Development and internal validation of a prediction model for long-term opioid use-an analysis of insurance claims data.

In the United States, a public-health crisis of opioid overuse has been observed, and in Europe, prescriptions of opioids are strongly increasing over time. The objective was to develop and validate a multivariable prognostic model to be used at the beginning of an opioid prescription episode, aiming to identify individual patients at high risk for long-term opioid use based on routinely collected data. Predictors including demographics, comorbid diseases, comedication, morphine dose at episode initiation, and prescription practice were collected. The primary outcome was long-term opioid use, defined as opioid use of either >90 days duration and ≥10 claims or >120 days, independent of the number of claims. Traditional generalized linear statistical regression models and machine learning approaches were applied. The area under the curve, calibration plots, and the scaled Brier score assessed model performance. More than four hundred thousand opioid episodes were included. The final risk prediction model had an area under the curve of 0.927 (95% confidence interval 0.924-0.931) in the validation set, and this model had a scaled Brier score of 48.5%. Using a threshold of 10% predicted probability to identify patients at high risk, the overall accuracy of this risk prediction model was 81.6% (95% confidence interval 81.2% to 82.0%). Our study demonstrated that long-term opioid use can be predicted at the initiation of an opioid prescription episode, with satisfactory accuracy using data routinely collected at a large health insurance company. Traditional statistical methods resulted in higher discriminative ability and similarly good calibration as compared with machine learning approaches

Manticore: Efficient Framework for Scalable Secure Multiparty Computation Protocols

We propose a novel MPC framework, Manticore, in the multiparty setting, with full threshold and semi-honest security model, supporting a combination of real number arithmetic (arithmetic shares), Boolean arithmetic (Boolean shares) and garbled circuits (Yao shares). In contrast to prior work [MZ17, MR18], Manticore never overflows, an important feature for machine learning applications. It achieves this without compromising efficiency or security. Compared to other overflow-free recent techniques such as MP-SPDZ [EGKRS20] that convert arithmetic to Boolean shares, we introduce a novel highly efficient modular lifting/truncation method that stays in the arithmetic domain. We revisit some of the basic MPC operations such as real-valued polynomial evaluation, division, logarithm, exponential and comparison by employing our modular lift in combination with existing efficient conversions between arithmetic, Boolean and Yao shares. Furthermore, we provide a highly efficient and scalable implementation supporting logistic regression models with real-world training data sizes and high numerical precision through PCA and blockwise variants (for memory and runtime optimizations). On a dataset of 50 million rows and 50 columns distributed among two players, it completes in one day with at least 10 decimal digits of precision.Our logistic regression solution placed first at Track 3 of the annual iDASH’2020 Competition. Finally, we mention a novel oblivious sorting algorithm built using Manticore

Development and validation of a prognostic model for the early identification of COVID-19 patients at risk of developing common long COVID symptoms

Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. The data set was split into a derivation and a geographical validation cohort. Predictors were selected out of twelve candidate predictors based on three methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total, 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation cohort. The same predictors were selected with the ABE and ABESS approach. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding scaled Brier score in the validation cohort was 18.74%, model discrimination was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). Conclusion: The proposed model was validated to identify COVID-19-infected patients at high risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended. Keywords: Clinical prediction model; Long COVID; Prognostic factors; Stratified medicin

