Selective degradation of phage RNAs by the Csm6 ribonuclease provides robust type III CRISPR immunity in Streptococcus thermophilus.

Type III CRISPR immune systems bind viral or plasmid RNA transcripts and activate Csm3/Cmr4 and Cas10 nucleases to uniquely cleave both invader RNA and DNA, respectively. Additionally, type III effector complexes generate cyclic oligoadenylate (cOA) signaling molecules to activate trans-acting, auxiliary Csm6/Csx1 ribonucleases, previously proposed to be non-specific in their in vivo RNA cleavage preference. Despite extensive in vitro studies, the nuclease requirements of type III systems in their native contexts remain poorly understood. Here we systematically investigated the in vivo roles for immunity of each of the three Streptococcus thermophilus (Sth) type III-A Cas nucleases and cOA signaling by challenging nuclease defective mutant strains with plasmid and phage infections. Our results reveal that RNA cleavage by Csm6 is both sufficient and essential for maintaining wild-type levels of immunity. Importantly, Csm6 RNase activity leads to immunity against even high levels of phage challenge without causing host cell dormancy or death. Transcriptomic analyses during phage infection indicated Csm6-mediated and crRNA-directed preferential cleavage of phage transcripts. Our findings highlight the critical role of Csm6 RNase activity in type III immunity and demonstrate specificity for invader RNA transcripts by Csm6 to ensure host cell survival upon phage infection.

Effect of Intensive Blood Pressure Control on Troponin and Natriuretic Peptide Levels: Findings From SPRINT.

BACKGROUND: Given the important role of cardiac injury and neurohormonal activation in the pathways leading from hypertension to heart failure and strong associations observed between hypertension and its sequelae on hs-cTnT (high-sensitivity cardiac troponin T) and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels, we hypothesized that intensive systolic blood pressure (SBP) lowering would decrease levels of hs-cTnT and NT-proBNP. METHODS: hs-cTnT and NT-proBNP were measured at baseline and 1 year from stored specimens in SPRINT (Systolic Blood Pressure Intervention Trial). Changes in biomarkers were evaluated continuously on the log scale and according to categories (≥50% increase, ≥50% decrease, or <50% change). The effect of intensive SBP lowering on continuous and categorical changes in biomarker levels were assessed using linear and multinomial logistic regression models, respectively. The association between changes in biomarkers on heart failure and death was assessed using multivariable-adjusted Cox proportional hazards models. RESULTS: Randomization to intensive SBP lowering (versus standard SBP management) resulted in a 3% increase in hs-cTnT levels over 1-year follow-up (geometric mean ratio, 1.03 [95% CI, 1.01-1.04]) and a higher proportion of participants with ≥50% increase (odds ratio, 1.47 [95% CI, 1.13, 1.90]). In contrast, randomization to intensive SBP lowering led to a 10% decrease in NT-proBNP (geometric mean ratio, 0.90 [95% CI, 0.87-0.93]) and a lower probability of ≥50% increase in NT-proBNP (odds ratio, 0.57 [95% CI, 0.46-0.72]). The association of randomized treatment assignment on change in hs-cTnT was completely attenuated after accounting for changes in estimated glomerular filtration rate over follow-up, whereas the association of treatment with NT-proBNP was completely attenuated after adjusting for change in SBP. Increases in hs-cTnT and NT-proBNP from baseline to 1 year were associated with higher risk for heart failure and death, with no significant interactions by treatment assignment. CONCLUSIONS: Intensive SBP lowering increased hs-cTnT, mediated by the effect of SBP lowering on reduced kidney filtration. In contrast, intensive SBP lowering decreased NT-proBNP, a finding that was explained by the decrease in SBP. These findings highlight the importance of noncardiac factors influencing variation in cardiac biomarkers and raise questions about the potential role of hs-cTnT as a surrogate marker for heart failure or death in SBP-lowering studies.

Final Report of a Trial of Intensive versus Standard Blood-Pressure Control.

