Individual Patient Research Articles

Estimating the Impact of Hospital-Level Variation on the Use of Inpatient Rehabilitation Facilities Versus Skilled Nursing Facilities on Individual Patients With Stroke.

There is substantial hospital-level variation in the use of Inpatient Rehabilitation Facilities (IRFs) versus Skilled Nursing Facilities (SNFs) among patients with stroke, which is poorly understood. Our objective was to quantify the net effect of the admitting hospital on the probability of receiving IRF or SNF care for individual patients with stroke. Using Medicare claims data (2011-2013), a cohort of patients with acute stroke discharged to an IRF or SNF was identified. We generated 2 multivariable logistic regression models. Model 1 predicted IRF admission (versus SNF) using only patient-level factors, whereas model 2 added a hospital random effect term to quantify the hospital effect. The statistical significance and direction of the random effect terms were used to categorize hospitals as being either IRF-favoring, SNF-favoring, or neutral with respect to their discharge patterns. The hospital's impact on individual patient's probability of IRF discharge was estimated by taking the change in individual predicted probabilities (change in individual predicted probability) between the 2 models. Hospital-level effects were categorized as small (<10%), moderate (10%-19%), or large (≥20%) depending on change in individual predicted probability. The cohort included 135 415 patients (average age, 81.5 [SD=8.0] years, 61% female, 91% ischemic stroke) who were discharged from 1816 acute care hospitals to IRFs (n=66 548) or SNFs (n=68 867). Half of hospitals were classified as being either IRF-favoring (n=461, 25.4%) or SNF-favoring (n=485, 26.7%) with the remainder (n=870, 47.9%) considered neutral. Overall, just over half (n=73 428) of patients were treated at hospitals that had moderate or large independent effects on discharge settings. Hospital effects for neutral hospitals were small (ie, change in individual predicted probability <10%) for most patients (72.5%). However, hospital effects were moderate or large for 78.8% and 84.6% of patients treated at IRF- or SNF-favoring hospitals, respectively. For most patients with stroke, the admitting hospital meaningfully changed the type of rehabilitation care that they received.

Biofluid, Imaging, Physiological, and Functional Biomarkers of Mild Traumatic Brain Injury and Subconcussive Head Impacts.

Post-concussive symptoms are frequently reported by individuals who sustain mild traumatic brain injuries (mTBIs) and subconcussive head impacts, even when evidence of intracranial pathology is lacking. Current strategies used to evaluate head injuries, which primarily rely on self-report, have a limited ability to predict the incidence, severity, and duration of post-concussive symptoms that will develop in an individual patient. In addition, these self-report measures have little association with the underlying mechanisms of pathology that may contribute to persisting symptoms, impeding advancement in precision treatment for TBI. Emerging evidence suggests that biofluid, imaging, physiological, and functional biomarkers associated with mTBI and subconcussive head impacts may address these shortcomings by providing more objective measures of injury severity and underlying pathology. Interest in the use of biomarker data has rapidly accelerated, which is reflected by the recent efforts of organizations such as the National Institute of Neurological Disorders and Stroke and the National Academies of Sciences, Engineering, and Medicine to prioritize the collection of biomarker data during TBI characterization in acute-care settings. Thus, this review aims to describe recent progress in the identification and development of biomarkers of mTBI and subconcussive head impacts and to discuss important considerations for the implementation of these biomarkers in clinical practice.

