Background: Patients with Parkinson's disease (PD) and progressive supranuclear palsy Richardson's syndrome (PSP-RS) often show overlapping clinical features, leading to misdiagnoses. The objective of this study was to investigate the feasibility and utility of using multi-modal MRI datasets for an automatic differentiation of PD patients, PSP-RS patients, and healthy control (HC) subjects.Material and Methods: T1-weighted, T2-weighted, and diffusion-tensor (DTI) MRI datasets from 45 PD patients, 20 PSP-RS patients, and 38 HC subjects were available for this study. Using an atlas-based approach, regional values of brain morphology (T1-weighted), brain iron metabolism (T2-weighted), and microstructural integrity (DTI) were measured and employed for feature selection and subsequent classification using combinations of various established machine learning methods.Results: The optimal machine learning model using regional morphology features only achieved a classification accuracy of 65% (67/103 correct classifications) differentiating PD patients, PSP-RS patients, and HC subjects. The optimal machine learning model using only quantitative T2 values performed slightly better and achieved an accuracy of 75.7% (78/103). The optimal classifier using DTI features alone performed considerably better with 95.1% accuracy (98/103). The optimal multi-modal classifier using all features also achieved an accuracy of 95.1% but required more features and achieved a slightly lower F1-score compared to the optimal model using DTI features alone.Conclusion: Machine learning models using multi-modal MRI perform significantly better than uni-modal machine learning models using morphological parameters based on T1-weighted MRI datasets alone or brain iron metabolism markers based on T2-weighted MRI datasets alone. However, machine learnig models using regional brain microstructural integrity metrics computed from DTI datasets perform similar to the optimal multi-modal machine learning model. Thus, given the results from this study cohort, it appears that morphology and brain iron metabolism markers may not provide additional value for classification compared to using DTI metrics alone. The early differential diagnosis of classical Parkinson's disease (PD) and progressive supranuclear palsy (PSP)—in particular the Richardson's syndrome (PSP-RS)—is often limited by overlapping symptom profiles, which are not effectively captured by existing clinical scores or established diagnostic methods. Within this context, failure rates of up to 24% have been reported, even by movement disorders specialists . In clinIn this context, group-wise studies using various magnetic resonance imaging (MRI) modalities such as T1-weighted , 4, T2-wHowever, only a few scientific studies have truly tried to harness the power of multi-modal imaging features to improve differential classification of patients with PD and PSP-RS so far e.g., , 18]. Mo. Mo18)].The study cohort used for this work has been previously described in detail by Boelmans et al. . Briefly*-weighted MRI datasets were acquired for each patient. The high-resolution T1-weighted MPRAGE dataset was acquired using TR = 1,900 ms, TE = 2.46 ms, flip angle = 90°, TI = 900 ms, image in-plane resolution of 0.94 ×0.94 mm2, and 0.94 mm slice thickness.All participants were scanned at the University Medical Center Hamburg-Eppendorf, Germany, using a 3T Siemens Skyra MR scanner . Among o*-weighted image sequences were acquired for this study for R2, R2*, and R2′ mapping. In detail, for R2 mapping, a spin-echo sequence with 15 echoes per shot was employed to record images using echo times of 12, 85, and 158 ms. A total of 24 slices with a thickness of 5 mm with a field-of-view of 240 mm were acquired using a repetition time of 4,590 ms and a flip angle of 150°. The T2*-weighted images were acquired with the same settings except for using a single shot echo-planar sequence with TEs of 21, 52, and 88 ms. The R2 map was calculated by fitting the exponential function SI(t) = SI0exp(−t/T2) to the signal intensity decay curve SI(t) given by the three TE images for each voxel of the T2-weighted sequence, whereas R2 is defined by R2 = 1/T2. The R2* map was calculated in the same fashion using the three TE images of the T2*-weighted sequence. Finally, the R2′ map was calculated using the formula: 1/T2′ = 1/qT2*−1/qT2, whereas R2′ is defined by R2′ = 1/T2′. All computations required for R2/T2 mapping were performed using the in-house developed software tool Antonia (T2-weighted and T22 were acquired without diffusion gradients (b = 0 s/mm2) and with diffusion gradients  applied along 20 non-collinear directions, averaged over two acquisitions. The DTI preprocess tool  brain atlas to each T1-weighted MPRAGE image using NiftyReg , which a2) DTI image was used as the reference for this due to improved anatomical details and higher similarity to the T1-weighted dataset. This registration also consisted of a rigid followed by an affine transformation used for initialization of the non-linear registration, which was performed using a symmetric diffeomorphic image registration method, to allow correcting for distortion artifacts. The resulting transformation was then used to transform the DTI-derived parameter maps  to the corresponding T1-weighted MRI dataset from the same patient. The same approach was used for registration of the T2-weighted datasets to the T1-weighted MRI dataset whereas the dataset from the triple-echo T2-weighted sequence acquired with the longest echo time was used as the reference in this case. The resulting transformation was then used to transform the T2 parameter maps  to the corresponding T1-weighted MRI dataset. All registration results were visually checked to ensure optimal registration quality, so that no missing values or significant outliers were present in the extracted features.After this, the T2-weighted and diffusion-weighted datasets were non-linearly registered to the corresponding T1-weighted MRI dataset from the same patients using ANTs  to enablAn overview of the extracted features using the different brain atlas regions is presented in In a first step, the registered Harvard-Oxford cortical, Harvard-Oxford sub-cortical, and MNI brain regions were used to quantify the volumes of the corresponding brain regions. To account for different global head sizes, the extracted volumes were normalized using the full intracranial volumes as described previously . Apart f*, R2′) in the corresponding atlas brain regions. Median instead of average values were used to account for potential non-normal value distribution and partial volume effects at the border of brain structures. The MNI brain regions were not used for analysis of the DTI and T2-weighted datasets because the corresponding brain regions are rather large, so that localized microstructural and iron deposition differences would not be captured. Using this approach, a total of 1,150 features describing the regional morphology, iron accumulation/deposition, and microstructural integrity were extracted and used for training and testing of machine learning models described below.After this, the registered Harvard-Oxford cortical, Harvard-Oxford sub-cortical, and JHU atlas brain regions were used to quantify the corresponding median DTI parameters  and T2 parameters , and multi-layer perceptron. All models were trained using the models implemented in Weka  with staA leave-one-out cross validation routine was employed for classifier performance evaluation. To prevent double dipping, the leave-one-out cross validation also included the feature ranking. The optimal number of highest ranked features used for training and testing of the classifier was systematically optimized by iteratively removing the lowest ranked feature from the training and testing sets. This recursive feature elimination approach was performed by continuously removing the features from the initial 100 highest ranked features until only a single feature was left in the training and testing sets.In order to identify the optimal combination of feature selection and classification method, the overall 3-level classification accuracy was used as the main evaluation metric. In case of equal classification performance, the feature selection and classification method combination requiring the lowest number of features is reported following the Occam's razor principle .The pipeline described above was applied four times: (1) using the morphological features only, (2) using the R2 features only, (3) using the diffusion features only, and (4) using all features together.In the following, the results of the best performing feature selection and classification combination using the single modality features and the combined multi-modal features, as well as the corresponding selected features are described.Regional brain volume, surface area, and surface area to volume ratio features derived from structural T1-weighted MRI datasets resulted in a top overall accuracy of 65% differentiating PD, PSP-RS, and HC subjects, respectively. The confusion matrix and additional evaluation metrics for the optimal machine learning model are presented in *, and R2′ features are described in The classification results using the regional R2, R2The classification results based on the DTI measurements alone  are shown in *, and R2′), as well as DTI  are shown in The classification results based on the complete multi-modal feature set utilizing features from T1-weighted MRI , T2-weighted MRI  were diffusion features. Diffusion attributes in regions such as parahippocampal gyrus, insular cortex, pallidum, thalamus, brainstem, putamen, and others were ranked as the most discriminative features. Similar numbers of all diffusion parameters were selected.The selected features included features from all three MRI sequences see . In detaLow accuracies of differential diagnosis between classical PD and PSP-RS based on established criteria, even when combined with standard anatomical MRI, have promoted the development of sophisticated machine learning frameworks for assisting with clinical diagnosis. Neuro-imaging data obtained from various MRI modalities have been widely employed for this purpose, whereas T1-, T2-, and diffusion-tensor MRI have been used most frequently. The main contribution of this work is that, for the first time, the benefit of a multi-parametric machine learning approach compared to uni-modal machine learning models was systematically investigated, whereas the results indicate that brain morphology and brain iron metabolism markers do not lead to quantitative benefits compared to using DTI features alone for an automatic classification of PD patients, PSP-RS patients, and HC subjects.Overall, the results of this study are generally well in line with