ mental health needs to be further investigated. In perspective, interventions targeting both patients and caregivers should be tailored, piloted, and evaluated. Finally, considering broader efforts to enhance care, health policymakers should pay closer attention to a regulatory framework . The patients/participants provided their written informed consent to participate in this study.MHar, DJ, H-CF, and MHau conceptualized the study. CB, NB, JT, and MHau collected, prepared, analyzed and visualized the data. JT, MHar, DJ, CB, H-CF, and MHau drafted the manuscript. All authors revised the manuscript critically for important intellectual content. All authors contributed to the article and approved the submitted version.Financial support for this study was provided entirely by a grant from the German Research Foundation  (Grant no. HA 7536/1-1). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ketone bodies, including β-hydroxybutyrate (BHB), acetoacetate (AA), and acetone, can substitute and alternate with glucose under conditions of fuel/food deficiency. Ketone-body metabolism is increased in a myriad of tissue-metabolism disorders. Perturbations in metabolism are major contributors to coronary artery disease (CAD). We investigated the association of BHB with CAD. A total of 2,970 people of Chinese Han ethnicity were enrolled. The Gensini score was calculated for all patients who had positive findings. The serum level of BHB and other laboratory parameters were measured. The association of serum levels of metabolites with traditionally risk factors and CAD severity was analyzed. The BHB was found to be associated with some traditional risk factors of CAD and CAD severity, as determined by the Gensini score or the number of diseased regions. Moreover, BHB was associated with the T3/T1 tertiles of the Gensini score after the adjustment for traditional risk factors by multivariable logistic regression analysis. The association of BHB with CAD severity was more obvious in women. Taken together, these data suggest that the circulating BHB level is independently associated with CAD severity, and that this association is more pronounced in women. Coronary artery disease (CAD) caused by atherosclerosis, has been reported to be the leading cause of death worldwide. Although new medical therapies have emerged in recent years, the risk of death from CAD is still high . TherefoMetabolic dysfunction is a hallmark of CAD pathophysiology, reflecting not only the altered metabolism of the myocardium but also the overall contributions from peripheral tissues and organs , 5. ThesKetone bodies  are water-soluble molecules that contain the ketone groups produced from fatty acids by the liver (ketogenesis). Ketone bodies are derived from increased beta oxidation of free fatty acid, BHB is a major component of the ketone body . During The protocol for this cross-sectional study was approved (2016BJYYEC-121-03) by the Ethics Committee of Beijing Hospital . Written informed consent was provided by all participants.The exclusion criteria were patients: (i) with severe congenital heart disease, severe cardiac insufficiency, primary pulmonary hypertension, hepatic/renal dysfunction, severe peripheral arterial disease, or related conditions which are contraindications to cardiac catheterization; (ii) receiving radiotherapy or chemotherapy; (iii) who were pregnant or nursing a baby; (iv) suffering from alcoholism or drug abuse; and (v) under treatment for mental illness.Patients suspected of having CAD (or adjudicated to have a CAD history) and subjected to coronary angiography in Beijing Hospital between March 2017 and October 2020 were enrolled. The demographic characteristics , medical history , cigarette smoking, and body mass index (BMI) of the study cohort were recorded. Before coronary angiography, samples of venous blood were collected after an overnight fast. The serum was isolated, aliquoted, and stored at −80°C until analyses.Coronary angiography was performed for CAD assessment by experienced cardiologists. All targeted coronary lesions of enrolled patients were analyzed by the built-in QCA software of the Allura Xper FD20 Angiography System . Fifteen coronary segments were analyzed quantitatively based on the American Heart Association classification. According to current guidelines, “coronary stenosis” was defined as a reduction of >50% in the arterial diameter, and if this was not present, was diagnosed as non-CAD. In addition, individuals with negative findings on CT of the coronary arteries or stress myocardial perfusion imaging were categorized as the non-CAD group.The Gensini score was used to assess the severity of damage to coronary arteries . The GenThe serum concentration of BHB was quantified using an LC-MS/MS system comprising a 1,260 Infinity II Series high-performance liquid chromatography (HPLC)  coupled with a Sciex 5,500 QTRAP mass spectrometer . MS parameters were set as previously described . BHB staIn addition, the serum samples were tested for fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), creatinine (Crea), and uric acid (UA) using the respective assay kits  on a chemistry analyzer . Two quality control materials, prepared by mixed fresh serum samples, were analyzed with patient samples in each run in LC-MS/MS and the laboratory assays to monitor the performance of the measurements.CIs. The value of p < 0.05 (two-tailed) was considered significant. Statistical analysis was performed using SPSS 25.0 .The normal distribution of samples was tested. Parameters with normal distribution are expressed as mean ± SD, while parameters with a skewed distribution are presented as the median and percentile (25–75th). Count data are reported as frequencies and percentages. The one-way ANOVA was conducted to compute the differences for continuous variables, while the non-parametric Jonckheere-Terpstra test was used to determine the differences when the data did not have a normal distribution. For categorical variables, the Chi-square test was used. Spearman's correlation analysis was employed to examine the associations between BHB and traditional CAD risk factors. The multivariable logistic regression analysis was employed to determine the relationship between the BHB level and the Gensini score. Potential confounding variables  were controlled in the regression models. Results are presented as odds ratios (ORs) and 95% p < 0.001 for trend). People with a higher BHB level tended to be older (but not significantly so). Whereas, levels of BMI, diastolic blood pressure (DBP), TG, HDL-C, Crea, and UA were similar among the groups. In addition, associations were not found between the BHB level and overweight/obesity, hypertension, history of stroke, smoking status, or statins use.The study population comprised 2,970 patients (62.5% men). Patient characteristics at baseline according to the tertile of the BHB levels are summarized in r = 0.067, p < 0.001), TC , and LDL-C . The serum BHB level was significantly positively correlated with age  and SBP . However, an association between the BHB level and level of DBP, TG, HDL-C, Crea, UA, and BMI was not significant (A significant positive correlation was found between the serum BHB level and the level of FBG (nificant .ptrend = 0.016) with an increase in the number of stenosed regions. Then, the patients with CAD were divided into subgroups with 1 stenosed or >1 stenosed vessels. As shown in ptrend = 0.05).To analyze the relationship between the BHB level and CAD severity, patients with positive findings upon coronary angiography were classified into subgroups for those with 1–3 and >3 stenosed regions. The BHB level was significantly increased (OR was increased with increasing BHB levels in Model 1 (p = 0.004). After adjustment for age and gender (Model 2), high BHB levels were significantly associated with CAD severity, with OR (95% CI) of 1.178 (1.045–1.327), p = 0.007. In Model 3, traditional risk factors of CAD  were all positively associated with the Gensini score, whereas being female was a protective factor for CAD, with OR of 0.417 (0.308–0.564). An increased level of BHB continued to be independently associated with T3/T1 tertiles of the Gensini score , after adjustment for traditional risk factors, such as age, gender, smoking status, overweight/obesity, hypertension, dyslipidemia, DM, history of stroke, and family history of premature CAD . The BHB level was associated with CAD in women , but not in men , after adjustment for age, BMI, smoking status, hypertension, dyslipidemia, DM, history of stroke, and family history of premature CAD. However, an interaction was not observed between the BHB level and age, BMI, smoking status, hypertension, dyslipidemia, DM, history of stroke or family history of premature CAD  and the severity of coronary artery lesion was conducted in different groups of age, gender, BMI, smoking status, hypertension, dyslipidemia, DM, history of stroke, and family history of premature CAD. The interaction between the BHB level and these factors on CAD distribution was analyzed. As presented in ture CAD . Then, wture CAD .In this study, we observed circulating BHB concentration was associated with the traditional risk factors and severity of CAD. An increased BHB level was associated with increased CAD severity, as defined by Gensini score or number of stenosed regions. This association of the BHB level with the Gensini score remained significant after adjustment for the conventional risk factors of CAD by multivariable logistic regression analysis. An increased level of BHB in patients with CAD indicated a more severe state of the disease and more severe systemic metabolic perturbations, especially in women . To the The heart is the most metabolically demanding organ in the body, so impaired metabolism may lead to CAD, thus, the identification and quantification of changes in levels of these metabolites is critical for the diagnosis and treatment of CAD . Ketone First we analyzed the association between the circulating BHB concentrations with CAD