Strategic reuse of rapid antigen tests for coagulation status assessment: an integrated machine learning approach

Addressing the pressing demand for rapid and inexpensive coagulation testing in cardiovascular care, this study introduces a novel application of repurposed COVID-19 rapid antigen tests (RATs) as paper-based lateral flow assays (LFAs) combined with machine learning for coagulation status evaluation. By further developing a mobile app prototype, we present a platform that enables clinicians to perform immediate and accurate anticoagulant dosing adjustments using existing post-pandemic resources. Our proof-of-concept employs a random forest machine learning classifier to interpret image feature variations on RAT NC membrane, correlating red blood cell (RBC) wicked diffusion distance in recalcified citrated whole blood with changes in coagulative viscosity, easily interpreted. Enhanced by confocal imaging studies of paper microfluidics, our approach provides insights into the mechanisms dissecting coagulation components, achieving high classification precision, recall, and F1-scores. The inverse relationship between RBC wicked diffusion distance and enoxaparin concentration paves the way for machine learning to inform real-time dose prescription adjustments, aligning with individual patient profiles to optimize therapeutic outcomes. This study not only demonstrates the potential of leveraging surplus RATs for coagulation management but also exemplifies a cost-effective, rapid, and smart strategy to enhance clinical decision-making in the post-pandemic era.Graphical

Racial and Ethnic Disparities in Occult Hypoxemia Prevalence and Clinical Outcomes Among Hospitalized Patients: A Systematic Review and Meta-analysis.

There is growing concern that pulse oximeters are routinely less accurate in hospitalized patients with darker skin pigmentation, in turn increasing risk of undetected (occult) hypoxemia and adverse clinical outcomes. The aim of this systematic review and meta-analysis was to synthesize evidence on racial and ethnic disparities in occult hypoxemia prevalence and clinical impacts of undetected hypoxemia. Ovid MEDLINE, Embase, and CINAHL databases were searched for relevant articles published through January 2024. Eligible studies must have been conducted among adults in inpatient or outpatient settings and report occult hypoxemia prevalence stratified by patient race or ethnicity, or clinical outcomes stratified by patient race or ethnicity and occult hypoxemia status. Screening for inclusion was conducted independently by two investigators. Data extraction and risk of bias assessment were conducted by one investigator then checked by a second. Outcome data were synthesized using random-effects meta-analyses. Fifteen primary studies met eligibility criteria and reported occult hypoxemia prevalence in 732,505 paired oximetry measurements from 207,464 hospitalized patients. Compared with White patients, occult hypoxemia is likely more common among Black patients (pooled prevalence ratio = 1.67, 95% CI 1.47 to 1.90) and among patients identifying as Asian, Latinx, Indigenous, multiracial, or other race or ethnicity (pooled prevalence ratio = 1.39, 95% CI 1.19 to 1.64). Findings from studies reporting clinical outcomes suggest that Black patients with undetected hypoxemia may experience poorer treatment delivery outcomes than White patients with undetected hypoxemia.No evidence was found from outpatient settings. This review and included primary studies rely on self-identified race or ethnicity, which may obscure variability in occult hypoxemia risk. Findings underscore that clinicians should be aware of the risk of occult hypoxemia in hospitalized patients with darker skin pigmentation. Moreover, oximetry data from included studies suggests that the accuracy of pulse oximeters could vary substantially from patient to patient and even within individual patients. PROSPERO ( CRD42023402152 ).

Organ and tumor dosimetry including method simplification for [177Lu]Lu-PSMA-I&T for treatment of metastatic castration resistant prostate cancer

