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Guttenthaler V, Fidorra J, Wittmann M, Menzenbach J. Predictiveness of preoperative laboratory values for postoperative delirium. Health Sci Rep 2024; 7:e2219. [PMID: 38952405 PMCID: PMC11215531 DOI: 10.1002/hsr2.2219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 07/03/2024] Open
Abstract
Background Postoperative delirium (POD) is a common postoperative complication, especially in patients over 60 years, with an incidence ranging from 15% to 50%. In most cases, POD manifests in the first 5 days after surgery. Multiple contributing risk factors for POD have been detected. Besides the predisposing factors such as higher age, cognitive impairment, high blood pressure, atrial fibrillation, and past stroke, pathophysiological mechanisms like neuroinflammation are also considered as contributing factors. Methods In a subanalysis of the "PRe- Operative Prediction of postoperative DElirium by appropriate SCreening" (PROPDESC) study, the preoperative laboratory values of sodium, potassium, total protein, hemoglobin concentration (Hgb), and white blood cells as well as the biomarkers creatinine, HbA1c, NT-pro-BNP, high sensitive Troponin T (hsTnT), and C-reactive protein (CRP) were assessed to investigate a possible relationship to the occurrence of POD. Results After correction for age, physical status classification, surgery risk after Johns Hopkins, and operative discipline (cardiac surgery vs. noncardiac surgery), male patients with a Hgb <13 g/dL had significantly higher odds for POD (p = 0.025). Furthermore, patients with CRP ≥ 10 mg/L, HbA1c value ≥ 8.5% as well as patients with hypernatraemia (>145 mmol/L) presented significantly higher odds to develop POD (p = 0.011, p < 0.001, and p = 0.021, respectively). A raised (>14-52 ng/L) or high (>52 ng/L) hsTnT value was also associated with a significantly higher chance for POD compared to the patient group with hsTnT <14 ng/L (p < 0.001 and p = 0.016, respectively). Conclusions Preoperative Hgb, CRP, HbA1c, sodium, and hsTnT could be used to complement and refine the preoperative screening for patients at risk for POD. Further studies should track these correlations to investigate the potential of targeted POD protection and enabling hospital staff to initiate POD-preventing measures in time.
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Affiliation(s)
- Vera Guttenthaler
- Clinic of Anaesthesia and Intensive Care MedicineUniversity BonnBonnGermany
| | - Jacqueline Fidorra
- Clinic of Anaesthesia and Intensive Care MedicineUniversity BonnBonnGermany
- Asklepios Clinic North HeidbergClinic for Internal Medicine Department IHamburgGermany
| | - Maria Wittmann
- Clinic of Anaesthesia and Intensive Care MedicineUniversity BonnBonnGermany
| | - Jan Menzenbach
- Clinic of Anaesthesia and Intensive Care MedicineUniversity BonnBonnGermany
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Sadlonova M, Hansen N, Esselmann H, Celano CM, Derad C, Asendorf T, Chebbok M, Heinemann S, Wiesent A, Schmitz J, Bauer FE, Ehrentraut J, Kutschka I, Wiltfang J, Baraki H, von Arnim CAF. Preoperative Delirium Risk Screening in Patients Undergoing a Cardiac Surgery: Results from the Prospective Observational FINDERI Study. Am J Geriatr Psychiatry 2024; 32:835-851. [PMID: 38228452 DOI: 10.1016/j.jagp.2023.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/18/2024]
Abstract
OBJECTIVE Postoperative delirium (POD) is a common complication of cardiac surgery that is associated with higher morbidity, longer hospital stay, cognitive decline, and mortality. Preoperative assessments may help to identify patients´ POD risk. However, a standardized screening assessment for POD risk has not been established. DESIGN Prospective observational FINd DElirium RIsk factors (FINDERI) study. PARTICIPANTS Patients aged ≥50 years undergoing cardiac surgery. MEASUREMENTS The primary aim was to analyze the predictive value of the Delirium Risk Screening Questionnaire (DRSQ) prior to cardiac surgery. Secondary aims are to investigate cognitive, frailty, and geriatric assessments, and to use data-driven machine learning (ML) in predicting POD. Predictive properties were assessed using receiver operating characteristics analysis and multivariate approaches (regularized LASSO regression and decision trees). RESULTS We analyzed a data set of 504 patients (68.3 ± 8.2 years, 21.4% women) who underwent cardiac surgery. The incidence of POD was 21%. The preoperatively administered DRSQ showed an area under the curve (AUC) of 0.68 (95% CI 0.62, 0.73), and the predictive OR was 1.25 (95% CI 1.15, 1.35, p <0.001). Using a ML approach, a three-rule decision tree prediction model including DRSQ (score>7), Trail Making Test B (time>118), and Montreal Cognitive Assessment (score ≤ 22) was identified. The AUC of the three-rule decision tree on the training set was 0.69 (95% CI 0.63, 0.75) and 0.62 (95% CI 0.51, 0.73) on the validation set. CONCLUSION Both the DRSQ and the three-rule decision tree might be helpful in predicting POD risk before cardiac surgery.
