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Background Prediction models can identify fall-prone individuals. Prediction models can be based on either data from research cohorts (cohort-based) or routinely collected data (RCD-based). We review and compare cohort-based and RCD-based studies describing the development and/or validation of fall prediction models for community-dwelling older adults. Methods Medline and Embase were searched via Ovid until January 2023. We included studies describing the development or validation of multivariable prediction models of falls in older adults (60+). Both risk of bias and reporting quality were assessed using the PROBAST and TRIPOD, respectively. Results We included and reviewed 28 relevant studies, describing 30 prediction models (23 cohort-based and 7 RCD-based), and external validation of two existing models (one cohort-based and one RCD-based). The median sample sizes for cohort-based and RCD-based studies were 1365 [interquartile range (IQR) 426–2766] versus 90 441 (IQR 56 442–128 157), and the ranges of fall rates were 5.4% to 60.4% versus 1.6% to 13.1%, respectively. Discrimination performance was comparable between cohort-based and RCD-based models, with the respective area under the receiver operating characteristic curves ranging from 0.65 to 0.88 versus 0.71 to 0.81. The median number of predictors in cohort-based final models was 6 (IQR 5–11); for RCD-based models, it was 16 (IQR 11–26). All but one cohort-based model had high bias risks, primarily due to deficiencies in statistical analysis and outcome determination. Conclusions Cohort-based models to predict falls in older adults in the community are plentiful. RCD-based models are yet in their infancy but provide comparable predictive performance with no additional data collection efforts. Future studies should focus on methodological and reporting quality. [ABSTRACT FROM AUTHOR]

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Background: Necroptosis could regulate immunity in cancers, and stratification of colorectal cancer (CRC) subtypes based on key genes related to necroptosis might be a novel strategy for CRC treatment. Method: The RNA-sequencing data of CRC and other 31 types of cancers were obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering was performed based on protein-coding genes (PCGs) related to necroptosis score calculated by single sample gene set enrichment analysis (ssGSEA). Module genes showing a significant positive correlation with the necroptosis score were identified by weighted correlation network analysis (WGCNA) and further used to develop a risk stratification model applying least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The risks score for each sample in CRC cohorts, immunotherapy cohorts and pan-cancer study cohorts was calculated. Result: Two subgroups (C1 cluster and C2 cluster) of CRC were identified based on the necroptosis score. Compared with C1 cluster, the survival possibility of C2 cluster was greatly reduced, the levels of necroptosis score, immune cell infiltration, immune score and expression of immune checkpoint molecules were significantly increased and immunotherapy response was less active. Low-risk patients defined by the risk model had a significant survival advantage than high-risk counterparts in both CRC and the other 31 cancer types. Furthermore, the risk model was also more efficient than the Tumor Immune Dysfunction and Exclusion (TIDE) tool in predicting OS and immunotherapy response for the samples in the immunotherapy cohort. Conclusion: CRC patients were classified by necroptosis score-related PCGs, and a risk model was designed to evaluate the immunotherapy and prognosis of patients with CRC. The current molecular subtype and prognostic model could help stratify patients with different risks and predict their prognosis and immunotherapy sensitivity.