BackgroundInternal dosimetry in individual patients is essential for safe and effective radioligand therapy. Multiple time point imaging for accurate dosimetry is time consuming and hence can be demanding for nuclear medicine departments as well as patients. The objectives of this study were (1) to assess absorbed doses to organs at risk and tumor lesions for [177Lu]Lu-PSMA-I&T using whole body SPECT imaging and (2) to investigate possible simplified dosimetry protocols.MethodsThis study included 16 patients each treated with 4 cycles of [177Lu]Lu-PSMA-I&T. They underwent quantitative whole body SPECT/CT imaging (3 bed positions) at four time points (TP) comprising 2 h, 24 h, 48 h and 72–168 h post-injection (p.i.). Full 3D dosimetry (reference method) was performed for all patients and dose cycles for organs at risk (kidneys, parotid glands and submandibular glands) and up to ten tumor lesions per patient (resulting in 90 lesions overall). The simplified dosimetry methods (SM) included (1) generating time activity curves for subsequent cycles using a single TP of imaging applying the kinetics of dose cycle 1, and for organs at risk also (2) simple extrapolation from dose cycle 1 and (3) from both, dose cycle 1 and 2.ResultsNormalized absorbed doses were 0.71 ± 0.32 mGy/MBq, 0.28 ± 0.12 mGy/MBq and 0.22 ± 0.08 mGy/MBq for kidneys, parotid glands and submandibular glands, respectively. Tumor doses decreased from 3.86 ± 3.38 mGy/MBq in dose cycle 1 to 2.01 ± 2.65 mGy/MBq in dose cycle 4. Compared to the full dosimetry approach the SM 1 using single TP imaging at 48 h p.i. resulted in the most accurate and precise results for the organs at risk in terms of absorbed doses per cycle and total cumulated dose. For tumor lesions better results were achieved using the fourth TP (≥ 72 h p.i.).ConclusionSimplification of safety dosimetry protocols is possible for [177Lu]Lu-PSMA-I&T therapy. If tumor dosimetry is of interest a later imaging TP (≥ 72 h p.i.) should be used/added to account for the slower kinetics of tumors compared to organs at risk.

When impact trials are not feasible: alternatives to study the impact of prediction models on clinical practice.

Patients with kidney disease have an uncertain future with prognosis varying greatly per patient. To get a better idea of what the future holds and tailor interventions to the individual patient, prediction models can be of great value. Before a prediction model can be applied in practice, its performance should be measured in target populations of interest (i.e., external validation) and whether it helps improve clinical practice (i.e., whether it impacts clinical practice) should be determined. The impact would ideally be determined using an impact trial, but such a trial is often not feasible, and the impact of prediction models is therefore rarely assessed. As a result, prediction models that may not be so impactful may end up in clinical practice and impactful models may not be implemented due to a lack of impact studies. Ultimately, many prediction models end up never being implemented, resulting in much research waste. To allow researchers to get an indication of a prediction model's impact on clinical practice, alternative methods to assess a prediction model's impact are important. In this paper, we discuss several alternatives, including interviews, case-based surveys, decision comparisons, outcome modelling, before-after analyses, and decision curve analyses. We discuss the general idea behind these approaches, including what information can be gathered from such studies and important pitfalls. Lastly, we provide examples of the different alternatives.

Novel insight into nicotinamide adenine dinucleotide and related metabolites in cancer patients undergoing surgery

Nicotinamide adenine dinucleotide (NAD +) plays a pivotal role in numerous cellular functions. Reduced NAD + levels are postulated to be associated with cancer. As interest in understanding NAD + dynamics in cancer patients with therapeutic applications in mind grows, there remains a shortage of comprehensive data. This study delves into NAD + dynamics in patients undergoing surgery for different digestive system cancers. This prospective study enrolled 99 patients with eight different cancers. Fasting blood samples were obtained during the perioperative period. The concentrations of NAD + , nicotinamide mononucleotide (NMN), and nicotinamide riboside were analyzed using tandem mass spectrometry. After erythrocyte volume adjustment, NAD + remained relatively stable after surgery. Meanwhile, NMN decreased the day after surgery and displayed a recovery trend. Interestingly, liver and pancreatic cancer patients exhibited poor postoperative NMN recovery, suggesting a potential cancer type-specific influence on NAD + metabolism. This study illuminated the behavior of NAD + in surgically treated cancer patients. We identified which cancer types have particularly low levels and at what point depletion occurs during the perioperative period. These insights suggest the need for personalized NAD + supplementation strategies, calibrated to individual patient needs and treatment timelines. Clinical trial registration jRCT1020210066.

The Use of Clips to Prevent Post-Polypectomy Bleeding: A Clinical Review.