Impact of sex and gender on post-COVID-19 syndrome, Switzerland, 2020

Background: Women are overrepresented among individuals with post-acute sequelae of SARS-CoV-2 infection (PASC). Biological (sex) as well as sociocultural (gender) differences between women and men might account for this imbalance, yet their impact on PASC is unknown. Aim: We assessed the impact of sex and gender on PASC in a Swiss population. Method: Our multicentre prospective cohort study included 2,856 (46% women, mean age 44.2 ± 16.8 years) outpatients and hospitalised patients with PCR-confirmed SARS-CoV-2 infection.ResultsAmong those who remained outpatients during their first infection, women reported persisting symptoms more often than men (40.5% vs 25.5% of men; p < 0.001). This sex difference was absent in hospitalised patients. In a crude analysis, both female biological sex (RR = 1.59; 95% CI: 1.41-1.79; p < 0.001) and a score summarising gendered sociocultural variables (RR = 1.05; 95% CI: 1.03-1.07; p < 0.001) were significantly associated with PASC. Following multivariable adjustment, biological female sex (RR = 0.96; 95% CI: 0.74-1.25; p = 0.763) was outperformed by feminine gender-related factors such as a higher stress level (RR = 1.04; 95% CI: 1.01-1.06; p = 0.003), lower education (RR = 1.16; 95% CI: 1.03-1.30; p = 0.011), being female and living alone (RR = 1.91; 95% CI: 1.29-2.83; p = 0.001) or being male and earning the highest income in the household (RR = 0.76; 95% CI: 0.60-0.97; p = 0.030). Conclusion: Specific sociocultural parameters that differ in prevalence between women and men, or imply a unique risk for women, are predictors of PASC and may explain, at least in part, the higher incidence of PASC in women. Once patients are hospitalised during acute infection, sex differences in PASC are no longer evident

Evaluation of Different Recruitment Methods: Longitudinal, Web-Based, Pan-European Physical Activity Through Sustainable Transport Approaches (PASTA) Project

BACKGROUND: Sufficient sample size and minimal sample bias are core requirements for empirical data analyses. Combining opportunistic recruitment with a Web-based survey and data-collection platform yields new benefits over traditional recruitment approaches. OBJECTIVE: This paper aims to report the success of different recruitment methods and obtain data on participants' characteristics, participation behavior, recruitment rates, and representativeness of the sample. METHODS: A longitudinal, Web-based survey was implemented as part of the European PASTA (Physical Activity through Sustainable Transport Approaches) project, between November 2014 and December 2016. During this period, participants were recruited from 7 European cities on a rolling basis. A standardized guide on recruitment strategy was developed for all cities, to reach a sufficient number of adult participants. To make use of the strengths and minimize weakness, a combination of different opportunistic recruitment methods was applied. In addition, the random sampling approach was applied in the city of Örebro. To reduce the attrition rate and improve real-time monitoring, the Web-based platform featured a participant's and a researchers' user interface and dashboard. RESULTS: Overall, 10,691 participants were recruited; most people found out about the survey through their workplace or employer (2300/10691, 21.51%), outreach promotion (2219/10691, 20.76%), and social media (1859/10691, 17.39%). The average number of questionnaires filled in per participant varied significantly between the cities (P<.001), with the highest number in Zurich (11.0, SE 0.33) and the lowest in Örebro (4.8, SE 0.17). Collaboration with local organizations, the use of Facebook and mailing lists, and direct street recruitment were the most effective approaches in reaching a high share of participants (P<.001). Considering the invested working hours, Facebook was one of the most time-efficient methods. Compared with the cities' census data, the composition of study participants was broadly representative in terms of gender distribution; however, the study included younger and better-educated participants. CONCLUSIONS: We observed that offering a mixed recruitment approach was highly effective in achieving a high participation rate. The highest attrition rate and the lowest average number of questionnaires filled in per participant were observed in Örebro, which also recruited participants through random sampling. These findings suggest that people who are more interested in the topic are more willing to participate and stay in a survey than those who are selected randomly and may not have a strong connection to the research topic. Although direct face-to-face contacts were very effective with respect to the number of recruited participants, recruiting people through social media was not only effective but also very time efficient. The collected data are based on one of the largest recruited longitudinal samples with a common recruitment strategy in different European cities

Association between depression and anxiety on symptom and function after surgery for lumbar spinal stenosis.

