Structured alcohol cessation support program versus current practice in acute alcoholic pancreatitis (PANDA):Study protocol for a multicentre cluster randomised controlled trial

Background/objectives: The most important risk factor for recurrent pancreatitis after an episode of acute alcoholic pancreatitis is continuation of alcohol use. Current guidelines do not recommend any specific treatment strategy regarding alcohol cessation. The PANDA trial investigates whether implementation of a structured alcohol cessation support program prevents pancreatitis recurrence after a first episode of acute alcoholic pancreatitis. Methods: PANDA is a nationwide cluster randomised superiority trial. Participating hospitals are randomised for the investigational management, consisting of a structured alcohol cessation support program, or current practice. Patients with a first episode of acute pancreatitis caused by harmful drinking (AUDIT score &gt;7 and &lt; 16 for men and &gt;6 and &lt; 14 for women) will be included. The primary endpoint is recurrence of acute pancreatitis. Secondary endpoints include cessation or reduction of alcohol use, other alcohol-related diseases, mortality, quality of life, quality-adjusted life years (QALYs) and costs. The follow-up period comprises one year after inclusion. Discussion: This is the first multicentre trial with a cluster randomised trial design to investigate whether a structured alcohol cessation support program reduces recurrent acute pancreatitis in patients after a first episode of acute alcoholic pancreatitis, as compared with current practice. Trial registration: Netherlands Trial Registry (NL8852). Prospectively registered.</p

Delivering colon cancer survivorship care in primary care; a qualitative study on the experiences of general practitioners

Background: With more patients in need of oncological care, there is a growing interest to transfer survivorship care from specialist to general practitioner (GP). The ongoing I CARE study was initiated in 2015 in the Netherlands to compare (usual) surgeon- to GP-led survivorship care, with or without access to a supporting eHealth application (Oncokompas). Methods: Semi-structured interviews were held at two separate points in time (i.e. after 1- and 5-years of care) to explore GPs’ experiences with delivering this survivorship care intervention, and study its implementation into daily practice. Purposive sampling was used to recruit 17 GPs. Normalisation Process Theory (NPT) was used as a conceptual framework. Results: Overall, delivering survivorship care was not deemed difficult and dealing with cancer repercussions was already considered part of a GPs’ work. Though GPs readily identified advantages for patients, caregivers and society, differences were seen in GPs’ commitment to the intervention and whether it felt right for them to be involved. Patients’ initiative with respect to planning, absence of symptoms and regular check-ups due to other chronic care were considered to facilitate the delivery of care. Prominent barriers included GPs’ lack of experience and routine, but also lack of clarity regarding roles and responsibilities for organising care. Need for a monitoring system was often mentioned to reduce the risk of non-compliance. GPs were reticent about a possible future transfer of survivorship care towards primary care due to increases in workload and financial constraints. GPs were not aware of their patients’ use of eHealth. Conclusions: GPs’ opinions and beliefs about a possible future role in colon cancer survivorship care vary. Though GPs recognize potential benefit, there is no consensus about transferring survivorship care to primary care on a permanent basis. Barriers and facilitators to implementation highlight the importance of both personal and system level factors. Conditions are put forth relating to time, reorganisation of infrastructure, extra personnel and financial compensation. Trial registration: Netherlands Trial Register; NTR4860. Registered on the 2nd of October 2014

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: a mixed methods evaluation

Background Many studies have investigated the use of clinical decision support systems as a means to improve care, but have thus far failed to show significant effects on patient-related outcomes. We developed a clinical decision support system that attempted to address issues that were identified in these studies. The system was implemented in Dutch general practice and was designed to be both unobtrusive and to respond in real time. Despite our efforts, usage of the system was low. In the current study we perform a mixed methods evaluation to identify remediable barriers which led to disappointing usage rates for our system. Methods A mixed methods evaluation employing an online questionnaire and focus group. The focus group was organized to clarify free text comments and receive more detailed feedback from general practitioners. Topics consisted of items based on results from the survey and additional open questions. Results The response rate for the questionnaire was 94%. Results from the questionnaire and focus group can be summarized as follows: The system was perceived as interruptive, despite its design. Participants felt that there were too many recommendations and that the relevance of the recommendations varied. Demographic based recommendations (e.g. age) were often irrelevant, while specific risk-based recommendations (e.g. diagnosis) were more relevant. The other main barrier to use was lack of time during the patient visit. Conclusion These results are likely to be useful to other researchers who are attempting to address the problems of interruption and alert fatigue in decision support.</p

Higher chances of survival to hospital admission after out-of-hospital cardiac arrest in patients with previously diagnosed heart disease

Aim This study aimed to determine whether patients suffering from out-of-hospital cardiac arrest (OHCA) with a pre-OHCA diagnosis of heart disease have higher survival chances than patients without such a diagnosis and to explore possible underlying mechanisms. Methods A retrospective cohort study in 3760 OHCA patients from the Netherlands (2010-2016) was performed. Information from emergency medical services, treating hospitals, general practitioner, resuscitation ECGs and civil registry was used to assess medical histories and the presence of pre-OHCA diagnosis of heart disease. We used multivariable regression analysis to calculate associations with survival to hospital admission or discharge, immediate causes of OHCA (acute myocardial infarction (AMI) vs non-AMI) and initial recorded rhythm. Results Overall, 48.1% of OHCA patients had pre-OHCA heart disease. These patients had higher odds to survive to hospital admission than patients without pre-OHCA heart disease (OR 1.25 (95%CI 1.05 to 1.47)), despite being older and more often having cardiovascular risk factors and some non-cardiac comorbidities. These patients also had higher odds of shockable initial rhythm (SIR) (OR 1.60 (1. 36 to 1.89)) and a lower odds of AMI as immediate cause of OHCA (OR 0.33 (0.25 to 0.42)). Their chances of survival to hospital discharge were not significantly larger (OR 1.16 (0.95 to 1.42)). Conclusion Having pre-OHCA diagnosed heart disease is associated with better odds to survive to hospital admission, but not to hospital discharge. This is associated with higher odds of a SIR and in a subgroup with available diagnosis a lower proportion of AMI as immediate cause of OHCA