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Affiliation(s)
- Monika Sadlonova
- Department of Cardiovascular and Thoracic Surgery (MS, IK, HB), University of Göttingen Medical Center, Göttingen, Germany; Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany; Department of Psychosomatic Medicine and Psychotherapy (MS,), University of Göttingen Medical Center, Göttingen, Germany; DZHK (German Center for Cardiovascular Research) (MS, IK, HB, CAFA), Göttingen, Germany; Department of Psychiatry (MS, CMC), Massachusetts General Hospital, Boston, MA.
| | - Niels Hansen
- Department of Psychiatry and Psychotherapy (NH, HE, JW), University of Göttingen Medical Center, Göttingen, Germany
| | - Hermann Esselmann
- Department of Psychiatry and Psychotherapy (NH, HE, JW), University of Göttingen Medical Center, Göttingen, Germany
| | - Christopher M Celano
- Department of Psychiatry (MS, CMC), Massachusetts General Hospital, Boston, MA; Department of Psychiatry (CMC), Harvard Medical Schol, Boston, MA
| | - Carlotta Derad
- Department of Medical Statistics (CD, TA), University of Göttingen Medical Center, Göttingen, Germany
| | - Thomas Asendorf
- Department of Medical Statistics (CD, TA), University of Göttingen Medical Center, Göttingen, Germany
| | - Mohammed Chebbok
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany; Department of Cardiology and Pneumology (MC), University of Göttingen Medical Center, Göttingen, Germany
| | - Stephanie Heinemann
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany
| | - Adriana Wiesent
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany
| | - Jessica Schmitz
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany
| | - Frederike E Bauer
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany
| | - Julia Ehrentraut
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany
| | - Ingo Kutschka
- Department of Cardiovascular and Thoracic Surgery (MS, IK, HB), University of Göttingen Medical Center, Göttingen, Germany; DZHK (German Center for Cardiovascular Research) (MS, IK, HB, CAFA), Göttingen, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy (NH, HE, JW), University of Göttingen Medical Center, Göttingen, Germany; German Center for Neurodegenerative Diseases (DZNE) (JW), Göttingen, Germany; Neurosciences and Signaling Group (JW), Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Hassina Baraki
- Department of Cardiovascular and Thoracic Surgery (MS, IK, HB), University of Göttingen Medical Center, Göttingen, Germany; DZHK (German Center for Cardiovascular Research) (MS, IK, HB, CAFA), Göttingen, Germany
| | - Christine A F von Arnim
- Department of Geriatrics (MS, MC, SH, AW, JS, FEB, JE, CAFA), University of Göttingen Medical Center, Göttingen, Germany; DZHK (German Center for Cardiovascular Research) (MS, IK, HB, CAFA), Göttingen, Germany
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Geßele C, Saller T, Smolka V, Dimitriadis K, Amann U, Strobach D. Development and validation of a new drug-focused predictive risk score for postoperative delirium in orthopaedic and trauma surgery patients. BMC Geriatr 2024; 24:422. [PMID: 38741037 DOI: 10.1186/s12877-024-05005-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 04/24/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Postoperative delirium (POD) is the most common complication following surgery in elderly patients. During pharmacist-led medication reconciliation (PhMR), a predictive risk score considering delirium risk-increasing drugs and other available risk factors could help to identify risk patients. METHODS Orthopaedic and trauma surgery patients aged ≥ 18 years with PhMR were included in a retrospective observational single-centre study 03/2022-10/2022. The study cohort was randomly split into a development and a validation cohort (6:4 ratio). POD was assessed through the 4 A's test (4AT), delirium diagnosis, and chart review. Potential risk factors available at PhMR were tested via univariable analysis. Significant variables were added to a multivariable logistic regression model. Based on the regression coefficients, a risk score for POD including delirium risk-increasing drugs (DRD score) was established. RESULTS POD occurred in 42/328 (12.8%) and 30/218 (13.8%) patients in the development and validation cohorts, respectively. Of the seven evaluated risk factors, four were ultimately tested in a multivariable logistic regression model. The final DRD score included age (66-75 years, 2 points; > 75 years, 3 points), renal impairment (eGFR < 60 ml/min/1.73m2, 1 point), anticholinergic burden (ACB-score ≥ 3, 1 point), and delirium risk-increasing drugs (n ≥ 2; 2 points). Patients with ≥ 4 points were classified as having a high risk for POD. The areas under the receiver operating characteristic curve of the risk score model were 0.89 and 0.81 for the development and the validation cohorts, respectively. CONCLUSION The DRD score is a predictive risk score assessable during PhMR and can identify patients at risk for POD. Specific preventive measures concerning drug therapy safety and non-pharmacological actions should be implemented for identified risk patients.
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Affiliation(s)
- Carolin Geßele
- Hospital Pharmacy, LMU University Hospital, LMU Munich, Munich, Germany.
