Author
David Prytherch
Other affiliations: St Mary's Hospital, University of Warwick, Queen Alexandra Hospital ...read more
Bio: David Prytherch is an academic researcher from University of Portsmouth. The author has contributed to research in topics: Early warning score & Vital signs. The author has an hindex of 37, co-authored 113 publications receiving 6282 citations. Previous affiliations of David Prytherch include St Mary's Hospital & University of Warwick.
Papers published on a yearly basis
Papers
More filters
TL;DR: News has a greater ability to discriminate patients at risk of the combined outcome of cardiac arrest, unanticipated ICU admission or death within 24h of a NEWS value than 33 other EWSs.
749 citations
TL;DR: There is a need for an accurate measure of surgical outcomes so that hospitals and surgeons can be compared properly regardless of case mix and POSSUM (Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity) provides a more accurate prediction of mortality.
Abstract: Background
There is a need for an accurate measure of surgical outcomes so that hospitals and surgeons can be compared properly regardless of case mix. POSSUM (Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity) uses a physiological score and an operative severity score to calculate risks of mortality and morbidity. In a previous small study it was found that Portsmouth POSSUM (P-POSSUM; a modification of the POSSUM system) provided a more accurate prediction of mortality.
Methods
Some 10 000 general surgical interventions (excluding paediatric and day cases) were studied prospectively between August 1993 and November 1995. The POSSUM mortality equation was applied to the full 10 000 surgical episodes. The 10 000 patients were arranged in chronological order and the first 2500 were used as a training set to produce the modified P-POSSUM predictor equation. This was then applied prospectively to the remaining 7500 patients arranged chronologically in five groups of 1500.
Results
The original POSSUM logistic regression equation for mortality overpredicts the overall risk of death by more than twofold and the risk of death for patients at lowest risk (5 per cent or less) by more than sevenfold. The P-POSSUM equation produced a very close fit with the observed in-hospital mortality.
Conclusion
P-POSSUM provides an accurate method for comparative surgical audit. © 1998 British Journal of Surgery Society Ltd
647 citations
TL;DR: The data confirm antecedents are common before death, cardiac arrest, and unanticipated ICU admission, and the study shows differences in patterns of primary events, the provision of ICU/HDU beds and resuscitation teams, between the UK and ANZ.
608 citations
TL;DR: A validated, paper-based, aggregate weighted track and trigger system (AWTTS) that could serve as a template for a national early warning score (EWS) for the detection of patient deterioration is developed and demonstrated that its performance for predicting mortality (within a range of timescales) is superior to all other published AWTTSs.
495 citations
TL;DR: The previously published POSSUM predictor equation for mortality performed badly when tested using a standard test of goodness of fit for logistic regression and must be modified.
Abstract: POSSUM (Physiological and Operative Severity Score for the enUmeration of Morbidity and mortality) has been studied as a possible surgical audit system for a 9-month interval using a sample of 28 per cent of the general surgical workload. Mortality or survival was analysed as an endpoint. In this sample the published POSSUM predictor equation for mortality overpredicted deaths by a factor of more than two. The bulk of the overprediction occurred in the group at lowest risk (predicted mortality 10 per cent or less), in which death was overpredicted by a factor of six. This is the most important group for audit purposes since it contains the majority of surgical patients and is composed of fit patients undergoing minor surgery. The published predictor equation for mortality returns a minimum predicted mortality of 1.08 per cent, clearly far higher than that expected for a fit patient having minor surgery. Logistic regression was done on a set of 1485 surgical episodes to generate a local predictor equation for mortality. This process gave a predictor equation that fitted well with the observed mortality rate and gave a minimum predicted risk of mortality of 0.20 per cent. The previously published POSSUM predictor equation for mortality performed badly when tested using a standard test of goodness of fit for logistic regression and must be modified.
367 citations
Cited by
More filters
TL;DR: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.
Abstract: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee
5,739 citations
TL;DR: The Statistical Update represents the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA's My Life Check - Life’s Simple 7, which include core health behaviors and health factors that contribute to cardiovascular health.
Abstract: Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter.
Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter.
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …
5,102 citations
TL;DR: This year's edition of the Statistical Update includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association’s 2020 Impact Goals.
Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovas...
5,078 citations
01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
4,408 citations
TL;DR: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascul...
Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascul...
3,034 citations