Predicting an unfavorable course of dizziness in older patients

PURPOSE Because dizziness in older people is often chronic and can substantially affect daily functioning, it is important to identify those at risk for an unfavorable course of dizziness to optimize their care. We aimed to develop and externally validate a prediction model for an unfavorable course of dizziness in older patients in primary care, and to construct an easy-to-use risk prediction tool. METHODS We used data from 2 prospective cohorts: a development cohort with 203 patients aged 65 years or older who consulted their primary care physician for dizziness and had substantial dizziness-related impairment (Dizziness Handicap Inventory [DHI] ≥30), and a validation cohort with 415 patients aged 65 years or older who consulted their primary care physician for dizziness of any severity. An unfavorable course was defined as presence of substantial dizziness-related impairment (DHI ≥30) after 6 months. RESULTS Prevalence of an unfavorable course of dizziness was 73.9% in the development cohort and 43.6% in the validation cohort. Predictors in the final model were the score on the screening version of the DHI, age, history of arrhythmia, and looking up as a provoking factor. The model showed good calibration and fair discrimination (area under the curve = 0.77). On external validation, discriminative ability remained stable (area under the curve = 0.78). The constructed risk score was strongly correlated with the prediction model. Performance measures for risk score cut-off values are presented to determine the optimal cut-off point for clinical practice. CONCLUSIONS We developed an easy-to-use risk score for dizziness-related impairment in primary care. The risk score, consisting of only 4 predictors, will help primary care physicians identify patients at high risk for an unfavorable course of dizziness

Effect of general practitioner-led versus surgeon-led colon cancer survivorship care, with or without eHealth support, on quality of life (I CARE): an interim analysis of 1-year results of a randomised, controlled trial

Background: Colon cancer is associated with an increased risk of physical and psychosocial morbidity, even after treatment. General practitioner (GP) care could be beneficial to help to reduce this morbidity. We aimed to assess quality of life (QOL) in patients who received GP-led survivorship care after treatment for colon cancer compared with those who received surgeon-led care. Furthermore, the effect of an eHealth app (Oncokompas) on QOL was assessed in both patient groups. Methods: We did a pragmatic two-by-two factorial, open-label, randomised, controlled trial at eight hospitals in the Netherlands. Eligible patients were receiving primary surgical treatment for stage I–III colon cancer or rectosigmoid carcinoma and qualified for routine follow-up according to Dutch national guidelines. Patients were randomly assigned (1:1:1:1)—via computer-generated variable block randomisation stratified by age and tumour stage—to survivorship care overseen by a surgeon, survivorship care overseen by a surgeon with access to Oncokompas, survivorship care overseen by a GP, or survivorship care overseen by a GP with access to Oncokompas. Blinding of the trial was not possible. The primary endpoint of the trial was QOL at 5 years, as measured by the change from baseline in the European Organistion for Research and Treatment of Cancer QLQ-C30 summary score. Here, we report an unplanned interim analysis of QOL at the 12-month follow-up. Grouped comparisons were done (ie, both GP-led care groups were compared with both surgeon-led groups, and both Oncokompas groups were compared with both no Oncokompas groups). Differences in change of QOL between trial groups were estimated with linear mixed-effects models. A change of ten units was considered clinically meaningful. Analysis was by intention to treat. This trial is registered with the Netherlands Trial Register, NTR4860. Findings: Between March 26, 2015, and Nov 21, 2018, 353 patients were enrolled and randomly assigned. There were 50 early withdrawals (27 patient decisions and 23 GP withdrawals). Of the remaining 303 participants, 79 were assigned to surgeon-led care, 83 to surgeon-led care with Oncokompas, 73 to GP-led care, and 68 to GP-led care with Oncokompas. Median follow-up was 12·2 months (IQR 12·0–13·0) in all groups. At baseline, QOL was high in all trial groups. At 12 months, there was no clinically meaningful difference in change from baseline in QOL between the GP-led care groups and the surgeon-led care groups (difference in summary score –2·3 [95% CI –5·0 to 0·4]) or between the Oncokompas and no Oncokompas groups (−0·1 [–2·8 to 2·6]). Interpretation: In terms of QOL, GP-led survivorship care can be considered as an alternative to surgeon-led care within the first year after colon cancer treatment. Other outcomes, including patient and physician preferences, will be important for decisions about the type of survivorship care. Funding: Dutch Cancer Society (KWF)

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings

The Accuracy of the Patient Health Questionnaire-9 (PHQ-9) Algorithm for Screening to Detect Major Depression : An Individual Participant Data Meta-analysis

Background: Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results. Objective: To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10. Methods: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview. Results: Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88). Conclusions: The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression