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Purpose: This study aimed to develop machine learning methods to estimate bone mineral density and detect osteopenia/osteoporosis from conventional lumbar MRI (T1-weighted and T2-weighted images) and planar radiography in combination with clinical data and imaging parameters of the acquisition protocol., Methods: A database of 429 patients subjected to lumbar MRI, radiographs and dual-energy x-ray absorptiometry within 6 months was created from an institutional database. Several machine learning models were trained and tested (373 patients for training, 86 for testing) with the following objectives: (1) direct estimation of the vertebral bone mineral density; (2) classification of T-score lower than - 1 or (3) lower than - 2.5. The models took as inputs either the images or radiomics features derived from them, alone or in combination with metadata (age, sex, body size, vertebral level, parameters of the imaging protocol)., Results: The best-performing models achieved mean absolute errors of 0.15-0.16 g/cm 2 for the direct estimation of bone mineral density, and areas under the receiver operating characteristic curve of 0.82 (MRIs) - 0.80 (radiographs) for the classification of T-scores lower than - 1, and 0.80 (MRIs) - 0.65 (radiographs) for T-scores lower than - 2.5., Conclusions: The models showed good discriminative performances in detecting cases of low bone mineral density, and more limited capabilities for the direct estimation of its value. Being based on routine imaging and readily available data, such models are promising tools to retrospectively analyse existing datasets as well as for the opportunistic investigation of bone disorders., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The objective of the study was to assess chronotype, sleep hygiene, and sleep characteristics of Italian athletes in order to identify differences among sport disciplines (team- vs individual-sports), level of competition (Elite vs Non-Elite) and sexes. Moreover, correlations between chronotype, sleep hygiene and sleep quality were evaluated. Two hundred eighty Italian athletes (Females:113; Males:167) participated in the study. They completed the Pittsburgh Sleep Quality Index (PSQI), the Sleep Hygiene Index (SHI) and the MorningnessEveningness Questionnaire (MEQ). Among the athletes, 66.4% were intermediate-type, 21.8% were morning-type and 11.8% were evening-type. 55.4% of the sample was classified as good sleeper (PSQI<5), while 16.1% had poor sleep hygiene (SHI≥35). Females had higher total sleep time (p=0.022) than males. Individual-sports showed more morning-oriented score (p=0.001) and lower PSQI (p=0.006) and SHI (p<0.001) scores, with earlier timing of sleep (bedtime:p<0.001; wake-up time:p<0.001) compared to teamsports. Elite athletes exhibited greater sleep efficiency (p=0.009), and lower sleep latency (p=0.018) and wake after sleep onset (p=0.043) than Non-Elite athletes. Additionally, significant correlations were found between PSQI and SHI (r=0.43, p<0.001), and between MEQ and SHI (r=-0.35, p<0.001). This study yields crucial insights into the sleep behaviors of Italian athletes, revealing that nearly half of the sample were bad sleepers., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Introduction: Epimuscular fat (EF) has rarely been studied in the context of low back pain (LBP)., Research Question: This study aims to assess the presence and extent of EF in the lumbar muscles and its association with vertebral level in patients with low back disorders and to explore correlations between EF, demographics, BMI, and LBP., Material and Methods: T2 axial MRIs from L1 to L5 were manually segmented to analyze the cross-sectional area (CSA) of EF (mm 2 ), and fat infiltration (FI,%) of 40 patients (23 females, 17 males; mean age:65.9 years) with lumbar degenerative pathologies awaiting a surgical procedure. COMI, LBP, demographic, and clinical data were extracted from the institutional registry. Statistical analyses included Wilcoxon and Mann-Whitney tests for differences in EF between sides and sexes, the Friedman test for EF size differences among lumbar levels, and Spearman's correlation for associations, adjusted for BMI, age, and sex., Results: EF was found in 77.5% of subjects at L1, 92.5% at L2, 100% at L3 and L4, and 95.0% at L5. EF was significantly larger at L4 (253.1 ± 183.6 mm 2 ) and L5 (220.2 ± 194.9 mm 2 ) than at L1 (36.1 ± 37.8 mm 2 ) and L2 (72.2 ± 84.4 mm 2 ). No significant EF differences were found between sides and sexes. EF correlated strongly with BMI (r s  = 0.65,p < 0.001) and moderately with FI (r s  = 0.31,p = 0.04), though its correlation with FI was not significant after adjustment. EF did not correlate with COMI scores but correlated with LBP