traditional risk factors. The result revealed a strong association between the BHB level with the concentration of FBG, TC, and LDL-C, as well as a significant association between the BHB concentration and age and SBP. These results were not in line with some of the previous reports , 24, posNext, we analyzed the relation of BHB with CAD and CAD severity. The study population was first divided into the non-CAD group and CAD group according to coronary angiography. People who developed CAD did not have a significantly higher BHB level in serum compared with that in healthy controls (data not shown). In a pilot study undertaken in Japan, Omori et al. found the BHB level to be significantly lower in the CAD group compared with that in the control subjects (in patients with DM), but the study cohorts were quite small . To analAdditional stratification analysis revealed the BHB level to have a strong association with CAD in women . FurtherTraditionally, severe ketosis, or ketoacidosis, is known as a harmful event. Ketone bodies are synthesized in the liver from acetyl-coenzyme-A derived primarily from fatty acid β-oxidation and are transported to extrahepatic tissues for terminal oxidation as a source for adenosine triphosphate generation at the expense of glucose oxidation . Myocardvia mitochondrial metabolism in tissue macrophages after high fat diet-induced fibrosis , the National Key R&D Program of China (2020YFC2008304), the Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences (2019TX310001), and the Beijing Hospital Special Fund Project (BJ-2019-184).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


While COVID-19 spreads aggressively and rapidly across the globe, many societies have also witnessed the spread of other viral phenomena like misinformation, conspiracy theories, and general mass suspicions about what is really going on. This study investigates how exposure to and trust in information sources, and anxiety and depression, are associated with conspiracy and misinformation beliefs in eight countries/regions  during the COVID-19 pandemic. Data were collected in an online survey fielded from May 29, 2020 to June 12, 2020, resulting in a multinational representative sample of 8,806 adult respondents. Results indicate that greater exposure to traditional media  is associated with lower conspiracy and misinformation beliefs, while exposure to politicians and digital media and personal contacts are associated with greater conspiracy and misinformation beliefs. Exposure to health experts is associated with lower conspiracy beliefs only. Higher feelings of depression are also associated with greater conspiracy and misinformation beliefs. We also found relevant group- and country differences. We discuss the implications of these results. We’re not just fighting an epidemic; we’re fighting an infodemic. Fake news spreads faster and more easily than this virus, and is just as dangerous”  as ‘manipulating and misleading people intentionally to achieve political ends’  artifacts with small impact on real-world actions, several events during the COVID-19 pandemic across different countries demonstrate the opposite. For example, in reaction to the conspiracy theories that claim that 5G cellular network is the cause of the diseasethe U.K. , and numthe U.K. . Furtherthe U.K. , lower lthe U.K. , and lesthe U.K. . Evidencthe U.K. . To highthe U.K. , followithe U.K. .Previous findings show that conspiracy thinking is associated with an avoidance of established and traditional media  and with a tendency to acquire information mainly through digital media, including the internet and social media . The digAside from effects of mere exposure, trust in these media are also expected to play a role. Research has shown that distrust in traditional news media leads to selective exposure to news  and incrfeature of the mind” that help shaping certainty and control in times of uncertainty and stress . The construction of the online survey was based on the Knowledge–Attitude–Practice model  living in each of the eight countries/regions listed above and able to answer an online questionnaire were eligible to participate in the online survey. Participants were randomly recruited from online panels. Several sources were used for the recruitment of panel members, including (a) random recruitment using traditional and mobile telephone methodologies, i.e., recruitment through the firm’s call center, and (b) recruitment by invitation, through social media (Facebook and Instagram), through offline recruitment, and through partner programs and campaigns such as the friend recommendation program. Significant efforts were made to maximize the representativeness of the sample by using software generating representative samples of the population and by including hard-to-reach groups through targeted recruitment. The final sample was composed of approximately 1,000 adults per country/region . See Supbelief in conspiracy theories , one with three items  and another one with six items , each