The goal of this clinical review is to provide an overview of the current literature regarding the utility of prophylactic clips in reducing postpolypectomy bleeding and to provide an expert statement regarding their appropriateness in clinical practice. Colonoscopy enables the identification and removal of premalignant and malignant lesions through polypectomy, yet complications including postpolypectomy bleeding (PPB) can arise. While various studies have explored applying clips prophylactically to prevent PPB, their effectiveness remains uncertain. A literature search conducted in PubMed and Embase identified 671 publications discussing clip use postpolypectomy; 67 were found to be relevant after screening, reporting outcomes related to PPB. Data related to clip utilization, polyp characteristics, and adverse events were extracted and discussed. The current literature suggests that prophylactic clipping is most beneficial for nonpedunculated polyps ≥20mm, especially those in the proximal colon. The utility of clipping smaller polyps and those in the distal colon remains less clear. Antithrombotic medication usage, particularly anticoagulants, has been linked to an increased risk of bleeding, prompting consideration for clip placement in this patient subgroup. While cost-effectiveness analyses may indicate potential savings, the decision to clip should be tailored to individual patient factors and polyp characteristics. Current research suggests that the application of prophylactic clips can be particularly beneficial in preventing delayed bleeding after removal of large nonpedunculated polyps, especially for those in the proximal colon and in patients on antithrombotic medications. In addition, for large pedunculated polyps prophylactic clipping is most effective at controlling immediate bleeding.

Qualitative Interviews Exploring Adverse Event Mitigation Strategies in Adults Receiving Amikacin Liposome Inhalation Suspension.

This study aimed to gain insight from patients with refractory Mycobacterium avium complex lung disease (MAC-LD) into strategies used to manage adverse events (AEs) associated with amikacin liposome inhalation suspension (ALIS). We conducted semi-structured interviews with US patients with refractory MAC-LD prescribed ALIS in a real-world setting. Interview transcripts were analyzed and coded to identify patterns in participants' descriptions of their ALIS treatment experiences, including AEs and their disruptiveness, and AE mitigation strategies, including participants' ratings of strategies' effectiveness. Concept saturation was also assessed. Twenty participants (mean age 48.7years; 80% women; mean ALIS duration 5.45months) were interviewed. At the time of the interview, 15 participants (75%) had received ALIS for > 1month and 13 (65%) were currently receiving ALIS. Participants described 44 unique AE mitigation strategies, which can be categorized into three groups: prepare for treatment; prevent increased emergence of AEs; and persist on treatment by mitigating AEs. Common strategies (reported by ≥ 50% of participants) included use of educational materials from the patient support program, localized management of throat irritation, and symptom management to reduce fatigue. Evidence of concept saturation was observed: no new strategies were identified in the last five interviews, which suggests the sample was robust enough to identify all mitigation strategies likely to be used by the broader patient population. This real-world study identified a diverse set of potential AE mitigation strategies intended to help individual patients prepare for ALIS treatment, prevent the increased emergence of certain AEs, and mitigate the impact of AEs on treatment persistence. Developing a comprehensive accounting of the types of mitigation strategies in use among patients in real-world settings can inform future investigation of the effectiveness of such strategies, and support evidence-based recommendations for treatment management.

The updated Asia-Pacific consensus statement on the role of endoscopic management in malignant hilar biliary obstruction.

The first Asia–Pacific consensus recommendations for endoscopic and interventional management of hilar cholangiocarcinoma were published in 2013. Since then, new evidence on the role of endoscopy for management of malignant hilar biliary obstruction (MHBO) has emerged. To update the recommendation, we reviewed the literature using a PICO (population/intervention/comparison/outcomes) framework and created consensus statements. The expert panel voted anonymously using the modified Delphi method, and all final statements were evaluated for the quality of evidence and strength of recommendation. The important points with inadequate supporting evidence were classified as key concepts. There were 7 statements and 5 key concepts that reached consensus. The statements and key concepts dealt with multiple aspects of endoscopy-based management in MHBO starting from diagnosis, strategies and options for biliary drainage, management of recurrent biliary obstruction, management of cholecystitis after biliary stenting, and adjunctive treatment before stenting. Although the recommendations may assist physicians in planning the treatment for MHBO patients, they should not replace the decision of a multidisciplinary team in the management of individual patients.

