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At least 145 records · Page 8Linked to original sources
PubMed2003

Assessing patient safety risk before the injury occurs: an introduction to sociotechnical probabilistic risk modelling in health care.

Since 1 July 2001 the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) has required each accredited hospital to conduct at least one proactive risk assessment annually. Failure modes and effects analysis (FMEA) was recommended as one tool for conducting this task. This paper examines the limitations of FMEA and introduces a second tool used by the aviation and nuclear industries to examine low frequency, high impact events in complex systems. The adapted tool, known as sociotechnical probabilistic risk assessment (ST-PRA), provides an alternative for proactively identifying, prioritizing, and mitigating patient safety risk. The uniqueness of ST-PRA is its ability to model combinations of equipment failures, human error, at risk behavioral norms, and recovery opportunities through the use of fault trees. While ST-PRA is a complex, high end risk modelling tool, it provides an opportunity to visualize system risk in a manner that is not possible through FMEA.

Hospital Administration↗
PubMed2000

Recurrence risk modelling of the genetic susceptibility to ankylosing spondylitis.

OBJECTIVES: It has long been suspected that susceptibility to ankylosing spondylitis (AS) is influenced by genes lying distant to the major histocompatibility complex. This study compares genetic models of AS to assess the most likely mode of inheritance, using recurrence risk ratios in relatives of affected subjects. METHODS: Recurrence risk ratios in different degrees of relatives were determined using published data from studies specifically designed to address the question. The methods of Risch were used to determine the expected recurrence risk ratios in different degrees of relatives, assuming equal first degree relative recurrence risk between models. Goodness of fit was determined by chi(2) comparison of the expected number of affected subjects with the observed number, given equal numbers of each type of relative studied. RESULTS: The recurrence risks in different degrees of relatives were: monozygotic (MZ) twins 63% (17/27), first degree relatives 8.2% (441/5390), second degree relatives 1.0% (8/834), and third degree relatives 0. 7% (7/997). Parent-child recurrence risk (7.9%, 37/466) was not significantly different from the sibling recurrence risk (8.2%, 404/4924), excluding a significant dominance genetic component to susceptibility. Poor fitting models included single gene, genetic heterogeneity, additive, two locus multiplicative, and one locus and residual polygenes (chi(2) >32 (two degrees of freedom), p<10(-6) for all models). The best fitting model studied was a five locus model with multiplicative interaction between loci (chi(2)=1.4 (two degrees of freedom), p=0.5). Oligogenic multiplicative models were the best fitting over a range of population prevalences and first degree recurrence risk rates. CONCLUSIONS: This study suggests that of the genetic models tested, the most likely model operating in AS is an oligogenic model with predominantly multiplicative interaction between loci.

Female↗
PubMed2004

Decompression sickness risk model: development and validation by 150 prospective hypobaric exposures.

INTRODUCTION: High altitude exposure has an inherent risk of altitude decompression sickness (DCS). A predictive DCS model was needed to reduce operational risk. To be operationally acceptable, such a theoretical model would need to be validated in the laboratory using human subjects. METHODS: The Air Force Research Laboratory (AFRL) has conducted numerous studies on human subjects exposed to simulated altitudes in hypobaric chambers. The database from those studies was used to develop a statistical altitude DCS model. In addition, a bubble growth model was developed using a finite difference method to solve for bubble radius as a function of time. The bubble growth model, integrated with the statistical model, constitutes the AFRL DCS Risk Assessment Model. Validation of the model was accomplished by comparing computer predictions of DCS risk with results from subsequent prospective human subject exposures. There were five exposure profiles, not previously found in the database, covering a wide parameter of ranges of altitude (18,000-35,000 ft), exposure time (180-360 min), prebreathe time (0-90 min), and activity level (rest-strenuous) that were used. The subjects were monitored for DCS symptoms and venous gas emboli. RESULTS: There were 30 subjects who were exposed to each of the 5 altitude profiles. The DCS incidence onset curves predicted by the model were not significantly different from the experimental values for all scenarios tested and were generally within +/- 5% of the actual values. CONCLUSION: A predictive altitude DCS model was successfully developed and validated.

