Comparison of the Physical Function Trajectories in Three Birth Cohorts of Chinese Older Adults: A 14-Year Longitudinal Study.

OBJECTIVES: It remains uncertain whether the favorable trend of reduction in physical disabilities has become reversed in the recent-born cohorts of older adults. This study aimed to compare the rate of decline with time in self-reported Instrumental Activity of Daily Living (IADL) difficulties, objective measurement of gait speed and grip strength, in three birth cohorts of Chinese older adults. DESIGN: A prospective cohort study. SETTING AND PARTICIPANTS: Four thousand Chinese older adults aged 65 years or above in three birth cohorts (1934-1938, 1929-1933, 1905-1928) were recruited from the community in Hong Kong. MEASUREMENTS: Grip strength, gait speed and IADL difficulties were measured between 2001 to 2017. Joint models were used to examine the trajectories of grip strength, gait speed and IADL difficulties over time, and the interaction effect of age-by-cohort (or also age2-by-cohort) was also examined. RESULTS: The recently born cohort (1934 - 1938) had worse grip strength and more IADL difficulties at the same age than the earlier two cohorts (1929 - 1933; 1905 - 1928). Furthermore, the most recently born cohort also followed a more rapid decline longitudinally with a greater decline observed in gait speed, grip strength and IADL difficulties for women whereas a greater decline in grip strength and IADL difficulties for men. CONCLUSIONS: The continuous improvement of physical limitations in old age may have halted and there appears to be a reversal of this favourable trend in the recent born cohort of older adults living in Hong Kong.

Human brown adipose tissue function: insights from current in vivo techniques.

The identification of brown adipose tissue (BAT) as a thermogenic organ in human adults approximately 20 years ago raised the exciting possibility of activating this tissue as a new treatment for obesity and cardiometabolic disease. [18F]Fluoro-2-deoxyglucose (18F-FDG) combined positron emission tomography and computed tomography (PET/CT) scanning is the most commonly used imaging modality to detect and quantify human BAT activity in vivo. This technique exploits the substantial glucose uptake by BAT during thermogenesis as a marker for BAT metabolism. 18F-FDG PET has provided substantial insights into human BAT physiology, including its regulatory pathways and the effect of obesity and cardiometabolic disease on BAT function. The use of alternative PET tracers and the development of novel techniques such as magnetic resonance imaging, supraclavicular skin temperature measurements, contrast-enhanced ultrasound, near-infrared spectroscopy and microdialysis have all added complementary information to improve our understanding of human BAT. However, many questions surrounding BAT physiology remain unanswered, highlighting the need for further research and novel approaches to investigate this tissue. This review critically discusses current techniques to assess human BAT function in vivo, the insights gained from these modalities and their limitations. We also discuss other promising techniques in development that will help dissect the pathways regulating human thermogenesis and determine the therapeutic potential of BAT activation.

Impact of postnatal dexamethasone timing on preterm mortality and bronchopulmonary dysplasia: a propensity score analysis.

BACKGROUND: Postnatal dexamethasone (PND) is used in high-risk preterm infants after the first week of life to facilitate extubation and prevent bronchopulmonary dysplasia (BPD) but the optimal treatment timing remains unclear. Our objective was to explore the association between the timing of PND commencement and mortality and respiratory outcomes. METHODS: This was a retrospective National Neonatal Research Database study of 84 440 premature infants born <32 weeks gestational age from 2010 to 2020 in England and Wales. Propensity score weighting analysis was used to explore the impact of PND commenced at three time-points (2-3 weeks (PND2/3), 4-5 weeks (PND4/5) and after 5 weeks (PND6+) chronological age) on the primary composite outcome of death before neonatal discharge and/or severe BPD (defined as respiratory pressure support at 36 weeks) alongside other secondary respiratory outcomes. RESULTS: 3469 infants received PND. Compared with PND2/3, infants receiving PND6+ were more likely to die and/or develop severe BPD (OR 1.68, 95% CI 1.28-2.21), extubate at later postmenstrual age (mean difference 3.1 weeks, 95% CI 2.9-3.4 weeks), potentially require respiratory support at discharge (OR 1.34, 95% CI 1.06-1.70) but had lower mortality before discharge (OR 0.38, 95% CI 0.29-0.51). PND4/5 was not associated with severe BPD or discharge respiratory support. CONCLUSIONS: PND treatment after 5 weeks of age was associated with worse respiratory outcomes although residual bias cannot be excluded. A definitive clinical trial to determine the optimal PND treatment window, based on early objective measures to identify high-risk infants, is needed.

