A systematic review and external validation of stroke prediction models demonstrates poor performance in dialysis patients

Treatment strategies of the thromboembolic risk in kidney failure patients with atrial fibrillation

The incidence and prevalence of atrial fibrillation (AF) in patients affected by kidney failure, i.e. glomerular filtration rate <15 ml/min/1.73 m2, is high and probably underestimated. Numerous uncertainties remain regarding how to prevent thromboembolic events in this population because both cardiology and nephrology guidelines do not provide clear recommendations. The efficacy and safety of oral anticoagulant therapy (OAC) in preventing thromboembolism in patients with kidney failure and AF has not been demonstrated for either vitamin K antagonists (VKAs) or direct anticoagulants (DOACs). Moreover, it remains unclear which is more effective and safer, because estimated creatinine clearance <25-30 ml/min was an exclusion criterion in the randomized controlled trials (RCTs). Three RCTs comparing DOACs and VKAs in kidney failure failed to reach the primary endpoint, as they were underpowered. The left atrial appendage is the main source of thromboembolism in the presence of AF. Left atrial appendage closure (LAAC) has recently been proposed as an alternative to OAC. RCTs comparing the efficacy and safety of LAAC versus OAC in kidney failure were terminated prematurely due to recruitment failure. A recent prospective study showed a reduction in thromboembolic events in haemodialysis patients with AF and undergoing LAAC compared with patients taking or not taking OAC. We review current treatment standards and discuss recent developments in managing the thromboembolic risk in kidney failure patients with AF. The importance of shared decision-making with the multidisciplinary team and the patient to consider individual risks and benefits of each treatment option is underlined.

[Atrial fibrillation - what should be taken into account with chronic kidney disease and hemodialysis?]

CKD is a common comorbidity in patients with atrial fibrillation. The CHA2DS2-VASc score is not validated in patients with severe CKD and has a low predictive value in dialysis patients. As NOACs are partly eliminated by the kidneys the dosage has to be adapted in CKD. Recent studies indicate an acceptable safety profile for NOACs in CKD. However, larger randomized studies are still lacking. The results from prospective studies with placebo i.e., no anticoagulation therapy, are pending.

Performance of risk scores in predicting major bleeding in left ventricular assist device recipients: a comparative external validation

Background

Implantation of a left ventricular assist device (LVAD) is a crucial therapeutic option for selected end-stage heart failure patients. However, major bleeding (MB) complications postimplantation are a significant concern.

Objectives

We evaluated current risk scores' predictive accuracy for MB in LVAD recipients.

Methods

We conducted an observational, single-center study of LVAD recipients (HeartWare or HeartMate-3, November 2010-December 2022) in the Netherlands. The primary outcome was the first post-LVAD MB (according to the International Society on Thrombosis and Haemostasis [ISTH] and Interagency Registry for Mechanically Assisted Circulatory Support [INTERMACS], and INTERMACS combined with intracranial bleeding [INTERMACS+] criteria). Mortality prior to MB was considered a competing event. Discrimination (C-statistic) and calibration were evaluated for the Hypertension, Abnormal Renal/Liver Function, Stroke, Bleeding History or Predisposition, Labile INR, Elderly, Drugs/Alcohol Concomitantly score, Hepatic or Renal Disease, Ethanol Abuse, Malignancy, Older Age, Reduced Platelet Count or Function, Re-Bleeding, Hypertension, Anemia, Genetic Factors, Excessive Fall Risk and Stroke score, Anticoagulation and Risk Factors in Atrial Fibrillation score, Outpatient Bleeding Risk Index, venous thromboembolism score, atrial fibrillation score, and Utah Bleeding Risk Score (UBRS).

Results

One hundred four patients were included (median age, 64 years; female, 20.2%; HeartWare, 90.4%; HeartMate-3, 9.6%). The cumulative MB incidence was 75.7% (95% CI 65.5%-85.9%) by ISTH and INTERMACS+ criteria and 67.0% (95% CI 56.0%-78.0%) per INTERMACS criteria over a median event-free follow-up time of 1916 days (range, 59-4521). All scores had poor discriminative ability on their intended prediction timeframe. Cumulative area under the receiving operator characteristic curve ranged from 0.49 (95% CI 0.35-0.63, venous thromboembolism-BLEED) to 0.56 (95% CI 0.47-0.65, UBRS) according to ISTH and INTERMACS+ criteria and from 0.48 (95% CI 0.40-0.56, Anticoagulation and Risk Factors in Atrial Fibrillation) to 0.56 (95% CI 0.47-0.65, UBRS) per INTERMACS criteria. All models showed poor calibration, largely underestimating MB risk.