previous research as discussed in the following. However, it should be noted that it is not possible to directly compare the individual classification results of this study with others due to different patient samples, different evaluation schemes, and specific aims.Most previously described classification models are based on morphological parameters determined using T1-weighted MRI datasets. While several other individual level classification studies using volumetric features have reported accuracies differentiating Parkinsonian syndromes ranging from <50% up to 86% e.g., , 28], pr, pr28)],The main findings of this research project with implications to future developments of classification methods for PD vs. PSP-RS vs. HC differentiation using morphology features are 2-fold. First, the inclusion of the surface area and SA:V values provide complimentary information compared to using volumetric features only as the top features for this classification task consist  of a wide variety of all three morphological metrics, which is in line with findings from another recent study . Second,In a similar study, Boelmans et al. utilized brain iron metabolism markers in a logistic discriminant analysis approach to classify 24 HC, 30 PD, and 12 PSP subjects . SubsequIn terms of PD vs. HC classification, the optimal machine learning model identified in this study performs rather poorly with seven PD wrongly classified as HC subjects and vice versa. The misclassification in this category was also the main contributor for downgrading the overall classification performance. A potential explanation for this result could be that iron metabolism markers do not differ considerably between HC subjects and PD patients, therefore resulting in sub-optimal classification performance. Similar to morphological information, brain iron metabolism markers, seem to be inadequate features to differentiate between PD patients and HC subjects. Likewise, the differentiation of PSP-RS vs. PD patients was rather modest with four PD and five PSP-RS patients wrongly classified as PSP-RS and PD, respectively. While the optimal classifier using morphological features also resulted in a total of nine misclassified instances differentiating PD vs. PSP-RS, the difference is that misclassified patients using brain iron metabolism features were rather balanced between the two diseases, whereas morphological features exhibited a weaker PSP-RS classification ability. In addition, the differentiation of HC subjects vs. PSP-RS patients was far better resulting in only two PSP-RS subjects misclassified as HC. Thus, regional iron metabolism markers seem to differ considerably between PSP-RS patients and HC subjects, which is consistent with current literature .Overall, brain iron metabolism markers do not seem to be good predictors for the differentiation of HC subjects from PD patients and PSP-RS from PD patients. Finally, it should be mentioned that the optimal feature selection method used for this classification task  composes new features from a linear combination of the original features, which makes it more complicated to investigate how individual features from the initial feature set contribute to the overall classification. Generally, more research needs to be focused on investigating the association of the regional brain atrophy  and tissue iron accumulation.Various previous studies have shown that diffusion-based features can be used for a classification of PD patients and HC subjects. For example, Scherfler et al. , Salamann = 17) and subjects with atypical forms (n = 23) of Parkinsonism using the RELIEFF feature selection method and a support vector machine classifier, and voxel-wise FA values as features (With respect to differentiating PD and PSP-RS syndromes, two PSP-RS and three PD patients were wrongly classified as PD and PSP-RS, respectively. The obtained sub-syndrome classification accuracy is among the top results reported in literature thus far. However, it should be noted that this is not the first work to employ DTI measurements for classification of PD and PSP-RS subjects although previous research on this is rather scarce. For example, Haller et al. presented an approach to classify PD subjects (features . A correSeveral interesting conclusions can be made by investigating the results of the optimal classification model and selected features in more detail. First, it appears that diffusion changes are a global effect since cortical as well as sub-cortical structures brain regions can be found among the highest ranked features selected for the classification. The 69 selected features used for classification included brain regions that are well-known to be affected in by PD such as the brainstem, and deep gray matter structures including the thalamus, putamen, and pallidum. Additionally, brain regions that are part of the frontal cortex, namely the superior frontal gyrus and frontal medial cortex are among the selected regions, which are part of the prefrontal dopaminergic system. Additionally, it appears useful to investigate all four diffusion parameters as similar numbers of the four DTI features were selected for the optimal machine learning model. Within this context, it should be noted that most previous studies have only used FA and MD values for classification or group-wise studies. Similar to the different morphological features, the incorporation of multi-facet DTI features seems to have the potential to improve machine learning models by elucidating several aspects of PD syndromes.Several studies have been performed in the past aiming to classify patients with PD and HC patients by combining multi-modal image features. For example, Long et al. utilized structural and functional MRI information to classify PD patients and HC subjects . The resSimilarly, multiple studies have also attempted to develop and evaluate multi-modal machine learning models for classification of PD vs. PSP. For example, Morisi et al. combined volumetric, diffusion, and proton spectroscopy measures within a linear kernel SVM model and obtained an accuracy of 98% . CherubiA large number of feature selection methods such as information gain, principal component analysis, linear-kernel SVM based feature selection, RELIEFF, Fisher vector algorithm, evolutionary based techniques, fuzzy based data transformation, graph theory methods, and others have been employed in previous studies. At the same time, many previous studies did not incorporate any feature selection algorithm and simply employed pre-selected sub-syndrome specific features from a limited number of regions-of-interest instead. Within this context, the use of feature selection methods allows identifying important regions in a data-driven way, while manually selecting brain regions for a machine learning model might miss important regions.Similar to the feature selection methods, a wide range of classification techniques such as support vector machines, different types of decision trees, linear and logistic regression, multi-layer perceptron models, and others have been used in previous machine learning models.The fact that different setups of feature selection methods and machine learning models were found to be optimal for the different classification tasks in this work shows that it is important to test and evaluate different setups to identify the optimal setup for a given classification task. Within this context, it is important to ensure that the developed models do not overfit the training data. For this reason, the machine learning models were trained and tested only using the standard hyper parameters in this work. Additionally, the results of all machine learning models were carefully checked and none of the models reported outperformed the next best machine learning model by far. Thus, further classification improvements might be possible by further fine-tuning of the hyper-parameters. Nevertheless, we are confident that the main findings of this research study will still hold true.This study has some limitations that should be discussed. First, the study cohort used in this work, while relatively large compared to similar studies, is still not large enough to fully expand on the generalizability of the proposed model. This limitation is further perpetuated by the lower incidences for PSP-RS compared to PD. Furthermore, an independent validation dataset, preferably acquired in different imaging centers, would be a more rigorous approach of model verification. However, this separate dataset was not available for this present study to further test the proposed model. We opted not to separate the current dataset into completely separate training and validation sub-groups as the training cohort would not have been sufficiently large enough to train a generalized classifier, potentially resulting in an over-fitted model. It is worth noting that studies employing separate validation datasets are rather scarce in this context, so that cross validation methods are used most frequently for classifier validation. Second, the ground truth classifications were determined by an expert clinician according to established consensus criteria without neuropathological proofs. Thus, there may be still a minor level of uncertainty left regarding the ground truth classification used for training and evaluation of the classifier. It should also be mentioned that due to the retrospective design of this study, the ground truth diagnoses were not based on the most recent guidelines for PD and PSP-RS diagnosis –43. HoweThe results of this study suggest that machine learning models using regional brain microstructural integrity metrics computed from DTI datasets perform similar to multi-modal machine learning models incorporating additional imaging metrics such as brain morphology and iron metabolism to differentiate PD, PSP-RS, and HC subjects.nils.forkert@ucalgary.ca.The data analyzed in this study is subject to the following licenses/restrictions: The datasets generated during and/or analyzed during the current study are not publicly available due to containing information that could compromise the privacy of research participants but are available upon reasonable request with approval of the local ethics board. Requests to access these datasets should be directed to AT: study design, image processing, data analysis, and drafting the manuscript and revising it critically. JS: data acquisition and critical revision of the manuscript. KB: study design, data acquisition, and critical revision of the manuscript. NF: study design, image processing, data analysis, and drafting the manuscript and revising it critically. All authors contributed to the article and approved the submitted version.NF owns equity in Eppdata GmbH. 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.


