risk estimates
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2022 ◽  
Vol 2 (1) ◽  
Author(s):  
Olga Kostopoulou ◽  
Kavleen Arora ◽  
Bence Pálfi

Abstract Background Cancer risk algorithms were introduced to clinical practice in the last decade, but they remain underused. We investigated whether General Practitioners (GPs) change their referral decisions in response to an unnamed algorithm, if decisions improve, and if changing decisions depends on having information about the algorithm and on whether GPs overestimated or underestimated risk. Methods 157 UK GPs were presented with 20 vignettes describing patients with possible colorectal cancer symptoms. GPs gave their risk estimates and inclination to refer. They then saw the risk score of an unnamed algorithm and could update their responses. Half of the sample was given information about the algorithm’s derivation, validation, and accuracy. At the end, we measured their algorithm disposition. We analysed the data using multilevel regressions with random intercepts by GP and vignette. Results We find that, after receiving the algorithm’s estimate, GPs’ inclination to refer changes 26% of the time and their decisions switch entirely 3% of the time. Decisions become more consistent with the NICE 3% referral threshold (OR 1.45 [1.27, 1.65], p < .001). The algorithm’s impact is greatest when GPs have underestimated risk. Information about the algorithm does not have a discernible effect on decisions but it results in a more positive GP disposition towards the algorithm. GPs’ risk estimates become better calibrated over time, i.e., move closer to the algorithm. Conclusions Cancer risk algorithms have the potential to improve cancer referral decisions. Their use as learning tools to improve risk estimates is promising and should be further investigated.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Makayla Kirksey ◽  
Brownsyne Tucker Edmonds

Background/Objective: The optimal mode of delivery (MOD) for malpresentation in periviable deliveries (22-24 weeks), remains a source of debate. Neonatal and maternal complications can arise from both vaginal (VD) and cesarean delivery (CD), and the threat of maternal morbidity extends to subsequent pregnancies. It has been difficult to compare these risks while counseling patients about MOD options, so we sought to create a decision tree that maps probable outcomes associated with breech deliveries at 23- and 24-weeks’ gestation, as well as complications posed for subsequent pregnancies.     Methods: An extensive literature review was conducted to identify risk estimates of periviable maternal and neonatal outcomes, along with elective repeat CD (ERCD) and trial of labor after cesarean (TOLAC) for subsequent pregnancies. Probabilities were inputted into TreeAge software, starting with primary maternal health states that may result from CD and VD – “death”, “hysterectomy”, or “no hysterectomy”, followed by the probability of neonatal health states– “death”, “severe morbidity”, or “no severe morbidity”. The likelihood of placenta previa or normal placenta was considered for subsequent pregnancies. We factored in the possibility of ERCD or TOLAC and the associated maternal and neonatal risks for each.      Results: Final design of the tree is complete and risk estimates have been inputted. Primary analysis and sensitivity analyses are planned for August 2021. Ultimately, we will also be able to use measured utility values to calculate quality adjusted life years (QALYs) for each health state.      Conclusion and Clinical Impact: Whether CD or VD is optimal for breech presentation in periviable delivery is influenced by a complex array of factors, including future reproductive plans and maternal values related to potential neonatal and maternal morbidity and mortality. Quantifying risks associated with each MOD will aid providers in their efforts to help families make informed decisions and reduce morbidity across the reproductive lifespan.  


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ji Soo Kim ◽  
Ami A. Shah ◽  
Laura K. Hummers ◽  
Scott L. Zeger

Abstract Background Scleroderma is a serious chronic autoimmune disease in which a patient’s disease state manifests in several irregularly spaced longitudinal measures of lung, heart, skin, and other organ systems. Threshold crossings of pulmonary and cardiac measures indicate potentially life-threatening key clinical events including interstitial lung disease (ILD), cardiomyopathy, and pulmonary hypertension (PH). The statistical challenge is to accurately and precisely predict these events by using all of the clinical history for the patient at hand and for a reference population of patients. Methods We use a Bayesian mixed model approach to simultaneously characterize each individual’s future trajectories for several biomarkers. We estimate this model using a large population of patients from the Johns Hopkins Scleroderma Center Research Registry. The joint probabilities of critical lung and heart events are then calculated as a byproduct of the mixed model. Results The performance of this approach is substantially better than standard, more common alternatives. In order to predict an individual’s risks in a clinical setting, we also develop a cross-validated, sequential prediction (CVSP) algorithm. As additional data are observed during a patient’s visit, the algorithm sequentially produces updated predictions for the future longitudinal trajectories and for ILD, cardiomyopathy, and PH. The updated prediction distributions with little additional computing, for example within an electronic health record (EHR). Conclusions This method that generates real-time personalized risk estimates has been implemented within the electronic health record system for clinical testing. To our knowledge, this work represents the first approach to compute personalized risk estimates for multiple scleroderma complications.