Altitude Sickness↗
PubMed2002

Central nervous system involvement following diagnosis of non-Hodgkin's lymphoma: a risk model.

BACKGROUND: To determine the incidence and risk factors for central nervous system (CNS) relapse in patients with non-Hodgkin's lymphoma (NHL). PATIENTS AND METHODS: Patient records were registered prospectively in successive patients with NHL admitted to the Norwegian Radium Hospital from 1980 to 1996. A total of 2514 patients had no CNS involvement at diagnosis and were treated according to standard protocols. The incidence and risk factors for CNS progression or relapse were examined retrospectively. RESULTS: In low-grade (L)-NHL, the risk of CNS involvement was low (2.8%). In high-grade (H)-NHL, lymphoblastic and Burkitt's NHL patients had a high risk of CNS recurrence (24.4%) at 5 years, and prophylaxis seemed to reduce this risk. For the other patients with H-NHL, the proportion with CNS involvement at 5 years was 5.2%. Multivariate analysis identified five independent risk factors, each present in >5% of patients: elevated serum lactate dehydrogenase, serum albumin <35 g/l, <60 years of age, retroperitoneal lymph node involvement and involvement of more than one extranodal site. If four or five of these risk factors were present, the risk of CNS recurrence was in excess of 25% at 5 years. CONCLUSIONS: The risk of CNS involvement in this study is comparable with the results from other large series. CNS prophylaxis is not recommended in any subgroup of L-NHL. The risk of CNS involvement among patients with either Burkitt's or lymphoblastic lymphomas is considerable and these patients should therefore receive intensive chemotherapy including systemic and intrathecal methotrexate. Patients with other types of H-NHL should receive adequate CNS prophylaxis if at least four of the five risk factors identified are present.

Adolescent↗
PubMed2006

An alternative competing risk model to the Weibull distribution for modelling aging in lifetime data analysis.

A simple competing risk distribution as a possible alternative to the Weibull distribution in lifetime analysis is proposed. This distribution corresponds to the minimum between exponential and Weibull distributions. Our motivation is to take account of both accidental and aging failures in lifetime data analysis. First, the main characteristics of this distribution are presented. Then, the estimation of its parameters are considered through maximum likelihood and Bayesian inference. In particular, the existence of a unique consistent root of the likelihood equations is proved. Decision tests to choose between an exponential, Weibull and this competing risk distribution are presented. And this alternative model is compared to the Weibull model from numerical experiments on both real and simulated data sets, especially in an industrial context.

Aging↗
PubMed2004

Cardiac surgery risk models: a position article.

Differences in medical outcomes may result from disease severity, treatment effectiveness, or chance. Because most outcome studies are observational rather than randomized, risk adjustment is necessary to account for case mix. This has usually been accomplished through the use of standard logistic regression models, although Bayesian models, hierarchical linear models, and machine-learning techniques such as neural networks have also been used. Many factors are essential to insuring the accuracy and usefulness of such models, including selection of an appropriate clinical database, inclusion of critical core variables, precise definitions for predictor variables and endpoints, proper model development, validation, and audit. Risk models may be used to assess the impact of specific predictors on outcome, to aid in patient counseling and treatment selection, to profile provider quality, and to serve as the basis of continuous quality improvement activities.

Bayes Theorem↗
PubMed2001

Risk modelling study for carotid endarterectomy.

