Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method.

BACKGROUND: Delirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge. OBJECTIVE: To characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review. METHODS: We conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review. RESULTS: Delirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5-26.8%), specificity 99.8% (95%CI: 99.5-99.9%), positive predictive value 97.6% (95%CI: 94.6-98.9%), and negative predictive value 79.2% (95%CI: 78.6-79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0-9.5 and $6824 greater cost, 95%CI: 4713-9264) and by chart review (11.9% greater mortality, 95%CI: 9.5-14.2% and $4967 greater cost, 95%CI: 4415-5701), compared to patients without delirium. CONCLUSIONS: Administrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed.

Association between pediatric postoperative delirium and regional cerebral oxygen saturation: a prospective observational study.

BACKGROUND: Postoperative delirium (POD) represents a prevalent and noteworthy complication in the context of pediatric surgical interventions. In recent times, a hypothesis has emerged positing that cerebral ischemia and regional cerebral oxygen desaturation might serve as potential catalysts in the pathogenesis of POD. The primary aim of this study was to methodically examine the potential relationship between POD and regional cerebral oxygen saturation (rSO2) and to assess the predictive and evaluative utility of rSO2 in the context of POD. METHODS: This prospective observational study was conducted at the Children's Hospital, Zhejiang University School of Medicine, Zhejiang, China, spanning the period from November 2020 to March 2021. The research cohort comprised children undergoing surgical procedures within this clinical setting. To measure rSO2 dynamics, cerebral near-infrared spectroscopy (NIRS) was used to monitor rSO2 levels both before and after surgery. In addition, POD was assessed in the paediatric patients according to the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) criteria. The analysis of the association between the rSO2 index and the incidence of POD was carried out through the application of either the independent samples t-test or the nonparametric rank-sum test. To ascertain the threshold value of the adjusted rSO2 index for predictive and evaluative purposes regarding POD in the pediatric population, the Receiver Operating Characteristics (ROC) curve was employed. RESULTS: A total of 211 cases were included in this study, of which 61 (28.9%) developed POD. Participants suffering delirium had lower preoperative rSO2mean, lower preoperative rSO2min, and lower postoperative rSO2min, higher ∆rSO2mean, higher amount of ∆rSO2mean, lower ∆rSO2min (P < 0.05). Preoperative rSO2mean (AUC = 0.716, 95%CI 0.642-0.790), ∆rSO2mean (AUC = 0.694, 95%CI 0.614-0.774), amount of ∆rSO2mean (AUC = 0.649, 95%CI 0.564-0.734), preoperative rSO2min (AUC = 0.702, 96%CI 0.628-0.777), postoperative rSO2min (AUC = 0.717, 95%CI 0.647-0.787), and ∆rSO2min (AUC = 0.714, 95%CI 0.638-0.790) performed well in sensitivity and specificity, and the best threshold were 62.05%, 1.27%, 2.41%, 55.68%, 57.36%, 1.29%. CONCLUSIONS: There is a close relationship between pediatric POD and rSO2. rSO2 could be used as an effective predictor of pediatric POD. It might be helpful to measure rSO2 with NIRS for early recognizing POD and making it possible for early intervention.

Development of an individualized model for predicting postoperative delirium in elderly patients with hepatocellular carcinoma.

Postoperative delirium (POD) is a common complication in older patients with hepatocellular carcinoma (HCC) that adversely impacts clinical outcomes. We aimed to evaluate the risk factors for POD and to construct a predictive nomogram. Data for a total of 1481 older patients (training set: n=1109; validation set: n=372) who received liver resection for HCC were retrospectively retrieved from two prospective databases. The receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance. The rate of POD was 13.3% (148/1109) in the training set and 16.4% (61/372) in the validation set. Multivariate analysis of the training set revealed that factors including age, history of cerebrovascular disease, American Society of Anesthesiologists (ASA) classification, albumin level, and surgical approach had significant effects on POD. The area under the ROC curves (AUC) for the nomogram, incorporating the aforementioned predictors, was 0.798 (95% CI 0.752-0.843) and 0.808 (95% CI 0.754-0.861) for the training and validation sets, respectively. The calibration curves of both sets showed a degree of agreement between the nomogram and the actual probability. DCA demonstrated that the newly established nomogram was highly effective for clinical decision-making. We developed and validated a nomogram with high sensitivity to assist clinicians in estimating the individual risk of POD in older patients with HCC.