The authors describe a case series of co-infection with COVID-19 and scrub typhus in two Indian patients. Clinical features like fever, cough, dyspnea and altered sensorium were common in both patients. Case 1 had lymphopenia, elevated IL-6 and history of hypertension, while case 2 had leukocytosis and an increased liver enzymes. Both patients had hypoalbuminemia and required admission to the intensive care unit; one of them succumbed to acute respiratory distress syndrome further complicated by multiple organ dysfunction syndrome. Seasonal tropical infections in COVID-19 patients in endemic settings may lead to significant morbidity and mortality. Therefore, high clinical suspicion and an early diagnosis for co-infections among COVID-19 patients are essential for better patient management. The ongoing COVID-19 pandemic, which began in December 2019, has posed a serious public health threat globally due to its varying presentations as well as the difficulty in diagnosis and treatment . Here, tIn August 2020, a 55-year-old hypertensive male patient, a resident of Madhya Pradesh , presented to the emergency department with fever, cough, dyspnea and altered sensorium. The patient was a known case of seizure disorder and was diagnosed to have meningoencephalitis and COVID-19 lower respiratory tract infection by cartridge-based nucleic acid amplification test (CBNAAT) (Cepheid's GeneXpert) in the emergency department. He was admitted to the intensive care unit (ICU) and was started on ceftriaxone, vancomycin and doxycycline, and his anti-hypertensive drugs were continued. Ceftriaxone and vancomycin were added as empiric antibiotic therapy for meningoencephalitis, and doxycycline was added to take care of other pathogens causing atypical pneumonia. The patient had lymphopenia , decreased albumin level  and increased IL-6  at the time of admission. He responded well to the treatment and was shifted out of the ICU on day 6. He was successfully discharged after 21 days of admission.In June 2020, a 35-year-old male, a resident of Delhi  with no prior comorbidities was brought to the emergency department in altered sensorium with fever, cough and dyspnea for the past week. His laboratory investigations revealed increased liver enzymes  and decreased albumin level . The patient had ARDS and was found to be COVID-19 positive by real-time reverse transcription polymerase chain reaction (RT-PCR) [Mycoplasma pneumoniae, Chlamydia pneumoniae and Legionella pneumophila), rickettsioses (spotted fever and typhus group) and scrub typhus were also performed to rule out other differentials, which are endemic in India. Both patients were serologically tested positive for scrub typhus using IgM enzyme-linked immunosorbent assay (ELISA) , whereas indirect immunofluorescence assay (IgM IFA)  for scrub typhus was only positive in case 1. The predetermined cut-offs for ELISA and IFA for scrub typhus were used [Screening for other diseases responsible for febrile illness such as leptospirosis, atypical pneumonia (ere used . Howevertsa) gene of scrub typhus was performed [Rickettsia, Leptospira and atypical bacteria  for laboratory diagnosis of scrub typhus, which includes qPCR using the Orientia spp. 47 kDa htra gene, a single admission IgM IFA titer  ≥1:3200, IFA ≥ 1:3200 on admission or fourfold rise to ≥3200 and a combination of PCR and IFA positivity [et al. found that an admission diagnosis of scrub typhus at a cut-off OD of 0.5 using ST InBios IgM ELISA corresponds to an IFA reciprocal titer cut-off of ≥1600. The use of 0.5 as the cut-off OD in ELISA was demonstrated to have sensitivity and specificity of 93% and 91%, respectively, and may thus be used as an excellent alternative to the gold standard IFA[et al. concluded that cut-off OD within the range of 0.75–1.25 using InBios ST IgM ELISA was the most suitable cut-off OD for the diagnosis of scrub typhus [Orientia tsutsugamushi, which may be missed by IFA, are circulating in the world [Blacksell sitivity . Howeversitivity ,11. A stndard IFA. Anotherb typhus . In the he world . A moleche world . The PCRhe world . The limScrub typhus is grossly under-reported and underdiagnosed, attributable to the misperception that this disease is only a concern in vigorously forested zones. The clinical presentation often mimics that of other common febrile illnesses that share similar seasonal patterns, such as chikungunya and dengue virus infection, creating a diagnostic dilemma and delay in definitive therapy that may lead to adverse clinical outcomes. Thus, the possibility of the co-existence of scrub typhus with COVID-19 during monsoon and post-monsoon season in endemic settings cannot be ruled out; therefore, it should be looked at cautiously and treated appropriately. Previously, the authors reported mortality in five patients due to scrub typhus during the chikungunya outbreak in the absence of timely suspicion, diagnosis and treatment . A recenMycoplasma pneumoniae, Chlamydia pneumoniae, Legionella pneumophila, Klebsiella pneumoniae, Acinetobacter baumanii, Aspergillus fumigatus [Candida auris [Recent studies have described the co-infection of COVID-19 with other respiratory pathogens like influenza, umigatus  and Candda auris ; howeverda auris . Hence, Scrub typhus is a prominent cause of acute febrile illness in the Asia–Pacific region. The most essential management challenge is the institution of appropriate therapy in a timely and effective manner. During outbreaks of viral fever, scrub typhus cases may get missed due to overlapping clinical presentations. Co-infection with such seasonal tropical infections in endemic settings leads to significant morbidity and mortality. Therefore, high clinical suspicion for co-infections among COVID-19 patients during an early stage of illness and precise diagnosis are essential for better patient management.The authors describe a case report of co-infection with COVID-19 and scrub typhus in two Indian patients.Tropical diseases such as scrub typhus also have varied presentations and may present with acute respiratory distress syndrome and multiorgan dysfunction syndrome, which can mimic the current COVID-19 in endemic countries such as India.The possibility of the co-existence of scrub typhus with COVID-19 during monsoon and post-monsoon season in endemic settings cannot be ruled out, and therefore it should be looked at cautiously and treated appropriately.Bacterial co-infections in the presence of viral pneumonia can result in morbidity and mortality.Clinicians must be aware of the existence of scrub typhus with or without COVID-19 in endemic areas, particularly in the absence of eschar.


Sex differences in presentation, management, and outcomes of heart failure (HF) have been observed, but it is uncertain whether these differences exist in South India.We describe sex differences in presentation, management, and in-hospital outcomes in patients hospitalized with HF in South India and explore sex-based differences in the effect of the quality improvement intervention in a secondary analysis of a prospective, interrupted time series study.The Heart Failure Quality Improvement in Kerala (HF QUIK) study evaluated the effect of a quality improvement toolkit on process of care measures and clinical outcomes in patients hospitalized with HF in eight hospitals in Kerala using an interrupted time series design from February 2018 to August 2018. The primary outcome was guideline-directed medical therapy (GDMT) at hospital discharge for patients with HF with reduced ejection fraction (HFrEF). We performed sex-stratified analyses using mixed effect logistic regression models.interaction = 0.69).Among 1,400 patients, 536 (38.3%) were female. Female patients were older , were less likely to have an ischemic etiology of HF  and were less likely to undergo coronary angiography or percutaneous coronary intervention. The quality improvement intervention had similar effects on the odds of GDMT at discharge in females with HFrEF  and males with HFrEF (adjusted OR 1.68, 95% CI 1.07, 2.64, pWe observed sex-specific differences in presentation and procedural management of patients with HF but no differences in the effect of the quality improvement intervention on discharge GDMT rates. Both male and female patients with HFrEF remained undertreated in the study intervention period, demonstrating the need for implementation strategies to close the HFrEF treatment gap in South India. Heart failure (HF) is a leading global public health problem. There are more than 64 million  people estimated to have HF globally with higher prevalence rates among females  compared to males  123456. Less is9Despite increasing international attention to the importance of sex-based differences in cardiovascular disease, there has been no significant proportional growth in sex-specific publications in the past decade based on a bibliometric analysis of all cardiovascular publications from 2006 to 2015 . To addrThe HF QUIK study was a prospective, interrupted time series study that evaluated the effect of a quality improvement intervention on process of care measures and clinical outcomes in patients hospitalized with HF in eight hospitals in South India from February 2018 to August 2018 . Detaile151617Study coordinators at each hospital site entered data into an electronic data capture tool  . The stuFormative research including a systematic review of quality improvement interventions for patients admitted with HF, gaps in quality of care identified by HF registries in the region, and key informant in-depth interviews contributed to the design of the HF QUIK quality improvement intervention 16172021.161720The primary outcome was the prescription of GDMT at discharge  for patients with HFrEF (defined as ejection fraction less than 40%) measured separately and as a combined outcome. Secondary outcomes included in-hospital process of care measures , discharge process of care measures  and clinical outcomes .t test and Chi-square test for continuous and categorical variables, respectively. We evaluated the odds of adherence