Use of generalised additive models to categorise continuous variables in clinical prediction

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Clinical prediction of occupational and non-specific low back pain

Non-specific Occupational Low Back Pain (NOLBP) is a health condition that generates a high absenteeism and disability. Due to multifactorial causes is difficult to determine accurate diagnosis and prognosis. The clinical prediction of NOLBP is identified as a series of models that integrate a multivariate analysis to determine early diagnosis, course, and occupational impact of this health condition. Objective: to identify predictor factors of NOLBP, and the type of material referred to in the scientific evidence and establish the scopes of the prediction. Materials and method: the title search was conducted in the databases PubMed, Science Direct, and Ebsco Springer, between1985 and 2012. The selected articles were classified through a bibliometric analysis allowing to define the most relevant ones. Results: 101 titles met the established criteria, but only 43 metthe purpose of the review. As for NOLBP prediction, the studies varied in relation to the factors for example: diagnosis, transition of lumbar pain from acute to chronic, absenteeism from work, disability and return to work. Conclusion: clinical prediction is considered as a strategic to determine course and prognostic of NOLBP, and to determine the characteristics that increase the risk of chronicity in workers with this health condition. Likewise, clinical prediction rules are tools that aim to facilitate decision making about the evaluation, diagnosis, prognosis and intervention for low back pain, which should incorporate risk factors of physical, psychological and social.

Validation of the Asthma Predictive Index and comparison with simpler clinical prediction rules

Background The loose and stringent Asthma Predictive Indices (API), developed in Tucson, are popular rules to predict asthma in preschool children. To be clinically useful, they require validation in different settings. Objective To assess the predictive performance of the API in an independent population and compare it with simpler rules based only on preschool wheeze. Methods We studied 1954 children of the population-based Leicester Respiratory Cohort, followed up from age 1 to 10 years. The API and frequency of wheeze were assessed at age 3 years, and we determined their association with asthma at ages 7 and 10 years by using logistic regression. We computed test characteristics and measures of predictive performance to validate the API and compare it with simpler rules. Results The ability of the API to predict asthma in Leicester was comparable to Tucson: for the loose API, odds ratios for asthma at age 7 years were 5.2 in Leicester (5.5 in Tucson), and positive predictive values were 26% (26%). For the stringent API, these values were 8.2 (9.8) and 40% (48%). For the simpler rule early wheeze, corresponding values were 5.4 and 21%; for early frequent wheeze, 6.7 and 36%. The discriminative ability of all prediction rules was moderate (c statistic ≤ 0.7) and overall predictive performance low (scaled Brier score < 20%). Conclusion Predictive performance of the API in Leicester, although comparable to the original study, was modest and similar to prediction based only on preschool wheeze. This highlights the need for better prediction rules.

Prognostic clinical prediction rules to identify a low-risk pulmonary embolism: a systematic review and meta-analysis

Prognostic assessment is important for the management of patients with a pulmonary embolism (PE). A number of clinical prediction rules (CPRs) have been proposed for stratifying PE mortality risk. The aim of this systematic review was to assess the performance of prognostic CPRs in identifying a low-risk PE.

Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms

OBJECTIVE Cognitive impairments are regarded as a core component of schizophrenia. However, the cognitive dimension of psychosis is hardly considered by ultra-high risk (UHR) criteria. Therefore, we studied whether the combination of symptomatic UHR criteria and the basic symptom criterion "cognitive disturbances" (COGDIS) is superior in predicting first-episode psychosis. METHOD In a naturalistic 48-month follow-up study, the conversion rate to first-episode psychosis was studied in 246 outpatients of an early detection of psychosis service (FETZ); thereby, the association between conversion, and the combined and singular use of UHR criteria and COGDIS was compared. RESULTS Patients that met UHR criteria and COGDIS (n=127) at baseline had a significantly higher risk of conversion (hr=0.66 at month 48) and a shorter time to conversion than patients that met only UHR criteria (n=37; hr=0.28) or only COGDIS (n=30; hr=0.23). Furthermore, the risk of conversion was higher for the combined criteria than for UHR criteria (n=164; hr=0.56 at month 48) and COGDIS (n=158; hr=0.56 at month 48) when considered irrespective of each other. CONCLUSIONS Our findings support the merits of considering both COGDIS and UHR criteria in the early detection of persons who are at high risk of developing a first psychotic episode within 48months. Applying both sets of criteria improves sensitivity and individual risk estimation, and may thereby support the development of stage-targeted interventions. Moreover, since the combined approach enables the identification of considerably more homogeneous at-risk samples, it should support both preventive and basic research.

