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  1. Article ; Online: A systematic review of cardiac surgery clinical prediction models that include intra-operative variables.

    Jones, Ceri / Taylor, Marcus / Sperrin, Matthew / Grant, Stuart W

    Perfusion

    2024  , Page(s) 2676591241237758

    Abstract: Background: Most cardiac surgery clinical prediction models (CPMs) are developed using pre-operative variables to predict post-operative outcomes. Some CPMs are developed with intra-operative variables, but none are widely used. The objective of this ... ...

    Abstract Background: Most cardiac surgery clinical prediction models (CPMs) are developed using pre-operative variables to predict post-operative outcomes. Some CPMs are developed with intra-operative variables, but none are widely used. The objective of this systematic review was to identify CPMs with intra-operative variables that predict short-term outcomes following adult cardiac surgery.
    Methods: Ovid MEDLINE and EMBASE databases were searched from inception to December 2022, for studies developing a CPM with at least one intra-operative variable. Data were extracted using a critical appraisal framework and bias assessment tool. Model performance was analysed using discrimination and calibration measures.
    Results: A total of 24 models were identified. Frequent predicted outcomes were acute kidney injury (9/24 studies) and peri-operative mortality (6/24 studies). Frequent pre-operative variables were age (18/24 studies) and creatinine/eGFR (18/24 studies). Common intra-operative variables were cardiopulmonary bypass time (16/24 studies) and transfusion (13/24 studies). Model discrimination was acceptable for all internally validated models (AUC 0.69-0.91). Calibration was poor (15/24 studies) or unreported (8/24 studies). Most CPMs were at a high or indeterminate risk of bias (23/24 models). The added value of intra-operative variables was assessed in six studies with statistically significantly improved discrimination demonstrated in two.
    Conclusion: Weak reporting and methodological limitations may restrict wider applicability and adoption of existing CPMs that include intra-operative variables. There is some evidence that CPM discrimination is improved with the addition of intra-operative variables. Further work is required to understand the role of intra-operative CPMs in the management of cardiac surgery patients.
    Language English
    Publishing date 2024-04-22
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 645038-6
    ISSN 1477-111X ; 0267-6591
    ISSN (online) 1477-111X
    ISSN 0267-6591
    DOI 10.1177/02676591241237758
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  2. Article ; Online: Healthcare utilisation in patients with long-term conditions during the COVID-19 pandemic: a population-based observational study of all patients across Greater Manchester, UK.

    Sammut-Powell, Camilla / Williams, Richard / Sperrin, Matthew / Thomas, Owain / Peek, N / Grant, Stuart W

    BMJ open

    2023  Volume 13, Issue 7, Page(s) e066873

    Abstract: Objectives: Data on population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. We describe primary and secondary HCU stratified by long-term conditions (LTCs) and deprivation, during the ... ...

    Abstract Objectives: Data on population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. We describe primary and secondary HCU stratified by long-term conditions (LTCs) and deprivation, during the first 19 months of COVID-19 pandemic across a large urban area in the UK.
    Design: A retrospective, observational study.
    Setting: All primary and secondary care organisations that contributed to the Greater Manchester Care Record throughout 30 December 2019 to 1 August 2021.
    Participants: 3 225 169 patients who were registered with or attended a National Health Service primary or secondary care service during the study period.
    Primary outcomes: Primary care HCU (incident prescribing and recording of healthcare information) and secondary care HCU (planned and unplanned admissions) were assessed.
    Results: The first national lockdown was associated with reductions in all primary HCU measures, ranging from 24.7% (24.0% to 25.5%) for incident prescribing to 84.9% (84.2% to 85.5%) for cholesterol monitoring. Secondary HCU also dropped significantly for planned (47.4% (42.9% to 51.5%)) and unplanned admissions (35.3% (28.3% to 41.6%)). Only secondary care had significant reductions in HCU during the second national lockdown. Primary HCU measures had not recovered to prepandemic levels by the end of the study. The secondary admission rate ratio between multi-morbid patients and those without LTCs increased during the first lockdown by a factor of 2.40 (2.05 to 2.82; p<0.001) for planned admissions and 1.25 (1.07 to 1.47; p=0.006) for unplanned admissions. No significant changes in this ratio were observed in primary HCU.
    Conclusion: Major changes in primary and secondary HCU were observed during the COVID-19 pandemic. Secondary HCU reduced more in those without LTCs and the ratio of utilisation between patients from the most and least deprived areas increased for the majority of HCU measures. Overall primary and secondary care HCU for some LTC groups had not returned to prepandemic levels by the end of the study.
    MeSH term(s) Humans ; Retrospective Studies ; State Medicine ; Pandemics ; COVID-19/epidemiology ; Communicable Disease Control ; Delivery of Health Care ; Patient Acceptance of Health Care ; United Kingdom/epidemiology
    Language English
    Publishing date 2023-07-07
    Publishing country England
    Document type Observational Study ; Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2599832-8
    ISSN 2044-6055 ; 2044-6055
    ISSN (online) 2044-6055
    ISSN 2044-6055
    DOI 10.1136/bmjopen-2022-066873
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Prediction models for diagnosis and prognosis in Covid-19.