A Comprehensive Multidisciplinary Approach to Diagnosing Chronic Inflammatory Bowel Diseases: Integration of Clinical, Endoscopic, and Imaging Modalities

Chronic inflammatory bowel diseases, such as Crohn’s disease and ulcerative colitis, present diagnostic challenges due to their complex and heterogeneous nature. While histology remains fundamental for accurate diagnosis, a multidisciplinary approach incorporating clinical, endoscopic, and imaging modalities is increasingly recognized as essential for comprehensive evaluation. This article delves into the importance of integrating various diagnostic techniques in the assessment of IBD. Colonoscopy and histology, with its ability to directly visualize the intestinal mucosa, play a central role in the diagnostic process. However, histological analysis alone may not suffice, necessitating the inclusion of advanced imaging techniques, such as magnetic resonance enterography (MRE), computed tomography enterography (CTE), and intestinal ultrasound (IUS). These techniques provide valuable insights into the disease’s extent, severity, and complications, and should be used in conjunction with biochemical parameters. These modalities complement traditional endoscopic and histological findings, offering a more holistic understanding of the disease process. A multidisciplinary approach that incorporates clinical, endoscopic, histological, serological, and imaging assessments enables clinicians to achieve a more accurate and timely diagnosis of IBD. Moreover, this integrated approach facilitates personalized treatment strategies tailored to individual patient needs, ultimately improving clinical outcomes and quality of life for those affected by chronic inflammatory bowel diseases.

Utilizing connectome fingerprinting functional MRI models for motor activity prediction in presurgical planning: A feasibility study.

Presurgical planning prior to brain tumor resection is critical for the preservation of neurologic function post-operatively. Neurosurgeons increasingly use advanced brain mapping techniques pre- and intra-operatively to delineate brain regions which are "eloquent" and should be spared during resection. Functional MRI (fMRI) has emerged as a commonly used non-invasive modality for individual patient mapping of critical cortical regions such as motor, language, and visual cortices. To map motor function, patients are scanned using fMRI while they perform various motor tasks to identify brain networks critical for motor performance, but it may be difficult for some patients to perform tasks in the scanner due to pre-existing deficits. Connectome fingerprinting (CF) is a machine-learning approach that learns associations between resting-state functional networks of a brain region and the activations in the region for specific tasks; once a CF model is constructed, individualized predictions of task activation can be generated from resting-state data. Here we utilized CF to train models on high-quality data from 208 subjects in the Human Connectome Project (HCP) and used this to predict task activations in our cohort of healthy control subjects (n = 15) and presurgical patients (n = 16) using resting-state fMRI (rs-fMRI) data. The prediction quality was validated with task fMRI data in the healthy controls and patients. We found that the task predictions for motor areas are on par with actual task activations in most healthy subjects (model accuracy around 90%-100% of task stability) and some patients suggesting the CF models can be reliably substituted where task data is either not possible to collect or hard for subjects to perform. We were also able to make robust predictions in cases in which there were no task-related activations elicited. The findings demonstrate the utility of the CF approach for predicting activations in out-of-sample subjects, across sites and scanners, and in patient populations. This work supports the feasibility of the application of CF models to presurgical planning, while also revealing challenges to be addressed in future developments. PRACTITIONER POINTS: Precision motor network prediction using connectome fingerprinting. Carefully trained models' performance limited by stability of task-fMRI data. Successful cross-scanner predictions and motor network mapping in patients with tumor.