presenting possible conspiracy theories regarding the coronavirus disease. The items originated from a Pew Research Center and Fondation Jean-Jaurès/Conspiracy Watch survey, which was one of the only sources available about COVID-19 and conspiracy beliefs when this study was developed  . These items originated from the WHO Mythbusters, a digital platform developed by the WHO to combat misinformation and fake news regarding a number of topics , television, radio, newspapers (on- and offline), social media, the internet, and friends/family. For each mode of information, answer options ranged from 1 (never) to 4 . Principal component analysis on these items indicated four components with an Eigenvalue > 1 and with moderate to high internal consistency. These components were: information through public health experts (α = 0.70), political actors (α = 0.67), traditional media (α = 0.71), digital media and personal contacts (α = 0.73). In the descriptive analyses, mean scores of these components were used for ease of interpretation, while factor scores were used in the SEM to increase model parsimony.Seven items were used to assess trust in different actors and information sources within society: scientists, doctors and health experts, national health organizations, global health organizations, news organizations, government, politicians, people you know. In order to remain in line with the sources of information, we calculated the mean score of the three items regarding health actors  and the mean score of the two items regarding political actors . Answer options ranged from 1  to 10 (fully trust). In the descriptive analyses, mean scores of these components were used for ease of interpretation, while factor scores were used in the SEM to increase model parsimony.Two psychological states were assessed: generalized anxiety disorder (GAD) and major depression episode (MDE), using the GAD-7  and the n = 18) and those who preferred not to answer (n = 6) were indicated as missing. Information regarding educational attainment was adapted for each country and harmonized following the data collection   . An overAs mentioned above, we developed two measures regarding belief in conspiracy theories; one with three items and another with six items. In this analysis, we present the results of the analyses per country using the three-item conspiracy scale because the additional items were not presented in Hong Kong. We conducted robustness analyses with all countries combined  and witht-tests and one-way ANOVA tests. We then estimated a structural equation model (SEM) for each country or region to investigate associations of exposure to information sources with anxiety and depression, and associations of exposure to and trust in information sources with conspiracy and misinformation beliefs. We also investigated if and how trust in information moderated the effect of exposure. In this model, we controlled for socio-demographic characteristics. We estimated a SEM because of its advantages over OLS regression in three ways in the current study. First, SEM allows for the incorporation of measurement error and offers greater power to detect effects, which is even more important for interaction terms (which we will include in our model)  . Second,r model) . Third, r model) . In thatM = 5.83), the United States (M = 5.19), and Hong Kong (M = 5.03) reported the highest scores with regards to conspiracy beliefs. Respondents from Switzerland (M = 4.31), but especially Canada (M = 3.95) and New Zealand (M = 3.86) reported the lowest scores. As for misinformation beliefs, results again pointed to significant country differences. Respondents from same three countries  reported the highest belief in misinformation, while respondents from New Zealand (M = 3.05), Canada (M = 2.75), and Belgium (M = 2.62) reported the lowest beliefs in misinformation. These results support the assumption in H6a: respondents from countries with a media-supportive and consensual political system in this study  report some of the lowest conspiracy/misinformation beliefs, although scores for English respondents are markedly higher than for those from other countries in this cluster. Conversely, we also confirm that conspiracy beliefs are higher among respondents in countries with a polarized political and media environment (H6b).In terms of belief in conspiracy theories, one-way ANOVA results signaled significant differences between countries . Mean scM = 5.22; 35–54: M = 4.81) and lower educated individuals (M = 4.83) held higher conspiracy beliefs than older age categories (55 + : M = 3.99) and highly educated individuals (M = 4.53). As for misinformation beliefs, we again found that younger age categories (M = 4.03 for 18–34), lower educated individuals (M = 3.52), and women (M = 3.33) were more inclined to believe in misinformation than older age categories (M = 2.85 for 55 +), higher educated individuals (M = 3.36), and men (M = 3.56).With regards to sociodemographic differences, the results in Subsequently, we present the (standardized) direct effects from the structural equation model (SEM). The model was estimated in SAS Version 9.4 using proc calis. Goodness-of-fit indices indicated that all eight models yielded a good fit to the data . We included sociodemographic indicators in all models, but only present them in the full model in The association of exposure to information sources with conspiracy and misinformation beliefs was significantly moderated by trust in these sources in several instances, confirming hypothesis 3. Although results differed between countries, two main trends could be discerned. In several countries, we found that the effect of exposure to health actors differed by levels of trust: as trust in information from health actors increased, the negative association between exposure to health actors and conspiracy and/or misinformation beliefs became stronger. Furthermore, we also found that the effect of exposure to digital media was moderated by trust in these media: as trust in digital media increased, the (positive) association between exposure to digital media and conspiracy and/or misinformation beliefs increased as well. In short, information from health actors was more likely to be associated with lower conspiracy or misinformation beliefs for those who report high trust in these actors, while information from digital media was more likely to be associated with higher conspiracy or misinformation beliefs among those who report high trust in these media. While there are some additional significant effects of the interaction between exposure to and trust in information sources, there was no clear pattern among these across countries.Anxiety was not associated with conspiracy or misinformation in most countries, although Hong Kong presents a clear exception. There, a higher score on the GAD was associated with lower conspiracy and misinformation beliefs. We also find similar associations in Belgium and the United States. However, feelings of depression were more strongly associated with conspiracy or misinformation beliefs across countries. In all countries/regions, except Canada and the Philippines, a higher score on the PHQ was associated with greater conspiracy and misinformation beliefs. The results of a robustness analysis of all countries combined , A7 showFinally, we considered the results of the control variables—which were included in all models. In terms of age, we found that older respondents held greater conspiracy beliefs, but lower misinformation beliefs than younger respondents, and that women held lower conspiracy and misinformation beliefs than men. No clear effects emerge in terms of educational attainment. These results were mostly in line with our earlier findings see .While the SARS-CoV-2 virus spread rapidly across the globe, many societies were also confronted with an inescapable spread of “viral” phenomena like misinformation and conspiracy theories. Conspiracy ideas and misinformation narratives are considered to be viral because the population dynamics underlying their spread hold many characteristic parallels to those involved in the spread of infections and communicable diseases: (1) they tend to spread at a higher pace through an ecosystem than other ideas, and (2) they might have serious consequences in terms of public health behavior and public safety  are more susceptible to these narratives while others  are more resilient. A potential explanation is the different political, media, and economic climates of the countries under scrutiny. Indeed, as recently theorized by In terms of socio-demographics, some interesting findings came to light. First, age was significantly associated with misinformation beliefs and conspiracy beliefs: younger respondents believed more strongly in these narratives than the older generations. This suggests that with age, one develops some type of resilience to misinformation. Second, gender was a significant factor for believing in misinformation but was not significant for conspiracies. Third, believing in conspiracies (but not misinformation) differed significantly across educational attainment: the higher the educational attainment, the weaker the belief in the COVID-19 conspiracy theories. While not significant, the opposite trend was found for misinformation beliefs. Although this corroborates previous findings , our resBeliefs in conspiracy theories and misinformation tend to be negatively associated with exposure to traditional media and positively associated with digital media and personal contacts. More specifically, exposure to COVID-19 related information through traditional news media sources such as newspapers, radio, and television, is associated with lower beliefs in conspiracy theories and misinformation narratives in Belgium and Switzerland. At the same time, exposure to digital media to acquire COVID-19 information is associated with greater conspiracy beliefs and misinformation in all countries/regions. With these results, we build on the findings of earlier studies that suggested