    Sperrin, Matthew / Grant, Stuart W / Peek, Niels

    BMJ (Clinical research ed.)

    2020  Volume 369, Page(s) m1464

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnosis ; Forecasting ; Humans ; Models, Statistical ; Pandemics ; Pneumonia, Viral ; Prognosis ; SARS-CoV-2
    Keywords covid19
    Language English
    Publishing date 2020-04-14
    Publishing country England
    Document type Editorial ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 1362901-3
    ISSN 1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    ISSN (online) 1756-1833
    ISSN 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    DOI 10.1136/bmj.m1464
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online: Prediction models for diagnosis and prognosis in Covid-19

    Sperrin, Matthew / Grant, Stuart W / Peek, Niels

    2020  

    Keywords EDITORIALS ; covid19
    Language English
    Publishing date 2020-04-14 06:36:05.0
    Publisher BMJ Publishing Group Ltd
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Prediction models for diagnosis and prognosis in Covid-19

    Sperrin, Matthew / Grant, Stuart W / Peek, Niels

    BMJ

    2020  , Page(s) m1464

    Keywords covid19
    Language English
    Publisher BMJ
    Publishing country uk
    Document type Article ; Online
    ZDB-ID 1362901-3
    ISSN 1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    ISSN (online) 1756-1833
    ISSN 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    DOI 10.1136/bmj.m1464
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: HEALTHCARE UTILISATION IN PATIENTS WITH LONG-TERM CONDITIONS DURING THE COVID-19 PANDEMIC: A POPULATION BASED STUDY ACROSS GREATER MANCHESTER, UK

    Sammut-Powell, Camilla / Williams, Richard / Sperrin, Matthew / Thomas, Owain / Peek, Niels / Grant, Stuart W

    medRxiv

    Abstract: Background: The COVID-19 pandemic has placed an unprecedented demand on global healthcare resources. Data on whole population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. Aim: To describe ... ...

    Abstract Background: The COVID-19 pandemic has placed an unprecedented demand on global healthcare resources. Data on whole population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. Aim: To describe primary and secondary HCU stratified by LTCs and deprivation, during the first 19 months of COVID-19 pandemic across a large urban area in the United Kingdom. Methods: Observational HCU data between 30th-December-2019 and 1st-August-2021 were extracted from the Greater Manchester Care Record. Primary care HCU (incident prescribing and recording of healthcare information) and secondary care HCU (planned and unplanned admissions) were assessed. Results: The first national lockdown was associated with reductions in all primary HCU measures, ranging from 24.7% (24.0% to 25.5%) for incident prescribing to 84.9% (84.2% to 85.5%) for cholesterol monitoring. Secondary HCU also dropped significantly for planned (47% (42.9% to 51.5%)) and unplanned admissions (35.0% (28.3% to 41.6%)). Only secondary care had significant reductions in HCU during the second national lockdown. Primary HCU measures had not recovered to pre-pandemic levels by the end of the study. The secondary admission rate ratio between multi-morbid patients and those without LTCs increased during the first lockdown by a factor of 2.4 (2.0 to 2.9;p<0.001) for planned admissions and by 1.3 (1.1 to 1.5;p=0.006) for unplanned admissions. No significant changes in this ratio were observed in primary HCU. Different patterns in secondary care HCU were observed by LTC group. Conclusion: Major changes in primary and secondary HCU have been observed during the COVID-19 pandemic. Secondary HCU reduced more in those without LTCs and the ratio of utilisation between the most and least deprived increased for the majority of HCU measures. Overall primary HCU measures and secondary care HCU for some LTC groups had not returned to pre-pandemic levels by the end of the study.
    Keywords covid19
    Language English
    Publishing date 2022-06-14
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2022.06.09.22276232
    Database COVID19