BACKGROUND: The aims of this study were to identify factors that influence the risk of stroke or death following carotid endarterectomy (CEA) and to develop a model to aid in comparative audit of vascular surgeons and units. METHODS: A series of 839 CEAs performed by four vascular surgeons between 1992 and 1999 was analysed. Multiple logistic regression analysis was used to model the effect of 15 possible risk factors on the 30-day risk of stroke or death. Outcome was compared for four surgeons and two units after adjustment for the significant risk factors. RESULTS: The overall 30-day stroke or death rate was 3.9 per cent (29 of 741). Heart disease, diabetes and stroke were significant risk factors. The 30-day predicted stroke or death rates increased with increasing risk scores. The observed 30-day stroke or death rate was 3.9 per cent for both vascular units and varied from 3.0 to 4.2 per cent for the four vascular surgeons. Differences in the outcomes between the surgeons and vascular units did not reach statistical significance after risk adjustment. CONCLUSION: Diabetes, heart disease and stroke are significant risk factors for stroke or death following CEA. The risk score model identified patients at higher risk and aided in comparative audit.

Adult↗
PubMed1987

Logistic risk model for the unique effects of inherent aerobic capacity on +Gz tolerance before and after simulated weightlessness.

Small sample size (n less than 10) and inappropriate analysis of multivariate data have hindered previous attempts to describe which physiologic and demographic variables are most important in determining how long humans can tolerate acceleration. Data from previous centrifuge studies conducted at NASA/Ames Research Center, utilizing a 7-14 d bed rest protocol to simulate weightlessness, were included in the current investigation. After review, data on 25 women and 22 men were available for analysis. Study variables included gender, age, weight, height, percent body fat, resting heart rate, mean arterial pressure, VO2max, and plasma volume. Since the dependent variable was time to greyout (failure), two contemporary biostatistical modeling procedures (proportional hazard and logistic discriminant function) were used to estimate risk, given a particular subject's profile. After adjusting for pre-bed-rest tolerance time, none of the profile variables remained in the risk equation for post-bed-rest tolerance greyout. However, prior to bed rest, risk of greyout could be predicted with 91% accuracy. All of the profile variables except weight, MAP, and those related to inherent aerobic capacity (VO2max, percent body fat, resting heart rate) entered the risk equation for pre-bed-rest greyout. A cross-validation using 24 new subjects indicated a very stable model for risk prediction, accurate within 5% of the original equation. The result for the inherent fitness variables is significant in that a consensus as to whether an increased aerobic capacity is beneficial or detrimental has not been satisfactorily established. We conclude that tolerance to +Gz acceleration before and after simulated weightlessness is independent of inherent aerobic fitness.

Acceleration↗
PubMed2005

Quantitative risk modelling for new pharmaceutical compounds.

The process of discovering and developing new drugs is long, costly and risk-laden. Faced with a wealth of newly discovered compounds, industrial scientists need to target resources carefully to discern the key attributes of a drug candidate and to make informed decisions. Here, we describe a quantitative approach to modelling the risk associated with drug development as a tool for scenario analysis concerning the probability of success of a compound as a potential pharmaceutical agent. We bring together the three strands of manufacture, clinical effectiveness and financial returns. This approach involves the application of a Bayesian Network. A simulation model is demonstrated with an implementation in MS Excel using the modelling engine Crystal Ball.

Algorithms↗
PubMed2000

Cumulative risk and early cognitive development: a comparison of statistical risk models.

Although it is generally accepted that social risk factors predict delays in early cognitive and language development, there is less agreement about how to represent such associations statistically. Using data collected prospectively on 87 African American children during their first 4 years, this study examined 3 analytic methods for describing a child's level of social risk: (a) individual risk variables, (b) factor scores derived from those risk variables, and (c) a risk index computed by tallying the number of risk conditions present. Comparisons indicated that the individual-risk-variables approach provides better overall prediction of developmental outcomes at a particular age but is less useful in predicting developmental patterns. The risk-factor approach provides good prediction of developmental trajectories when sample sizes are moderate to large. Finally, the risk-index approach is useful for relating social risk to developmental patterns when a large number of risk variables are assessed with a small sample or when other constructs are of primary interest.

Black or African American↗
PubMed1996

Exposure-response functions in Air Force toxic risk modeling.