Diabetologia ◽  
2021 ◽  
Author(s):  
Sabrina Schlesinger ◽  
Manuela Neuenschwander ◽  
Janett Barbaresko ◽  
Alexander Lang ◽  
Haifa Maalmi ◽  
...  

Abstract Aims/hypothesis The term prediabetes is used for individuals who have impaired glucose metabolism whose glucose or HbA1c levels are not yet high enough to be diagnosed as diabetes. Prediabetes may already be associated with an increased risk of chronic ‘diabetes-related’ complications. This umbrella review aimed to provide a systematic overview of the available evidence from meta-analyses of prospective observational studies on the associations between prediabetes and incident diabetes-related complications in adults and to evaluate their strength and certainty. Methods For this umbrella review, systematic reviews with meta-analyses reporting summary risk estimates for the associations between prediabetes (based on fasting or 2 h postload glucose or on HbA1c) and incidence of diabetes-related complications, comorbidities and mortality risk were included. PubMed, Web of Science, the Cochrane Library and Epistemonikos were searched up to 17 June 2021. Summary risk estimates were recalculated using a random effects model. The certainty of evidence was evaluated by applying the GRADE tool. This study is registered with PROSPERO, CRD42020153227. Results Ninety-five meta-analyses from 16 publications were identified. In the general population, prediabetes was associated with a 6–101% increased risk for all-cause mortality and the incidence of cardiovascular outcomes, CHD, stroke, heart failure, atrial fibrillation and chronic kidney disease, as well as total cancer, total liver cancer, hepatocellular carcinoma, breast cancer and all-cause dementia with moderate certainty of evidence. No associations between prediabetes and incident depressive symptoms and cognitive impairment were observed (with low or very low certainty of evidence). The association with all-cause mortality was stronger for prediabetes defined by impaired glucose tolerance than for prediabetes defined by HbA1c. Conclusions/interpretation Prediabetes was positively associated with risk of all-cause mortality and the incidence of cardiovascular outcomes, CHD, stroke, chronic kidney disease, cancer and dementia. Further high-quality studies, particularly on HbA1c-defined prediabetes and other relevant health outcomes (e. g. neuropathy) are required to support the evidence. Graphical abstract


2021 ◽  
Vol 6 (1) ◽  
pp. 16-24
Author(s):  
Mounir Khayli ◽  
◽  
Mehdi Kechna ◽  
Khalil Zro ◽  
Faouzi Kichou ◽  
...  

Objective The objective behind this article is to better characterize spatial distribution of animal rabies in Morocco through qualitative risk assessment framework. In Morocco, the occurrence of the disease is neither clearly distributed nor complete. Therefore, risk assessment methods become strongly recommended to cope with distorted geographic patterns. Methods Based on data collection set from 168 counties, qualitative changes on spatial epidemiology of rabies were analysed by mapMCDA tool covering a period from 2004 to 2017 and including information on determinants of the geographic distribution of animal rabies in Morocco defined in previous work. Results To validate the risk assessment model, the results were compared to rabies cases reported during the study period. The clustering of the rabies risk estimates is decisive and highly reliable. A significant alignment was shown between the very high and high-risk estimates. Conclusion This study is the first attempt that has been made for using MapMCDA for rabies. For a normative process aiming to avoid subjectivity related to expert-opinions, authors suggest conducting initially a statistical multiple component analysis that will provide quantified estimates of risk factors. It would be an advisable decision-making tool that helps to design oriented surveillance and allows better referral of actions to control the disease.