The serotonin transporter sustains human brown adipose tissue thermogenesis.

Activation of brown adipose tissue (BAT) in humans is a strategy to treat obesity and metabolic disease. Here we show that the serotonin transporter (SERT), encoded by SLC6A4, prevents serotonin-mediated suppression of human BAT function. RNA sequencing of human primary brown and white adipocytes shows that SLC6A4 is highly expressed in human, but not murine, brown adipocytes and BAT. Serotonin decreases uncoupled respiration and reduces uncoupling protein 1 via the 5-HT2B receptor. SERT inhibition by the selective serotonin reuptake inhibitor (SSRI) sertraline prevents uptake of extracellular serotonin, thereby potentiating serotonin's suppressive effect on brown adipocytes. Furthermore, we see that sertraline reduces BAT activation in healthy volunteers, and SSRI-treated patients demonstrate no 18F-fluorodeoxyglucose uptake by BAT at room temperature, unlike matched controls. Inhibition of BAT thermogenesis may contribute to SSRI-induced weight gain and metabolic dysfunction, and reducing peripheral serotonin action may be an approach to treat obesity and metabolic disease.

Previous fracture and subsequent fracture risk: a meta-analysis to update FRAX.

A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX. INTRODUCTION: The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD). METHODS: We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture, and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD, and duration of follow-up. The results of the different studies were merged by using the weighted ß-coefficients. RESULTS: A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06), or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination. CONCLUSION: A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies.

Forehead monitoring of heart rate in neonatal intensive care.

Heart rate is an extremely important physiological parameter to measure in critically unwell infants, as it is the main physiological marker that changes in response to a change in infant condition. Heart rate is routinely measured peripherally on a limb with a pulse oximeter. However, when infants are critically unwell, the blood supply to these peripheries is reduced in preference for central perfusion of vital organs such as the brain and heart. Measurement of heart rate with a reflection mode photoplethysmogram (PPG) sensor on the forehead could help minimise this problem and make it easier for other important medical equipment, such as cannulas, to be placed on the limbs. This study compares heart rates measured with a forehead-based PPG sensor against a wrist-based PPG sensor in 19 critically unwell infants in neonatal intensive care collecting 198 h of data. The two heart rates were compared using positive percentage agreement, Spearman's correlation coefficient and Bland-Altman analysis. The forehead PPG sensor showed good agreement with the wrist-based PPG sensor with limits of agreement of 8.44 bpm, bias of -0.22 bpm; positive percentage agreement of 98.87%; and Spearman's correlation coefficient of 0.9816. The analysis demonstrates that the forehead is a reliable alternative location for measuring vital signs using the PPG.

Observational cohort study of use of caffeine in preterm infants and association between early caffeine use and neonatal outcomes.

OBJECTIVE: To quantify trends in caffeine use in infants born at <32 weeks' gestational age (GA), and to investigate the effects of early vs late caffeine on neonatal outcomes. STUDY DESIGN: Retrospective propensity score matched cohort study using routinely recorded data from the National Neonatal Research Database of infants born at <32 weeks' GA admitted to neonatal units in England and Wales (2012-2020). RESULTS: 89% (58 913/66 081) of infants received caffeine. In 70%, caffeine was started early (on the day of birth or the day after), increasing from 55% in 2012 to 83% in 2020. Caffeine was given for a median (IQR) of 28 (17-43) days starting on day 2 (1-3) and continued up to 34 (33-34) weeks postmenstrual age.In the propensity score matched cohort of 13 045 pairs of infants, the odds of preterm brain injury (early caffeine, 2306/13 045 (17.7%) vs late caffeine, 2528/13 045 (19.4%), OR=0.89 (95% CI 0.84 to 0.95)) and bronchopulmonary dysplasia (BPD) (early caffeine, 4020/13 045 (32.8%) vs late caffeine, 4694/13 045 (37.7%), OR=0.81 (95% CI 0.76 to 0.85)) were lower in the group that received early caffeine compared with those who received it later. CONCLUSIONS: Early use of caffeine has increased in England and Wales. This is associated with reduced risks of BPD and preterm brain injury. Randomised trials are needed to find the optimal timing of caffeine use and the groups of infants who will benefit most from early administration of caffeine.

Bronchopulmonary dysplasia prediction models: a systematic review and meta-analysis with validation.