to process of care measures pre- and post-intervention overall and between sex groups through logistic regression models. The unadjusted model includes the group variable (control and intervention period). The adjusted mixed effect logistic regression model was adjusted for age, and we included a random effect model to account for within-hospital clustering. We performed a complete case analysis due to low rate of missing data (0.1%). Two-sided p value < 0.05 was used to define statistical significance. We used Stata version 14  for statistical analyses.For this report, we stratified analyses by sex. We used date of admission to allocate participants to the control period or the intervention period. Baseline characteristics are summarized for control and intervention periods by sex. Continuous variables are reported as means with standard deviations or medians with interquartile range if data were skewed, and categorical variables as counts with percentages. Between-group comparisons were made using Student’s We enrolled 1,469 patients from 8 hospitals in Kerala, India. Patients were excluded if there were duplicate data entries for the same patient (n = 13), had missing data (n = 2), or were admitted to the hospital after the final date of study enrollment (n = 54). The complete case analysis was performed on 1,400 patients with 758 patients  in the control period and 642 patients  in the intervention period .Sex-stratified baseline characteristics of study patients in control and intervention periods are shown in Table interaction = 0.69, Figure Table Among 1,400 patients admitted with HF in South India, we describe sex-specific differences in presentation, management, and in-hospital outcomes in a secondary analysis of a prospective interrupted time series study and explore sex-based differences in the effect of the quality improvement intervention. We observed that female HF patients were older, less likely to have comorbid chronic kidney disease, ischemic etiology of HF, and undergo coronary angiography and percutaneous coronary intervention during hospitalization compared to male patients. Importantly, there were no significant sex-specific differences in prescription of GDMT at hospital discharge using a HF-specific quality improvement toolkit, but overall rates remained suboptimal.Female patients remain the minority of patients with HF enrolled in HF-specific studies in South Asia. Compared to 38% female patients in HF QUIK, The Trivandrum Heart Failure Registry enrolled 31% women in South India, the International Congestive Heart Failure (INTER-CHF) cohort study enrolled 38% women in India, and REPORT-HF enrolled 36% women from Southeast Asia 152324. F1523252527259We observed no significant sex-specific differences in the effect of the quality improvement intervention on prescription of GDMT at hospital discharge between male and female HFrEF patients in the intervention period in HF QUIK. To our knowledge, no other in-hospital HF quality improvement intervention trials nor quasi-experimental studies have reported sex-specific outcomes . Importa32Multilevel implementation strategies targeting various sex-specific barriers at the patient, provider, and health-system level will be needed to narrow the GDMT treatment gap in India. Previous research in Kerala illustrates many community physicians discontinue GDMT during outpatient follow-up after hospitalization for HF due to concerns of side effects including relative hypotension . A seconpost hoc nature of the analyses, moderate sample size and power to detect potential differences, and a study design that did not prospectively seek to detect sex-specific differences. Furthermore, we are unable to comment on adherence to GDMT as patients were not followed after hospital discharge. However, this study highlights sex-based differences among patients hospitalized with HF in India, a region with limited data on sex-based differences in cardiovascular disease.This study has several strengths. This is the first quasi-experimental study evaluating the effect of an in-hospital quality improvement intervention for patients with HF in a low- or middle-income country to assess sex-specific presentation, management, and outcomes . We enro1520This secondary analysis of a quasi-experimental study in Kerala demonstrates female HF patients were older, less likely to have comorbid chronic kidney disease, ischemic etiology of HF, and undergo coronary angiography and percutaneous coronary intervention during hospitalization compared to male patients with HF. There were no significant sex-specific differences in the effect of the quality improvement intervention on prescription of GDMT in patients with HFrEF at hospital discharge. Both male and female patients with HFrEF remained undertreated in the intervention period, demonstrating the need for implementation strategies to close the HFrEF treatment gap in South India.The additional files for this article can be found as follows:10.5334/gh.1043.s1Supplementary Appendix Figure 1.Flowchart of HF QUIK patients.10.5334/gh.1043.s2Supplementary Appendix Table 1.Unadjusted and adjusted odds of process of care measures and clinical outcomes among HF QUIK participants by sex.


Monoclonal antibodies targeting HER2 are used for the management of early and metastatic HER2-positive breast cancer. Approximately 10–15% of patients diagnosed with breast cancer will be HER2-positive. The incidence of heart failure in breast cancer patients is becoming increasingly problematic, owing to the ageing of the population and the growing number of cancer survivors. The aim of our review was to assess the published evidence for the use of cardio-prevention strategies in HER2-monoclonal antibody-mediated cardiotoxicity. Whilst in the assessed trials the use of heart failure therapies did not reduce the risk of trastuzumab-associated cardiotoxicity, there was a reduction in the mean change in LVEF and in the rates of interruptions to HER2 therapy in patients treated with beta-blockers. This highlights the possible applications for neurohormonal therapies to prevent cardiotoxicity and mitigate interruption to vital HER2-monoclonal antibody treatment.n = 952) reporting data on the primary outcome of cardiotoxicity, there was no clear effect for patients assigned active treatment compared to control . Effects were similar for ACE-I/ARB and beta-blockers (p homogeneity = 0.50). Active treatment reduced the risk of HER2 therapy interruptions  with similar findings for ACE-I/ARB and beta-blockers (p homogeneity = 0.97). Prophylactic treatment with ACE-I/ARB or beta-blocker therapy may be of value for cardio-protection in patients with breast cancer prescribed monoclonal antibodies. Further, adequately powered randomized trials are required to define the role of routine prophylactic treatment in this patient group.Monoclonal antibodies including trastuzumab, pertuzumab, and antibody-drug conjugates, form the backbone of HER2-positive breast cancer therapy. Unfortunately, an important adverse effect of these agents is cardiotoxicity, occurring in approximately 10% of patients. There is increasing published data regarding prevention strategies for cardiotoxicity, though seldom used in clinical practice. We performed a systematic review and meta-analysis of randomized-controlled trials to evaluate pharmacotherapy for the prevention of monoclonal HER2-directed antibody-induced cardiotoxicity in patients with breast cancer. Online databases were queried from their inception until October 2021. Effects were determined by calculating risk ratios (RRs) and 95% confidence intervals (CI) or mean differences (MD) using random-effects models. We identified five eligible trials. In the three trials ( In 2020, breast cancer was the most frequently diagnosed malignancy and the fifth leading cause of cancer-related death globally . The humAn adverse effect associated with the use of all HER2 antibody-based therapy is cardiac dysfunction, which occurs in 5–11% ,7,8 of tReduced left ventricular systolic function is independently associated with an adverse prognosis, and importantly, necessitates an interruption or cessation of HER2-directed antibody therapy, which precludes patients from achieving the full survival benefit offered by this intervention ,18. WhilThe identification of a safe and effective therapy to prevent trastuzumab-associated cardiotoxicity and mitigate interruption to an essential backbone therapy will be of great significance to patients with breast cancer. Use of primary prevention for trastuzumab-related cardiotoxicity is not commonly utilised. As such, we systematically reviewed the literature for research pertaining to the primary prevention of HER2-monoclonal antibody-mediated cardiotoxicity. Specifically, we sought to assess the efficacy and safety of oral heart failure therapies in reducing the incidence of HER2-monoclonal antibody mediated cardiotoxicity.This systematic review was performed according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines . The sysTo be eligible for inclusion, studies needed to be randomized controlled trials (RCTs) comparing the use of oral heart failure agents to a placebo for the primary prevention of HER2-directed monoclonal antibody associated cardiotoxicity. Oral heart failure therapy included all agents consistent with current guideline recommendations for the treatment of HfrEF , namely A systematic search of four databases  was conducted using the following combination of MeSH and keyword terms: breast cancer, trastuzumab*, pertuzumab, prevention, and cardiotoxicity. The wild-card search elicited by the use of the asterisk (*) allows for terms of trastuzumab-emtansine and trastuzumab-deruxtecan to be evaluated, and thus studies of antibody-drug conjugates of trastuzumab were encompassed by this search. The search terms utilised were chosen to allow for the broadest possible search into prevention strategies for cardiotoxicity in HER2-positive breast cancer, with the HER2-positive population being encompassed through the terminology