The 4AT, a rapid delirium detection tool for use in hospice inpatient units: Findings from a validation study.

BACKGROUND: Delirium is a serious neuropsychiatric syndrome with adverse outcomes, which is common but often undiagnosed in terminally ill people. The 4 'A's test or 4AT (www.the4AT.com), a brief delirium detection tool, is widely used in general settings, but validation studies in terminally ill people are lacking. AIM: To determine the diagnostic accuracy of the 4AT in detecting delirium in terminally ill people, who are hospice inpatients. DESIGN: A diagnostic test accuracy study in which participants underwent the 4AT and a reference standard based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The reference standard was informed by Delirium Rating Scale Revised-98 and tests assessing arousal and attention. Assessments were conducted in random order by pairs of independent raters, blinded to the results of the other assessment. SETTING/PARTICIPANTS: Two hospice inpatient units in Scotland, UK. Participants were 148 hospice inpatients aged ⩾18 years. RESULTS: A total of 137 participants completed both assessments. Three participants had an indeterminate reference standard diagnosis and were excluded, yielding a final sample of 134. Mean age was 70.3 (SD = 10.6) years. About 33% (44/134) had reference standard delirium. The 4AT had a sensitivity of 89% (95% CI 79%-98%) and a specificity of 94% (95% CI 90%-99%). The area under the receiver operating characteristic curve was 0.97 (95% CI 0.94-1). CONCLUSION: The results of this validation study support use of the 4AT as a delirium detection tool in hospice inpatients, and add to the literature evaluating methods of delirium detection in palliative care settings. TRIAL REGISTRY: ISCRTN 97417474.

Machine learning-based model to predict delirium in patients with advanced cancer treated with palliative care: a multicenter, patient-based registry cohort.

This study aimed to present a new approach to predict to delirium admitted to the acute palliative care unit. To achieve this, this study employed machine learning model to predict delirium in patients in palliative care and identified the significant features that influenced the model. A multicenter, patient-based registry cohort study in South Korea between January 1, 2019, and December 31, 2020. Delirium was identified by reviewing the medical records based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. The study dataset included 165 patients with delirium among 2314 patients with advanced cancer admitted to the acute palliative care unit. Seven machine learning models, including extreme gradient boosting, adaptive boosting, gradient boosting, light gradient boosting, logistic regression, support vector machine, and random forest, were evaluated to predict delirium in patients with advanced cancer admitted to the acute palliative care unit. An ensemble approach was adopted to determine the optimal model. For k-fold cross-validation, the combination of extreme gradient boosting and random forest provided the best performance, achieving the following accuracy metrics: 68.83% sensitivity, 70.85% specificity, 69.84% balanced accuracy, and 74.55% area under the receiver operating characteristic curve. The performance of the isolated testing dataset was also validated, and the machine learning model was successfully deployed on a public website ( http://ai-wm.khu.ac.kr/Delirium/ ) to provide public access to delirium prediction results in patients with advanced cancer. Furthermore, using feature importance analysis, sex was determined to be the top contributor in predicting delirium, followed by a history of delirium, chemotherapy, smoking status, alcohol consumption, and living with family. Based on a large-scale, multicenter, patient-based registry cohort, a machine learning prediction model for delirium in patients with advanced cancer was developed in South Korea. We believe that this model will assist healthcare providers in treating patients with delirium and advanced cancer.

Development and validation of a new drug-focused predictive risk score for postoperative delirium in orthopaedic and trauma surgery patients.

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.

The role of heart rate variability in predicting delirium: A systematic review and meta-analysis.