A new methodology for estimating the probabilistic risk from acute toxic exposures is planned as a support tool for the Air Force at the Eastern and Western Ranges. Two such methodologies are programs entitled the Launch Area Toxic Analysis program (LATRA) and the Cold Spill Toxic Risk Analysis program (COSTRA). These programs combine probabilistic models of an accident (when applicable), release cloud formation and dispersion (appropriate to the toxic substance and accounting for meteorological conditions), and new exposure-response functions (ERFs) for sensitive and normal exposed populations. These ERFs, anchored on specific exposure standards, estimate the probability of a given severity of health effect in a particular population as a function of the concentration or dose to which it is exposed. The further development and acceptance of these ERFs by the toxicology community, especially for different sensitivities, are key concerns addressed in this paper.

Accidents, Aviation↗
PubMed2003

Risk model predictive of severe anemia requiring RBC transfusion after chemotherapy in pediatric solid tumor patients.

PURPOSE: Severe anemias requiring RBC transfusions is a frequent complication of chemotherapy. A model elaborated by Ray-Coquard et al in adults pointed to three independent risk factors for RBC transfusion: performance status (PS) more than 1, hemoglobin less than 12 g/dL, and prechemotherapy absolute lymphocyte count (ALC) < or = 700/microL. This model is tested on a pediatric population. PATIENTS AND METHODS: One hundred nineteen children with solid tumors consecutively admitted for conventional chemotherapy throughout 1 year were included. The study end point was the RBC-transfusion risk in the month following chemotherapy. Only one course was considered for each patient. Age, sex, number of courses, platinum-containing regimens, PS, and hemoglobin and lymphocyte count at day 1 were tested in univariate and multivariate analyses. RESULTS: Thirty-one (26%) of 119 children required RBC transfusion within 31 days of chemotherapy. Three factors correlated to transfusion risk in the univariate analysis: PS more than 1 (P <.001), hemoglobin less than 12 g/dL (P =.007), and pretreatment ALC < or = 700/microL (P <.001). In the multivariate analysis, hemoglobin less than 12 g/dL, PS more than 1, and ALC < or = 700/microL were identified as independent factors predicting RBC transfusion. The calculated probability of receiving RBC transfusion within 31 days of chemotherapy was high with three risk factors (96%), intermediate with two risk factors (53% to 77%), low with one risk factor (10% to 26%), and very low when no risk factor was present (2%). The difference of transfusion needs was significant (P <.001). CONCLUSION: The risk model elaborated for adults may also segregate children at high risk of postchemotherapy RBC transfusion, thus facilitating assessment of risk of transfusion and/or prophylactic erythropoietin support.

Adolescent↗
PubMed1995

Three-year root caries incidence and risk modeling in older adults in North Carolina.

OBJECTIVES: The purposes of this study were to describe the incidence of root caries and to identify its risk factors in a representative sample of older adults. METHODS: Root caries incidence was estimated and multivariate risk assessment models were developed to identify predictors for root caries in a three-year follow-up study of 234 black and 218 white noninstitutionalized adults aged 65 and older residing in North Carolina. RESULTS: During the observation period, 29 percent of blacks developed root caries, compared to 39 percent of whites (P < .05). The mean net DFS increment per person was 0.55 +/- 0.13 root surfaces for blacks vs 0.80 +/- 0.21 for whites (P > .32). Multivariate logistic regression analysis indicated that blacks wearing a partial denture, having some root fragments, having an average gingival recession > or = 2 mm, and being free of P. intermedia were at greater risk for developing new root caries. The model for whites showed that retired people with their most severe gingival recession > or = 4 mm, an average probing pocket depth > or = 2 mm, and taking antihistamines were more likely to develop new lesions. CONCLUSIONS: These findings suggest that older blacks had less risk of root caries than whites, and in both groups indicators of poor periodontal status increased the risk of root caries.