of trastuzumab, pertuzumab, and breast cancer. Databases were queried from their inception until October 2021; included studies were restricted to the English language. The search strategy and results are detailed in A standardized, pre-piloted form was used to extract data from included studies. Two reviewers (L.J.B. and T.M.) independently extracted data and then discussed discrepancies. Disagreement was settled through discussion with a third reviewer (C.A.).Extracted data included information pertaining to study type, methodology, population characteristics, interventions, and outcome measures. Pre-specified outcome data of interest included cardiotoxicity . Outcomes of interest included cardiotoxicity, as defined above, cardiac function as quantified by the left ventricular ejection fraction or global longitudinal strain, HER2 therapy interruption, and safety outcomes. Due to the paucity of studies and heterogeneity of outcome reporting, some results are presented qualitatively with relevant figures. To ensure homogeneity in data pooling, studies reporting outcomes consistent with our definition of cardiotoxicity, LVEF measured before and within 6 months of completing treatment, and HER2 therapy interruption, were deemed eligible.2 statistic and by calculating the p-value for heterogeneity . Of. Of29]. We identified five eligible trials; two studied the effects of an ACE-inhibitor, one the effects of an ARB, and four the effects of a beta-blocker. Comparators were placebo or no treatment. In the included studies, all participants were women and the mean age ranged from 46.5–57 years. One of the five studies included patients treated for metastatic cancer . The othThe dose and duration of trastuzumab were variably reported by the studies. In the adjuvant cohorts in Guglin et al. and Boekhoet et al. and Sherafati et al., trastuzumab was administered for 52 weeks as per standard protocol, or until progression of disease in the metastatic cohort of Sherafati et al. Farahani et al. utilized an unusual loading dose trastuzumab at 4 mg/kg, followed by a maintenance infusion of 6 mg/kg for a total of 52 weeks. Pituskin et al. reported the average dose of trastuzumab administered over the course of the study, which was 102–109 mg/kg +/− 9 mg/kg over 52 weeks.The doses of the study intervention are detailed in p = 0.57). Of these patients, anthracycline exposure occurred in 417 women (43.8%). For patients assigned to either an ACE-inhibitor or an ARB, there was no difference in the risk of cardiotoxicity compared with placebo . Similarly, the use of beta-blocking agents did not significantly reduce the risk of cardiotoxicity compared with control . Effects were similar for ACE/ARB and beta-blockade (p homogeneity = 0.50), however, there was a moderate level of heterogeneity in both individual ACE/ARB and beta-blockade subgroups  and overall .Three studies comprising 952 patients reported data about the primary outcome of cardiotoxicity  with no p < 0.001) with similar findings for ACE-inhibitors and beta-blockade (p homogeneity = 0.97). The use of beta-blockers significantly reduced the risk of HER2 therapy interruption . When analyzed separately, ACE-inhibitors or ARB did not significantly reduce drug interruption  .Two studies comprising 740 patients reported on HER2 therapy interruption ,37. The  = 0.07) . There wp < 0.001) and beta-blockers . There was a moderate level of heterogeneity overall , predominantly driven by heterogeneity in the trials of beta-blocking agents  with low heterogeneity in the ACE trials .All five studies comprising 1082 patients reported LVEF data . Of thesp = 0.01). When stratified by drug class, beta-blockade individually was not associated with a significant difference in follow up LVEF . ACE inhibitor/ARB agents demonstrated a borderline improvement in LVEF . Despite the absence of a significant subgroup effect , overall heterogeneity was high .Meta-analysis of studies that included follow-up LVEF values demonstrated an overall favorable effect of heart failure therapies, which were associated with a 2.24% greater LVEF than placebo . However, participants randomized to control demonstrated a significant worsening of GLS . The mean change in GLS between arms (0.5%) was statistically significant p < 0.001.One study of carvedilol (beta blocker) reported on GLS as a study outcome . The useTwo studies evaluated the serum biomarkers of troponin-T levels and brain natriuretic peptide (pro-BNP) for cardiotoxicity ,37. WhilAdverse event outcomes were reported in three studies ,36,37. Ip < 0.05). Hypotension was noted in 13% of patients treated with lisinopril compared with 3% on placebo (p < 0.01). In this trial, the rates of adverse effects were similar in the carvedilol and placebo arms. Pituskin et al. reported increased incidence of renal dysfunction in patients receiving either ACE inhibitors (perindopril 16%) or beta blockers (bisoprolol 19%) compared to placebo (3%). In contrast to the study by Guglin et al., the rates of hypotension were similar across all arms. Boekhout et al. reported adverse events of Common Terminology Criteria for Adverse Events (CTCAE) grade 3 or higher. Grade 3 fatigue, dizziness, or hypotension were reported in less than 1% of patients in both active (ARB) and placebo arms. There were no reported CTCAE grade 5 adverse in the included studies.Guglin et al. reported significantly more adverse events in patients allocated to ACE inhibitor (lisinopril) therapy compared to beta blockade or control. When compared to placebo, lisinopril was associated with fatigue in 26 vs. 16%, dizziness in 20 vs. 11%, headache in 8 vs. 3%, and cough in 11 vs. 4% , only 24% of patients received trastuzumab and pre-specified subgroup analyses were not performed [Whilst the aim of our review was assessment of HER2-mediated cardiotoxicity, multiple previous anthracycline-associated cardiotoxicity prevention trials have also included sub-populations of patients treated with trastuzumab. For example, Elkhateeb et al. randomized 126 breast cancer patients treated with anthracycline chemotherapy, with or without trastuzumab, to either a combination of enalapril and carvedilol or placebo, and although the intervention group was associated with statistically fewer participants experiencing a reduction in LVEF ≥10% as assessed by cardiac MRI (1.9% vs. 12.5%, erformed . Additioerformed , which aerformed . The resThe limitations of the included studies include the heterogeneous outcome definitions, incomplete outcome reporting, and variable participant exposure to anthracycline therapy. Within the included studies, the incidence of prior anthracycline exposure varied significantly; exposure rates were 23% in the study by Pituskin et al., 40.4% for Guglin et al., and 100% for Boekhout et al. The remaining two studies did not report anthracycline exposure status. Guglin et al. were the only group to report on exposure-stratified outcomes, and importantly demonstrated that although heart failure therapy did not result in a difference in cardiotoxicity across the entire cohort, there was a significant improvement in cardiotoxicity-free survival, protection against LVEF reduction, and treatment interruptions in the subgroup of patients with prior anthracycline exposure. The absence of stratified data in the remaining studies raises the possibility that this subgroup of patients with prior anthracycline exposure may experience benefit from prophylactic heart failure therapy, the observation of which is diluted when results are admixed with non-exposed participants. Our search was confined to studies investigating trastuzumab use, randomised control trials, and those in the English language. Thus, a limitation of the systematic review is the potential omission of other cardio-prevention trials in this space published in a different language or single-arm trials. Whilst this is a possible oversight of the design, randomized trials have the highest level of attributed evidence, and thus this is likely to be reflected in our article.Nevertheless, there are several limitations of our meta-analysis. Firstly, the meta-analysis relies on published data from reported trials rather than on individual patients’ data. Secondly, some patient data were excluded from our meta-analysis as we were not able to extract the individual data of patients who received or did not receive anti-HER2 therapy from the trials. In addition, heterogeneity assessment is less reliable in a meta-analysis with less than 10 studies, although funnel plot asymmetry testing for publication bias did not suggest bias in our analysis. For this reason, sensitivity analyses exploring the robustness of the meta-analyses and meta-regression exploring study-level predictors were also not conducted.The medical treatment for HFrEF has evolved significantly over the last several decades. Since one of the earliest landmark studies in 1986 demonstrated the mortality benefit associated with vasodilator therapy , multiplNotably, none of the studies identified reported on the use of newer agents such as neprilysin or SGLT2 inhibitors. SGLT2 inhibitors may have promise, after demonstrating a profound reduction in cardiovascular death and heart failure hospitalizations in patients with heart failure with reduced ejection fraction ,53. ThesIn this systematic review of five randomized trials, the prophylactic use of RAAS blockade or beta blockers did not reduce the risk of trastuzumab-associated cardiotoxicity. These studies demonstrate the assessment of cardiotoxicity in patients through the modality of transthoracic echocardiography and LVEF assessment. Future cardioprotective trials of established and novel heart failure treatments are needed to definitively answer this question given the clinical need to prevent cardiotoxicity and mitigate interruption of trastuzumab therapy, which is a crucial treatment for patients with breast cancer. The evaluation of serum biomarkers and further imaging modalities to assess early-onset cardiotoxicity may also help to guide therapeutic approaches.