Conclusion

Current bleeding risk scores exhibit inadequate predictive accuracy for LVAD recipients. There is a need for an accurate risk score to identify LVAD patients at high risk of MB who may benefit from patient-tailored antithrombotic therapy.

Prognostic Models in Nephrology: Where Do We Stand and Where Do We Go from Here? Mapping Out the Evidence in a Scoping Review

Prognostic models can strongly support individualized care provision and well-informed shared decision making. There has been an upsurge of prognostic research in the field of nephrology, but the uptake of prognostic models in clinical practice remains limited. Therefore, we map out the research field of prognostic models for kidney patients and provide directions on how to proceed from here. We performed a scoping review of studies developing, validating, or updating a prognostic model for patients with CKD. We searched all published models in PubMed and Embase and report predicted outcomes, methodological quality, and validation and/or updating efforts. We found 602 studies, of which 30.1% concerned CKD populations, 31.6% dialysis populations, and 38.4% kidney transplantation populations. The most frequently predicted outcomes were mortality ( n =129), kidney disease progression ( n =75), and kidney graft survival ( n =54). Most studies provided discrimination measures (80.4%), but much less showed calibration results (43.4%). Of the 415 development studies, 28.0% did not perform any validation and 57.6% performed only internal validation. Moreover, only 111 models (26.7%) were externally validated either in the development study itself or in an independent external validation study. Finally, in 45.8% of development studies no useable version of the model was reported. To conclude, many prognostic models have been developed for patients with CKD, mainly for outcomes related to kidney disease progression and patient/graft survival. To bridge the gap between prediction research and kidney patient care, patient-reported outcomes, methodological rigor, complete reporting of prognostic models, external validation, updating, and impact assessment urgently need more attention.

Bleeding Risk in Hemodialysis Patients

Cardiovascular diseases are highly prevalent among patients on dialysis. For these diseases, antiplatelets and antithrombotic therapies including heparin, vitamin K antagonists, and direct oral anticoagulants, are being used. However, the benefit-risk balance of these therapies could differ for dialysis patients compared with the general population. This review article focuses on the bleeding risk associated with the use of heparin, antiplatelets, vitamin K antagonists, and direct oral anticoagulants in patients receiving hemodialysis.

Atrial Fibrillation in Kidney Failure: Challenges in Risk Assessment and Anticoagulation Management

Management of atrial fibrillation (AF) is a clinical conundrum in people with kidney failure. Stroke risk is disproportionately high, but clinicians have a limited armamentarium to improve outcomes in this population in whom there is a concurrently high bleeding risk. Direct oral anticoagulants may have a superior benefit-risk profile compared with vitamin K antagonists in people on hemodialysis. Although research has predominantly focused on identifying a safe and effective oral anticoagulation option to reduce stroke risk in people with kidney failure (and predominantly those on hemodialysis), it remains uncertain how clinicians discriminate between people who would derive net clinical benefit as opposed to net harm. The recommended CHA2DS2-VASc score cutoffs provide poor discriminatory value, and there is an urgent need to identify robust markers of thromboembolic risk in kidney failure. There is increasing data to challenge the prior dogma of risk equivalence across AF type, and the American Heart Association highlights moving beyond AF as a binary entity to consider the prognostic significance of AF burden. Implantable cardiac monitor studies reveal high rates and varied burden of subclinical and paroxysmal AF in people on hemodialysis. The association between AF burden and the proarrhythmic environment of hemodialysis with cyclical volume loading, offloading, and electrolyte changes is not well studied. We review the significance of AF burden as a contributor to thromboembolic risk, its potential as the missing link in risk assessment, and updated evidence for anticoagulation in people with kidney failure.

Systematic metareview of prediction studies demonstrates stable trends in bias and low PROBAST inter-rater agreement

OBJECTIVES

To (1) explore trends of risk of bias (ROB) in prediction research over time following key methodological publications, using the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and (2) assess the inter-rater agreement of the PROBAST.

