Utility of MRI for Patients 45 Years Old and Older With Hip or Knee Pain: A Systematic Review

Background: MRI utility for patients 45 years old and older with hip or knee pain is not well established. Objective: We performed this systematic review to assess whether MRI-diagnosed hip or knee pathology in patients 45 years old and older correlates with symptomatology or benefits from arthroscopic surgery. Evidence Acquisition: A literature search (PubMed, Web of Science, Embase) was performed through October 3, 2022, to identify original research pertaining to the study question. Publication information, study design, cohort size, osteoarthritis severity, age (range, mean), measured outcomes, minimum follow-up length, and MRI field strength were extracted. Study methods were appraised with NIH Quality Assessment Tools. Evidence Synthesis: The search yielded 1125 potential studies, of which 31 met inclusion criteria (18 knee, 13 hip). Knee studies (10 prospective, eight retrospective) included 5907 patients (age range, 45-90 years). Bone marrow edemalike lesions, joint effusions, and synovitis on MRI were associated with symptoms. In patients with osteoarthritis, meniscal tears were less likely to be symptom generators and were less likely to respond to arthroscopic surgery with osteoarthritis progression. Hip studies (11 retrospective, two prospective) included 6385 patients (age range, 50-85 years). Patients with Tonnis grade 2 osteoarthritis and lower with and without femoroacetabular impingement showed improved outcomes after arthroscopy, suggesting a role for MRI in the diagnosis of labral tears, chondral lesions, and femoroacetabular impingement. Although this group benefited from arthroscopic surgery, outcomes were inferior to those in younger patients. Variability in study characteristics, follow-up, and outcome measures precluded a meta-analysis. Conclusion: In patients 45 years old and older, several knee structural lesions on MRI correlated with symptoms, representing potential imaging biomarkers. Meniscal tear identification on MRI likely has diminished clinical value as osteoarthritis progresses. For the hip, MRI can play a role in the diagnosis of labral tears, chondral lesions, and femoroacetabular impingement in patients without advanced osteoarthritis. Clinical Impact: Several structural lesions on knee MRI correlating with symptoms may represent imaging biomarkers used as treatment targets. Osteoarthritis, not age, may play the greatest role in determining utility of MRI for patients 45 years old and older with hip or knee pain.

Bone Density Screening Rates Among Medicare Beneficiaries: An Analysis with a focus on Asian Americans

PURPOSE

To report osteoporosis screening utilization rates among Asian American (AsA) populations in the USA.

METHODS

We retrospectively assessed the use of dual-energy X-ray absorptiometry (DXA) screening using the Medicare 5% Research Identifiable Files. Using Current Procedural Terminology (CPT) codes indicative of a DXA scan, we identified patients recommended for DXA screening according to the ACR-SPR-SSR Practice Parameters (females ≥ 65 years, males ≥ 70 years). Sociodemographic factors and their association with screening were evaluated using chi-square tests.

RESULTS

There were 80,439 eligible AsA beneficiaries, and 12,102 (15.1%) received osteoporosis screening. DXA rate for women was approximately four times greater than the rate for men (19.8% vs. 5.0%; p < 0.001). AsA beneficiaries in zip codes with higher mean household income (MHI) were more likely to have DXA than those in lower MHI areas (17.6% vs. 14.3%, p < 0.001). AsA beneficiaries aged < 80 were more likely to receive DXA (15.5%) than those aged ≥ 80 (14.1%, p < 0.001). There were 2,979,801 eligible non-AsA beneficiaries, and 496,957 (16.7%) received osteoporosis screening during the study period. Non-Hispanic white beneficiaries had the highest overall screening rate (17.5%), followed by North American Native (13.0%), Black (11.8%), and Hispanic (11.1%) beneficiaries. Comparing AsA to non-AsA populations, there were significantly lower DXA rates among AsA beneficiaries when controlling for years of Medicare eligibility, patient age, sex, location, and mean income (p < 0.001).

