Minimum sample size for external validation of a clinical prediction model with a continuous outcome.

Clinical prediction models provide individualized outcome predictions to inform patient counseling and clinical decision making. External validation is the process of examining a prediction model's performance in data independent to that used for model development. Current external validation studies often suffer from small sample sizes, and subsequently imprecise estimates of a model's predictive performance. To address this, we propose how to determine the minimum sample size needed for external validation of a clinical prediction model with a continuous outcome. Four criteria are proposed, that target precise estimates of (i) R2 (the proportion of variance explained), (ii) calibration-in-the-large (agreement between predicted and observed outcome values on average), (iii) calibration slope (agreement between predicted and observed values across the range of predicted values), and (iv) the variance of observed outcome values. Closed-form sample size solutions are derived for each criterion, which require the user to specify anticipated values of the model's performance (in particular R2 ) and the outcome variance in the external validation dataset. A sensible starting point is to base values on those for the model development study, as obtained from the publication or study authors. The largest sample size required to meet all four criteria is the recommended minimum sample size needed in the external validation dataset. The calculations can also be applied to estimate expected precision when an existing dataset with a fixed sample size is available, to help gauge if it is adequate. We illustrate the proposed methods on a case-study predicting fat-free mass in children

Minimum sample size calculations for external validation of a clinical prediction model with a time-to-event outcome.

Previous articles in Statistics in Medicine describe how to calculate the sample size required for external validation of prediction models with continuous and binary outcomes. The minimum sample size criteria aim to ensure precise estimation of key measures of a model's predictive performance, including measures of calibration, discrimination, and net benefit. Here, we extend the sample size guidance to prediction models with a time-to-event (survival) outcome, to cover external validation in datasets containing censoring. A simulation-based framework is proposed, which calculates the sample size required to target a particular confidence interval width for the calibration slope measuring the agreement between predicted risks (from the model) and observed risks (derived using pseudo-observations to account for censoring) on the log cumulative hazard scale. Precise estimation of calibration curves, discrimination, and net-benefit can also be checked in this framework. The process requires assumptions about the validation population in terms of the (i) distribution of the model's linear predictor and (ii) event and censoring distributions. Existing information can inform this; in particular, the linear predictor distribution can be approximated using the C-index or Royston's D statistic from the model development article, together with the overall event risk. We demonstrate how the approach can be used to calculate the sample size required to validate a prediction model for recurrent venous thromboembolism. Ideally the sample size should ensure precise calibration across the entire range of predicted risks, but must at least ensure adequate precision in regions important for clinical decision-making. Stata and R code are provided

Research productivity and academics’ conceptions of research

This paper asks the question: do people with different levels of research productivity and identification as a researcher think of research differently? It discusses a study that differentiated levels of research productivity among English and Australian academics working in research-intensive environments in three broad discipline areas: science, engineering and technology; social science and humanities; and medicine and health sciences. The paper explores the different conceptions of research held by these academics in terms of their levels of research productivity, their levels of research training, whether they considered themselves an active researcher and a member of a research team, and their disciplinary differences

Minimum sample size for external validation of a clinical prediction model with a binary outcome

In prediction model research, external validation is needed to examine an existing model's performance using data independent to that for model development. Current external validation studies often suffer from small sample sizes and consequently imprecise predictive performance estimates. To address this, we propose how to determine the minimum sample size needed for a new external validation study of a prediction model for a binary outcome. Our calculations aim to precisely estimate calibration (Observed/Expected and calibration slope), discrimination (C-statistic), and clinical utility (net benefit). For each measure, we propose closed-form and iterative solutions for calculating the minimum sample size required. These require specifying: (i) target SEs (confidence interval widths) for each estimate of interest, (ii) the anticipated outcome event proportion in the validation population, (iii) the prediction model's anticipated (mis)calibration and variance of linear predictor values in the validation population, and (iv) potential risk thresholds for clinical decision-making. The calculations can also be used to inform whether the sample size of an existing (already collected) dataset is adequate for external validation. We illustrate our proposal for external validation of a prediction model for mechanical heart valve failure with an expected outcome event proportion of 0.018. Calculations suggest at least 9835 participants (177 events) are required to precisely estimate the calibration and discrimination measures, with this number driven by the calibration slope criterion, which we anticipate will often be the case. Also, 6443 participants (116 events) are required to precisely estimate net benefit at a risk threshold of 8%. Software code is provided.</p

Minimal reporting improvement after peer review in reports of covid-19 prediction models: systematic review.

OBJECTIVE: To assess improvement in the completeness of reporting COVID-19 prediction models after the peer review process. STUDY DESIGN AND SETTING: Studies included in a living systematic review of COVID-19 prediction models, with both pre-print and peer-reviewed published versions available, were assessed. The primary outcome was the change in percentage adherence to the TRIPOD reporting guidelines between pre-print and published manuscripts. RESULTS: 19 studies were identified including seven (37%) model development studies, two external validations of existing models (11%), and 10 (53%) papers reporting on both development and external validation of the same model. Median percentage adherence amongst pre-print versions was 33% (min-max: 10 to 68%). The percentage adherence of TRIPOD components increased from pre-print to publication in 11/19 studies (58%), with adherence unchanged in the remaining eight studies. The median change in adherence was just 3 percentage points (pp, min-max: 0-14pp) across all studies. No association was observed between the change in percentage adherence and pre-print score, journal impact factor, or time between journal submission and acceptance. CONCLUSIONS: Pre-print reporting quality of COVID-19 prediction modelling studies is poor and did not improve much after peer review, suggesting peer review had a trivial effect on the completeness of reporting during the pandemic

