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Validation of shock index for predicting mortality in older patients with dengue fever. Aging Clin Exp Res 2021; 33:635-640. [PMID: 32399869 DOI: 10.1007/s40520-020-01563-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 04/11/2020] [Indexed: 10/24/2022]
Abstract
BACKGROUND Older adults have a higher mortality for dengue fever (DF). However, the best method for predicting mortality is still unclear. AIMS We conducted this study to evaluate the shock index (SI) for this issue. METHODS A retrospective case-control study was conducted by recruiting older patients (≥ 65 years old) with DF who visited the study hospital in southern Taiwan during the 2015 DF outbreak. Demographic data, vital signs, past histories, decision groups, complications, and mortality were included in the analyses. We evaluated the accuracy of SI ≥ 1 for predicting 30-day mortality in this population. RESULTS A total of 626 patients with a mean age of 74.1 years and nearly equal sex distribution were recruited. The mean of SI (± standard deviation [SD]) was 0.6 (± 0.2) and patients with a SI ≥ 1 accounted for 3.5% of the total patients. Logistic regression showed that patients with SI ≥ 1 had a higher mortality than those with SI < 1 (odds ratio: 8.49; 95% confidence interval: 1.76-17.92). The area under the receiver-operating characteristic was 0.76, and the Hosmer-Lemeshow goodness of fit test was 0.48. The SI ≥ 1 had a sensitivity, specificity, positive predictive value, and negative predictive value of 14.8%, 97.0%, 18.2%, and 96.2% for predicting mortality. CONCLUSIONS The SI ≥ 1 is an easy tool that can be potentially used to predict 30-day mortality in older DF patients, especially in DF outbreak. It has a high specificity and negative predictive value for excluding patients with high-risk mortality.
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Peng L, Chen Z, Chen T, Lei L, Long Z, Liu M, Deng Q, Yuan H, Zou G, Wan L, Wang C, Peng H, Shi Y, Wang P, Peng Y, Wang S, He L, Xie Y, Tang Z, Wan N, Gong Y, Hou X, Shen L, Xia K, Li J, Chen C, Zhang Z, Qiu R, Tang B, Jiang H. Prediction of the Age at Onset of Spinocerebellar Ataxia Type 3 with Machine Learning. Mov Disord 2020; 36:216-224. [PMID: 32991004 DOI: 10.1002/mds.28311] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 08/31/2020] [Accepted: 09/03/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND In polyglutamine (polyQ) disease, the investigation of the prediction of a patient's age at onset (AAO) facilitates the development of disease-modifying intervention and underpins the delay of disease onset and progression. Few polyQ disease studies have evaluated AAO predicted by machine-learning algorithms and linear regression methods. OBJECTIVE The objective of this study was to develop a machine-learning model for AAO prediction in the largest spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) population from mainland China. METHODS In this observational study, we introduced an innovative approach by systematically comparing the performance of 7 machine-learning algorithms with linear regression to explore AAO prediction in SCA3/MJD using CAG expansions of 10 polyQ-related genes, sex, and parental origin. RESULTS Similar prediction performance of testing set and training set in each models were identified and few overfitting of training data was observed. Overall, the machine-learning-based XGBoost model exhibited the most favorable performance in AAO prediction over the traditional linear regression method and other 6 machine-learning algorithms for the training set and testing set. The optimal XGBoost model achieved mean absolute error, root mean square error, and median absolute error of 5.56, 7.13, 4.15 years, respectively, in testing set 1, with mean absolute error (4.78 years), root mean square error (6.31 years), and median absolute error (3.59 years) in testing set 2. CONCLUSION Machine-learning algorithms can be used to predict AAO in patients with SCA3/MJD. The optimal XGBoost algorithm can provide a good reference for the establishment and optimization of prediction models for SCA3/MJD or other polyQ diseases. © 2020 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Linliu Peng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhao Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Tiankai Chen
- School of Computer Science and Engineering, Central South University, Changsha, China
| | - Lijing Lei
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhe Long
- Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Mingjie Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qi Deng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Hongyu Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Guangdong Zou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Linlin Wan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Chunrong Wang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China
| | - Huirong Peng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yuting Shi
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Puzhi Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yun Peng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Shang Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Lang He
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yue Xie
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhichao Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Na Wan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yiqing Gong
