Background: In a hospital setting and among older patients, inactivity and bedrest are associated with a wide range of negative outcomes such as functional decline, increased risk of falls, longer hospitalization and institutionalization. Our aim was to assess the distribution, determinants and predictors of physical activity (PA) levels using wrist-worn accelerometers in older patients hospitalized with acute medical illness. Methods: Observational study conducted from February to November 2018 at an acute internal medicine unit in the University hospital of Lausanne, Switzerland. We enrolled 177 patients aged ≥65 years, able to walk prior to admission. PA during acute hospital stay was continuously recorded via a 3D wrist accelerometer. Clinical data was collected from medical records or by interview. Autonomy level prior to inclusion was assessed using Barthel Index score. PA levels were defined as < 30 mg for inactivity, 30–99 mg for light and ≥ 100 for moderate PA. Physically active patients were defined as 1) being in the highest quartile of time spent in light and moderate PA or 2) spending ≥20 min/day in moderate PA. Results: Median [interquartile range - IQR] age was 83 [74–87] years and 60% of participants were male. The median [IQR] time spent inactive and in light PA was 613 [518–663] and 63 [30–97] minutes/day, respectively. PA peaked between 8 and 10 am, at 12 am and at 6 pm. Less than 10% of patients were considered physically active according to definition 2. For both definitions, active patients had a lower prevalence of walking aids and a lower dependency level according to Barthel Index score. For definition 1, use of medical equipment was associated with a 70% reduction in the likelihood of being active: odds ratio (OR) 0.30 [0.10–0.92] p = 0.034; for definition 2, use of walking aids was associated with a 75% reduction in the likelihood of being active: OR = 0.24 [0.06–0.89], p = 0.032. Conclusion: Older hospitalized patients are physically active only 10% of daily time and concentrate their PA around eating periods. Whether a Barthel Index below 95 prior to admission may be used to identify patients at risk of inactivity during hospital stay remains to be proven.

Background: Hospital-acquired venous thromboembolism (VTE) is one of the leading preventable causes of in-hospital mortality. However, its risk assessment in medically ill inpatients is complicated due to the patients’ heterogeneity and complexity of currently available risk assessment models (RAMs). The simplified Geneva score provides simplicity but has not yet been prospectively validated. Immobility is an important predictor for VTE in RAMs, but its definition is inconsistent and based on subjective assessment by nurses or physicians. In this study, we aim to prospectively validate the simplified Geneva score and to examine the predictive performance of a novel and objective definition of in-hospital immobilization using accelerometry.Methods and analysis: RISE is a multicenter prospective cohort study. The goal is to recruit 1350 adult inpatients admitted for medical illness in three Swiss tertiary care hospitals. We collect data on demographics, comorbidities, VTE risk and thromboprophylaxis. Mobility from admission to discharge is objectively measured using a wrist-worn accelerometer. Participants are followed for 90 days for the occurrence of symptomatic VTE (primary outcome). Secondary outcomes are the occurrence of clinically relevant bleeding, and mortality. The evolution of autonomy in the activities of daily living, the length of stay, and the occurrence of readmission are also recorded. Time-dependent area under the curve, sensitivity, specificity, and positive and negative predictive values are calculated for each RAM (i.e. the simplified and original Geneva score, Padua, and IMPROVE score) with and without the objective mobility measures to assess their accuracy in predicting hospital-acquired VTE at 90 days.Ethics and expected impact: The ethics committee approved the protocol and the study was registered on ClinicalTrials.gov asNCT04439383. RISE has the potential to optimize VTE risk stratification, and thus to improve the quality of care of medically hospitalized patients.

Many countries lack resources to identify patients at risk of developing Type 2 diabetes mellitus (diabetes). We aimed to develop and validate a diabetes risk score based on easily accessible clinical data. Prospective study including 5277 participants (55.0% women, 51.8±10.5 years) free of diabetes at baseline. Comparison with two other published diabetes risk scores (Balkau and Kahn clinical, respectively 5 and 8 variables) and validation on three cohorts (Europe, Iran and Mexico) was performed. After a mean follow-up of 10.9 years, 405 participants (7.7%) developed diabetes. Our score was based on age, gender, waist circumference, diabetes family history, hypertension and physical activity. The area under the curve (AUC) was 0.772 for our score, vs. 0.748 (p<0.001) and 0.774 (p = 0.668) for the other two. Using a 13-point threshold, sensitivity, specificity, positive and negative predictive values (95% CI) of our score were 60.5 (55.5–65.3), 77.1 (75.8–78.2), 18.0 (16.0–20.1) and 95.9 (95.2–96.5) percent, respectively. Our score performed equally well or better than the other two in the Iranian [AUC 0.542 vs. 0.564 (p = 0.476) and 0.513 (p = 0.300)] and Mexican [AUC 0.791 vs. 0.672 (p<0.001) and 0.778 (p = 0.575)] cohorts. In the European cohort, it performed similarly to the Balkau score but worse than the Kahn clinical [AUC 0.788 vs. 0.793 (p = 0.091) and 0.816 (p<0.001)]. Diagnostic capacity of our score was better than the Balkau score and comparable to the Kahn clinical one. Our clinically-based score shows encouraging results compared to other scores and can be used in populations with differing diabetes prevalence.