BACKGROUND: In a previously reported randomized trial of standard and intensive systolic blood-pressure control, data on some outcome events had yet to be adjudicated and post-trial follow-up data had not yet been collected. METHODS: We randomly assigned 9361 participants who were at increased risk for cardiovascular disease but did not have diabetes or previous stroke to adhere to an intensive treatment target (systolic blood pressure, <120 mm Hg) or a standard treatment target (systolic blood pressure, <140 mm Hg). The primary outcome was a composite of myocardial infarction, other acute coronary syndromes, stroke, acute decompensated heart failure, or death from cardiovascular causes. Additional primary outcome events occurring through the end of the intervention period (August 20, 2015) were adjudicated after data lock for the primary analysis. We also analyzed post-trial observational follow-up data through July 29, 2016. RESULTS: At a median of 3.33 years of follow-up, the rate of the primary outcome and all-cause mortality during the trial were significantly lower in the intensive-treatment group than in the standard-treatment group (rate of the primary outcome, 1.77% per year vs. 2.40% per year; hazard ratio, 0.73; 95% confidence interval [CI], 0.63 to 0.86; all-cause mortality, 1.06% per year vs. 1.41% per year; hazard ratio, 0.75; 95% CI, 0.61 to 0.92). Serious adverse events of hypotension, electrolyte abnormalities, acute kidney injury or failure, and syncope were significantly more frequent in the intensive-treatment group. When trial and post-trial follow-up data were combined (3.88 years in total), similar patterns were found for treatment benefit and adverse events; however, rates of heart failure no longer differed between the groups. CONCLUSIONS: Among patients who were at increased cardiovascular risk, targeting a systolic blood pressure of less than 120 mm Hg resulted in lower rates of major adverse cardiovascular events and lower all-cause mortality than targeting a systolic blood pressure of less than 140 mm Hg, both during receipt of the randomly assigned therapy and after the trial. Rates of some adverse events were higher in the intensive-treatment group. (Funded by the National Institutes of Health; SPRINT ClinicalTrials.gov number, NCT01206062.).

The modified Baveno classification for obstructive sleep apnoea - Development and evaluation based on the ESADA database.

BACKGROUND: The "Baveno classification" replaced the apnoea hypopnoea index (AHI) with symptoms and comorbidities for treatment indication in obstructive sleep apnoea (OSA). This study evaluates a modified Baveno classification which adds a validated cardiovascular disease (CVD) risk score and acknowledges severe breathing disturbances. METHOD: OSA patients from the European Sleep Apnoea Data Base (ESADA) were retrospectively allocated into CVD risk groups 1-3 based on SCORE-2 and the ESC guidelines. AHI ≥30 /h conferred strong treatment indication. When AHI was <30/h, symptoms and CVD risk dictated allocation to weak, intermediate or strong treatment indication group. Change in Epworth Sleepiness Scale (ESS) and office systolic blood pressure (SBP) at follow-up (12-24 months) under positive airway pressure (PAP) were assessed. RESULTS: 8625 patients were analysed (29% female, age 56 [49;64] years, BMI 31.9 [28.4;36.3] kg·m-2). Treatment indication was weak in 501 (6%), intermediate in 2085 (24%) and strong in 6039 (70%). There was a continuous increase in age, SBP, C-reactive protein and glycosylated haemoglobin from weak to strong (p<0.001). PAP prescription increased from 52% to 64% to 93% (weak to strong, p<0.001). The change in ESS score was -2, -4 and -5, respectively (p<0.001). Reductions of ≥3 mmHg of median SBP occurred when AHI was ≥30/h and in symptomatic patients with CVD risk levels>1 when AHI was <30/h. CONCLUSION: This analysis provides supporting evidence for the key role of CVD risk assessment and severe breathing disturbances in the identification of OSA patients most likely to benefit from treatment.

Moderate IV Fluid Resuscitation Is Associated With Decreased Sepsis Mortality.