STUDY DESIGN AND SETTING

PubMed and Web of Science were searched for reviews with extractable PROBAST scores on domain and signaling question (SQ) level. ROB trends were visually correlated with yearly citations of key publications. Inter-rater agreement was assessed using Cohen's Kappa.

RESULTS

One hundred and thirty nine systematic reviews were included, of which 85 reviews (containing 2,477 single studies) on domain level and 54 reviews (containing 2,458 single studies) on SQ level. High ROB was prevalent, especially in the Analysis domain, and overall trends of ROB remained relatively stable over time. The inter-rater agreement was low, both on domain (Kappa 0.04-0.26) and SQ level (Kappa -0.14 to 0.49).

CONCLUSION

Prediction model studies are at high ROB and time trends in ROB as assessed with the PROBAST remain relatively stable. These results might be explained by key publications having no influence on ROB or recency of key publications. Moreover, the trend may suffer from the low inter-rater agreement and ceiling effect of the PROBAST. The inter-rater agreement could potentially be improved by altering the PROBAST or providing training on how to apply the PROBAST.

Comprehensive comparison of stroke risk score performance: a systematic review and meta-analysis among 6 267 728 patients with atrial fibrillation

AIMS

Multiple risk scores to predict ischaemic stroke (IS) in patients with atrial fibrillation (AF) have been developed. This study aims to systematically review these scores, their validations and updates, assess their methodological quality, and calculate pooled estimates of the predictive performance.

METHODS AND RESULTS

We searched PubMed and Web of Science for studies developing, validating, or updating risk scores for IS in AF patients. Methodological quality was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). To assess discrimination, pooled c-statistics were calculated using random-effects meta-analysis. We identified 19 scores, which were validated and updated once or more in 70 and 40 studies, respectively, including 329 validations and 76 updates-nearly all on the CHA2DS2-VASc and CHADS2. Pooled c-statistics were calculated among 6 267 728 patients and 359 373 events of IS. For the CHA2DS2-VASc and CHADS2, pooled c-statistics were 0.644 [95% confidence interval (CI) 0.635-0.653] and 0.658 (0.644-0.672), respectively. Better discriminatory abilities were found in the newer risk scores, with the modified-CHADS2 demonstrating the best discrimination [c-statistic 0.715 (0.674-0.754)]. Updates were found for the CHA2DS2-VASc and CHADS2 only, showing improved discrimination. Calibration was reasonable but available for only 17 studies. The PROBAST indicated a risk of methodological bias in all studies.

CONCLUSION

Nineteen risk scores and 76 updates are available to predict IS in patients with AF. The guideline-endorsed CHA2DS2-VASc shows inferior discriminative abilities compared with newer scores. Additional external validations and data on calibration are required before considering the newer scores in clinical practice.

CLINICAL TRIAL REGISTRATION

ID CRD4202161247 (PROSPERO).

Predicting Gastrostomy Tube Placement After Intracerebral Hemorrhage: External Validation of the GRAVo Score

BACKGROUND

Dysphagia is a common consequence of intracerebral hemorrhages (ICH). It can lead to enduring impairments of dietary intake and the requirement for feeding via percutaneous gastrostomy (PEG) tubes. However, variabilities in the course of swallowing recovery after ICH make it difficult to anticipate the need for PEG placement in an individual patient. A new tool called the GRAVo score was recently developed to predict PEG tube placement after an ICH but has not been externally validated. Our study aims were to externally validate the GRAVo score in a multicenter cohort and reexamine the role of race in predicting PEG placement, given the uncertain biological plausibility for this relationship observed in the derivation cohort.

METHODS

Patients for this analysis were selected from a previously completed multicenter, randomized, double-blind futility design clinical trial, the Intracerebral Hemorrhage Deferoxamine trial, and underwent a retrospective review of prospectively collected data. The GRAVo scores were computed by using previously established methods using the following variables: Glasgow Coma Scale ≤ 12 (2 points), race (1 point for Black), age > 50 years (2 points), and ICH volume > 30 mL (1 point). Association of GRAVo scores with PEG placement were examined by using logistic regression analysis after adjustment for exposure to deferoxamine. Model performance was estimated by using area under the receiving operating characteristic curve (AUROC). Subsequently, a second model was created by excluding scores for race, and the AUROC of both models were compared.