CONCLUSION

We found lower than expected DXA screening rates for AsA patients. A better understanding of the barriers and facilitators to AsA osteoporosis screening is needed to improve patient care.

Common treatment strategies for calcium hydroxyapatite deposition disease: a cost-effectiveness analysis

OBJECTIVE

To determine the cost-effectiveness of rotator cuff hydroxyapatite deposition disease (HADD) treatments.

METHOD

A 1-year time horizon decision analytic model was created from the US healthcare system perspective for a 52-year-old female with shoulder HADD failing conservative management. The model evaluated the incremental cost-effectiveness ratio (ICER) and net monetary benefit (NMB) of standard strategies, including conservative management, ultrasound-guided barbotage (UGB), high- and low-energy extracorporeal shock wave therapy (ECSW), and surgery. The primary effectiveness outcome was quality-adjusted life years (QALY). Costs were estimated in 2022 US dollars. The willingness-to-pay (WTP) threshold was $100,000.

RESULTS

For the base case, UGB was the preferred strategy (0.9725 QALY, total cost, $2199.35, NMB, $95,048.45, and ICER, $33,992.99), with conservative management (0.9670 QALY, NMB $94,688.83) a reasonable alternative. High-energy ECSW (0.9837 QALY, NMB $94,805.72), though most effective, had an ICER of $121, 558.90, surpassing the WTP threshold. Surgery (0.9532 QALY, NMB $92,092.46) and low-energy ECSW (0.9287 QALY, NMB $87,881.20) were each dominated. Sensitivity analysis demonstrated that high-energy ECSW would become the favored strategy when its cost was < $2905.66, and conservative management was favored when the cost was < $990.34. Probabilistic sensitivity analysis supported the base case results, with UGB preferred in 43% of simulations, high-energy ECSW in 36%, conservative management in 20%, and low-energy ECSW and surgery in < 1%.

CONCLUSION

UGB appears to be the most cost-effective strategy for patients with HADD, while surgery and low-energy ECSW are the least cost-effective. Conservative management may be considered a reasonable alternative treatment strategy in the appropriate clinical setting.

Bone Marrow Biopsies: Is CT, Fluoroscopy, or no Imaging Guidance the Most Cost-Effective Strategy?

RATIONALE AND OBJECTIVES

To determine the most cost-effective strategy for pelvic bone marrow biopsies.

MATERIALS AND METHODS

A decision analytic model from the health care system perspective for patients with high clinical concern for multiple myeloma (MM) was used to evaluate the incremental cost-effectiveness of three bone marrow core biopsy techniques: computed tomography (CT) guided, and fluoroscopy guided, no-imaging (landmark-based). Model input data on utilities, costs, and probabilities were obtained from comprehensive literature review and expert opinion. Costs were estimated in 2023 U.S. dollars. Primary effectiveness outcome was quality adjusted life years (QALY). Willingness to pay threshold was $100,000 per QALY gained.

RESULTS

No-imaging based biopsy was the most cost-effective strategy as it had the highest net monetary benefit ($4218) and lowest overall cost ($92.17). Fluoroscopy guided was excluded secondary to extended dominance. CT guided biopsies were less preferred as it had an incremental cost-effectiveness ratio ($334,043) greater than the willingness to pay threshold. Probabilistic sensitivity analysis found non-imaging based biopsy to be the most cost-effective in 100% of simulations and at all willingness to pay thresholds up to $200,000.

CONCLUSION

No-imaging based biopsy appears to be the most cost-effective strategy for bone marrow core biopsy in patients suspected of MM.

CLINICAL RELEVANCE

No imaging guidance is the preferred strategy, although image-guidance may be required for challenging anatomy. CT image interpretation may be helpful for planning biopsies. Establishing a non-imaging guided biopsy service with greater patient anxiety and pain support may be warranted.

