Don’t ask, don’t tell: delirium in the intensive care unit*:

A bibliometric analysis on delirium in intensive care unit from 2013-2023

Background

Delirium is a common manifestation of acute brain dysfunction among patients in the Intensive Care Unit (ICU), afflicting an estimated 30-35% of this vulnerable population. The prevalence of delirium in ICU settings has catalyzed a surge in academic interest, as evidenced by a growing body of literature on the subject. This study seeks to synthesize the progress in understanding ICU delirium through a bibliometric analysis.

Methods

We conducted a comprehensive search of the Web of Science Core (WOS) Collection database for literature on ICU delirium, focusing on studies published between 2013 and 2023. Our analysis utilized two bibliometric software tools, Citespace and VOSviewer, to scrutinize the data across various dimensions, including country contributions, authorship patterns, publishing journals, key thematic terms, and other pertinent metrics, with the aim of identifying emerging trends in the field.

Results

Our search yielded a total of 1,178 publications on ICU delirium within the WOS database from January 2013 to June 2023. The United States emerged as the leading contributor in terms of published articles, with Ely, E. Wesley being the most prolific author, having published 85 articles, and "Critical Care Medicine" as the journal with the highest number of publications, totaling 105. The application of literature clustering and keyword analysis revealed that future research is poised to delve deeper into areas such as pediatric delirium, risk factors, and the development of preventive and therapeutic strategies.

Conclusion

This study employs bibliometric analysis to provide a multifaceted overview of the ICU delirium research landscape over the past decade. By examining the topic from various perspectives, we have not only mapped the current state of ICU delirium research but also illuminated potential avenues for future inquiry and areas of emphasis.

Delirium misdiagnosis risk in psychiatry: a machine learning-logistic regression predictive algorithm

BACKGROUND

Delirium is a frequent diagnosis made by Consultation-Liaison Psychiatry (CLP). Numerous studies have demonstrated misdiagnosis prior to referral to CLP. Few studies have considered the factors underlying misdiagnosis using multivariate approaches.

OBJECTIVES

To determine the number of cases referred to CLP, which are misdiagnosed at time of referral, to build an accurate predictive classifier algorithm, using input variables related to delirium misdiagnosis.

METHOD

A retrospective observational study was conducted at Alfred Hospital in Melbourne, collecting data from a record of all patients seen by CLP for a period of 5 months. Data was collected pertaining to putative factors underlying misdiagnosis. A Machine Learning-Logistic Regression classifier model was built, to classify cases of accurate delirium diagnosis vs. misdiagnosis.

RESULTS

Thirty five of 74 new cases referred were misdiagnosed. The proposed predictive algorithm achieved a mean Receiver Operating Characteristic (ROC) Area under the curve (AUC) of 79%, an average 72% classification accuracy, 77% sensitivity and 67% specificity.

CONCLUSIONS

Delirium is commonly misdiagnosed in hospital settings. Our findings support the potential application of Machine Leaning-logistic predictive classifier in health care settings.

[Latin American survey on delirium in critical patients]

OBJECTIVES

This study has aimed to establish the intensivist physician's concepts and practices in this region regarding the diagnosis, management and prevention of delirium in intensive care units (ICU).

DESIGN

A survey was distributed among the FEPIMCTI member societies for distribution among its medical members.

RESULTS

Eight hundred fifty-four intensive care physicians from 12 Latin America countries, most of them from Argentina, Mexico, Chile and Colombia, responded to the survey. There was a majority of academic ICUs (70.5%). A total of 56.55% responded that they always evaluated the diagnosis of delirium and only 10.2% answered never. A general clinical assessment was made by 69.5%, only 19.6% used the CAM-ICU scale and 9% the checklist assessment of delirium. It was agreed or strongly agreed by 88.3% that delirium was an expected event in the ICU and by 90.1% that delirium was underdiagnosed in ICU. A total of 97% responded that it was a problem that requires intervention and which is preventable (66.5%). It was considered that excessive sedation is given in the ICU by 74.5% and 70.5% believed that opiates are associated with the onset of delirium, while 87.1% considered that some sedatives are associated with its development. Ventilator-associated pneumonia (VAP) was considered as a risk factor by 70.2% of the respondents and 87.8% considered that it made extubation difficult.

CONCLUSIONS

Although delirium is considered to be a common and preventable problem with serious implications for critically ill patients, the intensivist physicians surveyed do not use a tool for its evaluation in the ICU. Educational efforts are needed to disseminate the effectiveness and usefulness of the scales that allow for early and accurate diagnosis of delirium in the ICU.