RESULTS

A total of 291 patients with complete data points served as the study cohort; 38 (13%) underwent PEG placement. The median GRAVo score for patients in the PEG and non-PEG groups were 4 (interquartile range 3-4) versus 2 (interquartile range 2-3), respectively (p < 0.0001). External validation of the GRAVo score yielded an AUROC of 0.7008 (95% confidence interval 0.6036-0.78); the model obtained without assignment of scores for the variable race yielded an AUROC of 0.6958 (95% confidence interval 0.6124-0.7891). The receiver operating characteristic curves from both models demonstrated close overlap.

CONCLUSIONS

The results of our external validation demonstrate the validity of GRAVo scores for predicting PEG tube placement after an ICH. However, its performance was more modest compared with that of the derivation cohort. Inclusion of the race variable had no measurable effect on model performance. Differences in patient characteristics between these cohorts may have influenced our results. These findings should be taken into consideration when using the GRAVo score to assist clinical decision making on PEG placement after an ICH.

Characteristics and Quality of Diagnostic and Risk Prediction Models for Frailty in Older Adults: A Systematic Review

Several prediction models for frailty in older adults have been published, but their characteristics and methodological quality are unclear. This review aims to summarize and critically appraise the prediction models. Studies describing multivariable prediction models for frailty among older adults were included. PubMed, Embase, Web of Science, and PsycINFO were searched from outset to Feb 21, 2021. Methodological and reporting quality of included models were evaluated by PROBAST and TRIPOD, respectively. All results were descriptively summarized. Twenty articles including 39 models were identified. The included models showed good predictive discrimination with C indices ranging from 0.70 to 0.98. However, all studies except one were assessed as high risk of bias mainly due to inappropriate analysis; meanwhile, poor reporting quality was also frequently observed. Few mature prediction models can be used in practice. Researchers should pay more attention to external validation and improving the quality both in methodology and reporting.

Chronic kidney disease and atrial fibrillation: A dangerous combination

Background

Chronic kidney disease (CKD) and atrial fibrillation (AF) are both risk factors for bleeding, stroke and mortality. The aim of our study was to investigate the interaction between CKD and atrial fibrillation and outcomes.

Methods

We included 12,394 subjects referred to the University Medical Center Utrecht (the Netherlands) from September 1996 to February 2018 for an out-patient visit (Utrecht Cardiovascular Cohort Second Manifestation of Arterial disease cohort). Hazard ratios (HRs) with 95% confidence intervals (CIs) for bleeding, ischemic stroke or mortality were calculated with Cox proportional hazard analyses. Presence of interaction between AF and CKD was examined by calculating the relative excess risk due to interaction (RERI), the attributable proportion (AP) due to interaction and the synergy index (S).

Results

Of the 12,394 patients, 699 patients had AF, 2,752 patients had CKD and 325 patients had both AF and CKD. Patients with both CKD and AF had a 3.0-fold (95% CI 2.0–4.4) increased risk for bleeding, a 4.2-fold (95% CI 3.0–6.0) increased ischemic stroke risk and a 2.2-fold (95% CI 1.9–2.6) increased mortality risk after adjustment as compared with subjects without atrial fibrillation and CKD. We did not find interaction between AF and CKD for bleeding and mortality. However, we found interaction between AF and CKD for ischemic stroke risk (RERI 1.88 (95% CI 0.31–3.46), AP 0.45 (95% CI 0.17–0.72) and S 2.40 (95% CI 1.08–5.32)).

Conclusion

AF and CKD are both associated with bleeding, ischemic stroke and mortality. There is a positive interaction between AF and CKD for ischemic stroke risk, but not for bleeding or mortality.

Psychosis Relapse Prediction Leveraging Electronic Health Records Data and Natural Language Processing Enrichment Methods

BACKGROUND

Identifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited. This study aimed to develop psychosis-relapse prediction models using various types of clinical notes and structured data.