Outcomes of imaging-guided corticosteroid injections in hip and knee osteoarthritis patients: a systematic review

PURPOSE

The purpose of this systematic review is to evaluate the current literature on the use of image-guided corticosteroid injections in the treatment of patients with knee and hip OA.

EVIDENCE ACQUISITION

We conducted a comprehensive literature search through June 30, 2022. Publication type, study design, imaging guidance modality, osteoarthritis severity, number of injections, steroid type and dose, anesthetic type and dose, the total number of patients, follow-up intervals, and measured outcomes were extracted from the included studies.

EVIDENCE SYNTHESIS

There were 23 included studies (10 hips, 12 knees, 1 both hip and knee). Hip injections were found to be effective in treating short- and long-term pain and more effective than hyaluronic acid, Mepivacaine, NSAIDs, and normal saline in terms of improvement in pain and/or function. There was less impact on QoL. Knee injections were found either to have little or no impact or were similar or inferior to comparison injections (intra-articular hyaluronic acid, PRP, NSAIDs, normal saline, adductor canal blocks). Study data could not be aggregated because the corticosteroid types and doses, methods of outcome assessment, and follow-up time points varied widely.

CONCLUSION

Our systematic review found generally positive outcomes for the hip, but overall negative outcomes for the knee, although hip injections may carry a risk of serious adverse outcomes. A larger trial with uniform methodology is warranted. Specific studies on the adverse effects of corticosteroid injections are also warranted.

Decoding information about cognitive health from the brainwaves of sleep

Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson's r = 0.37) and fluid cognition (Pearson's r = 0.56), while BAI correlated only with crystallized cognition (Pearson's r = - 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.

High prevalence of sleep-disordered breathing in the intensive care unit - a cross-sectional study

PURPOSE

Sleep-disordered breathing may be induced by, exacerbate, or complicate recovery from critical illness. Disordered breathing during sleep, which itself is often fragmented, can go unrecognized in the intensive care unit (ICU). The objective of this study was to investigate the prevalence, severity, and risk factors of sleep-disordered breathing in ICU patients using a single respiratory belt and oxygen saturation signals.

METHODS

Patients in three ICUs at Massachusetts General Hospital wore a thoracic respiratory effort belt as part of a clinical trial for up to 7 days and nights. Using a previously developed machine learning algorithm, we processed respiratory and oximetry signals to measure the 3% apnea-hypopnea index (AHI) and estimate AH-specific hypoxic burden and periodic breathing. We trained models to predict AHI categories for 12-h segments from risk factors, including admission variables and bio-signals data, available at the start of these segments.

RESULTS

Of 129 patients, 68% had an AHI ≥ 5; 40% an AHI > 15, and 19% had an AHI > 30 while critically ill. Median [interquartile range] hypoxic burden was 2.8 [0.5, 9.8] at night and 4.2 [1.0, 13.7] %min/h during the day. Of patients with AHI ≥ 5, 26% had periodic breathing. Performance of predicting AHI-categories from risk factors was poor.

CONCLUSIONS

Sleep-disordered breathing and sleep apnea events while in the ICU are common and are associated with substantial burden of hypoxia and periodic breathing. Detection is feasible using limited bio-signals, such as respiratory effort and SpO2 signals, while risk factors were insufficient to predict AHI severity.

Sleep staging in the ICU with heart rate variability and breathing signals. An exploratory cross-sectional study using deep neural networks

