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This retrospective cohort study evaluated the relationship between patient falls, Morse Fall Scale (MFS) items, patient demographics, length of stay and hospital site.
Data were acquired from 72 hospitals in a health system. Logistic regression models were conducted including MFS items, demographics, length of stay, and interaction terms. The final mixed effects logistic regression model included significant patient-level covariates as fixed effects and hospital site as a random effect.
6531 of 978,920 total admissions included a patient fall. Four MFS items (fall history, secondary diagnosis, gait weak/impaired, mental status—overestimates/forgets limitations) and three demographic items (male gender, increased age, longer length of stay) were associated with increased likelihood of falling. Two MFS items (ambulatory aids, intravenous therapy/lock) and Hispanic ethnicity were associated with decreased risk of falling. An interaction effect was present between male gender and mental status. Males who overestimate/forget limitations had 3.16 times higher odds of falling than females oriented to their own ability. The proportion of variance in falls between hospitals was 0.23 and the median odds ratio (MOR) 1.57.
This study uniquely assessed fall risk at the level of the patient and hospital, using data from nearly 1 million admissions at 72 hospitals. Controlling for patient characteristics, results demonstrate variability in fall risk among hospitals. Research informing hospital differences as well as gender and racial/ethnic differences in falls is needed to identify appropriate interventions.
As hospitals increasingly adopt risk-directed fall prevention, assessment tools should be re-evaluated for clinical utility and corresponding prevention practices. The MFS may be enhanced by removing intravenous lock as a risk and screening for additional risks such as medications and medical equipment. Quality improvement efforts must also consider the hospital's environment and processes that may further contribute to fall risk.
Authors adhered to STROBE guidelines for reporting.
No Patient or Public Contribution.
Detecting cancer earlier improves treatment options and long-term survival. A multicancer early detection test that reliably picks up early-stage cancer would potentially save lives and reduce the cost of treating cancer. One promising candidate is the Enlighten test, which applies machine learning to plasma amino acid concentrations to detect cancer. In a cohort of 77 patients recently diagnosed with breast, colorectal, pancreatic or prostate cancer, 60 (78%) were detected by the test (sensitivity), with no false positives in 20 healthy controls. The MODERNISED study will further develop the Enlighten test to detect 10 different cancers by adding bladder, lung, melanoma, oesophageal, ovarian and renal cancer to the test.
MODERNISED (ISRCTN17299125) is a multicentre prospective, non-interventional, case–control study. We aim to recruit 1000 adult participants with a recent cancer diagnosis, 250 adult participants with symptoms of cancer where a cancer diagnosis was ruled out by the National Health Service (NHS) standard of care and 100 healthy adult volunteers. Cancer tissue of origin (ToO) will include bladder, breast, colorectal, lung, melanoma, oesophageal, ovarian, pancreatic, prostate and renal. Participants in the two non-cancer cohorts who are later diagnosed with cancer will be moved to the cancer cases cohort. The primary aim is to train and validate a machine learning algorithm to detect cancer, which will be evaluated by AUROC. Secondary aims include training and validating an algorithm to predict ToO and stage of cancer, exploring differences in performance by demographics and estimating how sensitivity varies across specificity cut-offs of 95%, 99% and 99.9%. These results will provide a statistically powered estimate of how well the Enlighten test can discriminate between individuals with and without cancer, which can then be validated for clinical use in further research.
This study is sponsored by University Hospital Southampton NHS Foundation Trust and has been approved by the Health Research Authority and Health and Care Research West Midlands (24/WM/0234). Results will be presented at scientific meetings and published in international peer-reviewed journals. Lay summaries of study progress and findings will be published on the Southampton Clinical Trial Unit’s website.
Inhaled anaesthetics can be used in mechanically ventilated critically ill patients to provide sedation. This approach to sedation potentially improves patient and health system outcomes, but further supportive evidence is needed. The objective of the SAVE-ICU clinical trial is to compare the effectiveness of inhaled versus intravenous sedation in ventilated adults with acute hypoxaemic respiratory failure.
SAVE-ICU is a multicentre, open-label, pragmatic, randomised controlled trial conducted in 15 intensive care units (ICUs) in Canada and the USA. Eligible patients include mechanically ventilated and sedated adults with acute hypoxemic respiratory failure from COVID-19 or non-COVID causes with PaO2/FIO2 ratio 12 hour). A hierarchy of outcomes was identified at the time of trial design, as the trial was launched during the COVID-19 pandemic when study drug shortages, staffing challenges and healthcare system pressures were prevalent and there was a requirement for rapid evidence generation and implementation on this topic. The primary outcome and highest in the hierarchy is hospital mortality (requiring 758 participants). Secondary and lower hierarchical outcomes are ventilator-free days at day 30 (200 patients), quality of life at 3 months (144 participants) and ICU-free days at day 30 (128 participants). Additional secondary outcomes include median daily oxygenation at day 3 (PaO2/FIO2 ratio), need for adjunctive acute respiratory distress syndrome therapies (prone positioning, inhaled nitric oxide, paralysis with a neuromuscular blocking agent and extracorporeal membrane oxygenation) during ICU stay, days alive and free from delirium and coma at day 14, hospital-free days at day 60 and disability score at 3 months and 12 months after enrolment.
The protocol was approved by all hospital ethics committees and by Health Canada. Informed consent will be obtained from substitute decision makers or deferred consent (as permitted by site ethics board). Trial findings will be shared at the end of the study using peer-review publications, conference presentations and social media as part of the trial knowledge translation plan.
Although low-density lipoprotein cholesterol (LDL-C) is established as the primary cardiovascular disease (CVD) risk factor, some individuals with LDL-C within desirable limits still develop coronary artery disease (CAD). Lipoprotein(a) (Lp(a)) has emerged as a genetically determined independent risk factor for CVD. This study aims to investigate Lp(a) by determining its association with coronary artery stenosis severity, identifying its ethnic-specific genetic determinants and assessing its relationship with an energy-dense dietary pattern.
The PUTRA-CV study is a 3-year, multicentre, case-control observational study involving adult patients who have undergone coronary angiography. The primary outcome is the association between Lp(a) levels and the severity of angiographic CAD (assessed by Gensini or Syntax score). Secondary outcomes include the frequencies of Lp(a)-associated single nucleotide polymorphisms (SNPs) (rs10455872 and rs3798220) and the association between dietary patterns and Lp(a) levels. Lp(a) will be measured using a particle-enhanced immunoturbidimetric method, and SNPs will be genotyped using high-resolution melting. Dietary intake will be assessed using a validated semiquantitative food frequency questionnaire. Data will be analysed using SPSS. Descriptive statistics will be used to summarise population characteristics. Bivariate analyses will use chi-square (2), independent t-tests or Mann-Whitney U tests as appropriate. The independent association between Lp(a) and coronary artery stenosis severity will be determined using multivariable logistic regression, adjusting for confounders. Empirically driven dietary patterns will be derived using reduced rank regression, and their association with Lp(a) will be assessed. For genetic analysis, allele frequencies of the LPA SNPs rs10455872 and rs3798220 will be calculated and compared between cases and controls.
Ethical approval has been obtained from the ethics committees of the Ministry of Health Malaysia (NMRR ID-24-00877-2ID-IIR), Universiti Putra Malaysia (JKEUPM-2024–246), Universiti Teknologi MARA (REC/07/2024-OT/FB/2) and Universiti Malaya Medical Centre (MREC ID NO: 2 02 453–13692). The findings will be disseminated via peer-reviewed journals and conferences.
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