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xuan Hou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Kun Xia
- Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China.,Hunan Key Laboratory of Medical Genetics, Central South University, Changsha, China
| | - Jinchen Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China.,Hunan Key Laboratory of Medical Genetics, Central South University, Changsha, China
| | - Chao Chen
- Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China.,Hunan Key Laboratory of Medical Genetics, Central South University, Changsha, China
| | - Zuping Zhang
- School of Computer Science and Engineering, Central South University, Changsha, China
| | - Rong Qiu
- School of Computer Science and Engineering, Central South University, Changsha, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Hong Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
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Al Aseri Z, Al Ageel M, Binkharfi M. The use of the shock index to predict hemodynamic collapse in hypotensive sepsis patients: A cross-sectional analysis. Saudi J Anaesth 2020; 14:192-199. [PMID: 32317874 PMCID: PMC7164438 DOI: 10.4103/sja.sja_780_19] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 01/09/2020] [Indexed: 12/29/2022] Open
Abstract
Objectives: Septic shock, defined as sepsis with hypotension not responding to fluid resuscitation or requiring vasopressor support, results in the worst outcomes in sepsis patients. This subtype of the patient is often difficult to detect. The shock index (SI) has demonstrated the potential for predicting hemodynamic compromise and collapse and predicting patient outcomes in multiple medical and surgical settings. In our study, we assessed the utility of the SI as a hemodynamic screening tool to identify patients likely to fail to respond to fluids and ultimately to be diagnosed with septic shock. Methodology: A single-center cross-sectional analysis of patients presenting with hypotension and septicemia over 1 year. The study was conducted using the electronic medical records of the emergency department patients presenting to King Saud University Medical City. The charts were reviewed from 2 May 2015 to 24 April 2016 using the local medical registry. The study was approved by the hospital institutional review board (IRB). Data extraction was performed using a standardized form. Results: The area under the curve was 0.77 (P < 0.001) for the prediction of hemodynamic collapse. An initial SI ≥0.875 had a sensitivity of 81% and a specificity of 72% for the identification of patients in whom fluid resuscitation would fail. Conclusions: Based on our findings, we found that the SI was a reliable screening tool for the identification of hypotensive patients with sepsis who would ultimately be diagnosed with septic shock.
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Affiliation(s)
- Zohair Al Aseri
- Emergency Medicine and Critical Care Departments, College of Medicine, King Saud University, 11472, Riyadh, Saudi Arabia
| | - Mohammed Al Ageel
- Emergency Medicine and Critical Care Departments, College of Medicine, King Saud University, 11472, Riyadh, Saudi Arabia
| | - Mohammed Binkharfi
- Emergency Medicine and Critical Care Departments, College of Medicine, King Saud University, 11472, Riyadh, Saudi Arabia
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Myint PK, Sheng S, Xian Y, Matsouaka RA, Reeves MJ, Saver JL, Bhatt DL, Fonarow GC, Schwamm LH, Smith EE. Shock Index Predicts Patient-Related Clinical Outcomes in Stroke. J Am Heart Assoc 2019; 7:e007581. [PMID: 30371191 PMCID: PMC6222962 DOI: 10.1161/jaha.117.007581] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background The prognostic value of shock index (SI), heart rate divided by systolic blood pressure, in stroke for clinical outcomes other than mortality is not well understood. Methods and Results We examined the Get With The Guidelines–Stroke (GWTG‐Stroke) data to explore the usefulness of SI in predicting in‐hospital outcomes in 425 808 acute stroke cases (mean age: 71.0±14.5 years; 48.8% male; 89.7% ischemic stroke and 10.3% intracerebral hemorrhage) admitted between October 2012 and March 2015. Compared with patients with SI of 0.5 to 0.7, patients with SI >0.7 (13.6% of the sample) had worse outcomes, with adjusted odds ratios of 2.00 (95% confidence interval [CI], 1.92–2.08) for in‐hospital mortality, 1.46 (95% CI, 1.43–1.49) for longer length of hospital stay >4 days, 1.50 (95% CI, 1.47–1.54) for discharge destination other than home, 1.41 (95% CI, 1.38–1.45) for inability to ambulate independently at discharge, and 1.52 (95% CI, 1.47–1.57) for modified Rankin Scale score of 3 to 6 at discharge. Results were similar when analyses were confined to those with available National Institutes of Health Stroke Scale (NIHSS) or within individual stroke subtypes or when SI was additionally included in the models with or without blood pressure components. Every 0.1 increase in SI >0.5 was associated with significantly worse outcomes in linear spline models. The addition of SI to existing GWTG‐Stroke mortality prediction models without NIHSS demonstrated modest improvement, but little to no improvement was noted in models with NIHSS. Conclusions SI calculated at the point of care may be a useful prognostic indicator to identify those with high risk of poor outcomes in acute stroke, especially in hospitals with limited experience with NIHSS assessment.