2021 ◽  
Vol 77 (8) ◽  
pp. 516-521
Author(s):  
Beata Jacuś ◽  
Mirosława Kowalkowska ◽  
Paweł Miękus ◽  
Grzegorz Grześk

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lauri I. Lavikainen ◽  
Gordon H. Guyatt ◽  
Yung Lee ◽  
Rachel J. Couban ◽  
Anna L. Luomaranta ◽  
...  

Abstract Background Venous thromboembolism (VTE) and bleeding are serious and potentially fatal complications of surgical procedures. Pharmacological thromboprophylaxis decreases the risk of VTE but increases the risk of major post-operative bleeding. The decision to use pharmacologic prophylaxis therefore represents a trade-off that critically depends on the incidence of VTE and bleeding in the absence of prophylaxis. These baseline risks vary widely between procedures, but their magnitude is uncertain. Systematic reviews addressing baseline risks are scarce, needed, and require innovations in methodology. Indeed, systematic summaries of these baseline risk estimates exist neither in general nor gynecologic surgery. We will fill this knowledge gap by performing a series of systematic reviews and meta-analyses of the procedure-specific and patient risk factor stratified risk estimates in general and gynecologic surgeries. Methods We will perform comprehensive literature searches for observational studies in general and gynecologic surgery reporting symptomatic VTE or bleeding estimates. Pairs of methodologically trained reviewers will independently assess the studies for eligibility, evaluate the risk of bias by using an instrument developed for this review, and extract data. We will perform meta-analyses and modeling studies to adjust the reported risk estimates for the use of thromboprophylaxis and length of follow up. We will derive the estimates of risk from the median estimates of studies rated at the lowest risk of bias. The primary outcomes are the risk estimates of symptomatic VTE and major bleeding at 4 weeks post-operatively for each procedure stratified by patient risk factors. We will apply the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to rate evidence certainty. Discussion This series of systematic reviews, modeling studies, and meta-analyses will inform clinicians and patients regarding the trade-off between VTE prevention and bleeding in general and gynecologic surgeries. Our work advances the standards in systematic reviews of surgical complications, including assessment of risk of bias, criteria for arriving at the best estimates of risk (including modeling of the timing of events and dealing with suboptimal data reporting), dealing with subgroups at higher and lower risk of bias, and use of the GRADE approach. Systematic review registration PROSPERO CRD42021234119


2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Safa Al-Rawi ◽  
Monica Zolezzi ◽  
Yassin Eltorki

Introduction: Individuals with serious mental illness (SMI) experience premature death, likely due to increased rates of obesity and cardiovascular disease (CVD). This study was conducted to estimate the CVD risk in a cohort of individuals with SMI receiving outpatient psychiatric services in Qatar and to assess contributory CVD risk factors. Methods: This is a retrospective review of the electronic medical records of a cohort of outpatients with SMI attending a mental health clinic in Doha, Qatar. The CVD risk was estimated using two risk prediction tools: the American Heart Association and the American College of Cardiology (AHA/ACC) risk calculator and the World Health Organization/International Society of Hypertension (WHO/ISH) CVD risk prediction charts for the Eastern Mediterranean region. Descriptive and inferential statistics were used to analyze the demographic and clinical data. Data were analyzed using Statistical Package for the Social Sciences. Results: Of the 346 eligible patients, 28% (n = 97) had obtainable data for the estimation of their CVD risk using both tools. Approximately one-third of the cohort (33%) were classified as high risk using the AHA/ACC risk calculator, and 13.3% were classified as intermediate to high risk using the WHO/ISH CVD risk prediction charts. Based on the AHA/ACC risk scores, among those with a high CVD risk, almost two-thirds had CVD modifiable risk factors (i.e., smoking, diabetes, dyslipidemia, and hypertension). No statistically significant difference in the CVD risk estimates was observed among individuals with a body mass index of more or lower than 30 kg/m2 (p = 0.815). Conclusion: Based on the AHA/ACC risk calculator, approximately one-third of the study cohort had high CVD risk estimates. The WHO/ISH CVD risk prediction charts appeared to underestimate CVD risk, particularly for those identified as high risk using the AHA/ACC risk calculator. A closer alliance between psychiatrists and primary healthcare professionals to control modifiable cardiovascular risk factors among patients with SMI is necessary.


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