Validation of a consensus method for identifying delirium from hospital records.
<h4>Background</h4>Delirium is increasingly considered to be an important determinant of trajectories of cognitive decline. Therefore, analyses of existing cohort studies measuring cognitive outcomes could benefit from methods to ascertain a retrospective delirium diagnosis. This study a...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2014-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0111823 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849726760194670592 |
|---|---|
| author | Elvira Kuhn Xinyi Du Keith McGrath Sarah Coveney Niamh O'Regan Sarah Richardson Andrew Teodorczuk Louise Allan Dan Wilson Sharon K Inouye Alasdair M J MacLullich David Meagher Carol Brayne Suzanne Timmons Daniel Davis |
| author_facet | Elvira Kuhn Xinyi Du Keith McGrath Sarah Coveney Niamh O'Regan Sarah Richardson Andrew Teodorczuk Louise Allan Dan Wilson Sharon K Inouye Alasdair M J MacLullich David Meagher Carol Brayne Suzanne Timmons Daniel Davis |
| author_sort | Elvira Kuhn |
| collection | DOAJ |
| description | <h4>Background</h4>Delirium is increasingly considered to be an important determinant of trajectories of cognitive decline. Therefore, analyses of existing cohort studies measuring cognitive outcomes could benefit from methods to ascertain a retrospective delirium diagnosis. This study aimed to develop and validate such a method for delirium detection using routine medical records in UK and Ireland.<h4>Methods</h4>A point prevalence study of delirium provided the reference-standard ratings for delirium diagnosis. Blinded to study results, clinical vignettes were compiled from participants' medical records in a standardised manner, describing any relevant delirium symptoms recorded in the whole case record for the period leading up to case-ascertainment. An expert panel rated each vignette as unlikely, possible, or probable delirium and disagreements were resolved by consensus.<h4>Results</h4>From 95 case records, 424 vignettes were abstracted by 5 trained clinicians. There were 29 delirium cases according to the reference standard. Median age of subjects was 76.6 years (interquartile range 54.6 to 82.5). Against the original study DSM-IV diagnosis, the chart abstraction method gave a positive likelihood ratio (LR) of 7.8 (95% CI 5.7-12.0) and the negative LR of 0.45 (95% CI 0.40-0.47) for probable delirium (sensitivity 0.58 (95% CI 0.53-0.62); specificity 0.93 (95% CI 0.90-0.95); AUC 0.86 (95% CI 0.82-0.89)). The method diagnosed possible delirium with positive LR 3.5 (95% CI 2.9-4.3) and negative LR 0.15 (95% CI 0.11-0.21) (sensitivity 0.89 (95% CI 0.85-0.91); specificity 0.75 (95% CI 0.71-0.79); AUC 0.86 (95% CI 0.80-0.89)).<h4>Conclusions</h4>This chart abstraction method can retrospectively diagnose delirium in hospitalised patients with good accuracy. This has potential for retrospectively identifying delirium in cohort studies where routine medical records are available. This example of record linkage between hospitalisations and epidemiological data may lead to further insights into the inter-relationship between acute illness, as an exposure, for a range of chronic health outcomes. |
| format | Article |
| id | doaj-art-5034bcba2f9243fb8ed95c1399b1fa05 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-5034bcba2f9243fb8ed95c1399b1fa052025-08-20T03:10:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01911e11182310.1371/journal.pone.0111823Validation of a consensus method for identifying delirium from hospital records.Elvira KuhnXinyi DuKeith McGrathSarah CoveneyNiamh O'ReganSarah RichardsonAndrew TeodorczukLouise AllanDan WilsonSharon K InouyeAlasdair M J MacLullichDavid MeagherCarol BrayneSuzanne TimmonsDaniel Davis<h4>Background</h4>Delirium is increasingly considered to be an important determinant of trajectories of cognitive decline. Therefore, analyses of existing cohort studies measuring cognitive outcomes could benefit from methods to ascertain a retrospective delirium diagnosis. This study aimed to develop and validate such a method for delirium detection using routine medical records in UK and Ireland.<h4>Methods</h4>A point prevalence study of delirium provided the reference-standard ratings for delirium diagnosis. Blinded to study results, clinical vignettes were compiled from participants' medical records in a standardised manner, describing any relevant delirium symptoms recorded in the whole case record for the period leading up to case-ascertainment. An expert panel rated each vignette as unlikely, possible, or probable delirium and disagreements were resolved by consensus.<h4>Results</h4>From 95 case records, 424 vignettes were abstracted by 5 trained clinicians. There were 29 delirium cases according to the reference standard. Median age of subjects was 76.6 years (interquartile range 54.6 to 82.5). Against the original study DSM-IV diagnosis, the chart abstraction method gave a positive likelihood ratio (LR) of 7.8 (95% CI 5.7-12.0) and the negative LR of 0.45 (95% CI 0.40-0.47) for probable delirium (sensitivity 0.58 (95% CI 0.53-0.62); specificity 0.93 (95% CI 0.90-0.95); AUC 0.86 (95% CI 0.82-0.89)). The method diagnosed possible delirium with positive LR 3.5 (95% CI 2.9-4.3) and negative LR 0.15 (95% CI 0.11-0.21) (sensitivity 0.89 (95% CI 0.85-0.91); specificity 0.75 (95% CI 0.71-0.79); AUC 0.86 (95% CI 0.80-0.89)).<h4>Conclusions</h4>This chart abstraction method can retrospectively diagnose delirium in hospitalised patients with good accuracy. This has potential for retrospectively identifying delirium in cohort studies where routine medical records are available. This example of record linkage between hospitalisations and epidemiological data may lead to further insights into the inter-relationship between acute illness, as an exposure, for a range of chronic health outcomes.https://doi.org/10.1371/journal.pone.0111823 |
| spellingShingle | Elvira Kuhn Xinyi Du Keith McGrath Sarah Coveney Niamh O'Regan Sarah Richardson Andrew Teodorczuk Louise Allan Dan Wilson Sharon K Inouye Alasdair M J MacLullich David Meagher Carol Brayne Suzanne Timmons Daniel Davis Validation of a consensus method for identifying delirium from hospital records. PLoS ONE |
| title | Validation of a consensus method for identifying delirium from hospital records. |
| title_full | Validation of a consensus method for identifying delirium from hospital records. |
| title_fullStr | Validation of a consensus method for identifying delirium from hospital records. |
| title_full_unstemmed | Validation of a consensus method for identifying delirium from hospital records. |
| title_short | Validation of a consensus method for identifying delirium from hospital records. |
| title_sort | validation of a consensus method for identifying delirium from hospital records |
| url | https://doi.org/10.1371/journal.pone.0111823 |
| work_keys_str_mv | AT elvirakuhn validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT xinyidu validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT keithmcgrath validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT sarahcoveney validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT niamhoregan validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT sarahrichardson validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT andrewteodorczuk validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT louiseallan validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT danwilson validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT sharonkinouye validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT alasdairmjmaclullich validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT davidmeagher validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT carolbrayne validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT suzannetimmons validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords AT danieldavis validationofaconsensusmethodforidentifyingdeliriumfromhospitalrecords |