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Affiliation(s)
- Phyo Kyaw Myint
- Institute of Applied Health SciencesSchool of Medicine, Medical Sciences & NutritionUniversity of AberdeenUnited Kingdom
| | - Shubin Sheng
- Duke Clinical Research InstituteDuke University School of MedicineDurhamNC
| | - Ying Xian
- Duke Clinical Research InstituteDuke University School of MedicineDurhamNC
- Department of NeurologyDuke University Medical CenterDurhamNC
| | - Roland A. Matsouaka
- Duke Clinical Research InstituteDuke University School of MedicineDurhamNC
- Department of Biostatistics and BioinformaticsDuke UniversityDurhamNC
| | - Mathew J. Reeves
- Department of Epidemiology and BiostatisticsMichigan State UniversityMichiganMI
| | - Jeffrey L. Saver
- Stroke ProgramDepartment of NeurologyDavid Geffen School of Medicine at UCLALos AngelesCA
| | - Deepak L. Bhatt
- Brigham and Women's Hospital Heart & Vascular CenterHarvard Medical SchoolHarvard UniversityBostonMA
| | - Gregg C. Fonarow
- Division of CardiologyDavid Geffen School of Medicine at UCLALos AngelesCA
| | - Lee H. Schwamm
- Department of Neurology, Stroke ServiceMassachusetts General HospitalBostonMA
| | - Eric E. Smith
- Calgary Stroke Programme & Department of Clinical NeurosciencesUniversity of CalgaryCalgaryCanada
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Baumert M, Linz D, Stone K, McEvoy RD, Cummings S, Redline S, Mehra R, Immanuel S. Mean nocturnal respiratory rate predicts cardiovascular and all-cause mortality in community-dwelling older men and women. Eur Respir J 2019; 54:13993003.02175-2018. [PMID: 31151958 DOI: 10.1183/13993003.02175-2018] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 04/21/2019] [Indexed: 11/05/2022]
Abstract
Respiratory frequency (f R) predicts in-hospital and short-term mortality in patients with a variety of pathophysiological conditions, but its predictive value for long-term cardiovascular and all-cause mortality in the general population is unknown. Here, we investigated the relationship between mean nocturnal f R and mortality in community-dwelling older men and women.We measured mean nocturnal f R during sleep from overnight polysomnography in 2686 men participating in the Osteoporotic Fractures in Men Study (MrOS) Sleep study and 406 women participating in the Study of Osteoporotic Fractures (SOF) to investigate the relationship between mean nocturnal f R and long-term cardiovascular and all-cause mortality.166 (6.1%) men in the MrOS cohort (8.9±2.6 years' follow-up) and 46 (11.2%) women in the SOF cohort (6.4±1.6 years' follow-up) died from cardiovascular disease. All-cause mortality was 51.2% and 26.1% during 13.7±3.7 and 6.4±1.6 years' follow-up in the MrOS Sleep study and the SOF cohorts, respectively. Multivariable Cox regression analysis adjusted for significant covariates demonstrated that f R dichotomised at 16 breaths·min-1 was independently associated with cardiovascular mortality (MrOS: hazard ratio (HR) 1.57, 95% CI 1.14-2.15; p=0.005; SOF: HR 2.58, 95% CI 1.41-4.76; p=0.002) and all-cause mortality (MrOS: HR 1.18, 95% CI 1.04-1.32; p=0.007; SOF: HR 1.50, 95% CI 1.02-2.20; p=0.04).In community-dwelling older men and women, polysomnography-derived mean nocturnal f R ≥16 breaths·min-1 is an independent predictor of long-term cardiovascular and all-cause mortality. Whether nocturnal mean f R can be used as a risk marker warrants further prospective studies.