Aged↗
PubMed2003

Physician contribution to a cesarean delivery risk model.

OBJECTIVE: The purpose of this study was to assess the contribution of physician management to the probability of cesarean delivery. STUDY DESIGN: A prospective cohort study was performed of all live births who weighed > or =500 g for a 2-year period (1999-2000) at a large metropolitan hospital (n = 10,027 births). Factors that were associated significantly with cesarean delivery at one time excluded cases in which cesarean delivery was a necessary or probable outcome. In the planned vaginal delivery sample (n = 7940 births), a risk-adjusted logistic regression model was used to assess the prediction of cesarean delivery. To test for the effect of physician-management physician, we used the subset of physicians with > or =45 deliveries in the 2-year time period (n = 6563 deliveries). RESULTS: When physician-management physician data were added to the use of forward stepwise regression, entry order was abnormal position, nulliparity, birth weight of >4000 g, and physician. The model's predictive ability improved from 43.8% to 50.2%. CONCLUSION: Physician management adds a significant independent effect to the cesarean delivery risk model.

Adult↗
PubMed2007

Simple risk models to predict surgical mortality in acute type A aortic dissection: the International Registry of Acute Aortic Dissection score.

BACKGROUND: Surgical mortality for acute type A aortic dissection is frequently related to preoperative clinical conditions. We report a predictive score to identify risk of death that may be helpful to assist surgeons who are considering whether to proceed with surgical correction in the case of patients in extreme clinical risk. METHODS: Surgical outcome of 682 patients enrolled in the International Registry of Acute Aortic Dissection from 1996 to 2003 was analyzed. Two different models were used. The initial model included only preoperative variables such as demographics, history, symptoms, signs, and diagnostic methods (model 1). The second model also tested intraoperative hemodynamic and surgical variables (model 2). A bedside risk prediction tool to predict operative mortality in individual patients was developed. RESULTS: The overall in-hospital surgical mortality was 23.9%. Independent preoperative predictors of mortality in model 1 were age greater than 70 years, prior cardiac surgery, hypotension (systolic blood pressure less than 100 mm Hg) or shock at presentation, migrating pain, cardiac tamponade, any pulse deficit, and electrocardiogram with findings of myocardial ischemia or infarction. In model 2, other predictors of surgical death were intraoperative hypotension, a right ventricle dysfunction at surgery, and a necessity to perform coronary revascularization. An independent predictor for favorable surgical outcome was right hemiarch replacement. CONCLUSIONS: Surgery in unstable patients with acute type A aortic dissection can be highly unsuccessful. The International Registry of Acute Aortic Dissection risk models predict in-hospital mortality using a multivariable risk prediction tool, useful for surgeons and patients as they consider their surgical risk and the pros and cons of embarking on high-risk surgery.

Acute Disease↗
PubMed2004

Ki67 predicts progression in early CIN: validation of a multivariate progression-risk model.

This study of early CIN biopsies (25 CIN1 and 65 CIN2) with long follow-up was done to validate, in a new group of patients, the value of Ki67 immuno-quantitative features to predict high CIN grade in a follow-up biopsy (often denoted to as "progression"), as described in a previous study. Each biopsy in the present study was classified with the previously described Ki67-model (consisting of the stratification index and the % positive nuclei in the middle third layer of the epithelium) as "low-risk" or "high-risk", and matched with the follow-up outcome (progression-or-not). Furthermore, it was studied whether subjective evaluation of the Ki67 sections by experienced pathologists, who were aware of the prognostic quantitative Ki67 features, could also predict the outcome. Thirdly, the reproducibility of routine use of the quantitative Ki67-model was assessed. Fifteen cases progressed (17%) to CIN3, 2/25 CIN1 (8%) and 13/65 CIN2 (20%), indicating that CIN grade (as CIN1 or CIN2) is prognostic and that the percentage of CIN1 and CIN2 cases with progression in the present study is comparable to many previous studies. However, the quantitative Ki67 model had stronger prognostic value than CIN grade as none of the 40 "Ki67-model low-risk" patients progressed, in contrast to 15 (30%) of the 50 "Ki67-model high-risk" patients (p<0.001). In multivariate analysis, neither CIN grade nor any of the other quantitative Ki67 features added to the abovementioned prognostic Ki67-model. Subjective analysis of the Ki67 features was also prognostic, although quantitative assessments gave better results. Routine application of the quantitative Ki67-model in CIN1 and CIN2 was well reproducible. In conclusion, the results confirm that quantitative Ki67 features have strong prognostic value for progression in early CIN lesions.