Prediction models could identify infants at the greatest risk of bronchopulmonary dysplasia (BPD) and allow targeted preventative strategies. We performed a systematic review and meta-analysis with external validation of identified models. Studies using predictors available before day 14 of life to predict BPD in very preterm infants were included. Two reviewers assessed 7628 studies for eligibility. Meta-analysis of externally validated models was followed by validation using 62,864 very preterm infants in England and Wales. A total of 64 studies using 53 prediction models were included totalling 274,407 infants (range 32-156,587/study). In all, 35 (55%) studies predated 2010; 39 (61%) were single-centre studies. A total of 97% of studies had a high risk of bias, especially in the analysis domain. Following meta-analysis of 22 BPD and 11 BPD/death composite externally validated models, Laughon's day one model was the most promising in predicting BPD and death (C-statistic 0.76 (95% CI 0.70-0.81) and good calibration). Six models were externally validated in our cohort with C-statistics between 0.70 and 0.90 but with poor calibration. Few BPD prediction models were developed with contemporary populations, underwent external validation, or had calibration and impact analyses. Contemporary, validated, and dynamic prediction models are needed for targeted preventative strategies. IMPACT: This review aims to provide a comprehensive assessment of all BPD prediction models developed to address the uncertainty of which model is sufficiently valid and generalisable for use in clinical practice and research. Published BPD prediction models are mostly outdated, single centre and lack external validation. Laughon's 2011 model is the most promising but more robust models, using contemporary data with external validation are needed to support better treatments.

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology.

With the development of Artificial Intelligence techniques, smart health monitoring is becoming more popular. In this study, we investigate the trend of wearable sensors being adopted and developed in neonatal cardiorespiratory monitoring. We performed a search of papers published from the year 2000 onwards. We then reviewed the advances in sensor technologies and wearable modalities for this application. Common wearable modalities included clothing (39%); chest/abdominal belts (25%); and adhesive patches (15%). Popular singular physiological information from sensors included electrocardiogram (15%), breathing (24%), oxygen saturation and photoplethysmography (13%). Many studies (46%) incorporated a combination of these signals. There has been extensive research in neonatal cardiorespiratory monitoring using both single and multi-parameter systems. Poor data quality is a common issue and further research into combining multi-sensor information to alleviate this should be investigated. IMPACT STATEMENT: State-of-the-art review of sensor technology for wearable neonatal cardiorespiratory monitoring. Review of the designs for wearable neonatal cardiorespiratory monitoring. The use of multi-sensor information to improve physiological data quality has been limited in past research. Several sensor technologies have been implemented and tested on adults that have yet to be explored in the newborn population.

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring. Part 2: artificial intelligence.

BACKGROUND: With the development of Artificial Intelligence (AI) techniques, smart health monitoring, particularly neonatal cardiorespiratory monitoring with wearable devices, is becoming more popular. To this end, it is crucial to investigate the trend of AI and wearable sensors being developed in this domain. METHODS: We performed a review of papers published in IEEE Xplore, Scopus, and PubMed from the year 2000 onwards, to understand the use of AI for neonatal cardiorespiratory monitoring with wearable technologies. We reviewed the advances in AI development for this application and potential future directions. For this review, we assimilated machine learning (ML) algorithms developed for neonatal cardiorespiratory monitoring, designed a taxonomy, and categorised the methods based on their learning capabilities and performance. RESULTS: For AI related to wearable technologies for neonatal cardio-respiratory monitoring, 63% of studies utilised traditional ML techniques and 35% utilised deep learning techniques, including 6% that applied transfer learning on pre-trained models. CONCLUSIONS: A detailed review of AI methods for neonatal cardiorespiratory wearable sensors is presented along with their advantages and disadvantages. Hierarchical models and suggestions for future developments are highlighted to translate these AI technologies into patient benefit. IMPACT: State-of-the-art review in artificial intelligence used for wearable neonatal cardiorespiratory monitoring. Taxonomy design for artificial intelligence methods. Comparative study of AI methods based on their advantages and disadvantages.

Neonatal stroke surveillance study protocol in the United Kingdom and Republic of Ireland.

Neonatal stroke is a devastating condition that causes brain injury in babies and often leads to lifelong neurological impairment. Recent prospective population studies of neonatal stroke are lacking. Neonatal strokes are different from those in older children and adults. A better understanding of its aetiology, current management, and outcomes could reduce the burden of this rare condition. The study aims to explore the incidence and 2 year outcomes of neonatal stroke across an entire population in the UK and Republic of Ireland. This is an active national surveillance study using a purpose-built integrated case notification-data collection online platform. Over a 13 month period, with a potential 6 month extension, clinicians will notify neonatal stroke cases presenting in the first 90 days of life electronically via the online platform monthly. Clinicians will complete a primary questionnaire via the platform detailing clinical information, including neuroimaging, for analysis and classification. An outcome questionnaire will be sent at 2 years of age via the platform. Appropriate ethics and regulatory approvals have been received. The neonatal stroke study represents the first multinational population surveillance study delivered via a purpose-built integrated case notification-data collection online platform and data safe haven, overcoming the challenges of setting up the study.