Anesthetic management in orthopaedic surgery for rheumatic patients

Patients with rheumatic diseases frequently require orthopaedic surgeries due to progressive joint damage and deformities. These patients pose unique challenges for anesthesiologists due to systemic involvement, altered anatomy, and chronic pain management needs. This review explores optimal anesthetic strategies to improve surgical outcomes and enhance patient safety in this vulnerable population. Preoperative assessment is crucial for identifying systemic manifestations of rheumatic diseases, including cardiovascular, respiratory, and renal involvement, which can significantly impact anesthetic management. A thorough evaluation helps tailor the anesthetic plan to individual patient needs, ensuring better perioperative care.Regional anesthesia, particularly neuraxial blocks and peripheral nerve blocks, offers significant benefits over general anesthesia in this population. These techniques can reduce postoperative pain, enhance recovery times, and decrease opioid consumption. However, the presence of spinal deformities and anticoagulation therapy in these patients requires careful consideration and meticulous planning. Multimodal analgesia, combining regional techniques with systemic medications, is recommended to manage chronic pain and minimize opioid use postoperatively. Effective pain management strategies are essential for improving postoperative outcomes and patient satisfaction.

The impact of codeine rescheduling on non-opioid analgesic use by people who regularly use codeine: a prospective cohort study.

Codeine was rescheduled in Australia to prescription only in February 2018. Initial studies reported an increase in population level paracetamol and ibuprofen sales following codeine upscheduling. However, to date no study has been able to investigate changes in non-opioid analgesic use at the individual patient level to determine if sales data reflect actual consumption patterns. To address this gap, we aimed to determine the impact of codeine rescheduling on non-opioid analgesic use in people who regularly used over-the-counter codeine, primarily for pain, prior to the rescheduling change. We conducted a prospective cohort study with 260 participants who reported regular over-the-counter codeine consumption at cohort entry. Surveys were completed at baseline (November 2017, 3months before rescheduling) and at 1month (February 2018), 4months (June 2018), and 12months (February 2019), following rescheduling. The primary outcomes were mean daily doses of non-opioid analgesics, captured through a 7day medication diary. The mean daily paracetamol dose decreased from 1754.4mg (95% CI 1300.5-2208.3) at baseline to 1023.8mg (95% CI 808.5-1239.1) at the final time-point (+ 12months) (p = .009). The mean daily ibuprofen dose decreased from 305.1mg (95% CI 217.9-392.4) at baseline to 161.2mg (95% CI 98.5-224.0) 12months after rescheduling (p = .03). No significant change in doses of other medications remained was found. In people who regularly consumed over-the-counter codeine, doses of non-opioid analgesics either reduced or remained stable following codeine rescheduling, suggesting concerns of medication substitution or overuse following the change were not realised.

Factors affecting decisions of an HMO Drug Exemptions Committee on individual patient requests for coverage of non-formulary drugs

BackgroundIn Israel, coverage of health needs is delivered by four health maintenance organizations (HMOs), which are budgeted by the government according to the recommendations of the National Drug Formulary (NDF) Committee. For medications not listed in the NDF, individuals may request to cover the costs by the HMO Exemptions Committee (DEC). The objectives of the current study, a first of its kind, are to document the DEC decision process, to identify its components and to determine the decisions’ clinical outcome.MethodsThis retrospective cohort study included all members (≥ age 18) of the Maccabi Healthcare Service (MHS) who submitted a request to the DEC between June 2017 and December 2018. Collected data include patient demographics, clinical information and components of the decision process. Decision success (i.e., clinical outcome correlated with DEC decision) was determined by clinical outcome over at least one-year follow-up.ResultsA total of 335 requests were included. Strong evidence and rare disease were positively associated with approvals, while the availability of alternative treatments and costs were negatively associated. The majority of decisions (75%) met predicted clinical outcomes. Only estimated costs were found to be associated with decision success.ConclusionsFactors that reduce the potential costs of a requested drug are significantly associated with higher odds for drug approval, but only when the evidence supports potential benefit.