Can bile duct injuries be prevented? "A new technique in laparoscopic cholecystectomy"

BACKGROUND: Over the last decade, laparoscopic cholecystectomy has gained worldwide acceptance and considered to be as "gold standard" in the surgical management of symptomatic cholecystolithiasis. However, the incidence of bile duct injury in laparoscopic cholecystectomy is still two times greater compared to classic open surgery. The development of bile duct injury may result in biliary cirrhosis and increase in mortality rates. The mostly blamed causitive factor is the misidentification of the anatomy, especially by a surgeon who is at the beginning of his learning curve. Biliary tree injuries may be decreased by direct coloration of the cystic duct, ductus choledochus and even the gall bladder. METHODS: gall bladder fundus was punctured by Veress needle and all the bile was aspirated. The same amount of fifty percent methylene blue diluted by saline solution was injected into the gall bladder for coloration of biliary tree. The dissection of Calot triangle was much more safely performed after obtention of coloration of the gall bladder, cystic duct and choledocus. RESULTS: Between October 2003 and December 2004, overall 46 patients (of which 9 males) with a mean age of 47 (between 24 and 74) underwent laparoscopic cholecystectomy with methylene blue injection technique. The diagnosis of chronic cholecystitis (the thickness of the gall bladder wall was normal) confirmed by pre-operative abdominal ultrasonography in all patients. The diameters of the stones were greater than 1 centimeter in 32 patients and calcula of various sizes being smaller than 1 cm. were documented in 13 cases. One patient was operated for gall bladder polyp (our first case). Successful coloration of the gall bladder, cystic duct and ductus choledochus was possible in 43 patients, whereas only the gall bladder and proximal cystic duct were visualised in 3 cases. In these cases, ductus choledochus visibility was not possible. None of the patients developed bile duct injury. CONCLUSION: The number of bile duct injuries related to anatomic misidentification can be decreased and even vanished by using intraoperative methylene blue injection technique into the gall bladder fundus intraoperatively

Dietary calcium and zinc deficiency risks are decreasing but remain prevalent

Globally, more than 800 million people are undernourished while >2 billion people have one or more chronic micronutrient deficiencies (MNDs). More than 6% of global mortality and morbidity burdens are associated with undernourishment and MNDs. Here we show that, in 2011, 3.5 and 1.1 billion people were at risk of calcium (Ca) and zinc (Zn) deficiency respectively due to inadequate dietary supply. The global mean dietary supply of Ca and Zn in 2011 was 684 ± 211 and 16 ± 3 mg capita−1 d−1 (±SD) respectively. Between 1992 and 2011, global risk of deficiency of Ca and Zn decreased from 76 to 51%, and 22 to 16%, respectively. Approximately 90% of those at risk of Ca and Zn deficiency in 2011 were in Africa and Asia. To our knowledge, these are the first global estimates of dietary Ca deficiency risks based on food supply. We conclude that continuing to reduce Ca and Zn deficiency risks through dietary diversification and food and agricultural interventions including fortification, crop breeding and use of micronutrient fertilisers will remain a significant challenge

A new, large-bodied omnivorous bat (Noctilionoidea: Mystacinidae) reveals lost morphological and ecological diversity since the Miocene in New Zealand

A new genus and species of fossil bat is described from New Zealand's only pre-Pleistocene Cenozoic terrestrial fauna, the early Miocene St Bathans Fauna of Central Otago, South Island. Bayesian total evidence phylogenetic analysis places this new Southern Hemisphere taxon among the burrowing bats (mystacinids) of New Zealand and Australia, although its lower dentition also resembles Africa's endemic sucker-footed bats (myzopodids). As the first new bat genus to be added to New Zealand's fauna in more than 150 years, it provides new insight into the original diversity of chiropterans in Australasia. It also underscores the significant decline in morphological diversity that has taken place in the highly distinctive, semi-terrestrial bat family Mystacinidae since the Miocene. This bat was relatively large, with an estimated body mass of ~40 g, and its dentition suggests it had an omnivorous diet. Its striking dental autapomorphies, including development of a large hypocone, signal a shift of diet compared with other mystacinids, and may provide evidence of an adaptive radiation in feeding strategy in this group of noctilionoid bats

5-HTR3 and 5-HTR4 located on the mitochondrial membrane and functionally regulated mitochondrial functions

5-HT has been reported to possess significant effects on cardiac activities, but activation of 5-HTR on the cell membrane failed to illustrate the controversial cardiac reaction. Because 5-HT constantly comes across the cell membrane via 5-HT transporter (5-HTT) into the cytoplasm, whether 5-HTR is functional present on the cellular organelles is unknown. Here we show 5-HTR3 and 5-HTR4 were located in cardiac mitochondria, and regulated mitochondrial activities and cellular functions. Knock down 5-HTR3 and 5-HTR4 in neonatal cardiomyocytes resulted in significant increase of cell damage in response to hypoxia, and also led to alternation in heart beating. Activation of 5-HTR4 attenuated mitochondrial Ca2+ uptake under the both normoxic and hypoxic conditions, whereas 5-HTR3 augmented Ca2+ uptake only under hypoxia. 5-HTR3 and 5-HTR4 exerted the opposite effects on the mitochondrial respiration: 5-HTR3 increased RCR (respiration control ratio), but 5-HTR4 reduced RCR. Moreover, activation of 5-HTR3 and 5-HTR4 both significantly inhibited the opening of mPTP. Our results provided the first evidence that 5-HTR as a GPCR and an ion channel, functionally expressed in mitochondria and participated in the mitochondria function and regulation to maintain homeostasis of mitochondrial [Ca2+], ROS, and ATP generation efficiency in cardiomyocytes in response to stress and O2 tension