METHODS

Clinical data were extracted from the electronic health records of the Ajou University Medical Center in South Korea. The study population included patients with psychotic disorders, and outcome was psychosis relapse within 1 year. Using only structured data, we developed an initial prediction model, then three natural language processing (NLP)-enriched models using three types of clinical notes (psychological tests, admission notes, and initial nursing assessment) and one complete model. Latent Dirichlet Allocation was used to cluster the clinical context into similar topics. All models applied the least absolute shrinkage and selection operator logistic regression algorithm. We also performed an external validation using another hospital database.

RESULTS

A total of 330 patients were included, and 62 (18.8%) experienced psychosis relapse. Six predictors were used in the initial model and 10 additional topics from Latent Dirichlet Allocation processing were added in the enriched models. The model derived from all notes showed the highest value of the area under the receiver operating characteristic (AUROC = 0.946) in the internal validation, followed by models based on the psychological test notes, admission notes, initial nursing assessments, and structured data only (0.902, 0.855, 0.798, and 0.784, respectively). The external validation was performed using only the initial nursing assessment note, and the AUROC was 0.616.

CONCLUSIONS

We developed prediction models for psychosis relapse using the NLP-enrichment method. Models using clinical notes were more effective than models using only structured data, suggesting the importance of unstructured data in psychosis prediction.

Lessons learnt when accounting for competing events in the external validation of time-to-event prognostic models

Background

External validation of prognostic models is necessary to assess the accuracy and generalizability of the model to new patients. If models are validated in a setting in which competing events occur, these competing risks should be accounted for when comparing predicted risks to observed outcomes.

Methods

We discuss existing measures of calibration and discrimination that incorporate competing events for time-to-event models. These methods are illustrated using a clinical-data example concerning the prediction of kidney failure in a population with advanced chronic kidney disease (CKD), using the guideline-recommended Kidney Failure Risk Equation (KFRE). The KFRE was developed using Cox regression in a diverse population of CKD patients and has been proposed for use in patients with advanced CKD in whom death is a frequent competing event.

Results

When validating the 5-year KFRE with methods that account for competing events, it becomes apparent that the 5-year KFRE considerably overestimates the real-world risk of kidney failure. The absolute overestimation was 10%age points on average and 29%age points in older high-risk patients.

Conclusions

It is crucial that competing events are accounted for during external validation to provide a more reliable assessment the performance of a model in clinical settings in which competing risks occur.

Person centred care provision and care planning in chronic kidney disease: which outcomes matter? A systematic review and thematic synthesis of qualitative studies : Care planning in CKD: which outcomes matter?

RATIONALE & OBJECTIVE

Explore priorities related to outcomes and barriers of adults with chronic kidney disease (CKD) regarding person centred care and care planning.

STUDY DESIGN

Systematic review of qualitative studies.

SEARCH STRATEGY & SOURCES

In July 2018 six bibliographic databases, and reference lists of included articles were searched for qualitative studies that included adults with CKD stages 1-5, not on dialysis or conservative management, without a previous kidney transplantation.

ANALYTICAL APPROACH

Three independent reviewers extracted and inductively coded data using thematic synthesis. Reporting quality was assessed using the COREQ and the review reported according to PRISMA and ENTREQ statements.

RESULTS

Forty-six studies involving 1493 participants were eligible. The period after diagnosis of CKD is characterized by feelings of uncertainty, social isolation, financial burden, resentment and fear of the unknown. Patients show interest in ways to return to normality and remain in control of their health in order to avoid further deterioration of kidney function. However, necessary information is often unavailable or incomprehensible. Although patients and healthcare professionals share the predominant interest of whether or not dialysis or transplantation is necessary, patients value many more outcomes that are often unrecognized by their healthcare professionals. We identified 4 themes with 6 subthemes that summarize these findings: 'pursuing normality and control' ('pursuing normality'; 'a search for knowledge'); 'prioritizing outcomes' ('reaching kidney failure'; 'experienced health'; 'social life'; 'work and economic productivity'); 'predicting the future'; and 'realising what matters'. Reporting quality was moderate for most included studies.

LIMITATIONS

Exclusion of non-English articles.

CONCLUSIONS

The realisation that patients' priorities do not match those of the healthcare professionals, in combination with the prognostic ambiguity, confirms fatalistic perceptions of not being in control when living with CKD. These insights may contribute to greater understanding of patients' perspectives and a more person-centred approach in healthcare prioritization and care planning within CKD care.