Update of the fracture risk prediction tool FRAX: a systematic review of potential cohorts and analysis plan.

We describe the collection of cohorts together with the analysis plan for an update of the fracture risk prediction tool FRAX with respect to current and novel risk factors. The resource comprises 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. INTRODUCTION: The availability of the fracture risk assessment tool FRAX® has substantially enhanced the targeting of treatment to those at high risk of fracture with FRAX now incorporated into more than 100 clinical osteoporosis guidelines worldwide. The aim of this study is to determine whether the current algorithms can be further optimised with respect to current and novel risk factors. METHODS: A computerised literature search was performed in PubMed from inception until May 17, 2019, to identify eligible cohorts for updating the FRAX coefficients. Additionally, we searched the abstracts of conference proceedings of the American Society for Bone and Mineral Research, European Calcified Tissue Society and World Congress of Osteoporosis. Prospective cohort studies with data on baseline clinical risk factors and incident fractures were eligible. RESULTS: Of the 836 records retrieved, 53 were selected for full-text assessment after screening on title and abstract. Twelve cohorts were deemed eligible and of these, 4 novel cohorts were identified. These cohorts, together with 60 previously identified cohorts, will provide the resource for constructing an updated version of FRAX comprising 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. For each known and candidate risk factor, multivariate hazard functions for hip fracture, major osteoporotic fracture and death will be tested using extended Poisson regression. Sex- and/or ethnicity-specific differences in the weights of the risk factors will be investigated. After meta-analyses of the cohort-specific beta coefficients for each risk factor, models comprising 10-year probability of hip and major osteoporotic fracture, with or without femoral neck bone mineral density, will be computed. CONCLUSIONS: These assembled cohorts and described models will provide the framework for an updated FRAX tool enabling enhanced assessment of fracture risk (PROSPERO (CRD42021227266)).

Application and potential of artificial intelligence in neonatal medicine.

Neonatal care is becoming increasingly complex with large amounts of rich, routinely recorded physiological, diagnostic and outcome data. Artificial intelligence (AI) has the potential to harness this vast quantity and range of information and become a powerful tool to support clinical decision making, personalised care, precise prognostics, and enhance patient safety. Current AI approaches in neonatal medicine include tools for disease prediction and risk stratification, neurological diagnostic support and novel image recognition technologies. Key to the integration of AI in neonatal medicine is the understanding of its limitations and a standardised critical appraisal of AI tools. Barriers and challenges to this include the quality of datasets used, performance assessment, and appropriate external validation and clinical impact studies. Improving digital literacy amongst healthcare professionals and cross-disciplinary collaborations are needed to harness the full potential of AI to help take the next significant steps in improving neonatal outcomes for high-risk infants.

The association of coffee consumption with the risk of osteoporosis and fractures: a systematic review and meta-analysis.

To elucidate the association of coffee and bone health would help fracture risk reduction via dietary intervention. Although those who had higher coffee consumption were less likely to have osteoporosis, the associations between coffee consumption and fracture risk need further investigations with better study designs. INTRODUCTION: The associations between coffee consumption and the risk of osteoporosis and fracture remain inconclusive. We aimed to better quantify these associations by conducting meta-analyses of observational studies. METHODS: Relevant studies were systematically searched on PubMed, Web of Science, Cochrane library, and Embase Database up to November 25, 2021. The odds ratio (OR) or relative risk (RR) with 95% confidence intervals (CI) was pooled and a dose-response analysis was performed. RESULTS: Four studies with 7114 participants for osteoporosis and thirteen studies with 391,956 participants for fracture incidence were included in the meta-analyses. High versus low coffee consumption was associated with a lower risk of osteoporosis [pooled OR (95% CI): 0.79 (0.65-0.92)], while it was non-significantly associated with fracture incidence [pooled OR (95% CI): 0.86 (0.67-1.05) at hip and 0.89 (0.42-1.36) at non-hip]. A non-linear association between the level of coffee consumption and hip fracture incidence was shown (P = 0.004). The pooled RR (95% CI) of hip fracture risk in those who consumed 1, 2-3, 4, and ≥ 9 cups of coffee per day was 0.92 (0.87-0.97), 0.89 (0.83-0.95), 0.91 (0.85-0.98), and 1.10 (0.76-1.59), respectively. The significance in the association between coffee consumption and the hip fracture incidence decreased in those studies that had larger sample size, higher quality, and more adjustments. CONCLUSIONS: A dose-dependent relationship may exist between coffee consumption and hip fracture incidence. The effect of high versus low coffee consumption was influenced by study designs. Further studies with dedicated designs are needed to confirm the independent effects of coffee consumption on bone health.

