7 research outputs found

    Association of metabolic equivalent of task (MET) score in length of stay in hospital following radical cystectomy with urinary diversion:a multi-institutional study

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    PURPOSE: The Metabolic equivalent of task (MET) score is used in patientsā€™ preoperative functional capacity assessment. It is commonly thought that patients with a higher MET score will have better postoperative outcomes than patients withĀ a lower MET score. However, such a link remains the subject of debate and is yet unvalidated in major urological surgery. This study aimed to explore the association of patientsā€™ MET score with their postoperative outcomes following radical cystectomy. METHODS: We used records-linkage methodology with unique identifiers (Community Health Index/hospital number) and electronic databases to assess postoperative outcomes of patients who had underwent radical cystectomies between 2015 and 2020. The outcome measure was patientsā€™ length of hospital stay. This was compared with multiple basic characteristics such as age, sex, MET score and comorbid conditions. A MET score of less than four (<ā€‰4) is taken as the threshold for a poor functional capacity. We conducted unadjusted and adjusted Cox regression analyses for time to discharge against MET score. RESULTS: A total of 126 patients were included in the analysis. Mean age on date of operation was 66.2 (SD 12.2) years and 49 (38.9%) were female. A lower MET score was associated with a statistically significant lower time-dependent risk of hospital discharge (i.e. longer hospital stay) when adjusted for covariates (HR 0.224; 95% CI 0.077ā€“0.652; pā€‰=ā€‰0.006). Older age (adjusted HR 0.531; 95% CI 0.332ā€“0.848; pā€‰=ā€‰0.008) and postoperative complications (adjusted HR 0.503; 95% CI 0.323ā€“0.848; pā€‰=ā€‰0.002) were also found to be associated with longer hospital stay. Other comorbid conditions, BMI, disease staging and 30-day all-cause mortality were statistically insignificant. CONCLUSION: A lower MET score in this cohort of patients was associated with a longer hospital stay length following radical cystectomy with urinary diversion. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11255-021-02813-x

    Lightweight physiologic sensor performance during pre-hospital care delivered by ambulance clinicians

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    Acknowledgments We would like to extend our thanks to the Scottish Ambulance Service for granting us permission to undertake this research. We would also like to thank the ambulance clinicians who took part, and the patients. We also recognise the non-financial support given to us by the developers of the RESpeck sensor (University of Edinburgh). The research described here was supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.Peer reviewedPublisher PD

    Staging of schizophrenia with the use of PANSS: an international multi-center study

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    Introduction: A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. Methods: Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 Ā± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. Results: Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified &gt;85% of patients. Discussion: This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time

    Staging of Schizophrenia with the Use of PANSS: An International Multi-Center Study

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    Introduction: A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. Methods: Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 Ā± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. Results: Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified &gt;85% of patients. Discussion: This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time. Ā© 2019 The Author(s) 2019. Published by Oxford University Press on behalf of CINP

    Staging of Schizophrenia With the Use of PANSS: An International Multi-Center Study

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    INTRODUCTION: A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. METHODS: Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21ā€‰Ā±ā€‰11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. RESULTS: Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients. DISCUSSION: This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time
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