Risk reclassification analysis investigating the added value of fatigue to sickness absence predictions

Prognostic models including age, self-rated health and prior sickness absence (SA) have been found to predict high (a parts per thousand yen30) SA days and high (a parts per thousand yen3) SA episodes during 1-year follow-up. More predictors of high SA are needed to improve these SA prognostic models. The purpose of this study was to investigate fatigue as new predictor in SA prognostic models by using risk reclassification methods and measures. This was a prospective cohort study with 1-year follow-up of 1,137 office workers. Fatigue was measured at baseline with the 20-item checklist individual strength and added to the existing SA prognostic models. SA days and episodes during 1-year follow-up were retrieved from an occupational health service register. The added value of fatigue was investigated with Net Reclassification Index (NRI) and integrated discrimination improvement (IDI) measures. In total, 579 (51 %) office workers had complete data for analysis. Fatigue was prospectively associated with both high SA days and episodes. The NRI revealed that adding fatigue to the SA days model correctly reclassified workers with high SA days, but incorrectly reclassified workers without high SA days. The IDI indicated no improvement in risk discrimination by the SA days model. Both NRI and IDI showed that the prognostic model predicting high SA episodes did not improve when fatigue was added as predictor variable. In the present study, fatigue increased false-positive rates which may reduce the cost-effectiveness of interventions for preventing SA

Strategy for finding occupational health survey participants at risk of long-term sickness absence

BACKGROUND: When resources are limited, occupational health survey participants are usually invited to consultations based on an occupational health provider's subjective considerations. This study aimed to find health survey participants at risk of long-term (i.e., ≥ 42 consecutive days) sickness absence (LTSA) for consultations with occupational health providers (OHPs). METHODS: The data of 64 011 non-sicklisted participants in occupational health surveys between 2010 and 2015 were used for the study. In a random sample of 40 000 participants, 27 survey variables were included in decision tree analysis (DTA) predicting LTSA at 1-year follow-up. The decision tree was transferred into a strategy to find participants for OHP consultations, which was then tested in the remaining 24 011 participants. RESULTS: In the development sample, 1358 (3.4%) participants had LTSA at 1-year follow-up. DTA produced a decision tree with work ability as first splitting variable; company size and sleep problems were the other splitting variables. A strategy differentiating by company size would find 75% of the LTSA cases in small (≤99 workers) companies and 43% of the LTSA cases in medium-sized (100-499 workers) companies. For large companies (≥500 workers), case-finding was only 25%. CONCLUSIONS: In small and medium-sized companies, work ability and sleep problems can be used to find occupational health survey participants for OHP consultations aimed at preventing LTSA. Research is needed to further develop a case-finding strategy for large companies

Diagnostic models to predict structural spinal osteoarthritis on lumbar radiographs in older adults with back pain:Development and internal validation

Objective: It is difficult for health care providers to diagnose structural spinal osteoarthritis (OA), because current guidelines recommend against imaging in patients with back pain. Therefore, the aim of this study was to develop and internally validate multivariable diagnostic prediction models based on a set of clinical and demographic features to be used for the diagnosis of structural spinal OA on lumbar radiographs in older patients with back pain. Design: Three diagnostic prediction models, for structural spinal OA on lumbar radiographs (i.e. multilevel osteophytes, multilevel disc space narrowing (DSN), and both combined), were developed and internally validated in the ‘Back Complaints in Older Adults’ (BACE) cohort (N ​= ​669). Model performance (i.e. overall performance, discrimination and calibration) and clinical utility (i.e. decision curve analysis) were assessed. Internal validation was performed by bootstrapping. Results: Mean age of the cohort was 66.9 years (±7.6 years) and 59% were female. All three models included age, gender, back pain duration and duration of spinal morning stiffness as predictors. The combined model additionally included restricted lateral flexion and spinal morning stiffness severity, and exhibited the best model performance (optimism adjusted c-statistic 0.661; good calibration with intercept −0.030 and slope of 0.886) and acceptable clinical utility. The other models showed suboptimal discrimination, good calibration and acceptable decision curves. Conclusion: All three models for structural spinal OA displayed lesuboptimal discrimination and need improvement. However, these internally validated models have potential to inform primary care clinicians about a patient with risk of having structural spinal OA on lumbar radiographs. External validation before implementation in clinical care is recommended.</p

Framingham score and work-related variables for predicting cardiovascular disease in the working population