OBJECTIVES: Significant practice variation exists in the amount of resuscitative IV fluid given to patients with sepsis. Current research suggests equipoise between a tightly restrictive or more liberal strategy but data is lacking on a wider range of resuscitation practices. We sought to examine the relationship between a wide range of fluid resuscitation practices and sepsis mortality and then identify the primary driver of this practice variation. DESIGN: Retrospective analysis of the Premier Healthcare Database. SETTING: Six hundred twelve U.S. hospitals. PATIENTS: Patients with sepsis and septic shock admitted from the emergency department to the ICU from January 1, 2016, to December 31, 2019. INTERVENTIONS: The volume of resuscitative IV fluid administered before the end of hospital day- 1 and mortality. MEASUREMENTS AND MAIN RESULTS: In total, 190,682 patients with sepsis and septic shock were included in the analysis. Based upon patient characteristics and illness severity, we predicted that physicians should prescribe patients with sepsis a narrow mean range of IV fluid (95% range, 3.6-4.5 L). Instead, we observed wide variation in the mean IV fluids administered (95% range, 1.7-7.4 L). After splitting the patients into five groups based upon attending physician practice, we observed patients in the moderate group (4.0 L; interquartile range [IQR], 2.4-5.1 L) experienced a 2.5% reduction in risk-adjusted mortality compared with either the very low (1.6 L; IQR, 1.0-2.5 L) or very high (6.1 L; IQR, 4.0-9.0 L) fluid groups p < 0.01). An analysis of within- and between-hospital IV fluid resuscitation practices showed that physician variation within hospitals instead of practice differences between hospitals accounts for the observed variation. CONCLUSIONS: Individual physician practice drives excess variation in the amount of IV fluid given to patients with sepsis. A moderate approach to IV fluid resuscitation is associated with decreased sepsis mortality and should be tested in future randomized controlled trials.

Type III-A CRISPR systems as a versatile gene knockdown technology.

CRISPR-Cas systems are functionally diverse prokaryotic antiviral defense systems, which encompass six distinct types (I-VI) that each encode different effector Cas nucleases with distinct nucleic acid cleavage specificities. By harnessing the unique attributes of the various CRISPR-Cas systems, a range of innovative CRISPR-based DNA and RNA targeting tools and technologies have been developed. Here, we exploit the ability of type III-A CRISPR-Cas systems to carry out RNA-guided and sequence-specific target RNA cleavage for establishment of research tools for post-transcriptional control of gene expression. Type III-A systems from three bacterial species (L. lactis, S. epidermidis, and S. thermophilus) were each expressed on a single plasmid in E. coli, and the efficiency and specificity of gene knockdown was assessed by northern blot and transcriptomic analysis. We show that engineered type III-A modules can be programmed using tailored CRISPR RNAs to efficiently knock down gene expression of both coding and noncoding RNAs in vivo. Moreover, simultaneous degradation of multiple cellular mRNA transcripts can be directed by utilizing a CRISPR array expressing corresponding gene-targeting crRNAs. Our results demonstrate the utility of distinct type III-A modules to serve as specific and effective gene knockdown platforms in heterologous cells. This transcriptome engineering technology has the potential to be further refined and exploited for key applications including gene discovery and gene pathway analyses in additional prokaryotic and perhaps eukaryotic cells and organisms.

Deep-Learning-Based Screening and Ancillary Testing for Thyroid Cytopathology.

Thyroid cancer is the most common malignant endocrine tumor. The key test to assess preoperative risk of malignancy is cytologic evaluation of fine-needle aspiration biopsies (FNABs). The evaluation findings can often be indeterminate, leading to unnecessary surgery for benign post-surgical diagnoses. We have developed a deep-learning algorithm to analyze thyroid FNAB whole-slide images (WSIs). We show, on the largest reported data set of thyroid FNAB WSIs, clinical-grade performance in the screening of determinate cases and indications for its use as an ancillary test to disambiguate indeterminate cases. The algorithm screened and definitively classified 45.1% (130/288) of the WSIs as either benign or malignant with risk of malignancy rates of 2.7% and 94.7%, respectively. It reduced the number of indeterminate cases (N = 108) by reclassifying 21.3% (N = 23) as benign with a resultant risk of malignancy rate of 1.8%. Similar results were reproduced using a data set of consecutive FNABs collected during an entire calendar year, achieving clinically acceptable margins of error for thyroid FNAB classification.

Open Quantum System Dynamics from Infinite Tensor Network Contraction.

Approaching the long-time dynamics of non-Markovian open quantum systems presents a challenging task if the bath is strongly coupled. Recent proposals address this problem through a representation of the so-called process tensor in terms of a tensor network. We show that for Gaussian environments highly efficient contraction to a matrix product operator (MPO) form can be achieved with infinite MPO evolution methods, leading to significant computational speed-up over existing proposals. The result structurally resembles open system evolution with carefully designed auxiliary degrees of freedom, as in hierarchical or pseudomode methods. Here, however, these degrees of freedom are generated automatically by the MPO evolution algorithm. Moreover, the semigroup form of the resulting propagator enables us to explore steady-state physics, such as phase transitions.