Appraising prediction research: a guide and meta-review on bias and applicability assessment using the Prediction model Risk Of Bias ASsessment Tool (PROBAST)

Over the past few years, a large number of prediction models have been published, often of poor methodological quality. Seemingly objective and straightforward, prediction models provide a risk estimate for the outcome of interest, usually based on readily available clinical information. Yet, using models of substandard methodological rigour, especially without external validation, may result in incorrect risk estimates and consequently misclassification. To assess and combat bias in prediction research the prediction model risk of bias assessment tool (PROBAST) was published in 2019. This risk of bias (ROB) tool includes four domains and 20 signalling questions highlighting methodological flaws, and provides guidance in assessing the applicability of the model. In this paper, the PROBAST will be discussed, along with an in‐depth review of two commonly encountered pitfalls in prediction modelling that may induce bias: overfitting and composite endpoints. We illustrate the prevalence of potential bias in prediction models with a meta‐review of 50 systematic reviews that used the PROBAST to appraise their included studies, thus including 1510 different studies on 2104 prediction models. All domains showed an unclear or high ROB; these results were markedly stable over time, highlighting the urgent need for attention on bias in prediction research. This article aims to do just that by providing (1) the clinician with tools to evaluate the (methodological) quality of a clinical prediction model, (2) the researcher working on a review with methods to appraise the included models, and (3) the researcher developing a model with suggestions to improve model quality.

Most published prediction models have limited clinical uptake, are not externally validated and come with methodological issues. The PROBAST (Prediction model Risk Of Bias ASssessment Tool) guides the researcher writing a review, or the clinician interested in a model for risk calculation in a clinical setting. This review examines the aspects of bias in prediction research, and provides information on the prevalence of bias in published models.

Von Willebrand factor, ADAMTS13 and mortality in dialysis patients

BACKGROUND

Von Willebrand Factor (VWF) multimers are cleaved into smaller and less coagulant forms by the metalloprotease ADAMTS13. The aim of this study was to investigate the association between VWF and ADAMTS13 and mortality in dialysis patients.

METHODS

We prospectively followed 956 dialysis patients. VWF levels and ADAMTS13 activity were measured. Cox proportional hazard analyses were used to calculate hazard ratios (HRs) with 95 % confidence intervals (CIs) to investigate the association between quartiles of VWF levels and ADAMTS13 activity and all-cause mortality. HRs were adjusted for age, sex, body mass index, cardiovascular disease, dialysis modality, primary kidney disease, use of antithrombotic medication, systolic blood pressure, albumin, C-reactive protein and residual GFR.

RESULTS

Of the 956 dialysis patients, 288 dialysis patients died within three years (mortality rate 151 per 1000 person-years). The highest quartile of VWF as compared with lower levels of VWF was associated with a 1.4-fold (95 %CI 1.1-1.8) increased mortality risk after adjustment. The lowest quartile of ADAMTS13 activity as compared with other quartiles was associated with a 1.3-fold (95 %CI 1.0-1.7) increased mortality risk after adjustment. The combination of the highest VWF quartile and lowest ADAMTS13 quartile was associated with a 2.0-fold (95 %CI 1.3-3.0) increased mortality risk as compared with the combination of the lowest VWF quartile and highest ADAMTS13 quartile.

CONCLUSIONS

High VWF levels and low ADAMTS13 activity were associated with increased mortality risks in dialysis patients.

Validation of risk scores for ischaemic stroke in atrial fibrillation across the spectrum of kidney function

Aims 

The increasing prevalence of ischaemic stroke (IS) can partly be explained by the likewise growing number of patients with chronic kidney disease (CKD). Risk scores have been developed to identify high-risk patients, allowing for personalized anticoagulation therapy. However, predictive performance in CKD is unclear. The aim of this study is to validate six commonly used risk scores for IS in atrial fibrillation (AF) patients across the spectrum of kidney function.