Evidence on the role of depression and anxiety in patients undergoing surgical treatment for symptomatic degenerative lumbar spinal stenosis (DLSS) is conflicting. We aimed to assess the association between depression and anxiety with symptoms and function in patients undergoing surgery for DLSS. Included were patients with symptomatic DLSS participating in a prospective multicentre cohort study who underwent surgery and completed the 24-month follow-up. We used the hospital anxiety and depression scale (HADS) to assess depression/anxiety. We used mixed-effects models to quantify the impact on the primary outcome change in the spinal stenosis measure (SSM) symptoms/function subscale from baseline to 12- and 24-months. Logistic regression analysis was used to quantify the odds of the SSM to reach a minimal clinically important difference (MCID) at 24 months follow-up. The robustness of the results in the presence of unmeasured confounding was quantified using a benchmarking method based on a multiple linear model. Out of 401 patients 72 (17.95%) were depressed and 80 anxious (19.05%). Depression was associated with more symptoms (β = 0.36, 95% confidence interval (CI) 0.20 to 0.51, p < 0.001) and worse function (β = 0.37, 95% CI 0.24 to 0.50, p < 0.001) at 12- and 24-months. Only the association between baseline depression and SSM symptoms/function was robust at 12 and 24 months. There was no evidence for baseline depression/anxiety decreasing odds for a MCID in SSM symptoms and function over time. In patients undergoing surgery for symptomatic DLSS, preoperative depression but not anxiety was associated with more severe symptoms and disability at 12 and 24 months

On-site multi-component intervention to improve productivity and reduce the economic and personal burden of neck pain in Swiss office-workers (NEXpro): protocol for a cluster-randomized controlled trial

BACKGROUND: Non-specific neck pain and headache are major economic and individual burden in office-workers. The aim of this study is to investigate the effect of a multi-component intervention combining workstation ergonomics, health promotion information group workshops, neck exercises, and an app to enhance intervention adherence to assess possible reductions in the economic and individual burden of prevalent and incident neck pain and headache in office workers. METHODS/DESIGN: This study is a stepped wedge cluster-randomized controlled trial. Eligible participants will be any office-worker aged 18-65 years from two Swiss organisations in the Cantons of Zurich and Aargau, working more than 25 h a week in predominantly sedentary office work and without serious health conditions of the neck. One hundred twenty voluntary participants will be assigned to 15 clusters which, at randomly selected time steps, switch from the control to the intervention group. The intervention will last 12 weeks and comprises workstation ergonomics, health promotion information group workshops, neck exercises and an adherence app. The primary outcome will be health-related productivity losses (presenteeism, absenteeism) using the Work Productivity and Activity Impairment Questionnaire. Secondary outcomes are neck disability and pain (measured by the Neck Disability Index, and muscle strength and endurance measures), headache (measured by the short-form headache impact test), psychosocial outcomes (e.g. job-stress index, Fear-Avoidance Beliefs Questionnaire), workplace outcomes (e.g. workstation ergonomics), adherence to intervention, and additional measures (e.g. care-seeking). Measurements will take place at baseline, 4 months, 8 months, and 12 months after commencement. Data will be analysed on an intention to treat basis and per protocol. Primary and secondary outcomes will be examined using linear mixed-effects models. DISCUSSION: To the authors' knowledge, this study is the first that investigates the impact of a multi-component intervention combining current evidence of effective interventions with an adherence app to assess the potential benefits on productivity, prevalent and incident neck pain, and headache. The outcomes will impact the individual, their workplace, as well as private and public policy by offering evidence for treatment and prevention of neck pain and headache in office-workers. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04169646. Registered 15 November 2019 - Retrospectively registered

No evidence for an effect of working from home on neck pain and neck disability among Swiss office workers: Short-term impact of COVID-19

PURPOSE The aim of this study was to investigate the effect of working from home on neck pain (NP) among office workers during the COVID-19 pandemic. METHODS Participants from two Swiss organisations, aged 18-65 years and working from home during the lockdown (n = 69) were included. Baseline data collected in January 2020 before the lockdown (office work) were compared with follow-up data in April 2020 during lockdown (working from home). The primary outcome of NP was assessed with a measure of intensity and disability. Secondary outcomes were quality of workstation ergonomics, number of work breaks, and time spent working at the computer. Two linear mixed effects models were fitted to the data to estimate the change in NP. RESULTS No clinically relevant change in the average NP intensity and neck disability was found between measurement time points. Each working hour at the computer increased NP intensity by 0.36 points (95% CI: 0.09 to 0.62) indicating strong evidence. No such effect was found for neck disability. Each work break taken reduced neck disability by 2.30 points (95% CI:  - 4.18 to  - 0.42, evidence). No such effect was found for NP intensity. There is very strong evidence that workstation ergonomics was poorer at home. CONCLUSION The number of work breaks and hours spent at the computer seem to have a greater effect on NP than the place of work (office, at home), measurement time point (before COVID-19, during lockdown) or the workstation ergonomics. Further research should investigate the effect of social and psychological factors. TRIAL REGISTRATION ClinicalTrials.gov, NCT04169646. Registered 15 November 2019-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04169646