Local Disclosure of Quantum Memory in Non-Markovian Dynamics.

Non-Markovian processes may arise in physics due to memory effects of environmental degrees of freedom. For quantum non-Markovianity, it is an ongoing debate to clarify whether such memory effects have a verifiable quantum origin, or whether they might equally be modeled by a classical memory. In this contribution, we propose a criterion to test locally for a truly quantum memory. The approach is agnostic with respect to the environment, as it solely depends on the local dynamics of the system of interest. Experimental realizations are particularly easy, as only single-time measurements on the system itself have to be performed. We study memory in a variety of physically motivated examples, both for a time-discrete case, and for time-continuous dynamics. For the latter, we are able to provide an interesting class of non-Markovian master equations with classical memory that allows for a physically measurable quantum trajectory representation.

Guidelines for the development, performance evaluation and validation of new sleep technologies (DEVSleepTech guidelines) - a protocol for a Delphi consensus study.

New sleep technologies are being developed, refined and delivered at a fast pace. However, there are serious concerns about the validation and accuracy of new sleep-related technologies being made available, as many of them, especially consumer-sleep technologies, have not been tested in comparison with gold-standard methods or have been approved by health regulatory agencies. The importance of proper validation and performance evaluation of new sleep technologies has already been discussed in previous studies and some recommendations have already been published, but most of them do not employ standardized methodology and are not able to cover all aspects of new sleep technologies. The current protocol describes the methods of a Delphi consensus study to create guidelines for the development, performance evaluation and validation of new sleep devices and technologies. The resulting recommendations are not intended to be used as a quality assessment tool to evaluate individual articles, but rather to evaluate the overall procedures, studies and experiments performed to develop, evaluate performance and validate new technologies. We hope these guidelines can be helpful for researchers who work with new sleep technologies on the appraisal of their reliability and validation, for companies who are working on the development and refinement of new sleep technologies, and by regulatory agencies to evaluate new technologies that are looking for registration, approval or inclusion on health systems.

Plasmonics-enhanced spikey nanorattle-based biosensor for direct SERS detection of mRNA cancer biomarkers.

We present a plasmonics-enhanced spikey nanorattle-based biosensor for direct surface-enhanced Raman scattering (SERS) detection of mRNA cancer biomarkers. Early detection of cancers such as head and neck squamous cell carcinoma (HNSCC) is critical for improving patient outcomes in regions with limited access to traditional diagnostic methods. Our method targets Keratin 14 (KRT14), a promising diagnostic mRNA biomarker for HNSCC, using a sandwich hybridization approach with magnetic beads and SERS spikey nanorattles (SpNR). We synthesized SpNR with a core-gap-shell structure to enhance SERS signals, achieving a limit of detection of 90 femtomolar. A pilot study using clinical samples demonstrated the efficacy of our biosensor in distinguishing between tissue with positive or negative diagnosis for HNSCC, highlighting its potential for rapid and sensitive cancer diagnostics in low-resource settings. This plasmonic assay offers a promising avenue for portable and high-specificity detection of nucleic acid biomarkers, with implications for early cancer detection and improved patient care, especially in middle and low-resource settings.

Deterministic quantum state transfer and remote entanglement using microwave photons.

Sharing information coherently between nodes of a quantum network is fundamental to distributed quantum information processing. In this scheme, the computation is divided into subroutines and performed on several smaller quantum registers that are connected by classical and quantum channels 1 . A direct quantum channel, which connects nodes deterministically rather than probabilistically, achieves larger entanglement rates between nodes and is advantageous for distributed fault-tolerant quantum computation 2 . Here we implement deterministic state-transfer and entanglement protocols between two superconducting qubits fabricated on separate chips. Superconducting circuits 3 constitute a universal quantum node 4 that is capable of sending, receiving, storing and processing quantum information5-8. Our implementation is based on an all-microwave cavity-assisted Raman process 9 , which entangles or transfers the qubit state of a transmon-type artificial atom 10 with a time-symmetric itinerant single photon. We transfer qubit states by absorbing these itinerant photons at the receiving node, with a probability of 98.1 ± 0.1 per cent, achieving a transfer-process fidelity of 80.02 ± 0.07 per cent for a protocol duration of only 180 nanoseconds. We also prepare remote entanglement on demand with a fidelity as high as 78.9 ± 0.1 per cent at a rate of 50 kilohertz. Our results are in excellent agreement with numerical simulations based on a master-equation description of the system. This deterministic protocol has the potential to be used for quantum computing distributed across different nodes of a cryogenic network.

