Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information

Line Thorndal Moll; Anne Mette Schmidt; Christina Malmose Stapelfeldt; Merete Labriola; Ole Kudsk Jensen; Morten Wasmod Kindt; Tue Secher Jensen; Berit Schiøttz-Christensen

doi:10.1186/s12891-019-2906-4

Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information

Line Thorndal Moll^*, Anne Mette Schmidt, Christina Malmose Stapelfeldt, Merete Labriola, Ole Kudsk Jensen, Morten Wasmod Kindt, Tue Secher Jensen, Berit Schiøttz-Christensen

^*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Abstract

Background: In cases of neck and shoulder pain, the responsibility for assessing work prognosis is held by clinicians with access to different domains of information. One of these domains is magnetic resonance imaging (MRI), and although MRI is increasingly used, it is unknown which domains of information contribute the most to the prediction of work prognosis. This retrospective cohort study explored the contribution of demographic, patient-reported, clinical, and MRI information to the prediction of work participation in sickness absentees with neck or shoulder pain. Methods: From a secondary care setting, 168 sickness absentees with neck or shoulder pain were included. Based on registry data, a successful work outcome was defined as ≥50% work participation score (WPS) from Weeks 1 to 104 after enrolment. Prognostic variables were categorized into four domains (demographic, patient-reported, clinical, and MRI) resembling the order of information obtained in a clinical setting. Crude logistic regression analyses were used to identify prognostic variables for each domain (p < 0.2). This was followed by multivariable analyses including the identified variables in a domain-wise order. For each added domain, the probability of successful WPS was dichotomized leaving two possible classifications: ≥ 50% chance of successful WPS or not. In cross-tabulations of chance and the actual WPS outcome, positive and negative predictive values (PPV and NPV), sensitivity, specificity and area under the curve (AUC) were calculated. Results: The combination of demographic and patient-reported variables yielded an NPV of 0.72 and a PPV of 0.67, while specificity was 0.82, sensitivity 0.54 and AUC 0.77. None of these values improved notably by adding clinical and MRI variables as predictors of successful WPS. Conclusions: These results suggest that- A mong sickness absentees with neck or shoulder pain-clinical and MRI variables provide no additional information for the prediction of work participation compared with only demographic and patient-reported information.

Original language	English
Article number	525
Journal	BMC Musculoskeletal Disorders
Volume	20
Issue	1
ISSN	1471-2474
DOIs	https://doi.org/10.1186/s12891-019-2906-4
Publication status	Published - 2019

Keywords

Magnetic resonance imaging
Neck pain
Prediction
Prognosis
Shoulder pain
Sick leave

Access to Document

10.1186/s12891-019-2906-4

Cite this

Moll, L. T., Schmidt, A. M., Stapelfeldt, C. M., Labriola, M., Jensen, O. K., Kindt, M. W., Jensen, T. S., & Schiøttz-Christensen, B. (2019). Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information. BMC Musculoskeletal Disorders, 20(1), Article 525. https://doi.org/10.1186/s12891-019-2906-4

@article{e48f63be8a9a4bfabd98f4f27926d72c,

title = "Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information",

abstract = "Background: In cases of neck and shoulder pain, the responsibility for assessing work prognosis is held by clinicians with access to different domains of information. One of these domains is magnetic resonance imaging (MRI), and although MRI is increasingly used, it is unknown which domains of information contribute the most to the prediction of work prognosis. This retrospective cohort study explored the contribution of demographic, patient-reported, clinical, and MRI information to the prediction of work participation in sickness absentees with neck or shoulder pain. Methods: From a secondary care setting, 168 sickness absentees with neck or shoulder pain were included. Based on registry data, a successful work outcome was defined as ≥50% work participation score (WPS) from Weeks 1 to 104 after enrolment. Prognostic variables were categorized into four domains (demographic, patient-reported, clinical, and MRI) resembling the order of information obtained in a clinical setting. Crude logistic regression analyses were used to identify prognostic variables for each domain (p < 0.2). This was followed by multivariable analyses including the identified variables in a domain-wise order. For each added domain, the probability of successful WPS was dichotomized leaving two possible classifications: ≥ 50% chance of successful WPS or not. In cross-tabulations of chance and the actual WPS outcome, positive and negative predictive values (PPV and NPV), sensitivity, specificity and area under the curve (AUC) were calculated. Results: The combination of demographic and patient-reported variables yielded an NPV of 0.72 and a PPV of 0.67, while specificity was 0.82, sensitivity 0.54 and AUC 0.77. None of these values improved notably by adding clinical and MRI variables as predictors of successful WPS. Conclusions: These results suggest that- A mong sickness absentees with neck or shoulder pain-clinical and MRI variables provide no additional information for the prediction of work participation compared with only demographic and patient-reported information.",

keywords = "Magnetic resonance imaging, Neck pain, Prediction, Prognosis, Shoulder pain, Sick leave",

author = "Moll, {Line Thorndal} and Schmidt, {Anne Mette} and Stapelfeldt, {Christina Malmose} and Merete Labriola and Jensen, {Ole Kudsk} and Kindt, {Morten Wasmod} and Jensen, {Tue Secher} and Berit Schi{\o}ttz-Christensen",

year = "2019",

doi = "10.1186/s12891-019-2906-4",

language = "English",

volume = "20",

journal = "BMC Musculoskeletal Disorders",

issn = "1471-2474",

publisher = "BioMed Central Ltd.",

number = "1",

}

Moll, LT , Schmidt, AM, Stapelfeldt, CM, Labriola, M, Jensen, OK, Kindt, MW, Jensen, TS & Schiøttz-Christensen, B 2019, 'Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information', BMC Musculoskeletal Disorders, vol. 20, no. 1, 525. https://doi.org/10.1186/s12891-019-2906-4

Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information. / Moll, Line Thorndal ; Schmidt, Anne Mette; Stapelfeldt, Christina Malmose et al.
In: BMC Musculoskeletal Disorders, Vol. 20, No. 1, 525, 2019.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

TY - JOUR

T1 - Prediction of 2-year work participation in sickness absentees with neck or shoulder pain

T2 - The contribution of demographic, patient-reported, clinical and imaging information

AU - Moll, Line Thorndal

AU - Schmidt, Anne Mette

AU - Stapelfeldt, Christina Malmose

AU - Labriola, Merete

AU - Jensen, Ole Kudsk

AU - Kindt, Morten Wasmod

AU - Jensen, Tue Secher

AU - Schiøttz-Christensen, Berit

PY - 2019

Y1 - 2019

N2 - Background: In cases of neck and shoulder pain, the responsibility for assessing work prognosis is held by clinicians with access to different domains of information. One of these domains is magnetic resonance imaging (MRI), and although MRI is increasingly used, it is unknown which domains of information contribute the most to the prediction of work prognosis. This retrospective cohort study explored the contribution of demographic, patient-reported, clinical, and MRI information to the prediction of work participation in sickness absentees with neck or shoulder pain. Methods: From a secondary care setting, 168 sickness absentees with neck or shoulder pain were included. Based on registry data, a successful work outcome was defined as ≥50% work participation score (WPS) from Weeks 1 to 104 after enrolment. Prognostic variables were categorized into four domains (demographic, patient-reported, clinical, and MRI) resembling the order of information obtained in a clinical setting. Crude logistic regression analyses were used to identify prognostic variables for each domain (p < 0.2). This was followed by multivariable analyses including the identified variables in a domain-wise order. For each added domain, the probability of successful WPS was dichotomized leaving two possible classifications: ≥ 50% chance of successful WPS or not. In cross-tabulations of chance and the actual WPS outcome, positive and negative predictive values (PPV and NPV), sensitivity, specificity and area under the curve (AUC) were calculated. Results: The combination of demographic and patient-reported variables yielded an NPV of 0.72 and a PPV of 0.67, while specificity was 0.82, sensitivity 0.54 and AUC 0.77. None of these values improved notably by adding clinical and MRI variables as predictors of successful WPS. Conclusions: These results suggest that- A mong sickness absentees with neck or shoulder pain-clinical and MRI variables provide no additional information for the prediction of work participation compared with only demographic and patient-reported information.

AB - Background: In cases of neck and shoulder pain, the responsibility for assessing work prognosis is held by clinicians with access to different domains of information. One of these domains is magnetic resonance imaging (MRI), and although MRI is increasingly used, it is unknown which domains of information contribute the most to the prediction of work prognosis. This retrospective cohort study explored the contribution of demographic, patient-reported, clinical, and MRI information to the prediction of work participation in sickness absentees with neck or shoulder pain. Methods: From a secondary care setting, 168 sickness absentees with neck or shoulder pain were included. Based on registry data, a successful work outcome was defined as ≥50% work participation score (WPS) from Weeks 1 to 104 after enrolment. Prognostic variables were categorized into four domains (demographic, patient-reported, clinical, and MRI) resembling the order of information obtained in a clinical setting. Crude logistic regression analyses were used to identify prognostic variables for each domain (p < 0.2). This was followed by multivariable analyses including the identified variables in a domain-wise order. For each added domain, the probability of successful WPS was dichotomized leaving two possible classifications: ≥ 50% chance of successful WPS or not. In cross-tabulations of chance and the actual WPS outcome, positive and negative predictive values (PPV and NPV), sensitivity, specificity and area under the curve (AUC) were calculated. Results: The combination of demographic and patient-reported variables yielded an NPV of 0.72 and a PPV of 0.67, while specificity was 0.82, sensitivity 0.54 and AUC 0.77. None of these values improved notably by adding clinical and MRI variables as predictors of successful WPS. Conclusions: These results suggest that- A mong sickness absentees with neck or shoulder pain-clinical and MRI variables provide no additional information for the prediction of work participation compared with only demographic and patient-reported information.

KW - Magnetic resonance imaging

KW - Neck pain

KW - Prediction

KW - Prognosis

KW - Shoulder pain

KW - Sick leave

UR - http://www.scopus.com/inward/record.url?scp=85074741844&partnerID=8YFLogxK

U2 - 10.1186/s12891-019-2906-4

DO - 10.1186/s12891-019-2906-4

M3 - Journal article

C2 - 31706350

AN - SCOPUS:85074741844

SN - 1471-2474

VL - 20

JO - BMC Musculoskeletal Disorders

JF - BMC Musculoskeletal Disorders

IS - 1

M1 - 525

ER -

Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: The contribution of demographic, patient-reported, clinical and imaging information

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this