What are the immediate and sustained outcomes associated with metacognitive training (MCT) for psychosis, and are there specific treatment- or participant-related moderators of associations?This systematic review and meta-analysis of 43 studies  on individuals with schizophrenia spectrum and related psychotic disorders found MCT was associated with reduced delusions, hallucinations, and cognitive biases. Metacognitive training was also associated with reduced negative symptoms and improved self-esteem and functioning.The findings of this study suggest that MCT is an accessible evidence-based intervention, deliverable by a variety of mental health care professionals, and appears to be ready for large-scale implementation; MCT may merit inclusion in clinical guideline recommendations for the treatment of individuals with schizophrenia. A substantial increase in the number of trials examining metacognitive training (MCT) for psychosis necessitates an updated examination of the outcomes associated with MCT.To review the immediate and sustained associations of MCT with proximal (directly targeted) and distal (indirectly influenced) outcomes and assess treatment- and participant-related moderators to identify the potential factors associated with the expected heterogeneity of effect sizes.Eleven electronic databases were searched from 2007 to June 3, 2021 . Reference lists of earlier meta-analyses and included reports were screened.Reports examined MCT and included participants with schizophrenia spectrum and related psychotic disorders . There were no age, sex, gender, race and ethnicity, language, or study design restrictions. Two reviewers performed the selection of studies to be analyzed.g effect sizes were computed. The Mixed-Methods Appraisal tool was used to assess study quality.The Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline was followed. Data were extracted by 3 reviewers and pooled using random effects models. Hedges Proximal outcomes were global positive symptoms, delusions, hallucinations, and cognitive biases. Distal outcomes were self-esteem, negative symptoms, quality of life, well-being, and functioning. Immediate and sustained outcomes were examined. Meta-regressions, subgroup, and sensitivity analyses assessed moderators.g = 0.50; 95% CI, 0.34-0.67), delusions , hallucinations , cognitive biases , self-esteem , negative symptoms , and functioning . These associations were maintained up to 1 year. The quality of life effect size was nonsignificant ; only 1 study assessed well-being. Publication year was associated with moderated hallucinations . Overall, narrative review results corroborated meta-analytic findings.This systematic review and meta-analysis included 43 studies (46 reports). Forty reports were synthesized in meta-analysis (N=1816 participants) and 6 reports were included in narrative review. In the studies examined, MCT was associated with positive symptoms (In this meta-analysis, MCT for psychosis was associated with benefits up to 1 year postintervention in several treatment contexts. These findings suggest that MCT may merit integration in treatment guidelines for schizophrenia. This systematic review and meta-analysis examines the use of metacognitive training for psychosis to help in treatment of individuals with psychosis. Despite advancements in pharmacotherapy with antipsychotic medication, approximately 80% of people with schizophrenia spectrum disorders experience recurrent or persistent symptoms.5Schizophrenia spectrum disorders are commonly considered the most severe psychiatric illnesses, profoundly affecting individuals, their families and caregivers, and society.7 metacognitive therapy,9 and metacognitive insight and reflection therapy,10 are psychological treatments aimed at improving metacognitive function, which may help to mitigate persistent symptoms and positive symptoms more generally. Metacognitive training for psychosis is the most widely investigated among these interventions and combines psychoeducation, cognitive bias modification, and strategy teaching.7Metacognitive interventions, such as metacognitive training for psychosis (MCT),12 Metacognitive training for psychosis thus aims to plant doubt in delusional beliefs through raising awareness of cognitive biases13 and aims to raise service engagement by proposing work on this less-confrontational objective first, which is likely to facilitate the therapeutic alliance and more direct work on psychotic symptoms.13The intervention is low threshold: in lieu of directly targeting psychotic symptoms, MCT uses an indirect approach by promoting awareness of cognitive biases. Such biases are maladaptive thinking styles common to psychosis  and are hypothesized to contribute to the formation and maintenance of positive symptoms, particularly delusions.11 and given that modules are not successive, new group members may engage at any time. Furthermore, MCT is presented in a flexible manualized slide format with accompanying at-home activity sheets, which minimizes preparation and increases accessibility and adherence for less-experienced facilitators.13Metacognitive training has several important features as a brief (8-10 module) intervention. All therapeutic materials are available at no cost and are culturally sensitive (currently available in 37 languages). It is deliverable both as a group or individual intervention (MCT+),21 Previous studies report that MCT is acceptable at a large effect size (ES)14 and reduces delusions and other positive symptoms, with ES values ranging from small to moderate at postintervention18 and follow-up.15 Meta-analyses have also observed small to moderate reductions in cognitive biases17 and moderate improvements in insight.19 Two meta-analyses failed to observe significant ES values for MCT21; there is debate regarding whether conservative exclusion criteria and nonexhaustive search strategies may have contributed to these inconsistencies.24 One meta-analysis observed that neither an active control intervention nor the intervention delivery type statistically significantly moderated outcomes on delusions and other positive symptoms.14 Another reported that MCT+ (compared with group MCT) as well as studies published in Eastern compared with Western countries were statistically significant moderators.15 However, results were based on a small number of studies (n = 11) and were not maintained at follow-up.To our knowledge, 8 meta-analyses have assessed MCT since its development in 2007.25 Acuña et al,26 and Tanoue et al.27 Together, these considerations provide the impetus for the present study.Given the considerable influence that meta-analyses have on policy and international treatment guideline recommendations, it is necessary to rigorously address inconsistent findings, reassess specific intervention or participant-related moderators that may enhance outcomes, and update the literature as evidence accumulates. At least a dozen international studies focusing on psychotic symptoms have been published since the prior meta-analyses, for example, Chen et al,Outcomes for this systematic review and meta-analysis are organized following a proximal-distal framework. Proximal outcomes include those directly targeted by MCT. Distal outcomes are those not directly targeted by MCT, but may be either directly or indirectly associated with improvement in proximal outcomes. Distal outcomes are identified as secondary clinical or person-centered variables often assessed in MCT trials, but not previously or thoroughly assessed in past meta-analyses. In this study, outcomes were examined quantitatively and qualitatively, from preintervention to postintervention and follow-up, which to our knowledge, is a novel contribution. Specific aims were to assess the immediate and sustained outcomes of MCT associated with improving proximal outcomes  and distal outcomes  not thoroughly assessed in prior meta-analyses, and examine possible treatment- and participant-related moderators  to identify the potential causes of expected heterogeneity of ES values.PRISMA) reporting guideline was followed.28 Detailed methods (eAppendix 1) are available in the The study protocol was registered on the PROSPERO database (CRD 42021259291) and the Preferred Reporting Items for Systematic Reviews and Meta-analyses , record (the title and/or abstract of a report indexed in a database or website), and study . A systematic review and meta-analysis might have multiple reports, records, and studies  verified the comprehensiveness of the search results and, to mitigate conflict of interest, was not involved in study or report selection, data extraction, quality control, or analyses. Search updates were performed via automatic alert for the Web of Science database until September 10, 2021.The search was conducted on material published from 2007 to June 3, 2021, using 11 electronic databases: Cochrane Central Register of Controlled Trials, CINAHL (EBSCO), PubMed, Embase (Ovid), MEDLINE (Ovid), PsycINFO (Ovid), Social Work Abstracts (Ovid), and Web of Science. Grey literature was searched using OpenGrey, ProQuest Dissertations, and Social Science Research Network eLibrary. The search strategy is presented in eTable 1 in the  studies . SearcheData extraction was performed by 3 of us , and another of us (G.S.) reviewed 10% of the extracted data for accuracy. Discrepancies were resolved via majority agreement among the 4 reviewers. Data from the most recent report were selected when multiple reports corresponded to the same study.Only reports that investigated selected proximal  and/or distal  outcomes were included. eTable 3 in the 29 Methodological quality criteria and results are presented in eTable 4 in the Two of us (D.P. and D.M.) independently assessed study risk of bias using the Mixed Methods Appraisal Tool, version 2018.30 Borenstein et al,31 and Efthimiou et al,32 who suggest that if studies address a common question (treatment effects on the same outcomes), limiting meta-analyses to RCTs is arbitrary; the process of randomization does not infer study quality (the extent that a study yields an unbiased estimate of effect). Meta-analyses based on non-RCTs typically yield ES estimates similar to those assessing RCTs.30 Therefore, we assessed study design as a moderator of MCT effectiveness and ran separate meta-analyses on proximal and distal outcomes using only RCTs to verify whether results were comparable. Information for studies and reports included in the systematic review but ineligible for the quantitative synthesis (n = 6) are displayed in Table 161 and results are outlined in a narrative review. To conduct meta-analyses, Hedges g ES values were computed using the extracted data and were pooled for reports assessing multiple follow-up time points or for scales measuring the same outcome.Selected outcomes were synthesized with separate meta-analyses using Comprehensive Meta-analysis, version 3.0 (Biostat). Reports were eligible for quantitative synthesis if they reported sample sizes, means (SDs), percentages, and/or ES values with a measure of variance , for pretreatment and posttreatment outcome measures. Meta-analyses were not limited to randomized clinical trials (RCTs); the rationale was guided by Shrier et al,Q statistics with