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  8. Article ; Online: Infection-related complications after common infection in association with new antibiotic prescribing in primary care: retrospective cohort study using linked electronic health records.

    van Bodegraven, Birgitta / Palin, Victoria / Mistry, Chirag / Sperrin, Matthew / White, Andrew / Welfare, William / Ashcroft, Darren M / van Staa, Tjeerd Pieter

    BMJ open

    2021  Volume 11, Issue 1, Page(s) e041218

    Abstract: Objective: Determine the association of incident antibiotic prescribing levels for common infections with infection-related complications and hospitalisations by comparing high with low prescribing general practitioner practices.: Design retrospective ...

    Abstract Objective: Determine the association of incident antibiotic prescribing levels for common infections with infection-related complications and hospitalisations by comparing high with low prescribing general practitioner practices.
    Design retrospective cohort study: Retrospective cohort study.
    Data source: UK primary care records from the Clinical Practice Research Datalink (CPRD GOLD) and SAIL Databank (SAIL) linked with Hospital Episode Statistics (HES) data, including 546 CPRD, 346 CPRD-HES and 338 SAIL-HES practices.
    Exposures: Initial general practice visit for one of six common infections and the proportion of antibiotic prescribing in each practice.
    Main outcome measures: Incidence of infection-related complications (as recorded in general practice) or infection-related hospital admission within 30 days after consultation for a common infection.
    Results: A practice with 10.4% higher antibiotic prescribing (the IQR) was associated with a 5.7% lower rate of infection-related hospital admissions (adjusted analysis, 95% CI 3.3% to 8.0%). The association varied by infection with larger associations in hospital admissions with lower respiratory tract infection (16.1%; 95% CI 12.4% to 19.7%) and urinary tract infection (14.7%; 95% CI 7.6% to 21.1%) and smaller association in hospital admissions for upper respiratory tract infection (6.5%; 95% CI 3.5% to 9.5%) The association of antibiotic prescribing levels and hospital admission was largest in patients aged 18-39 years (8.6%; 95% CI 4.0% to 13.0%) and smallest in the elderly aged 75+ years (0.3%; 95% CI -3.4% to 3.9%).
    Conclusions: There is an association between lower levels of practice level antibiotic prescribing and higher infection-related hospital admissions. Indiscriminately reducing antibiotic prescribing may lead to harm. Greater focus is needed to optimise antibiotic use by reducing inappropriate antibiotic prescribing and better targeting antibiotics to patients at high risk of infection-related complications.
    MeSH term(s) Adolescent ; Adult ; Aged ; Anti-Bacterial Agents/therapeutic use ; Electronic Health Records ; Humans ; Inappropriate Prescribing ; Practice Patterns, Physicians' ; Primary Health Care ; Respiratory Tract Infections/drug therapy ; Respiratory Tract Infections/epidemiology ; Retrospective Studies ; Young Adult
    Chemical Substances Anti-Bacterial Agents
    Language English
    Publishing date 2021-01-15
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2599832-8
    ISSN 2044-6055 ; 2044-6055
    ISSN (online) 2044-6055
    ISSN 2044-6055
    DOI 10.1136/bmjopen-2020-041218
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  9. Article ; Online: Invitation strategies and participation in a community-based lung cancer screening programme located in areas of high socioeconomic deprivation.

    Goodley, Patrick / Balata, Haval / Alonso, Alberto / Brockelsby, Christopher / Conroy, Matthew / Cooper-Moss, Nicola / Craig, Christopher / Evison, Matthew / Hewitt, Kath / Higgins, Coral / Johnson, William / Lyons, Judith / Merchant, Zoe / Rowlands, Ailsa / Sharman, Anna / Sinnott, Nicola / Sperrin, Matthew / Booton, Richard / Crosbie, Philip A J

    Thorax

    2023  Volume 79, Issue 1, Page(s) 58–67

    Abstract: Introduction: Although lung cancer screening is being implemented in the UK, there is uncertainty about the optimal invitation strategy. Here, we report participation in a community screening programme following a population-based invitation approach, ... ...