Introduction: To measure sleep in the intensive care unit (ICU), full polysomnography is impractical, while activity monitoring and subjective assessments are severely confounded. However, sleep is an intensely networked state, and reflected in numerous signals. Here, we explore the feasibility of estimating conventional sleep indices in the ICU with heart rate variability (HRV) and respiration signals using artificial intelligence methods Methods: We used deep learning models to stage sleep with HRV (through electrocardiogram) and respiratory effort (through a wearable belt) signals in critically ill adult patients admitted to surgical and medical ICUs, and in age and sex-matched sleep laboratory patients Results: We studied 102 adult patients in the ICU across multiple days and nights, and 220 patients in a clinical sleep laboratory. We found that sleep stages predicted by HRV- and breathing-based models showed agreement in 60% of the ICU data and in 81% of the sleep laboratory data. In the ICU, deep NREM (N2 + N3) proportion of total sleep duration was reduced (ICU 39%, sleep laboratory 57%, p < 0.01), REM proportion showed heavy-tailed distribution, and the number of wake transitions per hour of sleep (median 3.6) was comparable to sleep laboratory patients with sleep-disordered breathing (median 3.9). Sleep in the ICU was also fragmented, with 38% of sleep occurring during daytime hours. Finally, patients in the ICU showed faster and less variable breathing patterns compared to sleep laboratory patients Conclusion: The cardiovascular and respiratory networks encode sleep state information, which, together with artificial intelligence methods, can be utilized to measure sleep state in the ICU.

Optimal spindle detection parameters for predicting cognitive performance

STUDY OBJECTIVES

Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition.

METHODS

Adult patients (n = 167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores.

RESULTS

Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r = 0.503) and age-adjusted fluid cognition scores (r = 0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings.

CONCLUSIONS

Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

666 Sleep Architecture in the Intensive Care Unit As Revealed via Breathing and Heart Rate Variability

Introduction

Sleep in the intensive care unit (ICU) is difficult to measure by conventional polysomnography. We investigated the feasibility of assessing sleep state from readily available ICU signals: heart rate variability (HRV) from electrocardiography and breathing from a wearable respiratory band. We compared findings with an age and sex matched sleep laboratory group.

Methods

As part of a clinical trial, 102 adult non-ventilated patients in three ICUs in the Massachusetts General Hospital wore a respiratory band. Both heart rate variability (RR-intervals) from ECG, and breathing (respiratory effort waveforms) data for up to seven days per patient were obtained. 220 age- and sex-matched subjects from a sleep lab cohort who wore the same respiratory effort band and ECG were selected for comparison. We staged sleep from the HRV and breathing data using previously published deep neural network models. We defined discordant sleep epochs as those where HRV- and breathing-based models disagreed. Agreement was computed for the following pairs: (R,R),(N1,N1),(N2,N2),(N3,N3),(N1,W),(N1,N2),(N2,N3).

Results

Demographics: Mean(STD) age: ICU 68(9), sleeplab 68(9); BMI: ICU 27(6), sleeplab 31(6); ICU 40% female, sleeplab 44% female; race: ICU%:Sleeplab% 90:69 White, 5:4 Black, 2:7 Asian. 34% of ICU-subjects were in a medical ICU, 66% in a surgical ICU. Mean total sleep duration in the ICU was 8.9 hours (4.5h concordant, 4.4h discordant sleep). We observed increased amounts of discordant sleep in the ICU compared with the sleeplab cohort (4.4h vs. 1h, p&lt;0.01). We found different REM sleep distributions (p&lt;0.01) with reduced median (10% vs. 20%) but elevated 90% quantile (45% vs. 26%), elevated N1(%) (41% vs. 26%, p&lt;0.05), reduced N2(%) (19 vs. 44, p&lt;0.01), and reduced N2+N3(%) (34 vs. 59, p&lt;0.05). We further observed higher mean respiratory rate (17.4 vs. 15.9 breaths per minute, p&lt;0.01), lower inter-breath-intervals (3.9 vs. 4.7 seconds per breath, p&lt;0.01), and more breathing variability than in sleeplab AHI&lt;5 group but less than in AHI&gt;15 group.

Conclusion

HRV and respiratory-based measures can assess sleep in the ICU. The findings of increased discordant sleep in the ICU might stem from limitations of the models, fundamental changes in sleep biology during critical illness, pharmaceutical drugs, sleep fragmentation, and/or associated pathology in the ICU.

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