Pediatric renal transplant recipients (RTRs) face heightened risks when they transition from a childhood nephrologist to an adult-centered one. The transition of care usually occurs when an individual is between ages 18 and 21 years, although some change providers earlier or later depending on varying circumstances. Turbulence during this shift can significantly impact daily life and, in severe cases, lead to graft loss. Several modern studies have explored the transition from pediatric to adult-centered nephrology care post-renal transplant. In this review, we first provide an overview of the differences between pediatric and adult renal transplant, highlighting unique challenges faced by pediatric patients such as donor-recipient size disparity, growth impairment, and need for additional immunizations. We then emphasize the criticality of a well-planned transition process, identifying factors that can hinder a smooth transition-such as medical and medication nonadherence, lack of health literacy, patient psychosocial challenges, and systemic shortcomings in coordination between care teams. Furthermore, this review outlines existing protocols and risk assessment tools, in addition to highlighting recent advancements aimed at facilitating smoother transitions such as the RISE protocol, readiness assessment, and the use of multidisciplinary teams. Proper implementation of coordinated, evidence-based transition protocols can improve patient outcomes, promote medication and appointment adherence, and reduce graft rejection rates. Efforts from multidisciplinary teams utilizing technology, risk stratification tools, and open communication between providers and patients are key to optimizing the transition process for pediatric RTRs as they transfer to adult-centered care., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-24-149/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Pulmonary arterial hypertension (PAH) is characterized by elevated pulmonary arterial blood pressure secondary to increased pulmonary vascular resistance. Invasive hemodynamic assessment by heart catheterization (RHC) remains the gold standard to confirm the diagnosis, to determine the severity of right ventricular dysfunction and to test for pulmonary vasoreactivity. After diagnosis and initiation of therapy, many PAH centers continue to perform RHC at regular intervals to monitor for disease progression and alter management. We discuss the importance of risk stratification in PAH, the role of RHC in the evaluation and treatment of these patients and compare non-invasive risk assessment tools to that of RHC. RHC is useful for diagnosis of PAH, assessing the risk of mortality and morbidity, directing the escalation and de-escalation of therapy, and monitoring for disease progression. In the current era of improved non-invasive cardiac hemodynamic assessment, the role for routine follow-up serial RHC in patients with PAH needs to be reassessed in future studies. With the availability of non-invasive risk assessment tools such as REVEAL Lite 2, it may be reasonable to reconsider the role of annual or protocoled RHC, and instead, move on to an "as needed" and individual approach. [ABSTRACT FROM AUTHOR]

Background: Necroptosis could regulate immunity in cancers, and stratification of colorectal cancer (CRC) subtypes based on key genes related to necroptosis might be a novel strategy for CRC treatment., Method: The RNA-sequencing data of CRC and other 31 types of cancers were obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering was performed based on protein-coding genes (PCGs) related to necroptosis score calculated by single sample gene set enrichment analysis (ssGSEA). Module genes showing a significant positive correlation with the necroptosis score were identified by weighted correlation network analysis (WGCNA) and further used to develop a risk stratification model applying least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The risks score for each sample in CRC cohorts, immunotherapy cohorts and pan-cancer study cohorts was calculated., Result: Two subgroups (C1 cluster and C2 cluster) of CRC were identified based on the necroptosis score. Compared with C1 cluster, the survival possibility of C2 cluster was greatly reduced, the levels of necroptosis score, immune cell infiltration, immune score and expression of immune checkpoint molecules were significantly increased and immunotherapy response was less active. Low-risk patients defined by the risk model had a significant survival advantage than high-risk counterparts in both CRC and the other 31 cancer types. Furthermore, the risk model was also more efficient than the Tumor Immune Dysfunction and Exclusion (TIDE) tool in predicting OS and immunotherapy response for the samples in the immunotherapy cohort., Conclusion: CRC patients were classified by necroptosis score-related PCGs, and a risk model was designed to evaluate the immunotherapy and prognosis of patients with CRC. The current molecular subtype and prognostic model could help stratify patients with different risks and predict their prognosis and immunotherapy sensitivity., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Rationale: Accurate peri-operative risk prediction is an essential element of clinical practice. Various risk stratification tools for assessing patients' risk of mortality or morbidity have been developed and applied in clinical practice over the years. This review aims to outline essential characteristics (predictive accuracy, objectivity, clinical utility) of currently available risk scoring tools for hip fracture patients.Methods: We searched eight databases; AMED, CINHAL, Clinical Trials.gov, Cochrane, DARE, EMBASE, MEDLINE and Web of Science for all relevant studies published until April 2015. We included published English language observational studies that considered the predictive accuracy of risk stratification tools for patients with fragility hip fracture.Results: After removal of duplicates, 15,620 studies were screened. Twenty-nine papers met the inclusion criteria, evaluating 25 risk stratification tools. Risk stratification tools considered in more than two studies were; ASA, CCI, E-PASS, NHFS and O-POSSUM. All tools were moderately accurate and validated in multiple studies; however there are some limitations to consider. The E-PASS and O-POSSUM are comprehensive but complex, and require intraoperative data making them a challenge for use on patient bedside. The ASA, CCI and NHFS are simple, easy and inexpensive using routinely available preoperative data. Contrary to the ASA and CCI which has subjective variables in addition to other limitations, the NHFS variables are all objective.Conclusion: In the search for a simple and inexpensive, easy to calculate, objective and accurate tool, the NHFS may be the most appropriate of the currently available scores for hip fracture patients. However more studies need to be undertaken before it becomes a national hip fracture risk stratification or audit tool of choice. [ABSTRACT FROM AUTHOR]