    Abstract Introduction: Although lung cancer screening is being implemented in the UK, there is uncertainty about the optimal invitation strategy. Here, we report participation in a community screening programme following a population-based invitation approach, examine factors associated with participation, and compare outcomes with hypothetical targeted invitations.
    Methods: Letters were sent to all individuals (age 55-80) registered with a general practice (n=35 practices) in North and East Manchester, inviting ever-smokers to attend a Lung Health Check (LHC). Attendees at higher risk (PLCO
    Results: Letters were sent to 35 899 individuals, 71% from the most socioeconomically deprived quintile. Estimated response rate in ever-smokers was 49%; a lower response rate was associated with younger age, male sex, and primary care recorded current smoking status (
    Discussion: Using a population-based invitation strategy, in an area of high socioeconomic deprivation, is effective and may increase screening accessibility. Due to limitations in primary care records, targeted approaches should incorporate historical smoking codes and individuals with absent smoking records.
    MeSH term(s) Humans ; Male ; Middle Aged ; Aged ; Aged, 80 and over ; Early Detection of Cancer ; Lung Neoplasms/diagnostic imaging ; Lung Neoplasms/epidemiology ; Smokers ; Smoking/epidemiology ; Mass Screening ; Socioeconomic Factors
    Language English
    Publishing date 2023-12-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 204353-1
    ISSN 1468-3296 ; 0040-6376
    ISSN (online) 1468-3296
    ISSN 0040-6376
    DOI 10.1136/thorax-2023-220001
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  10. Article ; Online: Multivariable and Bayesian Network Analysis of Outcome Predictors in Acute Aneurysmal Subarachnoid Hemorrhage: Review of a Pure Surgical Series in the Post-International Subarachnoid Aneurysm Trial Era.

    Zador, Zsolt / Huang, Wendy / Sperrin, Matthew / Lawton, Michael T

    Operative neurosurgery (Hagerstown, Md.)

    2017  Volume 14, Issue 6, Page(s) 603–610

    Abstract: Background: Following the International Subarachnoid Aneurysm Trial (ISAT), evolving treatment modalities for acute aneurysmal subarachnoid hemorrhage (aSAH) has changed the case mix of patients undergoing urgent surgical clipping.: Objective: To ... ...

    Abstract Background: Following the International Subarachnoid Aneurysm Trial (ISAT), evolving treatment modalities for acute aneurysmal subarachnoid hemorrhage (aSAH) has changed the case mix of patients undergoing urgent surgical clipping.
    Objective: To update our knowledge on outcome predictors by analyzing admission parameters in a pure surgical series using variable importance ranking and machine learning.
    Methods: We reviewed a single surgeon's case series of 226 patients suffering from aSAH treated with urgent surgical clipping. Predictions were made using logistic regression models, and predictive performance was assessed using areas under the receiver operating curve (AUC). We established variable importance ranking using partial Nagelkerke R2 scores. Probabilistic associations between variables were depicted using Bayesian networks, a method of machine learning.
    Results: Importance ranking showed that World Federation of Neurosurgical Societies (WFNS) grade and age were the most influential outcome prognosticators. Inclusion of only these 2 predictors was sufficient to maintain model performance compared to when all variables were considered (AUC = 0.8222, 95% confidence interval (CI): 0.7646-0.88 vs 0.8218, 95% CI: 0.7616-0.8821, respectively, DeLong's P = .992). Bayesian networks showed that age and WFNS grade were associated with several variables such as laboratory results and cardiorespiratory parameters.
    Conclusion: Our study is the first to report early outcomes and formal predictor importance ranking following aSAH in a post-ISAT surgical case series. Models showed good predictive power with fewer relevant predictors than in similar size series. Bayesian networks proved to be a powerful tool in visualizing the widespread association of the 2 key predictors with admission variables, explaining their importance and demonstrating the potential for hypothesis generation.
    MeSH term(s) Acute Disease ; Adult ; Aged ; Aneurysm, Ruptured/complications ; Area Under Curve ; Bayes Theorem ; Brain Damage, Chronic/etiology ; Female ; Glasgow Outcome Scale ; Humans ; Intracranial Aneurysm/complications ; Logistic Models ; Machine Learning ; Male ; Middle Aged ; Pilot Projects ; ROC Curve ; Retrospective Studies ; Subarachnoid Hemorrhage/etiology ; Subarachnoid Hemorrhage/surgery ; Treatment Outcome
    Language English
    Publishing date 2017-10-03
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2767575-0
    ISSN 2332-4260 ; 2332-4252
    ISSN (online) 2332-4260
    ISSN 2332-4252
    DOI 10.1093/ons/opx163
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