Brain and heart interact through multiple ways. Heart rate variability, a non-invasive measurement is studied extensively as a predicting model for various health conditions including subarachnoid hemorrhage, cancer, and diabetes. There is limited evidence to predict delirium, an acute fluctuating disorder of brain dysfunction, as it poses a significant challenge in the intensive care unit (ICU) and post-operative setting. In this systematic review of 9 articles, heart rate variability indices were used to investigate the occurrence of post-operative and ICU delirium. This systematic review and meta-analysis reveal evidence of a strong predilection between postoperative and intensive care unit delirium and alterations in the heart rate variability, measured by mean differences for standard deviation of NN-intervals. Other heart rate variability indices [root mean squares of successive differences, low-frequency (LF), high-frequency (HF), and LF:HF ratio] showed lack of or very weak association. A non-invasive tool of brain and heart interaction may refine diagnostic predictions for acute brain dysfunctions like delirium in such population and would be an important step in delirium research.

Introducing a machine learning algorithm for delirium prediction-the Supporting SURgery with GEriatric Co-Management and AI project (SURGE-Ahead).

INTRODUCTION: Post-operative delirium (POD) is a common complication in older patients, with an incidence of 14-56%. To implement preventative procedures, it is necessary to identify patients at risk for POD. In the present study, we aimed to develop a machine learning (ML) model for POD prediction in older patients, in close cooperation with the PAWEL (patient safety, cost-effectiveness and quality of life in elective surgery) project. METHODS: The model was trained on the PAWEL study's dataset of 878 patients (no intervention, age ≥ 70, 209 with POD). Presence of POD was determined by the Confusion Assessment Method and a chart review. We selected 15 features based on domain knowledge, ethical considerations and a recursive feature elimination. A logistic regression and a linear support vector machine (SVM) were trained, and evaluated using receiver operator characteristics (ROC). RESULTS: The selected features were American Society of Anesthesiologists score, multimorbidity, cut-to-suture time, estimated glomerular filtration rate, polypharmacy, use of cardio-pulmonary bypass, the Montreal cognitive assessment subscores 'memory', 'orientation' and 'verbal fluency', pre-existing dementia, clinical frailty scale, age, recent falls, post-operative isolation and pre-operative benzodiazepines. The linear SVM performed best, with an ROC area under the curve of 0.82 [95% CI 0.78-0.85] in the training set, 0.81 [95% CI 0.71-0.88] in the test set and 0.76 [95% CI 0.71-0.79] in a cross-centre validation. CONCLUSION: We present a clinically useful and explainable ML model for POD prediction. The model will be deployed in the Supporting SURgery with GEriatric Co-Management and AI project.

Metabolomic Analysis in Saliva and Different Brain Regions of Older Mice with Postoperative Delirium Behaviors.

Objective: Postoperative delirium (POD) has become a critical challenge with severe consequences and increased incidences as the global population ages. However, the underlying mechanism is yet unknown. Our study aimed to explore the changes in metabolites in three specific brain regions and saliva of older mice with postoperative delirium behavior and to identify potential non-invasive biomarkers. Methods: Eighteen-month-old male C57/BL6 mice were randomly assigned to the anesthesia/surgery or control group. Behavioral tests were conducted 24 h before surgery and 6, 9, and 24 h after surgery. Complement C3 (C3) and S100 calcium-binding protein B protein (S100beta) levels were measured in the hippocampus, and a metabolomics analysis was performed on saliva, hippocampus, cortex, and amygdala samples. Results: In total, 43, 33, 38, and 14 differential metabolites were detected in the saliva, hippocampus, cortex, and amygdala, respectively. "Pyruvate" "alpha-linolenic acid" and "2-oleoyl-1-palmitoy-sn-glycero-3-phosphocholine" are enriched in one common pathway and may be potential non-invasive biomarkers for POD. Common changes were observed in the three brain regions, with the upregulation of 1-methylhistidine and downregulation of D-glutamine. Conclusion: Dysfunctions in energy metabolism, oxidative stress, and neurotransmitter dysregulation are implicated in the development of POD. The identification of changes in the level of salivary metabolite biomarkers could aid in the development of noninvasive diagnostic methods for POD.

Understanding the association between pain and delirium in older hospital inpatients: systematic review and meta-analysis.

OBJECTIVE: Delirium and pain are common in older adults admitted to hospital. The relationship between these is unclear, but clinically important. We aimed to systematically review the association between pain (at rest, movement, pain severity) and delirium in this population. METHODS: PubMed, EMBASE, CINAHL, PsycINFO, Cochrane and Web of Science were searched (January 1982-November 2022) for Medical Subject Heading terms and synonyms ('Pain', 'Analgesic', 'Delirium'). Study eligibility: (1) validated pain measure as exposure, (2) validated delirium tool as an outcome; participant eligibility: (1) medical or surgical (planned/unplanned) inpatients, (2) admission length ≥ 48 h and (3) median cohort age over 65 years. Study quality was assessed with the Newcastle Ottawa Scale. We collected/calculated odds ratios (ORs) for categorical data and standard mean differences (SMDs) for continuous data and conducted multi-level random-intercepts meta-regression models. This review was prospectively registered with PROSPERO [18/5/2020] (CRD42020181346). RESULTS: Thirty studies were selected: 14 reported categorical data; 16 reported continuous data. Delirium prevalence ranged from 2.2 to 55%. In the multi-level analysis, pain at rest (OR 2.14; 95% confidence interval [CI] 1.39-3.30), movement (OR 1.30; 95% CI 0.66-2.56), pain categorised as 'severe' (OR 3.42; 95% CI 2.09-5.59) and increased pain severity when measured continuously (SMD 0.33; 95% CI 0.08-0.59) were associated with an increased delirium risk. There was substantial heterogeneity in both categorical (I2 = 0%-77%) and continuous analyses (I2 = 85%). CONCLUSION: An increase in pain was associated with a higher risk of developing delirium. Adequate pain management with appropriate analgesia may reduce incidence and severity of delirium.

Assessment and report of individual symptoms in studies of delirium in postoperative populations: a systematic review.

OBJECTIVES: Delirium is most often reported as present or absent. Patients with symptoms falling short of the diagnostic criteria for delirium fall into 'no delirium' or 'control' groups. This binary classification neglects individual symptoms and may be hindering identification of the pathophysiology underlying delirium. This systematic review investigates which individual symptoms of delirium are reported by studies of postoperative delirium in adults. METHODS: Medline, EMBASE and Web of Science databases were searched on 03 June 2021 and 06 April 2023. Two reviewers independently examined titles and abstracts. Each paper was screened in duplicate and conflicting decisions settled by consensus discussion. Data were extracted, qualitatively synthesised and narratively reported. All included studies were quality assessed. RESULTS: These searches yielded 4,367 results. After title and abstract screening, 694 full-text studies were reviewed, and 62 deemed eligible for inclusion. This review details 11,377 patients including 2,049 patients with delirium. In total, 78 differently described delirium symptoms were reported. The most reported symptoms were inattention (N = 29), disorientation (N = 27), psychomotor agitation/retardation (N = 22), hallucination (N = 22) and memory impairment (N = 18). Notably, psychomotor agitation and hallucinations are not listed in the current Diagnostic and Statistical Manual for Mental Disorders-5-Text Revision delirium definition. CONCLUSIONS: The 78 symptoms reported in this systematic review cover domains of attention, awareness, disorientation and other cognitive changes. There is a lack of standardisation of terms, and many recorded symptoms are synonyms of each other. This systematic review provides a library of individual delirium symptoms, which may be used to inform future reporting.

Evaluation of Delirium Among Elders in the Emergency Department: A Cross-Sectional Study.

BACKGROUND: Health care professionals underestimate the recognition of delirium in emergency departments (EDs). In these settings, between 57% and 83% of cases of delirium go undetected. When delirium occurs, it causes an increase in the length of hospitalization, readmissions within 30 days, and mortality. No studies were carried out in Italy to assess the prevalence of delirium among elders in EDs. OBJECTIVES: The primary goal of the study was to evaluate the prevalence of the risk of delirium in people 65 years and older hospitalized in the ED for a minimum of 8 hours. The study's secondary goal was to identify the variables that influenced the risk of delirium. METHOD: A multicenter cross-sectional study was conducted in 2 EDs. The risk of delirium was assessed using the delirium screening tool 4 A's test. One hundred patients were enrolled. Data collection took place from June 28 to August 31, 2022. RESULTS: The risk of delirium was detected in 29% of the sample, whereas the risk of cognitive impairment was 13%. The use of psychotropic drugs increased the risk of delirium by 11.8 times (odds ratio [OR], 11.80; P = .003). Bed confinement increased the risk by 4.3 times (OR, 4.31; P = .009). Being dehydrated increased the risk of onset by 4.6 times (OR, 4.62; P = .010). Having dementia increased the risk of delirium manifestation by 4.4 times (OR, 4.35; P = .021). DISCUSSION: The risk of delirium was detected in a considerable portion of the sample. The results of this study can be used by health care professionals to implement preventive measures as well as support clinical judgment and establish priorities of care for patients at risk of developing delirium.

Validity and reliability of the Turkish version of the Informant Assessment of Geriatric Delirium Scale.

Background and purpose:

Delirium is a common complication developing in el­der­ly patients. Therefore, it is important to diagnose delirium earlier. Family caregivers play an active role in early diagnosis of de­lirium and build a bridge between health pro­fessionals and patients. The purpose of this research was to achieve the validity and reliability of the Turkish version of the Informant Assessment of Geriatric Delirium Scale (I-AGeD).

This is a methodological study. The sample comprised 125 caregivers ac­cepting to participate in the study and offering care to older patients with hip fracture aged ≥60 years. Data were gathered preoperatively and on postoperative days 0, 1 and 2. After achieving the linguistic and content validity of the scale, the known-groups comparison was used to achieve its construct validity. The ROC curve analysis was made to determine the sensitivity and specificity of the scale. Item-total correlations, item analysis based on the difference between the upper 27% and lower 27%, Kuder–Richardson 20 (KR-20) coefficient and parallel forms reliability with the NEECHAM Confusion Scale were adapted to assess discriminant indices of the items in the I-AGeD.

The item-total correlation coeffi­cients of the scale ranged from 0.54 to 0.89 and KR-20 coefficient ranged from 0.09 to 0.91 depending on the measurement times. According to the ROC curve analysis, the sensitivity and specificity of the scale were ≥ 91% and ≥ 96% respectively. The parallel forms reliability analysis showed a highly significant, strong negative relation at each measurement between the I-AGeD and the NEECHAM Confusion Scale. 

The I-AGeD is valid and reliable to diagnose delirium in older Turkish patients in perioperative processes.

Incidence of confusional syndrome (delirium) in a Latin American university hospital.

BACKGROUND: Little is known about the incidence of delirium and its subtypes in patients admitted to different departments of university hospitals in Latin America. OBJECTIVE: To determine the incidence of delirium and the frequency of its subtypes, as well as its associated factors, in patients admitted to different departments of a university hospital in Bogotá, Colombia. METHODS: A cohort of patients over 18 years of age admitted to the internal medicine (IM), geriatrics (GU), general surgery (GSU), orthopaedics (OU) and intensive care unit (ICU) services of a university hospital was followed up between January and June 2018. To detect the presence of delirium, we used the CAM (Confusion Assessment Method) and the CAM-ICU if the patient had decreased communication skills. The delirium subtype was characterised using the RASS (Richmond Agitation and Sedation Scale). Patients were assessed on their admission date and then every two days until discharged from the hospital. Those in whom delirium was identified were referred for specialised intra-institutional interdisciplinary management. RESULTS: A total of 531 patients admitted during the period were assessed. The overall incidence of delirium was 12% (95% CI, 0.3-14.8). They represented 31.8% of patients in the GU, 15.6% in the ICU, 8.7% in IM, 5.1% in the OU, and 3.9% in the GSU. The most frequent clinical display was the mixed subtype, at 60.9%, followed by the normoactive subtype (34.4%) and the hypoactive subtype (4.7%). The factors most associated with delirium were age (adjusted RR = 1.07; 95% CI, 1.05-1.09), the presence of four or more comorbidities (adjusted RR = 2.04; 95% CI, 1.31-3.20), and being a patient in the ICU (adjusted RR = 2.02; 95% CI, 1.22-3.35). CONCLUSIONS: The incidence of delirium is heterogeneous in the different departments of the university hospital. The highest incidence occurred in patients that were admitted to the GU. The mixed subtype was the most frequent one, and the main associated factors were age, the presence of four or more comorbidities, and being an ICU patient.

