Patients in palliative care-Development of a predictive model for anxiety using routine data.
<h4>Introduction</h4>Anxiety is one of the most common psychological symptoms in patients in a palliative care situation. This study aims to develop a predictive model for anxiety using data from the standard documentation routine.<h4>Methods</h4>Data sets of palliative care...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0179415&type=printable |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850230393202016256 |
|---|---|
| author | Sonja Hofmann Stephanie Hess Carsten Klein Gabriele Lindena Lukas Radbruch Christoph Ostgathe |
| author_facet | Sonja Hofmann Stephanie Hess Carsten Klein Gabriele Lindena Lukas Radbruch Christoph Ostgathe |
| author_sort | Sonja Hofmann |
| collection | DOAJ |
| description | <h4>Introduction</h4>Anxiety is one of the most common psychological symptoms in patients in a palliative care situation. This study aims to develop a predictive model for anxiety using data from the standard documentation routine.<h4>Methods</h4>Data sets of palliative care patients collected by the German quality management benchmarking system called Hospice and Palliative Care Evaluation (HOPE) from 2007 to 2011 were randomly divided into a training set containing two-thirds of the data and a test set with the remaining one-third. We dichotomized anxiety levels, proxy rated by medical staff using the validated HOPE Symptom and Problem Checklist, into two groups with no or mild anxiety versus moderate or severe anxiety. Using the training set, a multivariable logistic regression model was developed by backward stepwise selection. Predictive accuracy was evaluated by the area under the receiver operating characteristic curve (AUC) based on the test set.<h4>Results</h4>An analysis of 9924 data sets suggests a predictive model for anxiety in patients receiving palliative care which contains gender, age, ECOG, living situation, pain, nausea, dyspnea, loss of appetite, tiredness, need for assistance with activities of daily living, problems with organization of care, medication with sedatives/anxiolytics, antidepressants, antihypertensive drugs, laxatives, and antibiotics. It results in a fair predictive value (AUC = 0.72).<h4>Conclusions</h4>Routinely collected data providing individual-, disease- and therapy-related information contain valuable information that is useful for the prediction of anxiety risks in patients receiving palliative care. These findings could thus be advantageous for providing appropriate support for patients in palliative care settings and should receive special attention in future research. |
| format | Article |
| id | doaj-art-a3246717e2644e94aa71e25dd5d3a72f |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-a3246717e2644e94aa71e25dd5d3a72f2025-08-20T02:03:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01128e017941510.1371/journal.pone.0179415Patients in palliative care-Development of a predictive model for anxiety using routine data.Sonja HofmannStephanie HessCarsten KleinGabriele LindenaLukas RadbruchChristoph Ostgathe<h4>Introduction</h4>Anxiety is one of the most common psychological symptoms in patients in a palliative care situation. This study aims to develop a predictive model for anxiety using data from the standard documentation routine.<h4>Methods</h4>Data sets of palliative care patients collected by the German quality management benchmarking system called Hospice and Palliative Care Evaluation (HOPE) from 2007 to 2011 were randomly divided into a training set containing two-thirds of the data and a test set with the remaining one-third. We dichotomized anxiety levels, proxy rated by medical staff using the validated HOPE Symptom and Problem Checklist, into two groups with no or mild anxiety versus moderate or severe anxiety. Using the training set, a multivariable logistic regression model was developed by backward stepwise selection. Predictive accuracy was evaluated by the area under the receiver operating characteristic curve (AUC) based on the test set.<h4>Results</h4>An analysis of 9924 data sets suggests a predictive model for anxiety in patients receiving palliative care which contains gender, age, ECOG, living situation, pain, nausea, dyspnea, loss of appetite, tiredness, need for assistance with activities of daily living, problems with organization of care, medication with sedatives/anxiolytics, antidepressants, antihypertensive drugs, laxatives, and antibiotics. It results in a fair predictive value (AUC = 0.72).<h4>Conclusions</h4>Routinely collected data providing individual-, disease- and therapy-related information contain valuable information that is useful for the prediction of anxiety risks in patients receiving palliative care. These findings could thus be advantageous for providing appropriate support for patients in palliative care settings and should receive special attention in future research.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0179415&type=printable |
| spellingShingle | Sonja Hofmann Stephanie Hess Carsten Klein Gabriele Lindena Lukas Radbruch Christoph Ostgathe Patients in palliative care-Development of a predictive model for anxiety using routine data. PLoS ONE |
| title | Patients in palliative care-Development of a predictive model for anxiety using routine data. |
| title_full | Patients in palliative care-Development of a predictive model for anxiety using routine data. |
| title_fullStr | Patients in palliative care-Development of a predictive model for anxiety using routine data. |
| title_full_unstemmed | Patients in palliative care-Development of a predictive model for anxiety using routine data. |
| title_short | Patients in palliative care-Development of a predictive model for anxiety using routine data. |
| title_sort | patients in palliative care development of a predictive model for anxiety using routine data |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0179415&type=printable |
| work_keys_str_mv | AT sonjahofmann patientsinpalliativecaredevelopmentofapredictivemodelforanxietyusingroutinedata AT stephaniehess patientsinpalliativecaredevelopmentofapredictivemodelforanxietyusingroutinedata AT carstenklein patientsinpalliativecaredevelopmentofapredictivemodelforanxietyusingroutinedata AT gabrielelindena patientsinpalliativecaredevelopmentofapredictivemodelforanxietyusingroutinedata AT lukasradbruch patientsinpalliativecaredevelopmentofapredictivemodelforanxietyusingroutinedata AT christophostgathe patientsinpalliativecaredevelopmentofapredictivemodelforanxietyusingroutinedata |