Validation of the Risk Model for Delirium in hip fracture patients

Moerman, Sophie; Tuinebreijer, W.E.; Boo, Maarten de; Pilot, Peter; Nelissen, Rob G H H; Vochteloo, Anne J. H.

doi:10.1016/j.genhosppsych.2011.11.011

Cited by 23 publications

(16 citation statements)

References 29 publications

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“… 28 41 49 One of these studies retrospectively confirmed the diagnosis of delirium through consensus review of two authors; disagreement was resolved by a psychiatrist. 41 One study did not report details on personnel performing delirium assessments. 42 …”

Section: Resultsmentioning

confidence: 99%

“…Functional impairment was defined as follows: (1 study) needing assistance with any basic activities in daily living (ADL), 27 (1 study) domestic help, help with meals or physical care 41 and (2 studies) residence in nursing facility or at home with caregivers, 33 and (2 studies) requiring a home care package with professional caregivers or residence in a care home. 33 48 The latter being obtained on admission from medical records.…”

Section: Resultsmentioning

confidence: 99%

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Systematic review of prediction models for delirium in the older adult inpatient

et al. 2018

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ObjectiveTo identify existing prognostic delirium prediction models and evaluate their validity and statistical methodology in the older adult (≥60 years) acute hospital population.DesignSystematic review.Data sources and methodsPubMed, CINAHL, PsychINFO, SocINFO, Cochrane, Web of Science and Embase were searched from 1 January 1990 to 31 December 2016. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses and CHARMS Statement guided protocol development. Inclusion criteria: age >60 years, inpatient, developed/validated a prognostic delirium prediction model. Exclusion criteria: alcohol-related delirium, sample size ≤50. The primary performance measures were calibration and discrimination statistics. Two authors independently conducted search and extracted data. The synthesis of data was done by the first author. Disagreement was resolved by the mentoring author.ResultsThe initial search resulted in 7,502 studies. Following full-text review of 192 studies, 33 were excluded based on age criteria (<60 years) and 27 met the defined criteria. Twenty-three delirium prediction models were identified, 14 were externally validated and 3 were internally validated. The following populations were represented: 11 medical, 3 medical/surgical and 13 surgical. The assessment of delirium was often non-systematic, resulting in varied incidence. Fourteen models were externally validated with an area under the receiver operating curve range from 0.52 to 0.94. Limitations in design, data collection methods and model metric reporting statistics were identified.ConclusionsDelirium prediction models for older adults show variable and typically inadequate predictive capabilities. Our review highlights the need for development of robust models to predict delirium in older inpatients. We provide recommendations for the development of such models.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Systematic review of prediction models for delirium in the older adult inpatient

et al. 2018

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“…After examining the full text of these articles, 100 were excluded; 58 because the performance of the RPM was examined using an ineligible (statistically) measure (see ), 28 because they did not examine the outcome POD, seven because they did not use a cohort design, six because they did not describe at least one RPM, and one because of duplicate publication. Ultimately, 30 articles were included in the systematic review …”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, preoperative MMSE may not be useable in an acute surgery setting, because completing the MMSE score preoperatively may take too much time and may result in an inaccurately low score due to preexisting preoperative delirium. Finally, individuals with delirium in their history might be expected to be susceptible to POD, although this was found to be an independent predictor in only three studies . It may have been that there were too few individuals with this history item for previous POD to be selected into these models using statistical selection methods.…”

Section: Discussionmentioning

confidence: 97%

Risk Prediction Models for Postoperative Delirium: A Systematic Review and Meta‐Analysis

Meenen

Rooij

et al. 2014

J American Geriatrics Society

105

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Postoperative delirium (POD) is a common neuropsychiatric disorder characterized by inattention, fluctuating levels of consciousness, and disorganized thinking. POD can have serious consequences, including institutionalization and death. Risk stratification may target prevention to individuals at greater risk of POD. The objective of this study was to identify all published POD risk prediction models (RPMs) and to compare them with regard to their clinical practicability and predictive and discriminative performance. PubMed and EMBASE were searched from inception to January 1, 2013, for articles describing POD RPMs. Studies were included if they presented data from a cohort study, examined one or more RPMs, examined POD as an outcome, and assessed the performance of the RPM(s). Thirty of 2,246 articles were included, and 37 RPMs were found. Sixteen and six studies described individuals who had undergone cardiovascular and orthopedic surgery, respectively. The Confusion Assessment Method (CAM) for the intensive care unit checklist was the most often used diagnostic method (65%), followed by the Diagnostic and Statistical Manual of Mental Disorders (DSM), Fourth Edition criteria (16%). Predictors most often used in RPMs were age (20), preoperative Mini-Mental State Examination score (10), and preoperative increased alcohol use (7). Thirty RPMs were not validated, three were validated internally, and four were validated externally. Size of the models was not associated with their discriminatory performance. Instead of creating steadily new RPMs, existing RPMs should be further tested, improved, and meta-analytically integrated. It may be too early to implement a particular PODRPM in clinical practice with confidence.

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“…However, both models were developed in general ICU patients and not fully considering the impact of surgical factors. The other eight identified models were for hip surgery (Kalisvaart et al, 2006;Moerman et al, 2012), cardiac surgery (Koster, Oosterveld, Hensens, Wijma, & van der Palen, 2008;Rudolph et al, 2009), vascular surgery (Bohner et al, 2003, non-cardiac surgery (Marcantonio et al, 1994), and general surgery (Dworkin, Lee, An, & Goodlin, 2016;Kim, Park, Kim, & Cho, 2016). Most of these models were developed based on pre-operative data and did not target ICU patients.…”

Section: Introductionmentioning

confidence: 99%

Incidence and risk factors of PostopeRativE delirium in intensive care unit patients: A study protocol for the PREDICt study

Cai

Latour

et al. 2019

Journal of Advanced Nursing

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Aim The aims of this study are: (a) to determine the incidence of postoperative delirium (POD) among surgical intensive care unit (ICU) patients in China and identify risk factors, especially, which are modifiable and have value for developing a prediction model; (b) to develop and validate a prediction model of delirium to recognize high‐risk patients in surgical ICUs; (c) to investigate the short‐ and long‐term outcomes of delirious patients and identify the predictors of patient outcomes. Design A single‐centre prospective cohort study. Methods Patients will be enrolled from three surgical ICUs in a tertiary teaching hospital. Delirium assessment and perioperative data will be collected throughout the hospitalization. Delirious patients will be followed up for 2 years. The study was approved by the ethics committee in May 2018 and was funded by the clinical research grant from Zhongshan hospital, Fudan University, Shanghai. Discussion Developing POD can be a burden to patients both for the short‐ and long‐term period. Due to the lack of effective treatments for POD, prevention remains the best strategy. This study will provide an effective tool for early screening of high‐risk patients of POD and provide a better understanding of the aetiology and outcome of delirium. Impact In clinical practice, a prediction model will offer an effective tool for ICU nurses to assess high‐risk patients, which can support them to implement preventive strategies at the early stages to targeted patients. The follow‐up results will help us better understand the impact of delirium on patients’ long‐term outcome.

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Validation of the Risk Model for Delirium in hip fracture patients

Cited by 23 publications

References 29 publications

Systematic review of prediction models for delirium in the older adult inpatient

Systematic review of prediction models for delirium in the older adult inpatient

Risk Prediction Models for Postoperative Delirium: A Systematic Review and Meta‐Analysis

Incidence and risk factors of PostopeRativE delirium in intensive care unit patients: A study protocol for the PREDICt study

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