in the adjusted analysis (r s :0.31,p = 0.04)., Discussion and Conclusion: EF is present across all lumbar levels, with higher concentrations at L4 and L5, and a significant correlation between EF and LBP intensity was observed. The present findings are limited to a specific subset of patients with lumbar degenerative disorders who are awaiting surgical procedures., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: The aims of this cross-sectional study were to (a) assess actigraphy-based sleep parameters (total sample and gender differences), (b) assess differences in morphological parameters and physical function between short- versus normal-sleepers and poor- versus good-sleepers, and (c) assess the possible correlations between sleep variables and morphological and physical function parameters in older subjects., Methods: This study enrolled 42 healthy older participants (60-80 years). Participants completed the following clinical evaluations: (1) whole-body dual-energy X-ray absorptiometry to assess the appendicular skeletal muscle mass index; (2) magnetic resonance imaging acquisition to determine the cross-sectional muscle area of thigh muscles and intermuscular adipose tissue; (3) risk of fall assessment through the mini-Balance Evaluation Systems Test; (4) strength assessment: (a) chair stand test and (b) handgrip strength test; (5) sleep monitoring by actigraphy to assess total sleep time, sleep efficiency, wake after sleep onset, sleep latency, fragmentation index, mobile time, and subjective sleep quality., Results: 31.0% of subjects were short-sleepers (total sleep time < 6 hr), 19.1% were poor-sleepers (sleep efficiency < 85%), and gender differences were detected in mobile time (males: 15.8 ± 6.0 and females: 13.4 ± 6.8; p < .001) and fragmentation index (males: 35.3 ± 14.3 and females: 29.6 ± 14.6; p < .001); no significant differences were observed between groups (short- vs. normal-sleepers and poor- vs. good-sleepers) in morphological and physical function variables; correlation analysis showed that sleep latency negatively correlated with Mini-Balance Evaluation Systems Test (r = -.352; p = .022) and a positive correlation was detected between cross-sectional muscle area and mobile time (r = .349, p = .023)., Conclusion: No differences were observed in morphological and function parameters between good- versus poor-sleepers, those subjects with worse sleep onset latency (i.e., longer time to fall asleep) registered higher for risk of fall. The potential role of sleep in the physiological mechanisms of muscular aging must be explored through cross-sectional cohort studies with a larger population.

Background: Several systematic reviews (SRs) assessing the use of telemedicine for musculoskeletal conditions have been published in recent years. However, the landscape of evidence on multiple clinical outcomes remains unclear., Objective: We aimed to summarize the available evidence from SRs on telemedicine for musculoskeletal disorders., Methods: We conducted an umbrella review of SRs with and without meta-analysis by searching PubMed and EMBASE up to July 25, 2022, for SRs of randomized controlled trials assessing telemedicine. We collected any kind of patient-reported outcome measures (PROMs), patient-reported experience measures (PREMs), and objective measures, including direct and indirect costs. We assessed the methodological quality with the AMSTAR 2 tool (A Measurement Tool to Assess systematic Reviews 2). Findings were reported qualitatively., Results: Overall, 35 SRs published between 2015 and 2022 were included. Most reviews (n=24, 69%) were rated as critically low quality by AMSTAR 2. The majority of reviews assessed "telerehabilitation" (n=29) in patients with osteoarthritis (n=13) using PROMs (n=142 outcomes mapped with n=60 meta-analyses). A substantive body of evidence from meta-analyses found telemedicine to be beneficial or equal in terms of PROMs compared to conventional care (n=57 meta-analyses). Meta-analyses showed no differences between groups in PREMs (n=4), while objectives measures (ie, "physical function") were mainly in favor of telemedicine or showed no difference (9/13). All SRs showed notably lower costs for telemedicine compared to in-person visits., Conclusions: Telemedicine can provide more accessible health care with noninferior results for various clinical outcomes in comparison with conventional care. The assessment of telemedicine is largely represented by PROMs, with some gaps for PREMs, objective measures, and costs., Trial Registration: PROSPERO CRD42022347366; https://osf.io/pxedm/., (©Silvia Bargeri, Greta Castellini, Jacopo Antonino Vitale, Stefania Guida, Giuseppe Banfi, Silvia Gianola, Federico Pennestrì. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 02.02.2024.)