Methods and results 

Overall, 36 004 subjects with newly diagnosed AF from SCREAM (Stockholm CREAtinine Measurements), a healthcare utilization cohort of Stockholm residents, were included. Predictive performance of the AFI, CHADS₂, Modified CHADS₂, CHA₂DS₂-VASc, ATRIA, and GARFIELD-AF risk scores was evaluated across three strata of kidney function: normal kidney function [estimated glomerular filtration rate (eGFR) >60 mL/min/1.73 m²], mild CKD (eGFR 30–60 mL/min/1.73 m²), and advanced CKD (eGFR <30 mL/min/1.73 m²). Predictive performance was assessed by discrimination and calibration. During 1.9 years, 3069 (8.5%) patients suffered an IS. Discrimination was dependent on eGFR: the median c-statistic in normal eGFR was 0.75 (range 0.68–0.78), but decreased to 0.68 (0.58–0.73) and 0.68 (0.55–0.74) for mild and advanced CKD, respectively. Calibration was reasonable and largely independent of eGFR. The Modified CHADS₂ score showed good performance across kidney function strata, both for discrimination [c-statistic: 0.78 (95% confidence interval 0.77–0.79), 0.73 (0.71–0.74) and 0.74 (0.69–0.79), respectively] and calibration.

Conclusion 

In the most clinically relevant stages of CKD, predictive performance of the majority of risk scores was poor, increasing the risk of misclassification and thus of over- or undertreatment. The Modified CHADS₂ score performed good and consistently across all kidney function strata, and should therefore be preferred for risk estimation in AF patients.

Low Heart Rate Variability Predicts Stroke and Other Complications in the First Six Postoperative Months After a Hip Fracture Operation

Background: One-year mortality after hip fractures is underestimated and is reported as 25%. An improved risk stratifying could contribute to a better follow up of these patients. Heart Rate Variability (HRV) is an easy point-of-care investigation and is been used in cardiology, endocrinology, and perioperative care. This observational study intended to explore relevant associations between HRV parameters and 6-months mortality and morbidity after a hip fracture. Methods: One hundred and sixty-five patients admitted to two hospitals were included, and short-time HRV measurements (5 min, and 10 min at the two hospitals, respectively) were obtained. Mortality data were gathered by means of the Norwegian central address register. Patients, close relatives of patients, and in some cases their general physicians or nursery home physicians were interviewed 6 months postoperatively regarding the incidence of pneumonia, cardiac events, or stroke. Results: One and hundred fifty-seven (95.2%) patients were followed up after 6 months post-surgery. Twenty-one (13%) died during this period. Twenty patients (13%) developed pneumonia, eight (5 %) stroke, and four (2%) myocardial infarction. No HRV parameter was associated with 6-month general mortality. However, patients who developed stroke had significantly lower High Frequency Power (HF, p < 0.001) and lower Very Low Frequency Power (VLF, p = 0.003) at inclusion compared to patients without complications. Patients who developed pneumonia had at the inclusion lower root mean square of successive differences (RMSSD, p = 0.044). Patients with a history of coronary heart disease (n = 41) showed a mortality of 7%. Mortality in this group was associated with standard deviation of beat-to-beat intervals (SDNN, p = 0.006), Total Power (TP, p = 0.009), HF (p = 0.026), and Low Frequency Power (LF, p = 0.012). Beta-blocker intake was associated with lower heart rate, but not with differences in HRV parameters. Conclusion: In this exploratory study, we present for the first-time significant associations between different preoperative HRV parameters and stroke, myocardial infarction, and pneumonia during a 6-month period after hip fracture. HRV might be a simple and effective tool to identify patients at risk that would warrant better follow-up.

External validation of prognostic models: what, why, how, when and where?

Prognostic models that aim to improve the prediction of clinical events, individualized treatment and decision-making are increasingly being developed and published. However, relatively few models are externally validated and validation by independent researchers is rare. External validation is necessary to determine a prediction model's reproducibility and generalizability to new and different patients. Various methodological considerations are important when assessing or designing an external validation study. In this article, an overview is provided of these considerations, starting with what external validation is, what types of external validation can be distinguished and why such studies are a crucial step towards the clinical implementation of accurate prediction models. Statistical analyses and interpretation of external validation results are reviewed in an intuitive manner and considerations for selecting an appropriate existing prediction model and external validation population are discussed. This study enables clinicians and researchers to gain a deeper understanding of how to interpret model validation results and how to translate these results to their own patient population.