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Affiliation(s)
- Mathias Baumert
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, Australia
| | - Dominik Linz
- Center for Heart Rhythm Disorders (CHRD), South Australian Health and Medical Research Institute (SAHMRI), University of Adelaide and Royal Adelaide Hospital, Adelaide, Australia
| | - Katie Stone
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - R Doug McEvoy
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, and Sleep Health Service, Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, Australia
| | - Steve Cummings
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Dept of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Reena Mehra
- Center of Sleep Disorders, Neurologic Institute, Respiratory Institute, Heart and Vascular Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Sarah Immanuel
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, Australia.,College of Medicine and Public Health and Flinders Digital Health Research Centre, Flinders University, Adelaide, Australia
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6
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Chung JY, Hsu CC, Chen JH, Chen WL, Lin HJ, Guo HR, Huang CC. Shock index predicted mortality in geriatric patients with influenza in the emergency department. Am J Emerg Med 2019; 37:391-394. [PMID: 29866414 DOI: 10.1016/j.ajem.2018.05.059] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Revised: 05/20/2018] [Accepted: 05/28/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The shock index is a rapid and simple tool used to predict mortality in patients with acute illnesses including sepsis, multiple trauma, and postpartum hemorrhage. However, its ability to predict mortality in geriatric patients with influenza in the emergency department (ED) remains unclear. This study was conducted to clarify this issue. METHODS We conducted a retrospective case-control study, recruiting geriatric patients (≥ 65 years) with influenza visiting the ED of a medical center between January 01, 2010 and December 31, 2015. Demographic data, vital signs, shock index, past histories, subtypes of influenza, and outcomes were included for the analysis. We investigated the association between shock index ≥1 and 30-day mortality. RESULTS In total, 409 geriatric ED patients with mean age of 79.5 years and nearly equal sex ratio were recruited. The mean shock index ± standard deviation was 0.7 ± 0.22 and shock index ≥1 was accounted for in 7.1% of the total patients. Logistic regression showed that shock index ≥1 predicted mortality (odds ratio: 6.80; 95% confidence interval: 2.39-19.39). The area under the receiver operating characteristic was 0.62 and the result of the Hosmer-Lemeshow goodness-of-fit test was 0.23. The sensitivity, specificity, positive predictive value, and negative predictive value of a shock index ≥1 were 30.0%, 94.1%, 20.0%, and 96.4%. CONCLUSIONS A shock index ≥1 has a high specificity, negative predictive value, and good reliability to predict 30-day mortality in geriatric ED patients with influenza.
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Affiliation(s)
- Jui-Yuan Chung
- Department of Emergency Medicine, Cathay General Hospital, Taipei, Taiwan
| | - Chien-Chin Hsu
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan; Department of Biotechnology, Southern Taiwan University of Science and Technology, Tainan, Taiwan
| | - Jiann-Hwa Chen
- Department of Emergency Medicine, Cathay General Hospital, Taipei, Taiwan; Fu Jen Catholic University School of Medicine, Taipei, Taiwan
| | - Wei-Lung Chen
- Department of Emergency Medicine, Cathay General Hospital, Taipei, Taiwan; Fu Jen Catholic University School of Medicine, Taipei, Taiwan
| | - Hung-Jung Lin
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan; Department of Biotechnology, Southern Taiwan University of Science and Technology, Tainan, Taiwan; Department of Emergency Medicine, Taipei Medical University, Taipei, Taiwan
| | - How-Ran Guo
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Occupational and Environmental Medicine, National Cheng Kung University Hospital, Tainan, Taiwan.
| | - Chien-Cheng Huang
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan; Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Bachelor Program of Senior Service, Southern Taiwan University of Science and Technology, Tainan, Taiwan; Department of Geriatrics and Gerontology, Chi-Mei Medical Center, Tainan, Taiwan; Department of Occupational Medicine, Chi-Mei Medical Center, Tainan, Taiwan.