Background: The Framingham score is commonly used to estimate the risk of cardiovascular disease (CVD). This study investigated whether work-related variables improve Framingham score predictions of sickness absence due to CVD. Methods: Eleven occupational health survey variables (descent, marital status, education, work type, work pace, cognitive demands, supervisor support, co-worker support, commitment to work, intrinsic work motivation and distress) and the Framingham Point Score (FPS) were combined into a multi-variable logistic regression model for CVD sickness absence during 1-year follow-up of 19 707 survey participants. The Net Reclassification Index (NRI) was used to investigate the added value of work-related variables to the FPS risk classification. Discrimination between participants with and without CVD sickness absence during follow-up was investigated by the area under the receiver operating characteristic curve (AUC). Results: A total of 129 (0.7%) occupational health survey participants had CVD sickness absence during 1-year follow-up. Manual work and high cognitive demands, but not the other work-related variables contributed to the FPS predictions of CVD sickness absence. However, work type and cognitive demands did not improve the FPS classification for risk of CVD sickness absence [NRI = 2.3%; 95% confidence interval (CI) -2.7 to 9.5%; P = 0.629]. The FPS discriminated well between participants with and without CVD sickness absence (AUC = 0.759; 95% CI 0.724-0.794). Conclusion: Work-related variables did not improve predictions of CVD sickness absence by the FPS. The non-laboratory Framingham score can be used to identify health survey participants at risk of CVD sickness absence

An innovative implementation strategy to improve the use of Dutch guidelines on hypertensive disorders in pregnancy:A randomized controlled trial

Objective: To evaluate the effectiveness of an innovative strategy to improve implementation of evidence-based guidelines on the management of hypertension in pregnancy compared to a common strategy of professional audit and feedback. Design: Cluster randomized controlled trial (c-RCT). Setting: Sixteen Dutch hospitals. Population: All patients with a hypertensive disorder during pregnancy who were admitted to one of the participating hospitals between April 1st 2010 and May 1st 2011, were suitable for inclusion; the only exclusion criterion was the presence of lethal fetal abnormalities. Methods: Hospitals were randomly assigned to either an innovative implementation strategy including a computerized decision support system (DSS) and professional audit and feedback or a minimal implementation strategy of audit and feedback only. Main outcome measures: Primary outcome measure was a combined rate of major maternal complications. Secondary outcome measures included process-related measures on guideline adherence, and patient-related outcomes. A process evaluation was performed alongside. Results: No statistically significant difference was found in both the occurrence of major complications and most secondary outcome measures between the two groups. Process evaluation showed limited use of the computerized DSS, with a large variation between hospitals (0–49,5% of the eligible patients), but positive experiences of actual users. Conclusion: Using a computerized DSS for implementation of the clinical guidelines for the management of hypertension in pregnancy did not result in fewer major maternal and fetal complications. Limited use of the DSS in the innovative strategy group could be an explanation for the lack of effect

Oral appliance therapy versus nasal continuous positive airway pressure in obstructive sleep apnea : a randomized, placebo-controlled trial on psychological distress

The aim of this randomized placebo-controlled trail was to compare the effects of an objectively titrated mandibular advancement device (MAD) with those of nasal continuous positive airway pressure (nCPAP) and an intraoral placebo device on symptoms of psychological distress in OSA patients. In a parallel design, 64 mild/moderate OSA patients (52.0 +/- 9.6 years) were randomly assigned to an objectively titrated MAD, nCPAP, or an intraoral placebo appliance. All patients filled out the Symptom Checklist-90-Revised twice: one before treatment and one after 6 months of treatment. The Symptom Checklist-90-Revised is a multidimensional symptom inventory designed to measure symptomatic psychological distress over the past week. Linear mixed model analyses were performed to study differences between the therapy groups for the different dimensions of the Symptom Checklist-90-Revised over time. The MAD group showed significant improvements over time in the dimensions "somatization," "insufficiency of thinking and acting," "agoraphobia," "anxiety," "sleeping problems," and "global severity index" (F = 4.14-16.73, P = 0.048-0.000). These improvements in symptoms of psychological distress were, however, not significantly different from those observed in the nCPAP and placebo groups (P = 0.374-0.953). There is no significant difference between MAD, nCPAP, and an intraoral placebo appliance in their beneficial effects on symptoms of psychological distress. The improvement in psychological distress symptoms in mild/moderate OSA patients under MAD or nCPAP treatment may be explained by a placebo effect.Peer reviewe

Development of a Prediction Model to Identify Children at Risk of Future Developmental Delay at Age 4 in a Population-Based Setting