Effectiveness of a Brief Hypnotic Induction in Third Molar Extraction: A Randomized Controlled Trial (HypMol)

Third molar extraction is a painful treatment for patients, and thus, it can be used to investigate the effects of analgesics on pain. Hypnosis can help to reduce pain and to decrease the intake of postoperative systemic analgesics. In this study, the effectiveness of a brief hypnotic induction for patients undergoing third molar extractions was investigated. Data were collected from 33 patients with third molar extractions on the right and left sides. Patients received 2 different types of pain interventions in this monocentric randomized crossover trial. Third molar extraction was conducted on 1 side with reduced preoperative local anesthetics and an additional brief hypnotic induction (Dave Elman technique). The other side was conducted with regular preoperative local anesthetics without a brief hypnotic induction (standard care). Intake of postoperative systemic analgesics was allowed in both treatments. Patients' expectations about hypnosis were assessed at baseline. The primary outcome was the area under the curve with respect to ground of pain intensity after the treatment. Secondary outcomes were the amount of postoperative analgesics consumed and the preferred treatment. There was no evidence that the area under the curve with respect to ground of pain differed between the 2 interventions (controlling for gender), but the patients' expectations affected the effectiveness of the brief hypnotic induction. This means that patients with high expectations about hypnosis benefit more from treatment with reduced preoperative local anesthetics and additional brief hypnotic induction. Perspective: Hypnosis is used as a treatment to reduce pain in general and dental settings. In this study, additional a brief hypnotic induction with reduced preoperative local anesthetic use did not generally reduce posttreatment pain after third molar extraction more than regular local anesthetics. The expectation of the patients about the effectiveness of hypnosis affected the effectiveness of the brief hypnotic induction so that patients with high expectations had a larger benefit from a brief hypnotic induction than patients with low expectations. Keywords: Dental pain; clinical trial; expectations; hypnosis; surgery

No evidence for an effect of working from home on neck pain and neck disability among Swiss office workers: Short-term impact of COVID-19

Purpose: The aim of this study was to investigate the effect of working from home on neck pain (NP) among office workers during the COVID-19 pandemic. Methods: Participants from two Swiss organisations, aged 18–65 years and working from home during the lockdown (n = 69) were included. Baseline data collected in January 2020 before the lockdown (office work) were compared with follow-up data in April 2020 during lockdown (working from home). The primary outcome of NP was assessed with a measure of intensity and disability. Secondary outcomes were quality of workstation ergonomics, number of work breaks, and time spent working at the computer. Two linear mixed effects models were fitted to the data to estimate the change in NP. Results: No clinically relevant change in the average NP intensity and neck disability was found between measurement time points. Each working hour at the computer increased NP intensity by 0.36 points (95% CI: 0.09 to 0.62) indicating strong evidence. No such effect was found for neck disability. Each work break taken reduced neck disability by 2.30 points (95% CI: − 4.18 to − 0.42, evidence). No such effect was found for NP intensity. There is very strong evidence that workstation ergonomics was poorer at home. Conclusion: The number of work breaks and hours spent at the computer seem to have a greater effect on NP than the place of work (office, at home), measurement time point (before COVID-19, during lockdown) or the workstation ergonomics. Further research should investigate the effect of social and psychological factors. Trial registration: ClinicalTrials.gov, NCT04169646. Registered 15 November 2019—Retrospectively registered, https://clini caltr ials. gov/ ct2/ show/ NCT04 169646