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Development of a Machine Learning–Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study

Development of a Machine Learning–Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study

By retaining subjects with positive delirium assessment records during the baseline period and incorporating delirium evaluation results monitored within 24 h of ICU admission as model features, the study effectively addresses the modeling limitations of traditional research regarding delirium state transitions (including complex clinical processes such as initial onset, recurrence, prolongation, and remission).

Houfeng Li, Qinglai Zang, Qi Li, Yanchen Lin, Jintao Duan, Jing Huang, Huixiu Hu, Ying Zhang, Dengyun Xia, Miao Zhou

J Med Internet Res 2025;27:e67258

Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation

Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation

As a result, a basic assessment for delirium is recommended for all hospitalized patients aged 65 years or older [5], and formal screening for delirium is recommended for critically ill patients [6]. Despite these recommendations, delirium frequently remains undiagnosed [7]. An automated delirium prediction tool could help address this, by alerting clinicians to at-risk patients so that they could be more carefully assessed for delirium.

Kendrick Matthew Shaw, Yu-Ping Shao, Manohar Ghanta, Valdery Moura Junior, Eyal Y Kimchi, Timothy T Houle, Oluwaseun Akeju, Michael Brandon Westover

JMIR Med Inform 2025;13:e60442

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

Moreover, a study by Ely et al [4] reported that ICU patients with delirium had a 3.2 times higher 6-month mortality rate compared with those without delirium. Financially, Vasilevskis et al [5] estimated that delirium increases ICU costs by US $17,838 to US $24,584 per patient. Patients with delirium are at a higher risk for complications, such as falls, infections, and pressure ulcers [6].

Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

J Med Internet Res 2025;27:e59520

Machine Learning–Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study

Machine Learning–Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study

Specifically, it became evident that urine output decreased proportionally, serving as a risk factor for ICU delirium. Comparative analysis of explanatory factors for intensive care unit (ICU) delirium in patients with burns using violin plots. This figure illustrates the distribution of key clinical and laboratory variables among 2 groups of ICU patients with burns: those who developed delirium (with delirium) and those who did not (without delirium).

Ryo Esumi, Hiroki Funao, Eiji Kawamoto, Ryota Sakamoto, Asami Ito-Masui, Fumito Okuno, Toru Shinkai, Atsuya Hane, Kaoru Ikejiri, Yuichi Akama, Arong Gaowa, Eun Jeong Park, Ryo Momosaki, Ryuji Kaku, Motomu Shimaoka

JMIR Form Res 2025;9:e65190

Evaluation of the Quality of Delirium Website Content for Patient and Family Education: Cross-Sectional Study

Evaluation of the Quality of Delirium Website Content for Patient and Family Education: Cross-Sectional Study

The increasing availability of websites related to delirium is likely reflective of the creation of delirium societies or associations (American Delirium Society, European Delirium Association, and Australasian Delirium Association), World Delirium Awareness Day (established in 2017), and an increase in the implementation of regular delirium screening in hospitals [42,43].

Karla Krewulak, Kathryn Strayer, Natalia Jaworska, Krista Spence, Nadine Foster, Scotty Kupsch, Khara Sauro, Kirsten M Fiest

J Med Internet Res 2025;27:e53087

Predictive Validity of Hospital-Associated Complications of Older People Identified Using Diagnosis Procedure Combination Data From an Acute Care Hospital in Japan: Observational Study

Predictive Validity of Hospital-Associated Complications of Older People Identified Using Diagnosis Procedure Combination Data From an Acute Care Hospital in Japan: Observational Study

Third, hospital-associated delirium was identified based on a recorded diagnosis of delirium (Multimedia Appendix 1) as a postadmission complication and recorded prescriptions of drugs used to manage agitation in delirium (injections of haloperidol or other antipsychotic drugs identified using prescription codes that remained constant throughout the study period).

Seigo Mitsutake, Tatsuro Ishizaki, Shohei Yano, Takumi Hirata, Kae Ito, Ko Furuta, Yoshitomo Shimazaki, Hideki Ito, Alison Mudge, Kenji Toba

JMIR Aging 2025;8:e68267

Assessment of Geriatric Problems and Risk Factors for Delirium in Surgical Medicine: Protocol for Multidisciplinary Prospective Clinical Study

Assessment of Geriatric Problems and Risk Factors for Delirium in Surgical Medicine: Protocol for Multidisciplinary Prospective Clinical Study

Perioperative delirium of vulnerable older patients is a major problem. Delirium is distressing for the individual, increases the burden of care, and has long-term negative consequences in terms of cognition, self-care ability, and prognosis [9]. Thus, incidences of perioperative delirium in older people are reported to be as high as 50% [10,11].

Henriette Louise Möllmann, Eman Alhammadi, Soufian Boulghoudan, Julian Kuhlmann, Anica Mevissen, Philipp Olbrich, Louisa Rahm, Helmut Frohnhofen

JMIR Res Protoc 2025;14:e59203

Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study

Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study

Visits that did not have documented delirium (ie, delirium ICD code or positive CAM) but did have nurse-documented confusion were excluded from the control pool to ensure controls were not actually misclassified cases; confusion (without delirium) could possibly represent subsyndromal delirium. If a case had more than 1 potential control, a control was randomly selected. For each eligible visit, the index date was defined as the date of hospital admission.

Emma Holler, Christina Ludema, Zina Ben Miled, Molly Rosenberg, Corey Kalbaugh, Malaz Boustani, Sanjay Mohanty

JMIR Perioper Med 2025;8:e59422

Developing a Life Story Intervention for Older Adults With Dementia or at Risk of Delirium Who Were Hospitalized: Multistage, Stakeholder-Engaged Co-Design Study

Developing a Life Story Intervention for Older Adults With Dementia or at Risk of Delirium Who Were Hospitalized: Multistage, Stakeholder-Engaged Co-Design Study

This impairment can be a chronic deteriorating impairment as is seen in Alzheimer or other dementias, or it can be an acute and likely reversible impairment which happens in hospital-induced delirium. For older adults with dementia or at risk of delirium, hospitalizations are often dehumanizing and disorienting [2,3].

Sarah J Flessa, James D Harrison, Roniela Turnigan, Megan Rathfon, Michael Chandler, Jay Newton-Small, Stephanie E Rogers

JMIR Aging 2024;7:e59306