Background: The association of physical activity (PA) and lung function (LF) varies from no measurable effect to delayed LF decline. We assessed the association between accelerometery-assessed PA and LF in a sample of apparently healthy, community-dwelling subjects. Methods: We included two cross-sectional studies using data from the PneumoLaus study (2014–17 and 2018–21), conducted in Lausanne, Switzerland. PA was assessed by accelerometry and categorised as inactivity, light, moderate or vigorous. Forced expiratory volume in 1 second (FEV₁), forced volume capacity (FVC) and maximal mid-expiratory flow (MMEF) were measured by spirometry and expressed in percentage of predicted value (PV). Results: Overall, 1′910 (54.7% women, 62.0 ± 9.7 years) and 1′174 (53.4% women, 65.8 ± 9.5 years) participants were included in the first and the second surveys, respectively. In both surveys, moderate and vigorous PA showed a weak but significant correlation with FEV₁ in percentage (PV) (R = 0.106 and 0.132 for the first and 0.111 and 0.125 for the second surveys, p < 0.001). Similar correlations with FVC (p < 0.001) were found. Associations held irrespective of smoking status and remained after multivariable adjustment. Fewer associations were detected between LF and light PA or between MMEF and PA. Conclusion: Moderate and vigorous intensity PA are associated with increased LF regardless of smoking status in apparently healthy community-dwelling European population. These associations are statistically but not clinically significant due to the small correlation coefficients (R < 0.30), corresponding to a weak association.

Aim: To assess the validity of seven type 2 diabetes mellitus (T2DM) risk scores in predicting the 10-year incidence of T2DM in a Swiss population-based study. Methods: The prospective study included 5131 participants (55% women, age range 35 to 75 years) living in Lausanne, Switzerland. The baseline survey was conducted between 2003 and 2006, and the average follow-up was 10.9 years. Five clinically-based scores (the Balkau, Kahn clinical, Griffin, Swiss Diabetes Association [SDAS], and Finnish Diabetes Risk Score [FINDRISC]) and two clinically and biologically based scores (the Kahn CB and Wilson) were tested. Results: 405 (7.9%) participants developed T2DM. The overall prevalence of participants at high risk ranged from 13.7% for the Griffin score to 43.3% for the Balkau score. The prevalence of participants at high risk among those who developed T2DM ranged from 34.6% for the Griffin score to 82.0% for the Kahn CB score. The Kahn CB score had the highest area under the ROC (value and 95% confidence interval: 0.866 [0.849–0.883]), followed by the FINDRISC (0.818 [0.798–0.838]), while the Griffin score had the lowest (0.740 [0.718–0.762]). Sensitivities and specificities were above 70%, except for the Griffin and the Kahn C scores (for sensitivity) and the Balkau score (for specificity). The numbers needed to screen ranged from 15.5 for the Kahn CB score to 36.7 for the Griffin score. Conclusion: The Kahn CB and the FINDRISC scores performed the best out of all the scores. The FINDRISC score could be used in an epidemiological setting, while the need for blood sampling for the Kahn CB score restricts its use to a more clinical setting.

Aim: To assess whether the Mediterranean diet (MD) is associated with lower levels of type 2 diabetes (T2D) in a non-Mediterranean population. Methods: Cross-sectional analysis of follow-ups 1 (FU1, 2009–2012, n = 4398, 45.7% men, 57.7 ± 10.5 years), 2 (FU2, 2014–2017, n = 3154, 45.0% men, 61.7 ± 9.9 years), and 3 (FU3, 2018–2021, n = 2394, 45.2% men, 65.0 ± 9.6 years) of the Colaus|PsyCoLaus study (Lausanne, Switzerland). Two MD scores (Trichopoulou, noted MD1, and Sofi, noted MD2) were calculated using participants’ dietary data. T2D was defined as a fasting plasma glucose ≥7 mmol/L and/or the presence of an antidiabetic drug treatment. Results: Participants with the highest MD adherence had a higher educational level, a lower BMI, were less frequent smokers, presented less frequently with hypertension, and were more frequent alcohol consumers. After multivariable adjustment, no differences were found between participants with and without T2D regarding MD scores: 3.93 ± 0.07 vs. 3.97 ± 0.02; 4.08 ± 0.10 vs. 3.98 ± 0.03, and 3.83 ± 0.11 vs. 3.97 ± 0.03, respectively, for the MD1 score in FU1, FU2, and FU3. In addition, no association was found between adherence to MD and T2D: odds ratio (and 95% confidence interval) for medium and high relative to low adherence to MD1: 0.87 (0.68–1.10) and 0.89 (0.64–1.24) in FU1, 1.04 (0.76–1.42) and 1.07 (0.68–1.67) in FU2, and 0.73 (0.53–1.03) and 0.61 (0.37–1.02) in FU3, respectively. Corresponding results for MD2 were 0.90 (0.70–1.15) and 1.03 (0.69–1.53) in FU1, 1.16 (0.82–1.63) and 1.40 (0.81–2.41) in FU2, and 0.93 (0.65–1.34) and 0.55 (0.28–1.08) in FU3. Conclusion: We found no association between Mediterranean diet adherence and T2D in a non-Mediterranean population.