significance tests were used for the following categorical variables: risk of bias, type of analyses, study design, comparator type, intervention delivery format, manual adherence, number of sessions, facilitator training, and facilitator credentials. Meta-regression analyses were performed for continuous variables .Subgroups and 70 A conservative value of 0.7 was used when overall results were robust to the use of imputed correlations, as recommended by Rosenthal.71 Risk of publication bias was assessed via visual examination of the funnel plot by one of us (G.S.), the Egger asymmetry test,72 and the Rosenthal73 fail-safe N for all outcomes. Cochran Q statistic74 and the I2 index75 were calculated to estimate heterogeneity of ES values. A random-effects model was used given the anticipated differences between studies regarding test administration and MCT intervention features .76Sensitivity analyses estimated the correlations between pretreatment and posttreatment scores when they were not reported.69 and Table 361 and eAppendix 1 in the Based on our criteria, 43 studies (46 reports) were included in the present review . When proximal outcomes were analyzed separately, global evaluations of positive symptoms reached a moderate ES , the largest ES was obtained for delusions , and small ES values were observed for hallucinations  and cognitive biases .As shown in g = 0.31; 95% CI, 0.19-0.44; P < .001; 26 reports). Separate analyses revealed small but significant ES values for self-esteem  and negative symptoms ; a small to moderate ES for functioning ; and a small, nonsignificant ES for QOL . No changes in the direction of effect emerged for meta-analyses assessing MCT effectiveness (including only RCTs); however, analyses were underpowered for QOL and self-esteem and showed a trend for cognitive biases and functioning. Results on MCT effectiveness are located in eFigure 4 in the A small to moderate ES was also observed for distal outcomes . Thus, therapeutic gains made by the experimental group were steadily maintained. In additional analyses comparing the difference scores between follow-up and baseline for both groups, small to moderate ES values were obtained for proximal  and distal  outcomes. These results further indicate that net therapeutic gains remain significant even 1 year following MCT. Results pertaining to the maintenance of therapeutic effectiveness greater than 1 year are preliminary owing to an insufficient number of studies (eTable 8 in the Maintenance effectiveness (eTable 8 in the P = .03). Larger ES values were reported in more recently published reports. Although some other moderators reached statistical significance, results are not interpretable owing to data not reported in subgroups or an insufficient number of reports per subgroup.Results of the moderator analyses are displayed in eTable 9, eTable 10, and eFigure 2 in the Q4 = 9.33; P = .05) but not proximal outcomes. Significant Q statistics for heterogeneity were obtained for most outcomes in the posttreatment − baseline analyses  may therefore help to alleviate burden  associated with the ongoing need for access to psychological services targeting persistent symptoms. Supporting the treatment gains of MCT thus has a pragmatic implication for care management.This meta-analysis also supports the sustained effectiveness of MCT, up to 1-year following the intervention, on all significant outcomes. The maintenance of treatment gains is critical in the long-term functioning of individuals with severe mental illness, and markedly so in psychotic disorders given the experience of persistent, debilitating symptoms. Most of these individuals are followed up in the public health system and often have limited personal resources to access private sector services.57; however, no sex-specific benefits were observed following meta-analysis.The positive outcomes of MCT were observed regardless of age, sex, illness duration, and medication dosage. It can be successfully delivered by a variety of mental health practitioners, either as an 8-, 10-, or 16-session group or individual intervention. Such attributes, coupled with the establishment of treatment gains, align with broader implementation given the reality of cost-benefit mandates in the public mental health system, and yet remain compatible with person-centered models of care. Year of publication moderated the association between MCT and hallucinations, such that newer studies reported higher ES values. However, this finding should be interpreted with caution given the small number of included reports (n = 9). No other participant or treatment characteristic emerged as a moderator between MCT and any other proximal or distal outcome. Prior evidence suggests that women may improve more in general symptoms compared with men after MCT82 and functioning.83 Similarly, prior cognitive remediation meta-analyses have reported small to moderate ES values for negative symptoms, global symptoms, and functioning.86 Thus, ES values observed for MCT appear similar to these other evidence-based interventions. The open-access availability of the intervention, combined with visual presentations and clinical e-training, makes MCT an accessible option for any mental health practitioner aspiring to deliver an evidence-based psychological intervention for psychosis.It is important to position these findings within the broader context of evidence-based psychological interventions for psychosis. Cognitive behavioral therapy for psychosis and cognitive remediation are 2 well-established interventions. Meta-analyses examining cognitive behavioral therapy for psychosis have observed a small to moderate ES for delusions and small ES values for hallucinations, negative symptoms,17 meta-analysis. Sauvé et al reported on a combination of 5 metacognitive interventions and their variants, which likely speaks to this discrepancy. Another potential explanation concerns the construct validity of popular standard measures of cognitive bias, such as the beads/fish tasks.87 Yet, in line with previous hypotheses,12 our findings suggest that MCT likely attenuates the overall outcomes associated with maladaptive thinking styles in the maintenance of positive symptoms, particularly given that symptoms are not directly addressed in the intervention, and evidenced by the significant reductions we observed in delusions and hallucinations. Hence, even a small reduction in cognitive biases is clinically meaningful.Although ES values were significant for cognitive biases, noted benefits were lower than those observed in the Sauvé et al88 However, the QOL meta-analysis was likely underpowered with the inclusion of only 7 reports. A 3-year follow-up RCT assessing MCT efficacy revealed improvements in QOL and self-esteem compared with active control.53 These results were nonsignificant at 4-week and 6-month postintervention evaluation, perhaps speaking to a delayed effect of MCT on these outcomes. The variability of QOL domains assessed by the included measures  may be another important factor accounting for null findings. Furthermore, our search did not yield sufficient studies to examine well-being (n = 1), although well-being is deemed a distinct construct.89 Given the importance of these outcomes in person-centered/patient-oriented recovery models,90 future trials would benefit from more precise examination and better operationalization of these constructs.The nonsignificant ES for QOL was unexpected given observed improvements in functioning, considerable reductions in psychotic symptom severity, and the negative association between QOL and psychotic symptoms.21; methodological quality was investigated, and the findings were robust to sensitivity analyses.This meta-analysis has strengths, including synthesizing more than 14 years of evidence, and represents what is, to our knowledge, the most comprehensive systematic review and meta-analysis evaluating the use and effectiveness of MCT. This also may be the first to assess distal outcomes, highlighting the apparent benefit of the intervention on negative symptoms, self-esteem, and functioning. Our approach addresses prior meta-analytic inconsistencies This study also has limitations. We observed significant heterogeneity of ES values for studies assessing global positive symptoms, delusions, QOL, and functioning, although heterogeneity was not evident at follow-up.31 Publication bias was present for hallucinations, cognitive biases, negative symptoms, self-esteem, and QOL. A publication bias likely exists for cognitive biases; however, a publication bias for the other variables is unlikely given they were never identified in the literature as primary study outcomes. In addition, lower-quality studies had significantly lower ES values for distal outcomes and we could not include well-being in our quantitative review because it was assessed by only 1 study. Furthermore, the number of RCTs reporting a follow-up exceeding 1 year was insufficient to conduct reliable analyses across outcomes, and some moderator analyses were not interpretable owing to small subgroups or those with data not reported. Hence, important moderators and/or delayed effectiveness53 perhaps were not captured. Another limitation was noted with all analyses underpowered for QOL, and self-esteem was underpowered in the RCT-only meta-analysis.The use of a random-effects model, which assumes that real ES values vary between studies, was implemented to mitigate this limitation.92; future meta-analyses might consider investigating MCT as a transdiagnostic treatment. The inclusion of several new high-quality international trials attests to the intervention’s accessibility, adaptability, and cultural sensitivity. These findings provide some evidence to consider MCT in international treatment guidelines and the focus may now shift toward implementation and cost-effectiveness trials in real-world clinical settings. In addition, the COVID-19 pandemic has exacerbated the need for virtual evidence-based psychological intervention delivery, especially among vulnerable populations. It may be useful for future work to also assess the feasibility, acceptability, and effectiveness of MCT as a virtually delivered93 intervention.The findings of this systematic review and meta-analysis suggest that MCT is a beneficial and durable low-threshold intervention that can be flexibly delivered at minimal cost in a variety of contexts to individuals with psychotic disorders. Metacognitive training has also been associated with positive outcomes in different patient populations, such as those with borderline personality disorder, depression, and obsessive-compulsive disorder


Previous studies demonstrated the adverse impact corticosteroids can have on blood glucose homeostasis in both diabetics and non-diabetics. This raises concern for corticosteroid use in severe COVID-19 where the population is enriched for those at highest risk of severe disease, such as diabetics and patients with obesity. Previous studies of dexamethasone in COVID-19 were limited by the inability to assess steroid-induced hyperglycemia or the impact of hyperglycemia on hospital resources. The study aimed to describe the clinical characteristics, management, and outcomes related to hyperglycemia, before and after dexamethasone therapy was used as the standard of care in patients with severe COVID-19.We performed a pre/post retrospective study of patients with severe COVID-19 pneumonia admitted from May to July 2020 to Harbor-UCLA Medical Center. 126 patients were evaluated. 64 received dexamethasone and 62 did not. To quantify the effect of dexamethasone on diabetic vs. non-diabetic patients, we documented the average blood glucoses and frequency of correctional insulin doses required by each patient group .While dexamethasone was associated with higher median blood glucose and more frequent correctional insulin dosing in diabetic patients, there was minimal effect of dexamethasone on hyperglycemia in non-diabetic patients. Furthermore, while non-diabetic patients receiving dexamethasone required more doses of correctional insulin per day vs non-diabetic patients not receiving dexamethasone (0.3 doses per day vs 0.1 doses per day), the frequency of correctional insulin doses required by non-diabetics on dexamethasone remained low at 0.3 doses per day.NIH COVID-19 guidelines recommend administering dexamethasone only if the patient is in a monitored setting. Our data support the NIH concerns that outpatients with diabetes receiving steroids are at risk for hyperglycemic complications. However, contrary to the NIH guidelines, our data suggest that patients without diabetes receiving steroids are at low risk for complications due to hyperglycemia and a majority do not require monitoring.Eric Daar, MD, Gilead (Consultant)Gilead (Research Grant or Support)Merck (Research Grant or Support)Merck (Consultant)ViiV (Research Grant or Support)


Background: The objective is to study whether the cardiovascular protective effects of colchicines could be applied to non-cardiogenic ischemic stroke (IS) patients. Patients and Methods: Non-cardiogenic IS patients were identified from the National Health Insurance Research Database. Eligible patients were divided into chronic and non-chronic use categories based on their long-term status of colchicine use. The non-chronic use category was subdivided into (1) non-user and (2) new user groups while the chronic use category was divided into (3) former user and (4) long-term user groups according to the patient’s recent status of colchicine use. Inverse probability of treatment weights for propensity scores was used to balance the baseline characteristics. The primary outcome was recurrent IS, which was compared within the non-chronic use and chronic use categories. Results: In the non-chronic use category, the number of patients was 355,498 and 912 in the non-user and new user groups, respectively. In the chronic use category, the number of patients was 4737 and 4354 in the former user and long-term user groups, respectively. In the non-chronic use category, patients in the new user group had a marginally lower risk of recurrent IS at 6-months  and 2-years  follow up. In the chronic use category, patients in the long-term user group also had a marginally lower risk of recurrent IS at 6-months  and 2-years  follow up. The effect of colchicine on the reduced risk of recurrent IS was more favorable in patients who also used statins. Conclusions: Recent colchicine use in acute non-cardiogenic IS patients is associated with marginal fewer incidences of recurrent IS. Patients with concurrent statin use may have more profound protective effects. Risk factor modification and antithrombotic drugs are crucial for reducing ischemic stroke (IS) recurrence ,2. RecenColchicine is an anti-inflammatory treatment which attracted much clinical attention . The ColThis retrospective population-based cohort study included patients who were admitted to hospital due to IS between 1 January 2001 and 31 December 2013, as listed in the National Health Insurance Research Database (NHIRD). The first IS admission for each patient was used as the index date if they suffered from multiple IS episodes during the study period. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes were used for the registration of all diagnoses ,15.The patients of interest in the current study were those with a principal discharge diagnosis of IS. Patients who did not have definite cerebral infarction on admission were excluded . The ICDPatients with different statuses of chronic colchicine use could reflect different metabolic and vascular statuses at enrolment. Therefore, the eligible patients were divided into two categories according to their status of chronic colchicine use before the IS index date. The non-chronic use category included patients who did not take any colchicine 91–365 days before the IS index date, whereas the chronic use category included patients who constantly took colchicine 91–365 days before the IS index date. Each category was sub-divided into two groups based on their recent colchicine use (within the last 90 days) before the IS index date. Patients in the non-chronic use category were divided into (1) non-user and (2) new user groups. The non-user group was defined as patients who did not take any colchicine within the 90 days before the IS index date. The new user group included patients who newly received colchicine during this 90-day period. Patients in the chronic use category were divided into (3) former user, and (4) long-term user groups. The former user group included patients who stopped using colchicines within the 90 days before the IS index date. The long-term user group was defined as patients who kept taking colchicine during this 90-day period.We extracted information on medication use from the claims data for pharmacy refills for chronic illnesses or outpatient visits. We defined patients as stable users if they received a prescription for colchicine for 28 or more days during either the 90 days or 91–365 days before the IS index date. Patients who were prescribed colchicines for less than 28 days in these two periods (non-stable users) were excluded . The defThe patient’s sex and age during their index hospitalization were obtained. The medical records before the index date of hospitalization were traced to track any history of comorbidities. We defined previous stroke and myocardial infarction (MI) history by using any inpatient diagnosis prior to the index date. Underlying comorbidities were defined if the patient had at least 2 outpatient diagnoses or an inpatient diagnosis in the previous year. Most of the diagnostic codes for these events and comorbidities were validated in previous NHIRD studies . We adjuThe primary outcome in this study was recurrent IS during the 2-year follow up. The secondary outcomes included CV death, all-cause mortality, and new diagnosed AF. Recurrent IS was considered when patients were admitted primarily due to IS during the follow-up period. AF was diagnosed based on the ICD-9-CM code (427.31) in two consecutive outpatient visits or one hospital admission. The positive predictive value of AF diagnosis was around 90% in a previous validation study . The defWhen comparing the risk of outcomes among multiple treatment groups, we conducted an inverse probability of treatment weights (IPTW) for propensity scores (PSs) to balance the baseline characteristics among groups. As there were multiple treatment groups in this study, we estimated the PSs using the generalized boosted model (GBM) . Table 1p value < 0.05 was considered to be statistically significant and no adjustment of multiple testing (multiplicity) was made in this study. Statistical analyses were performed using SAS version 9.4 , including the ‘phreg’ procedure for conducting survival analyses and the ‘TWANG’ macro for GBM-IPTW estimation.The event rates of outcomes as well as survival analyses were estimated in the cohort after IPTW. The risk of fatal outcomes among treatment groups was compared using the Cox proportional hazard model. The incidence of other time-to-event outcomes among the treatment groups was compared using the Fine and Gray subdistributional hazard model, which considered all-cause mortality as a competing risk. The treatment group was the only one explanatory variable in the aforementioned survival analyses. We further conducted pre-specified subgroup analyses on the primary outcome using the following subgroup variables: age, previous IS, previous MI or CAD, diabetes mellitus, hypertension, CKD, and use of statins. A two-sided n = 36,789), AF , endocarditis (n = 238) and valvular heart disease (n = 1336). Additionally, 10,410 patients who were less than 40 years old and 9773 patients who died in-hospital were also excluded. In addition, we excluded 15,455 individuals who were non-stable colchicine users before the IS index date. Finally, 365,501 IS patients were confirmed as eligible for inclusion within the study analyses. There were 356,410 patients in the non-chronic use category, including 355,498 in the non-user group and 912 in the new user group. There were 9091 patients in the chronic use category, including 4737 in the former user group and 4354 in the long-term user group , and had a higher prevalence of gout (84.3%), hypertension (87.6%), previous MI (4.1%), CAD (27.9%), and CKD (11.6%). In addition, patients in the long-term user group had the highest frequency of statin (14.7%), non-steroidal anti-inflammatory drug (48.3%), steroid use (6.1%), multiple antihypertensive drugs (1.73 ± 1.22) and antiplatelets use (aspirin: 27.0%) . ConversLong-term outcome of study patients before GBM-IPTW was presented in the supplemental Compared with the non-user group, the new user group had a higher risk of all-cause mortality , and CV death  at the 2-year follow-up . Comparep < 0.05; Subgroup analyses were performed between the new users and non-users. There was a significant difference between colchicine use and a history of IS, CAD or MI, diabetes mellitus, hypertension, and CKD before the index event. The observed effect of colchicine in reducing recurrent IS risks was less apparent in patients who had these underlying diseases. Significant interactions were also observed between colchicine use and concurrent statin use. The observed effect of colchicine in reducing recurrent IS risks was also more profound in patients who concurrently took statins  trial , our resThe main mechanism for colchicine’s vascular protectiveness is its anti-inflammatory effect . Plaque Colchicine may have anti-fibrosis effects . In patiOur study demonstrated that both continuous use of colchicine in former users and a new prescription of colchicine during IS events can have universal benefits. Plaque inflammation can be most profound after IS and could lead to higher stroke recurrence . This coThe current study had limitations. First, some patients may have had chronic colchicine use because of frequent gouty arthritis rather than inflammatory modulation for CV diseases . We trieOur study demonstrated that recent use of colchicines in acute non-cardiogenic IS patients is associated with marginally fewer incidences of recurrent IS in an Asian population. This protective effect was observed at both 6 months and 2 years after IS. Concomitant use of statins with colchicine may potentiate its protective effects. Results of clinical trials are needed to give a more conclusive answer, particularly in the atherosclerotic IS subgroup.