that conspiracy thinking was rather associated with an avoidance of established and traditional media , and thaOur data show that anxiety was not strongly associated with conspiracy beliefs or misinformation beliefs in most regions, while depression was associated with higher beliefs in both misinformation and conspiracy theories. Both indicators mediate the relationship between exposure to information sources and conspiracy/misinformation beliefs. This seems to be best interpreted by looking at the intersection between (coping with) stress, uncertainties, and threats on the one hand, and Beck’s cognitive theory of depression , on the Even though we did not include stress as a measurement in the current study, previous studies have shown that stressful life events are a significant predictor for beliefs in conspiracy theories above and beyond other psychological distress factors such as anxiety . NeverthThe findings of the present study are subject to some limitations. First and foremost, while we use data from eight different countries, all our data were cross-sectional. This means that none of the findings in the current study should be interpreted as causal but rather as correlational. Because there is no temporal ordering between data points, all arrows in the model follow merely theory-driven hypothesized paths. Recent examples of internationally comparative studies on the COVID-19 pandemic where the relationship between misinformation beliefs and anxiety and depression was reversed also exist . We can Second, while we collected data in eight different countries, it should be noted here that our cross-country comparison has also some limitations. At the moment of collecting the data  several countries were in different stages of the pandemic. For example, whereas Hong Kong and several European countries already passed a first peak in terms of COVID-related deaths, cases in the United States were still surging. This means that our results should be interpreted with this in mind and may also provide potential explanations for (the lack of) some effects. Particularly in regions where the peak of the first COVID-19-wave had passed at the time of the study, media effects were smaller or absent, while they were more pronounced in regions in which the infection rate was still growing.While the world is fighting a pandemic, it is also fighting an infodemic  in whichThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Research Ethics Board of the CIUSSS de l’Estrie—CHUS. The patients/participants provided their written informed consent to participate in this study.DD, TF, KM, Ld’H, GL, OC-P, M-EC, MD, NP-C, SS, and MG were involved in the study conceptualization, design, and implementation. MG obtained the funding , and her coinvestigators. DD and TF were the study statisticians and were involved in the data analysis. DD, TF, KM, and Ld’H were involved in interpreting the data. DD, TF, KM, Ld’H, GL, and the CCOUC team wrote the first draft. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


R2 0.68). The INQoL performed less well and was poorly associated with the NSAD total score (Pseudo R2 0.18). EK scores were strongly associated with PUL (Pseudo R2 0.69). IPAQ was poorly associated with NSAD scores (Pseudo R2 0.09). This study showed that several of the chosen PROMs demonstrated change over time and a good association with functional outcomes. An alternative quality of life measure and method of collecting data on physical activity may need to be selected for assessing dysferlinopathy.Dysferlinopathy is a muscular dystrophy with a highly variable functional disease progression in which the relationship of function to some patient reported outcome measures (PROMs) has not been previously reported. This analysis aims to identify the suitability of PROMs and their association with motor performance.Two-hundred and four patients with dysferlinopathy were identified in the Jain Foundation's Clinical Outcome Study in Dysferlinopathy from 14 sites in 8 countries. All patients completed the following PROMs: Individualized Neuromuscular Quality of Life Questionnaire (INQoL), International Physical Activity Questionnaire (IPAQ), and activity limitations for patients with upper and/or lower limb impairments (ACTIVLIMs). In addition, nonambulant patients completed the Egen Klassifikation Scale (EK). Assessments were conducted annually at baseline, years 1, 2, 3, and 4. Data were also collected on the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD) and Performance of Upper Limb (PUL) at these time points from year 2. Data were analyzed using descriptive statistics and Rasch analysis was conducted on ACTIVLIM, EK, INQoL. For associations, graphs  were generated from generalized estimating equations (GEE). The ACTIVLIM appeared robust psychometrically and was strongly associated with the NSAD total score (Pseudo  DYSF gene, which encodes the skeletal muscle protein dysferlin  or Patient Centered Outcome Measures (PCOMs). They are deemed a necessity for evaluating disease