Adult↗
PubMed2026

EMPEROR-Preserved Risk Model and Outcomes in the FINEARTS-HF Trial: A Prespecified Secondary Analysis of FINEARTS-HF.

IMPORTANCE: Patients with heart failure (HF) and mildly reduced ejection fraction (HFmrEF) or preserved EF (HFpEF) show substantial heterogeneity in prognosis. OBJECTIVES: To evaluate the performance of biomarker-driven prognostic models derived from the Empagliflozin Outcome Trial in Patients With Chronic Heart Failure With Preserved Ejection Fraction (EMPEROR-Preserved) Trial in the Finerenone Trial to Investigate Efficacy and Safety Superior to Placebo in Patients With Heart Failure (FINEARTS-HF) and to examine whether baseline risk modified the therapeutic effect of finerenone. DESIGN, SETTING, AND PARTICIPANTS: This is a prespecified secondary analysis of the FINEARTS-HF trial, which was conducted across 653 sites in 37 countries among adults aged 40 years and older with symptomatic HF and left ventricular EF (LVEF) of 40% or greater. Patients were randomized between September 2020 and January 2023, and data analysis for this study was conducted from September to October 2025. The median (IQR) follow-up period was 32 (23-37) months. INTERVENTION: Finerenone (titrated to 20 mg or 40 mg) or placebo. MAIN OUTCOMES AND MEASURES: EMPEROR-Preserved risk scores for the outcomes of first HF hospitalization or cardiovascular death, cardiovascular death, and all-cause death were calculated in FINEARTS-HF using models incorporating N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, New York Heart Association functional class, history of chronic obstructive pulmonary disease and diabetes, insulin use, and-depending on outcome-age, hemoglobin and albumin levels, HF duration, time from prior HF hospitalization, and sodium-glucose transporter 2 inhibitor use. Estimated risks were compared with observed event rates, and model performance was assessed using Harrell C statistic. Treatment effects were evaluated across risk quintiles (Q1 to Q5) and across the continuous risk distribution. RESULTS: Among 6001 patients (mean [SD] age, 72.0 [9.6] years; 2732 [45.5%] women; 3003 randomized to finerenone and 2998 randomized to placebo), the EMPEROR-Preserved risk model estimated risk of outcomes, with Q5 vs Q1 hazard ratios (HRs) of 10.49 (95% CI, 8.14-13.52) for the composite of HF hospitalization or cardiovascular death and 13.47 (95% CI, 8.79-20.64) for cardiovascular death. The model demonstrated good discrimination. The treatment effect of finerenone was consistent across risk quintiles for first HF hospitalization or cardiovascular death (Q1: HR, 0.93 [95% CI, 0.58-1.49]; Q2: HR, 1.04 [95% CI, 0.76-1.43]; Q3: HR, 0.82 [95% CI, 0.62-1.07]; Q4: HR, 0.81 [95% CI, 0.65-1.01]; and Q5: HR, 0.88 [95% CI, 0.74-1.05]; P for interaction&#x2009;=&#x2009;.68) and remained uniform across the continuous risk spectrum. CONCLUSIONS AND RELEVANCE: The EMPEROR-Preserved risk models demonstrated good performance in FINEARTS-HF. Baseline risk did not modify the relative treatment effect of finerenone. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04435626.

Humans↗