Our aim was to develop a prediction model for infants from the general population, with easily obtainable predictors, that accurately predicts risk of future developmental delay at age 4 and then assess its performance. Longitudinal cohort data were used (N = 1983), including full-term and preterm children. Development at age 4 was assessed using the Ages and Stages Questionnaire. Candidate predictors included perinatal and parental factors as well as growth and developmental milestones during the first two years. We applied multiple logistic regression with backwards selection and internal validation, and we assessed calibration and discriminative performance (i.e., area under the curve (AUC)). The model was evaluated in terms of sensitivity and specificity at several cut-off values. The final model included sex, maternal educational level, pre-existing maternal obesity, several milestones (smiling, speaking 2–3 word sentences, standing) and weight for height z score at age 1. The fit was good, and the discriminative performance was high (AUC: 0.837). Sensitivity and specificity were 73% and 80% at a cut-off probability of 10%. Our model is promising for use as a prediction tool in community-based settings. It could aid to identify infants in early life (age 2) with increased risk of future developmental problems at age 4 that may benefit from early interventions

Predicting long-term sickness absence among retail workers after four days of sick-listing

Objective This study tested and validated an existing tool for its ability to predict the risk of long-term (ie, ≥6 weeks) sickness absence (LTSA) after four days of sick-listing. Methods A 9-item tool is completed online on the fourth day of sick-listing. The tool was tested in a sample (N=13 597) of food retail workers who reported sick between March and May 2017. It was validated in a new sample (N=104 698) of workers (83% retail) who reported sick between January 2020 and April 2021. LTSA risk predictions were calibrated with the Hosmer-Lemeshow (H-L) test; non-significant H-L P-values indicated adequate calibration. Discrimination between workers with and without LTSA was investigated with the area (AUC) under the receiver operating characteristic (ROC) curve. Results The data of 2203 (16%) workers in the test sample and 14 226 (13%) workers in the validation sample was available for analysis. In the test sample, the tool together with age and sex predicted LTSA (H-L test P=0.59) and discriminated between workers with and without LTSA [AUC 0.85, 95% confidence interval (CI) 0.83–0.87]. In the validation sample, LTSA risk predictions were adequate (H-L test P=0.13) and discrimination was excellent (AUC 0.91, 95% CI 0.90–0.92). The ROC curve had an optimal cut-off at a predicted 36% LTSA risk, with sensitivity 0.85 and specificity 0.83. Conclusion The existing 9-item tool can be used to invite sick-listed retail workers with a ≥36% LTSA risk for expedited consultations. Further studies are needed to determine LTSA cut-off risks for other economic sectors

Two-year effectiveness of a stepped-care depression prevention intervention and predictors of incident depression in primary care patients with diabetes type 2 and/or coronary heart disease and subthreshold depression; data from the Step-Dep cluster randomized controlled trial

Introduction Major depressive disorders (MDD), diabetes mellitus type 2 (DM2) and coronary heart disease (CHD) are leading contributors to the global burden of disease and often co-occur. Objectives To evaluate the two-year effectiveness of a stepped-care intervention to prevent MDD compared to usual care and to develop a prediction model for incident depression in DM2 and/or CHD patients with subthreshold depression. Methods Data of 236 Dutch primary care DM2/CHD patients with subthreshold depression (Patient Health Questionnaire 9 (PHQ-9) score ≥6, no current MDD according to the Mini International Neuropsychiatric Interview (DSM-IV criteria)), who participated in the Step-Dep trial were used. A PHQ-9 score of ≥10 at minimally one measurement during follow-up (at 3, 6, 9, 12 and 24 months) was used to determine the cumulative incidence of MDD. Potential demographic and psychological predictors were measured at baseline via web-based self-reported questionnaires and evaluated using a multivariable logistic regression model. Model performance was assessed with the Hosmer–Lemeshow test, Nagelkerke’s R2 explained variance and Area Under the Receiver Operating Characteristic curve (AUC). Bootstrapping techniques were used to internally validate our model. Results 192 patients (81%) were available at two-year follow-up. The cumulative incidence of MDD was 97/192 (51%). There was no statistically significant overall treatment effect over 24 months of the intervention (OR 1.37; 95% CI 0.52; 3.55). Baseline levels of anxiety, depression, the presence of >3 chronic diseases and stressful life-events predicted the incidence of MDD (AUC 0.80 interquartile range (IQR) 0.79-0.80; Nagelkerke’s R2 0.34 IQR 0.33-0.36). Conclusion A model with four factors predicted depression incidence during two-year follow-up in patients with DM2/CHD accurately, based on the AUC. The Step-Dep intervention did not influence the incidence of MDD. Future depression prevention programs should target patients with these four predictors present, and aim to reduce both anxiety and depressive symptoms