progression and the efficacy and clinical meaningfulness of therapeutic interventions by experts  and reguThe Jain Clinical Outcomes Study (COS) for dysferlinopathy was established to address the lack of comprehensive natural history data for dysferlinopathy, particularly around PROMs, and to identify if these were associated with functional changes related to disease progression. The aim of the present paper is to evaluate the suitability and change of selected PROMs from baseline up to a maximum of 4 years and to examine the association between these measures and the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD)  and the DYSF, or one pathogenic mutation plus either absent dysferlin expression on immunoblot or <20% dysferlin monocyte expression. Each participating site received local ethics approval and written informed consent was obtained for all patients. The study was registered at ClinicalTrials.gov (NCT01676077).Clinical Outcomes Study is a multicenter, international study of patients with a confirmed diagnosis of dysferlinopathy. Detailed study methods have been published previously , 14. In The present study includes data from 204 patients at 14 sites; one original site was excluded from the present analysis due to the level of missing data over the 4-year period. Participants were evaluated on PROMs up to five times over the course of the study: baseline (visit 1), 12 (V2), 24 (V3), 36 (V4), and for some at 48 (V5) months. Visits took place between November 2012 and March 2018. Follow-up rate was high with 163 participants (87.2%) completing all five study visits across the 14 sites.Self-reported race  and patient gender were recorded at baseline. Age at each study visit was approximated using the visit date and patient's year of birth. Clinical diagnosis of LGMDR2, MM1, or other (consisting primarily of hyperCKemia) was recorded based on the diagnostic label given by the diagnosing clinician, as reported by patients. Ambulatory status was defined at the point of assessment by the ability to complete a 10-m walk distance independently (gait aids permissible) as part of the physiotherapy assessment.A wide range of measures were included in the study, including measures of function and muscle strength, in order to establish their usefulness in assessing disease progression over time. For this study, we examined all patients who completed the following PROMs as appropriate: ACTIVLIM, International Physical Activity Questionnaire (IPAQ), and the Individualized Neuromuscular Quality of Life Questionnaire (INQoL). Nonambulant patients also completed the Egen Klassifikation (EK) scale. Assessments were conducted annually at baseline, years 1, 2, and 3 for some at year 4. Data were also collected on motor performance at these time points .The ACTIVLIM is a validated patient reported outcome measure of functional ability based on perceived difficulty in performing specific activities of daily living . Total sInternational Physical Activity Questionnaire assesses a person's physical activity levels using a set of seven questions and describes that activity in terms of time spent and level of intensity . There aIndividualized Neuromuscular Quality of Life Questionnaire is a quality of life measure that aims to capture the impact of key muscle disease symptoms and the impact on activities, independence, relationships, and body image .The EK scale is a patient's assessment of their “own functioning” related to daily tasks and was designed for nonambulant pediatric and adult patients with Duchenne muscular dystrophy (DMD) and spinal muscular atrophy , 21.The NSAD is a Rasch-developed clinician reported outcome (ClinRO) of motor performance suitable for ambulant and nonambulant adults and children, validated in this dysferlinopathy (LGMDR2) cohort, and has been shown to be very sensitive to change over 1 year .The PUL scale was designed specifically to measure upper limb motor performance across the spectrum of severity in pediatric and adult DMD, is also a Rasch-built ClinRO, and has been shown to be valid and sensitive to change in DMD over time , 23.t-test of unidimensionality. Details on these methods can be found elsewhere , Rasch analysis (RUMM2030 software) was conducted. Essentially, a Rasch analysis examines the extent to which the observed data  “fit” with predictions of those ratings from the Rasch model  . Data welsewhere .R2 for fixed effects were estimated from generalized linear mixed models using techniques described by Jaeger et al.  were generated from generalized estimating equations (GEE) based on preliminary examination of cubic spline graphs. Spearman correlation coefficients are presented for reference. Pseudo r et al. .Of the cohort of 204 patients, 97 were men and 107 were women. Median age at baseline assessment was 36 years of age, range of 8–86. At baseline 76% of the study cohort were ambulant.For ACTIVLIM, a total of 733 questionnaires were reviewed over 4 time points (787 for Rasch over 5 time points); 2% showed scores under 16 