Dynamics of a strongly coupled quantum heat engine-Computing bath observables from the hierarchy of pure states.

We present a fully quantum dynamical treatment of a quantum heat engine and its baths based on the Hierarchy of Pure States (HOPS), an exact and general method for open quantum system dynamics. We show how the change of the bath energy and the interaction energy can be determined within HOPS for arbitrary coupling strength and smooth time dependence of the modulation protocol. The dynamics of all energetic contributions during the operation can be carefully examined both in its initial transient phase and, also later, in its periodic steady state. A quantum Otto engine with a qubit as an inherently nonlinear work medium is studied in a regime where the energy associated with the interaction Hamiltonian plays an important role for the global energy balance and, thus, must not be neglected when calculating its power and efficiency. We confirm that the work required to drive the coupling with the baths sensitively depends on the speed of the modulation protocol. Remarkably, departing from the conventional scheme of well-separated phases by allowing for temporal overlap, we discover that one can even gain energy from the modulation of bath interactions. We visualize these various work contributions using the analog of state change diagrams of thermodynamic cycles. We offer a concise, full presentation of HOPS with its extension to bath observables, as it serves as a universal tool for the numerically exact description of general quantum dynamical (thermodynamic) scenarios far from the weak-coupling limit.

Application of the IOC Relative Energy Deficiency in Sport (REDs) Clinical Assessment Tool version 2 (CAT2) across 200+ elite athletes.

OBJECTIVE: This cross-sectional retrospective and prospective study implemented the 2023 International Olympic Committee Relative Energy Deficiency in Sport (REDs) Clinical Assessment Tool version 2 (CAT2) to determine the current severity of REDs (primary outcome) and future risk of bone stress injuries (BSI, exploratory outcome) in elite athletes. METHODS: Female (n=143; 23.3±4.3 years) and male (n=70; 23.1±3.7 years) athletes (performance tier 3 (52%), tier 4 (36%), tier 5 (12%)) participated in a baseline CAT2 (with minor modifications) assessment, including a self-report questionnaire (menstrual function (females), BSI, Eating Disorder Examination Questionnaire (EDE-Q)), bone mineral density (BMD via DXA) and fasted blood analysis (triiodothyronine (T3), testosterone, cholesterol). Athletes were assigned a green, yellow, orange or red light via CAT2. The prospective risk of new self-report of physician-diagnosed BSI was assessed over a subsequent 6-24 months. RESULTS: REDs prevalence was 55% green, 36% yellow, 5% orange and 4% red light. The CAT2 identified a greater prevalence of amenorrhoea and BSI and lower T3, testosterone and BMD (p<0.01) in red, orange and yellow (those with REDs) versus green light. ORs for a prospective self-reported BSI (majority physician diagnosed) were greater in orange vs green (OR 7.71, 95% CI (1.26 to 39.83)), in females with severe amenorrhoea (OR 4.6 (95% CI 0.98 to 17.85)), in males with low sex drive (OR 16.0 (95% CI 4.79 to 1038.87)), and athletes with elevated EDE-Q global scores (OR 1.45 (95% CI 0.97 to 1.97)). CONCLUSION: The CAT2 has high validity in demonstrating current severity of REDs, with increased future risk of self-reported BSI in athletes with a more severe REDs traffic light category.

An overview of human single-cell RNA sequencing studies in neurobiological disease.

Neurobiological disorders are highly prevalent medical conditions that contribute to significant morbidity and mortality. Single-cell RNA sequencing (scRNA-seq) is a technique that measures gene expression in individual cells. In this review, we survey scRNA-seq studies of tissues from patients suffering from neurobiological disease. This includes postmortem human brains and organoids derived from peripheral cells. We highlight a range of conditions, including epilepsy, cognitive disorders, substance use disorders, and mood disorders. These findings provide new insights into neurobiological disease in multiple ways, including discovering novel cell types or subtypes involved in disease, proposing new pathophysiological mechanisms, uncovering novel drug targets, or identifying potential biomarkers. We discuss the quality of these findings and suggest potential future directions and areas open for additional research, including studies of non-cortical brain regions and additional conditions such as anxiety disorders, mood disorders, and sleeping disorders. We argue that additional scRNA-seq of tissues from patients suffering from neurobiological disease could advance our understanding and treatment of these conditions.