Efficacy of iron supplementation on physical capacity in non-anaemic iron-deficient individuals: protocol for an individual patient data meta-analysis

BackgroundA deficiency in iron stores is associated with various adverse health complications, which, if left untreated, can progress to states of anaemia, whereby there is significant detriment to an individual’s work capacity and quality of life due to compromised erythropoiesis. The most common methods employed to treat an iron deficiency include oral iron supplementation and, in persistent and/or unresponsive cases, intravenous iron therapy. The efficacy of these treatments, particularly in states of iron deficiency without anaemia, is equivocal. Indeed, both randomised control trials and aggregate data meta-analyses have produced conflicting evidence. Therefore, this study aims to assess the efficacy of both oral and intravenous iron supplementation on physical capacity, quality of life, and fatigue scores in iron-deficient non-anaemic individuals using individual patient data (IPD) meta-analysis techniques.MethodsAll potential studies, irrespective of design, will be sourced through systematic searches on the following databases: Cochrane Central Register of Controlled Trials, MEDLINE Ovid, Embase Ovid, Web of Science: Science Citation Index Expanded, Web of Science: Conference Proceedings Citation Index-Science, ClinicalTrials.gov, and World Health Organization (WHO) International Clinical Trials Registry Platform. Individual patient data from all available trials will be included and subsequently analysed in a two-stage approach. Predetermined subgroup and sensitivity analyses will be employed to further explain results.DiscussionThe significance of this IPD meta-analysis is one of consolidating a clear consensus to better inform iron-deficient individuals of the physiological response associated with iron supplementation. The IPD approach, to the best of our knowledge, is novel for this research topic. As such, the findings will significantly contribute to the current body of evidence.Systematic review registrationPROSPERO CRD42020191739.

Natural history of initially asymptomatic severe aortic stenosis: a one-stage meta-analysis.

Current guidelines on the management strategy for patients with asymptomatic severe aortic stenosis (AS) remain unclear. This uncertainty stems from the lack of data regarding the natural history of these patients. To address this gap, we performed a systematic review and meta-analysis examining the natural history of asymptomatic severe AS patients receiving conservative treatment. The PubMed, Cochrane, and Embase databases were searched from inception to 24 January 2024 using the keywords "asymptomatic" AND "aortic" AND "stenosis". We included studies examining patients with asymptomatic severe AS. In interventional trials, only data from conservatively managed arms were collected. A one-stage meta-analysis was conducted using individual patient data reconstructed from published Kaplan-Meier curves. Sensitivity analysis was performed for major adverse cardiovascular outcomes in patients who remained asymptomatic throughout follow-up. A total of 46 studies were included (n = 9545). The median time to the development of symptoms was 1.11years (95% CI 0.90-1.53). 49.36% (40.85-58.59) of patients who were asymptomatic had suffered a major adverse cardiovascular event by 5years. The median event-free time for heart failure hospitalization (HFH) was 5.50years (95% CI 5.14-5.91) with 36.34% (95% CI 33.34-39.41) of patients experiencing an HFH by year 5. By 5years, 79.81% (95% CI 69.26-88.58) of patients developed symptoms (angina, dyspnoea, syncope and others) and 12.36% (95% CI 10.01-15.22) of patients died of cardiovascular causes. For all-cause mortality, the median survival time was 9.15years (95% CI 8.50-9.96) with 39.43% (CI 33.41-36.40) of patients dying by 5years. The median time to AVR was 4.77years (95% CI 4.39-5.17), with 52.64% (95% CI 49.85-55.48) of patients requiring an AVR by 5years. Our results reveal poor cardiovascular outcomes for patients with asymptomatic severe AS on conservative treatment. A significant proportion eventually requires an AVR. Further research is needed to determine if early intervention with AVR is more effective than conservative treatment.

Development and validation of 10-year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning-based methods.