Observational cohort study of changing trends in non-invasive ventilation in very preterm infants and associations with clinical outcomes.

OBJECTIVE: To determine the change in non-invasive ventilation (NIV) use over time in infants born at <32 weeks' gestation and the associated clinical outcomes. STUDY DESIGN: Retrospective cohort study using routinely recorded data from the National Neonatal Research Database of infants born at <32 weeks admitted to neonatal units in England and Wales from 2010 to 2017. RESULTS: In 56 537 infants, NIV use increased significantly between 2010 and 2017 (continuous positive airway pressure (CPAP) from 68.5% to 80.2% in 2017 and high flow nasal cannula (HFNC) from 14% to 68%, respectively) (p<0.001)). Use of NIV as the initial mode of respiratory support also increased (CPAP, 21.5%-28.0%; HFNC, 1%-7% (p<0.001)).HFNC was used earlier, and for longer, in those who received CPAP or mechanical ventilation. HFNC use was associated with decreased odds of death before discharge (adjusted OR (aOR) 0.19, 95% CI 0.17 to 0.22). Infants receiving CPAP but no HFNC died at an earlier median chronological age: CPAP group, 22 (IQR 10-39) days; HFNC group 40 (20-76) days (p<0.001). Among survivors, HFNC use was associated with increased odds of bronchopulmonary dysplasia (BPD) (aOR 2.98, 95% CI 2.81 to 3.15) and other adverse outcomes. CONCLUSIONS: NIV use is increasing, particularly as initial respiratory support. HFNC use has increased significantly with a sevenfold increase soon after birth which was associated with higher rates of BPD. As more infants survive with BPD, we need robust clinical evidence, to improve outcomes with the use of NIV as initial and ongoing respiratory support.

Effectiveness of B Vitamins and Their Interactions with Aspirin in Improving Cognitive Functioning in Older People with Mild Cognitive Impairment: Pooled Post-Hoc Analyses of Two Randomized Trials.

BACKGROUND AND OBJECTIVES: A randomized placebo-controlled trial found a significant negative interaction between aspirin and B vitamins in cognitive functioning in older people with mild cognitive impairment (MCI). To validate this finding, we pooled data of this trial with that of a similar B-vitamin trial (VITACOG) to examine the effectiveness of B vitamins and their interactions with aspirin in improving global cognitive functioning and slowing brain atrophy in older people with MCI. DESIGN: Pooled post-hoc analyses of two randomized placebo-controlled trials. PARTICIPANTS: In total, 545 older people with MCI were included in the study. INTERVENTION: Placebo or B-vitamin supplements (vitamin B12, folic acid with or without vitamin B6) for 24 months. MEASUREMENTS: The primary outcome was the Clinical Dementia Rating scale-global score (CDR-global). The secondary outcomes were CDR-sum of box score (CDR-SOB), memory Z-score, executive function Z-score, and whole brain atrophy rate. RESULTS: 71 (26.2%) and 83 (30.3%) subjects in the active and placebo group respectively were aspirin users. Overall, B vitamins reduced whole brain atrophy rate significantly (P = 0.003), but did not have significant effect on CDR-global, CDR-SOB, memory and executive function. Aspirin use had significant negative interaction effects on B vitamins in CDR-global and CDR-SOB (Beta = 0.993, P = 0.038, and Beta = 0.583, P = 0.009, respectively), but not in memory or executive function Z-scores. Among aspirin non-users, B-vitamin group subjects had more favourable changes in CDR-global and CDR-SOB (P = 0.019 and 0.057, respectively). B vitamins significantly slowed brain atrophy in aspirin non-users (P = 0.001), but not in aspirin users, though the interaction term was not significant (Beta = 0.192, P = 0.276). CONCLUSION: In older people with MCI, B vitamins had significantly favourable effects on global cognitive functioning and whole brain atrophy rate in those who were not taking aspirin, but not in aspirin users.