Thyroid Cytopathology Cancer Diagnosis from Smartphone Images Using Machine Learning.

We examined the performance of deep learning models on the classification of thyroid fine-needle aspiration biopsies using microscope images captured in 2 ways: with a high-resolution scanner and with a mobile phone camera. Our training set consisted of images from 964 whole-slide images captured with a high-resolution scanner. Our test set consisted of 100 slides; 20 manually selected regions of interest (ROIs) from each slide were captured in 2 ways as mentioned above. Applying a baseline machine learning algorithm trained on scanner ROIs resulted in performance deterioration when applied to the smartphone ROIs (97.8% area under the receiver operating characteristic curve [AUC], CI = [95.4%, 100.0%] for scanner images vs 89.5% AUC, CI = [82.3%, 96.6%] for mobile images, P = .019). Preliminary analysis via histogram matching showed that the baseline model was overly sensitive to slight color variations in the images (specifically, to color differences between mobile and scanner images). Adding color augmentation during training reduces this sensitivity and narrows the performance gap between mobile and scanner images (97.6% AUC, CI = [95.0%, 100.0%] for scanner images vs 96.0% AUC, CI = [91.8%, 100.0%] for mobile images, P = .309), with both modalities on par with human pathologist performance (95.6% AUC, CI = [91.6%, 99.5%]) for malignancy prediction (P = .398 for pathologist vs scanner and P = .875 for pathologist vs mobile). For indeterminate cases (pathologist-assigned Bethesda category of 3, 4, or 5), color augmentations confer some improvement (88.3% AUC, CI = [73.7%, 100.0%] for the baseline model vs 96.2% AUC, CI = [90.9%, 100.0%] with color augmentations, P = .158). In addition, we found that our model's performance levels off after 15 ROIs, a promising indication that ROI data collection would not be time-consuming for our diagnostic system. Finally, we showed that the model has sensible Bethesda category (TBS) predictions (increasing risk malignancy rate with predicted TBS category, with 0% malignancy for predicted TBS 2 and 100% malignancy for TBS 6).

Consumer sleep technology for the screening of obstructive sleep apnea and snoring: current status and a protocol for a systematic review and meta-analysis of diagnostic test accuracy.

There are concerns about the validation and accuracy of currently available consumer sleep technology for sleep-disordered breathing. The present report provides a background review of existing consumer sleep technologies and discloses the methods and procedures for a systematic review and meta-analysis of diagnostic test accuracy of these devices and apps for the detection of obstructive sleep apnea and snoring in comparison with polysomnography. The search will be performed in four databases (PubMed, Scopus, Web of Science, and the Cochrane Library). Studies will be selected in two steps, first by an analysis of abstracts followed by full-text analysis, and two independent reviewers will perform both phases. Primary outcomes include apnea-hypopnea index, respiratory disturbance index, respiratory event index, oxygen desaturation index, and snoring duration for both index and reference tests, as well as the number of true positives, false positives, true negatives, and false negatives for each threshold, as well as for epoch-by-epoch and event-by-event results, which will be considered for the calculation of surrogate measures (including sensitivity, specificity, and accuracy). Diagnostic test accuracy meta-analyses will be performed using the Chu and Cole bivariate binomial model. Mean difference meta-analysis will be performed for continuous outcomes using the DerSimonian and Laird random-effects model. Analyses will be performed independently for each outcome. Subgroup and sensitivity analyses will evaluate the effects of the types (wearables, nearables, bed sensors, smartphone applications), technologies (e.g., oximeter, microphone, arterial tonometry, accelerometer), the role of manufacturers, and the representativeness of the samples.

Performance of Cox regression models for composite time-to-event endpoints with component-wise censoring in randomized trials.