To develop 10-year cardiovascular disease (CVD) risk prediction models in Chinese patients with type 2 diabetes mellitus (T2DM) managed in primary care using machine learning (ML) methods. In this 10-year population-based retrospective cohort study, 141 516 Chinese T2DM patients aged 18 years or above, without history of CVD or end-stage renal disease and managed in public primary care clinics in 2008, were included and followed up until December 2017. Two-thirds of the patients were randomly selected to develop sex-specific CVD risk prediction models. The remaining one-third of patients were used as the validation sample to evaluate the discrimination and calibration of the models. ML-based methods were applied to missing data imputation, predictor selection, risk prediction modelling, model interpretation, and model evaluation. Cox regression was used to develop the statistical models in parallel for comparison. During a median follow-up of 9.75 years, 32 445 patients (22.9%) developed CVD. Age, T2DM duration, urine albumin-to-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), systolic blood pressure variability and glycated haemoglobin (HbA1c) variability were the most important predictors. ML models also identified nonlinear effects of several predictors, particularly the U-shaped effects of eGFR and body mass index. The ML models showed a Harrell's C statistic of >0.80 and good calibration. The ML models performed significantly better than the Cox regression models in CVD risk prediction and achieved better risk stratification for individual patients. Using routinely available predictors and ML-based algorithms, this study established 10-year CVD risk prediction models for Chinese T2DM patients in primary care. The findings highlight the importance of renal function indicators, and variability in both blood pressure and HbA1c as CVD predictors, which deserve more clinical attention. The derived risk prediction tools have the potential to support clinical decision making and encourage patients towards self-care, subject to further research confirming the models' feasibility, acceptability and applicability at the point of care.

Metabolic Reprogramming in Human Cancer Patients and Patient-Derived Models.

Stable isotope-resolved metabolomics delineates reprogrammed intersecting metabolic networks in human cancers. Knowledge gained from in vivo patient studies provides the "benchmark" for cancer models to recapitulate. It is particularly difficult to model patients' tumor microenvironment (TME) with its complex cell-cell/cell-matrix interactions, which shapes metabolic reprogramming crucial to cancer development/drug resistance. Patient-derived organotypic tissue cultures (PD-OTCs) represent a unique model that retains an individual patient's TME. PD-OTCs of non-small-cell lung cancer better recapitulated the in vivo metabolic reprogramming of patient tumors than the patient-derived tumor xenograft (PDTX), while enabling interrogation of immunometabolic response to modulators and TME-dependent resistance development. Patient-derived organoids (PDOs) are also good models for reconstituting TME-dependent metabolic reprogramming and for evaluating therapeutic responses. Single-cell based 'omics on combinations of PD-OTC and PDO models will afford an unprecedented understanding on TME dependence of human cancer metabolic reprogramming, which should translate into the identification of novel metabolic targets for regulating TME interactions and drug resistance.

Early 2-Factor Transcription Factors Associated with Progression and Recurrence in Bevacizumab-Responsive Subtypes of Glioblastoma

The early 2-factor (E2F) family of transcription factors, including E2F1 through 8, plays a critical role in apoptosis, metabolism, proliferation, and angiogenesis within glioblastoma (GBM). However, the specific functions of E2F transcription factors (E2Fs) and their impact on the malignancy of Bevacizumab (BVZ)-responsive GBM subtypes remain unclear. This study used data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), and Gene Expression Omnibus (GEO) to explore the impact of eight E2F family members on the clinical characteristics of BVZ-responsive GBM subtypes and possible mechanisms of recurrence after BVZ treatment. Using machine learning algorithms, including TreeBagger and deep neural networks, we systematically predicted and validated GBM patient survival terms based on the expression profiles of E2Fs across BVZ-responsive GBM subtypes. Our bioinformatics analyses suggested that a significant increase in E2F8 post-BVZ treatment may enhance the function of angiogenesis and stem cell proliferation, implicating this factor as a candidate mechanism of GBM recurrence after treatment. In addition, BVZ treatment in unresponsive GBM patients may potentially worsen disease progression. These insights underscore that E2F family members play important roles in GBM malignancy and BVZ treatment response, highlighting their potential as prognostic biomarkers, therapeutic targets, and recommending precision BVZ treatment to individual GBM patients.