Validation of the Delirium Observation Screening Scale in long-term care facilities in Flanders.

AIM: The aim of this study was to validate the Delirium Observation Screening Scale (DOSS) in a population of long-term care facility (LTCF) residents in Flanders. Currently there is no validated screening tool for delirium available for the population in this setting in Flanders. METHODS: A multisite, cross-sectional study was conducted in six LTCFs. A total of 338 residents aged 65 years and older were included. Sociodemographic and clinical data, including data from the Montreal Cognitive Assessment (MoCA), Confusion Assessment Method (CAM) and DOSS, were obtained by three trained nurse researchers. For the DOSS, internal consistency was determined, and inter-rater reliability was calculated. To validate the DOSS, the sensitivity, specificity, and positive and negative predictive value of the DOSS relative to the CAM were determined through receiver operating characteristic analysis. This article adheres to the Strengthening the Reporting of Observational Studies (STROBE) checklist for observational research. RESULTS: For 338 residents, delirium assessments were completed during an early or late shift. The prevalence of delirium was 14.2% as measured with the DOSS. The reliability (α) for the CAM and DOSS was assessed, as was the inter-rater reliability (κ) and the area under the curve. The sensitivity and specificity for a cut-off value of 3 on the DOSS by Youden's index were very high, as was the negative predictive value. The positive predictive value was good. CONCLUSIONS: This study showed that the DOSS is a reliable and valid instrument to screen for delirium in LTCF residents in Flanders. Geriatr Gerontol Int 2024; 24: 619-625.

Clinical characteristics of older patients with suspected or diagnosed dementia during hospitalization.

AIM: In Japan, an additional system for patients with suspected or diagnosed dementia during hospitalization for physical illness began in 2016. We examined the clinical characteristics of older patients with suspected or diagnosed dementia during hospitalization. METHODS: The study participants consisted of 569 patients. Current age, sex, comorbidities, causative disease for admission, body mass index (BMI), blood tests, environment before admission, prescription history before admission and rate of delirium were examined. Simple regression analysis for high-frequency diseases was carried out with the respective risk factors as independent variables. Multiple regression analysis was then carried out. RESULTS: Infection had the highest frequency in the causative diseases for admission. A total of 48% of patients had delirium during hospitalization. The delirium group had the highest frequency of being at home. In the infection group, BMI and serum albumin were lower in the non-infection group (BMI 19.0 ± 3.7 vs 20.4 ± 4.1; P < 0.001, albumin 2.1 ± 0.7 vs 3.3 ± 0.6 g/dL; P < 0.001 respectively). White blood cell count and C-reactive protein were higher than in the non-infection group, respectively (white blood cell count 11181.4 ± 6533.3 vs 8765.8 ± 111 424.3/µL; P = 0.007, C-reactive protein 8.6 ± 8.6 vs 3.0 ± 5.2 mg/dL; P < 0.001 respectively). Using independent factors associated with infection, multiple regression analysis was performed. BMI (P = 0.013), serum albumin (P < 0.001) and nursing home care before admission (P < 0.001) had significant correlations. CONCLUSIONS: Assessment of delirium and the environment before admission of older patients with suspected or diagnosed dementia when hospitalized are necessary. Furthermore, evaluation of nutrition might also contribute to reducing deterioration due to physical illness. Geriatr Gerontol Int 2024; 24: 641-645.