BACKGROUND: Composite time-to-event endpoints are beneficial for assessing related outcomes jointly in clinical trials, but components of the endpoint may have different censoring mechanisms. For example, in the PRagmatic EValuation of evENTs And Benefits of Lipid-lowering in oldEr adults (PREVENTABLE) trial, the composite outcome contains one endpoint that is right censored (all-cause mortality) and two endpoints that are interval censored (dementia and persistent disability). Although Cox regression is an established method for time-to-event outcomes, it is unclear how models perform under differing component-wise censoring schemes for large clinical trial data. The goal of this article is to conduct a simulation study to investigate the performance of Cox models under different scenarios for composite endpoints with component-wise censoring. METHODS: We simulated data by varying the strength and direction of the association between treatment and outcome for the two component types, the proportion of events arising from the components of the outcome (right censored and interval censored), and the method for including the interval-censored component in the Cox model (upper value and midpoint of the interval). Under these scenarios, we compared the treatment effect estimate bias, confidence interval coverage, and power. RESULTS: Based on the simulation study, Cox models generally have adequate power to achieve statistical significance for comparing treatments for composite outcomes with component-wise censoring. In our simulation study, we did not observe substantive bias for scenarios under the null hypothesis or when the treatment has a similar relative effect on each component outcome. Performance was similar regardless of if the upper value or midpoint of the interval-censored part of the composite outcome was used. CONCLUSION: Cox regression is a suitable method for analysis of clinical trial data with composite time-to-event endpoints subject to different component-wise censoring mechanisms.

Kidney tubule health, mineral metabolism and adverse events in persons with CKD in SPRINT.

BACKGROUND: Measures of kidney tubule health are risk markers for acute kidney injury (AKI) in persons with chronic kidney disease (CKD) during hypertension treatment, but their associations with other adverse events (AEs) are unknown. METHODS: Among 2377 Systolic Blood Pressure Intervention Trial (SPRINT) participants with CKD, we measured at baseline eight urine biomarkers of kidney tubule health and two serum biomarkers of mineral metabolism pathways that act on the kidney tubules. Cox proportional hazards models were used to evaluate biomarker associations with risk of a composite of pre-specified serious AEs (hypotension, syncope, electrolyte abnormalities, AKI, bradycardia and injurious falls) and outpatient AEs (hyperkalemia and hypokalemia). RESULTS: At baseline, the mean age was 73 ± 9 years and mean estimated glomerular filtration rate (eGFR) was 46 ± 11 mL/min/1.73 m2. During a median follow-up of 3.8 years, 716 (30%) participants experienced the composite AE. Higher urine interleukin-18, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin (NGAL) and monocyte chemoattractant protein-1 (MCP-1), lower urine uromodulin (UMOD) and higher serum fibroblast growth factor-23 were individually associated with higher risk of the composite AE outcome in multivariable-adjusted models including eGFR and albuminuria. When modeling biomarkers in combination, higher NGAL [hazard ratio (HR) = 1.08 per 2-fold higher biomarker level, 95% confidence interval (CI) 1.03-1.13], higher MCP-1 (HR = 1.11, 95% CI 1.03-1.19) and lower UMOD (HR = 0.91, 95% CI 0.85-0.97) were each associated with higher composite AE risk. Biomarker associations did not vary by intervention arm (P > 0.10 for all interactions). CONCLUSIONS: Among persons with CKD, several kidney tubule biomarkers are associated with higher risk of AEs during hypertension treatment, independent of eGFR and albuminuria.

Obstructive sleep apnea: transition from pathophysiology to an integrative disease model.

Obstructive sleep apnea (OSA) is characterised by recurring episodes of upper airway obstruction during sleep and the fundamental abnormality reflects the inability of the upper airway dilating muscles to withstand the negative forces generated within the upper airway during inspiration. Factors that result in narrowing of the oropharynx such as abnormal craniofacial anatomy, soft tissue accumulation in the neck, and rostral fluid shift in the recumbent position increase the collapsing forces within the airway. The counteracting forces of upper airway dilating muscles, especially the genioglossus, are negatively influenced by sleep onset, inadequacy of the genioglossus responsiveness, ventilatory instability, especially post arousal, and loop gain. OSA is frequently associated with comorbidities that include metabolic, cardiovascular, renal, pulmonary, and neuropsychiatric, and there is growing evidence of bidirectional relationships between OSA and comorbidity, especially for heart failure, metabolic syndrome, and stroke. A detailed understanding of the complex pathophysiology of OSA encourages the development of therapies targeted at pathophysiological endotypes and facilitates a move towards precision medicine as a potential alternative to continuous positive airway pressure therapy in selected patients.