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7
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Ablett AD, McCarthy K, Carter B, Pearce L, Stechman M, Moug S, Ceelen W, Hewitt J, Myint PK. A practical risk scale for predicting morbidity and mortality in the emergency general surgical setting: A prospective multi-center study. Int J Surg 2018; 60:236-244. [PMID: 30481611 DOI: 10.1016/j.ijsu.2018.11.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 10/30/2018] [Accepted: 11/19/2018] [Indexed: 11/18/2022]
Abstract
BACKGROUND Low albumin is a prognostic factor associated with poor surgical outcomes. We aimed to examine the predicative ability of easily obtainable point-of-care variables in combination, to derive a practical risk scale for predicting older adults at risk of poor outcomes on admission to the emergency general surgical setting. METHODS This is an international multi-center prospective cohort study conducted as part of the Older Persons Surgical Outcomes Collaboration (www.OPSOC.eu). The effect of having hypoalbuminemia (defined as albumin ≤3.5 g/dL) on selected outcomes was examined using fully adjusted multivariable models. In a subgroup of patients with hypoalbuminemia, we observed four risk characteristics (Male, Anemia, Low albumin, Eighty-five and over [MALE]). Subsequently, the impact of incremental increase in MALE score (each characteristic scoring 1 point (maximum score 4) on measured outcomes was assessed. RESULTS The cohort consisted of 1406 older patients with median (IQR) age of 76 (70-83) years. In fully adjusted models, hypoalbuminemia was significantly associated with undergoing emergency surgery (1.32 (95%CI 1.03-1.70); p = 0.03), 30-day mortality (4.23 (2.22-8.08); p < 0.001), 90-day mortality (3.36 (2.14-5.28); p < 0.001) (primary outcome), and increased hospital length of stay, irrespective of whether a patient received emergency surgical intervention. Every point increase in MALE score was associated with higher odds of mortality, with a MALE score of 4 being associated with 30-day mortality (adjusted OR(95% CI) = 33.38 (3.86-288.7); p = 0.001) and 90-day mortality (11.37 (3.85-33.59); p < 0.001) compared to the reference category of those with MALE score 0. CONCLUSIONS The easy to use and practical MALE risk score calculated at point of care identifies older adults at a greater risk of poor outcomes, thereby allowing clinicians to prioritize patients who may benefit from early comprehensive geriatric assessment in the emergency general surgical setting.
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Affiliation(s)
- A D Ablett
- Institute of Applied Health Sciences, University of Aberdeen & Aberdeen Royal Infirmary, NHS Grampian, United Kingdom
| | - K McCarthy
- Department of General Surgery, King's College London, United Kingdom
| | - B Carter
- Department of Biostatistics and Health Informatics, Institute of Psychology Psychiatry and Neuroscience, King's College London, United Kingdom
| | - L Pearce
- Department of General Surgery, Manchester Royal Infirmary, United Kingdom
| | - M Stechman
- Department of General Surgery, University Hospital of Wales, United Kingdom
| | - S Moug
- Department of General Surgery, Royal Alexandra Hospital, Paisley, United Kingdom
| | - W Ceelen
- Department of GI Surgery, University Hospital, Ghent, Belgium
| | - J Hewitt
- Department of Population Medicine, Cardiff University, United Kingdom
| | - P K Myint
- Institute of Applied Health Sciences, University of Aberdeen & Aberdeen Royal Infirmary, NHS Grampian, United Kingdom.