and were excluded from Rasch analysis as they would have answered a different subset of four items. Median score was 23 (range 0–36).For IPAQ, a total of 748 questionnaires were reviewed over 4 time points. Eighty-two percent of patients undertook no vigorous exercise, 59% undertook no moderate exercise, 40% did no walking exercise for more than 10 min. The mean time spent sitting per day was 9.4 h (SD 4.7). Twenty-four percent were nonambulant.For INQoL, a total of 660 questionnaires were reviewed over 4 time points. Total scores were calculated on a subset of items not including the treatment section, as only 23% of the cohort answered the questions relating to treatment and their responses included a wide variety of management techniques which were not comparable. However, a sub-total score was calculated on all questions unrelated to treatment.For EK, a total of 208 questionnaires were reviewed over 4 time points (245 for Rasch over 5 time points) in nonambulant individuals. The median score was 7 (range 1–21), out of a maximum of 30, with higher scores indicating being less able.See The results of the Rasch analysis for the three rating scales are presented in The INQoL performed less well with poor ordering of thresholds (38%), unacceptable unidimensionality and limited item fit to the construct of Health Related Quality of Life (HRQoL), although adequate targeting was apparent with only a small floor effect. For the EK, ordering of the thresholds was low but items showed good fit and targeting  and unidR2 0.68), whereas the INQoL was poorly associated with the NSAD total score (Pseudo R2 0.18), as was the IPAQ Total METS (Pseudo R2 0.09). For the nonambulant population, the EK was strongly associated with the PUL total score (Pseudo R2 0.69)  –6.Findings from the present study in dysferlinopathy provide useful information on the suitability  of four PROMs to capture the patient's opinion. In addition, understanding the relationship between patient-centered outcomes with measures of motor performance can add clinical meaning to motor measures which in turn could be valuable within the clinical trial setting. For example, do changes in arm function measured on the PUL reflect changes in how easy or hard it is for an individual to wash and dress their upper body?At the beginning of COS, the choice of PROMs needed careful consideration as no gold standard existed for this population. The ACTIVLIM and INQoL were chosen as they had been built using modern psychometric methods and had demonstrated some evidence of suitability in neuromuscular disease , 19. TheThis study had some limitations. Not all the measures selected were suitable for nonambulant individuals, which made up a quarter of our cohort, which, for example, could result in a limited understanding of activity levels in this group. It may have been beneficial to review and adapt some of the PROMs prior to testing in such a large cohort. This could have identified any unnecessary or unsuitable questions: for example, the swallowing and eating items within the EK scale. However, evidence of how scales work in their original format removes the concern that changes made to it prior to full evaluation were unjustified. We also acknowledge that although chronic pain is recognized as being a significant issue for LGMD , we did The results of this analysis have benefited the design of an extension to this current study, where the quality of life measure has been replaced. More work needs to be undertaken to understand function in relationship to these new PROMs and to evaluate if change in function over time is reflected in the related PROM. Further work can also commence on refinement of some of the current tools such as the EK scale and IPAQ.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by NRES Committee, North East-Newcastle & North Tyneside 2. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.AM, MKJ, VS, LL, LA, and LR: conceptualization of the project, methodology design, research implementation, results analysis, and manuscript writing. UM, HS, JF, RM, KR, and TD: research implementation, results analysis, and manuscript writing. MJ: results analysis and manuscript writing. HG: methodology design, research implementation, results analysis, and manuscript writing. HH: methodology design, research implementation, and manuscript writing. NS-A, ST, CSi, BV, BD, EM, MG, J-YH, AB, PC, SS, JD, KJ, DB-G, ES-C, AP, MW, CP, TS, MM-Y, EB, JD-M, EP, JM, LB, IP-H, SH, CSa, and AC: research implementation and manuscript writing. All authors contributed to the article and approved the submitted version.www.jainfoundation.org). The John Walton Muscular Dystrophy Research Centre is part of the MRC Centre for Neuromuscular Diseases (Grant Number MR/K000608/1).The estimated US $4 million needed to fund this study was provided by the Jain Foundation (MJ receives fee support for PhD studies from the Jain Foundation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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