- Doctoral Program Clinical Pharmacy, LMU University Hospital, LMU Munich, Munich, Germany.
| | - Thomas Saller
- Department of Anaesthesiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Vera Smolka
- Department of Orthopaedics and Trauma Surgery, LMU University Hospital, LMU Munich, Munich, Germany
| | | | - Ute Amann
- Faculty of Medicine, LMU Munich, Munich, Germany
| | - Dorothea Strobach
- Hospital Pharmacy, LMU University Hospital, LMU Munich, Munich, Germany
- Doctoral Program Clinical Pharmacy, LMU University Hospital, LMU Munich, Munich, Germany
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Guttenthaler V, Kunsorg A, Mayr A, Hering T, Menzenbach J, Wittmann M. [PROPDESC Score Validation (PROPDESC-Val)]. DIE ANAESTHESIOLOGIE 2024; 73:56-59. [PMID: 38172421 PMCID: PMC10791728 DOI: 10.1007/s00101-023-01371-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/11/2023] [Indexed: 01/05/2024]
Affiliation(s)
- V Guttenthaler
- Klinik für Anästhesiologie und Operative Intensivmedizin, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland
| | - A Kunsorg
- Klinik für Anästhesiologie und Operative Intensivmedizin, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland
| | - A Mayr
- Institut für Medizinische Biometrie, Informatik und Epidemiologie, Universitätsklinikum Bonn, Bonn, Deutschland
| | - T Hering
- Klinik für Anästhesiologie, Intensivmedizin, Notfallmedizin und Schmerztherapie, Kreiskrankenhaus Mechernich GmbH, Mechernich, Deutschland
| | - J Menzenbach
- Klinik für Anästhesiologie und Operative Intensivmedizin, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland
| | - M Wittmann
- Klinik für Anästhesiologie und Operative Intensivmedizin, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland.
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Dodsworth BT, Reeve K, Falco L, Hueting T, Sadeghirad B, Mbuagbaw L, Goettel N, Schmutz Gelsomino N. Development and validation of an international preoperative risk assessment model for postoperative delirium. Age Ageing 2023; 52:7192246. [PMID: 37290122 DOI: 10.1093/ageing/afad086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Indexed: 06/10/2023] Open
Abstract
BACKGROUND Postoperative delirium (POD) is a frequent complication in older adults, characterised by disturbances in attention, awareness and cognition, and associated with prolonged hospitalisation, poor functional recovery, cognitive decline, long-term dementia and increased mortality. Early identification of patients at risk of POD can considerably aid prevention. METHODS We have developed a preoperative POD risk prediction algorithm using data from eight studies identified during a systematic review and providing individual-level data. Ten-fold cross-validation was used for predictor selection and internal validation of the final penalised logistic regression model. The external validation used data from university hospitals in Switzerland and Germany. RESULTS Development included 2,250 surgical (excluding cardiac and intracranial) patients 60 years of age or older, 444 of whom developed POD. The final model included age, body mass index, American Society of Anaesthesiologists (ASA) score, history of delirium, cognitive impairment, medications, optional C-reactive protein (CRP), surgical risk and whether the operation is a laparotomy/thoracotomy. At internal validation, the algorithm had an AUC of 0.80 (95% CI: 0.77-0.82) with CRP and 0.79 (95% CI: 0.77-0.82) without CRP. The external validation consisted of 359 patients, 87 of whom developed POD. The external validation yielded an AUC of 0.74 (95% CI: 0.68-0.80). CONCLUSIONS The algorithm is named PIPRA (Pre-Interventional Preventive Risk Assessment), has European conformity (ce) certification, is available at http://pipra.ch/ and is accepted for clinical use. It can be used to optimise patient care and prioritise interventions for vulnerable patients and presents an effective way to implement POD prevention strategies in clinical practice.
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Affiliation(s)
| | - Kelly Reeve
- Institute of Data Analysis and Process Design, Zurich University of Applied Sciences, Winterthur 8400, Switzerland
| | - Lisa Falco
- Zühlke Engineering AG, Zürcherstrasse 39J, Schlieren 8952, Switzerland
| | - Tom Hueting
- Evidencio, Irenesingel 19, Haaksbergen 7481 GJ, Netherlands
| | - Behnam Sadeghirad
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton ON L8S 4L8, Canada
- Department of Anesthesia, McMaster University, Hamilton ON L8S 4L8, Canada
| | - Lawrence Mbuagbaw
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton ON L8S 4L8, Canada
- Department of Anesthesia, McMaster University, Hamilton ON L8S 4L8, Canada
- Department of Pediatrics, McMaster University, Hamilton, ON L8S 4L8, Canada
- Biostatistics Unit, Father Sean O'Sullivan Research Centre, St Joseph's Healthcare, Hamilton, ON L8S 4L8, Canada
- Centre for Development of Best Practices in Health (CDBPH), Yaoundé Central Hospital, Yaoundé 12117, Cameroon
- Division of Epidemiology and Biostatistics, Department of Global Health, Stellenbosch University, Cape Town 7600, South Africa
| | - Nicolai Goettel
- Department of Anesthesiology, University of Florida College of Medicine, Gainesville FL 32610, USA
- Department of Clinical Research, University of Basel, Basel 4031, Switzerland
| | - Nayeli Schmutz Gelsomino
- PIPRA AG, Zurich 8005, Switzerland
- Department of Anaesthesia, University Hospital Basel, Spitalstrasse 21, Basel 4031, Switzerland
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