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Chivite D, Formiga F. Nonagenarians in Internal Medicine: Another 21st century epidemic. Rev Clin Esp 2018. [DOI: 10.1016/j.rceng.2018.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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9
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Validación externa de la regla NaURSE para predecir mortalidad intrahospitalaria en nonagenarios. Rev Clin Esp 2018; 218:110-111. [DOI: 10.1016/j.rce.2017.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 09/22/2017] [Accepted: 09/28/2017] [Indexed: 11/20/2022]
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10
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Validation of the NaURSE rule for predicting in-hospital mortality in nonagenarians. Rev Clin Esp 2018. [DOI: 10.1016/j.rceng.2017.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Chivite D, Formiga F. Nonagenarios en Medicina Interna: otra epidemia del siglo XXI. Rev Clin Esp 2018; 218:70-71. [DOI: 10.1016/j.rce.2018.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2017] [Accepted: 01/07/2018] [Indexed: 11/25/2022]
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Mannu GS, Honney K, Spooner R, Clark AB, Bettencourt-Silva JH, Zaman MJS, Loke YK, Myint PK. Incidentally Raised Cardiac Troponin I Has a Worse Prognosis in Older Patients Compared to Those with Normal Cardiac Troponin I and Patients with Acute Coronary Syndrome: A Cohort Study. Gerontology 2016; 62:581-587. [PMID: 27007948 DOI: 10.1159/000444083] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2015] [Accepted: 01/18/2016] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Incidentally elevated cardiac troponin I (cTnI) levels are common in acutely unwell older patients. However, little is known about how this impacts on the prognosis of these patients. OBJECTIVE We aimed to investigate whether incidentally elevated cTnI levels (group 1) are associated with poorer outcome when compared to age- and sex-matched patients without an elevated cTnI level (group 2), and to patients diagnosed with acute coronary syndrome (group 3). PATIENTS AND METHODS This prospective, matched cohort study placed patients ≥75 years old who were admitted to a University teaching hospital into groups 1-3, based on the cTnI levels and underlying diagnosis. Outcomes were compared between the groups using mixed-effects regression models and adjusted for renal function and C-reactive protein. All-cause mortality at discharge, at 1 month and 3 months, alongside the length of hospital stay (LOS), were recorded. RESULTS In total, 315 patients were included, with 105 patients in each of the 3 groups. The mean age was 84.8 ± 5.5 years, with 41.9% males. All patients were followed up for 3 months. The percent all-cause mortality at discharge and the LOS for groups 1, 2 and 3 were 12.4, 3.8 and 8.6% and 11.2, 8.5 and 7.7 days, respectively. Group 1 had significantly increased mortality at 3 months [odds ratio (OR) 2.80, 95% confidence interval (CI) 1.12-6.96; p = 0.040] and LOS (OR 1.39, 95% CI 1.08-1.79; p = 0.008) compared to group 2 and did not differ significantly when compared to 3-month mortality (OR 2.39, 95% CI 0.91-6.29; p = 0.079) or LOS (OR 1.26, 95% CI 0.96-1.66; p = 0.097) in group 3. CONCLUSION There is a significant association between an incidental rise in cTnI level with mortality and LOS in older patients. Further research is required to evaluate whether a more systematic management of these patients would improve the prognosis.
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Abstract
Urea is generated by the urea cycle enzymes, which are mainly in the liver but are also ubiquitously expressed at low levels in other tissues. The metabolic process is altered in several conditions such as by diets, hormones, and diseases. Urea is then eliminated through fluids, especially urine. Blood urea nitrogen (BUN) has been utilized to evaluate renal function for decades. New roles for urea in the urinary system, circulation system, respiratory system, digestive system, nervous system, etc., were reported lately, which suggests clinical significance of urea.
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McCall SJ, Musgrave SD, Potter JF, Hale R, Clark AB, Mamas MA, Metcalf AK, Day DJ, Warburton EA, Bachmann MO, Myint PK. The shock index predicts acute mortality outcomes in stroke. Int J Cardiol 2015; 182:523-7. [DOI: 10.1016/j.ijcard.2014.12.175] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Revised: 12/22/2014] [Accepted: 12/31/2014] [Indexed: 10/24/2022]
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