A clinical prediction model to identify patients at high risk of death in the emergency department.

PURPOSE Rapid assessment and intervention is important for the prognosis of acutely ill patients admitted to the emergency department (ED). The aim of this study was to prospectively develop and validate a model predicting the risk of in-hospital death based on all available information available at the time of ED admission and to compare its discriminative performance with a non-systematic risk estimate by the triaging first health-care provider. METHODS Prospective cohort analysis based on a multivariable logistic regression for the probability of death. RESULTS A total of 8,607 consecutive admissions of 7,680 patients admitted to the ED of a tertiary care hospital were analysed. Most frequent APACHE II diagnostic categories at the time of admission were neurological (2,052, 24 %), trauma (1,522, 18 %), infection categories [1,328, 15 %; including sepsis (357, 4.1 %), severe sepsis (249, 2.9 %), septic shock (27, 0.3 %)], cardiovascular (1,022, 12 %), gastrointestinal (848, 10 %) and respiratory (449, 5 %). The predictors of the final model were age, prolonged capillary refill time, blood pressure, mechanical ventilation, oxygen saturation index, Glasgow coma score and APACHE II diagnostic category. The model showed good discriminative ability, with an area under the receiver operating characteristic curve of 0.92 and good internal validity. The model performed significantly better than non-systematic triaging of the patient. CONCLUSIONS The use of the prediction model can facilitate the identification of ED patients with higher mortality risk. The model performs better than a non-systematic assessment and may facilitate more rapid identification and commencement of treatment of patients at risk of an unfavourable outcome.

External validation study of a clinical prediction rule for ambulation outcomes after traumatic spinal cord injury

The main objective of this study was to determine the external validity of a clinical prediction rule developed by the European Multicenter Study on Human Spinal Cord Injury (EM-SCI) to predict the ambulation outcomes 12 months after traumatic spinal cord injury. Data from the North American Clinical Trials Network (NACTN) data registry with approximately 500 SCI cases were used for this validity study. The predictive accuracy of the EM-SCI prognostic model was evaluated using calibration and discrimination based on 231 NACTN cases. The area under the receiver-operating-characteristics curve (ROC) curve was 0.927 (95% CI 0.894 – 0.959) for the EM-SCI model when applied to NACTN population. This is lower than the AUC of 0.956 (95% CI 0.936 – 0.976) reported for the EM-SCI population, but suggests that the EM-SCI clinical prediction rule distinguished well between those patients in the NACTN population who were able to achieve independent ambulation and those who did not achieve independent ambulation. The calibration curve suggests that higher the prediction score is, the better the probability of walking with the best prediction for AIS D patients. In conclusion, the EM-SCI clinical prediction rule was determined to be generalizable to the adult NACTN SCI population.^

Clinical prediction of large vessel occlusion in anterior circulation stroke: mission impossible?

Simple clinical scores to predict large vessel occlusion (LVO) in acute ischemic stroke would be helpful to triage patients in the prehospital phase. We assessed the ability of various combinations of National Institutes of Health Stroke Scale (NIHSS) subitems and published stroke scales (i.e., RACE scale, 3I-SS, sNIHSS-8, sNIHSS-5, sNIHSS-1, mNIHSS, a-NIHSS items profiles A-E, CPSS1, CPSS2, and CPSSS) to predict LVO on CT or MR arteriography in 1085 consecutive patients (39.4 % women, mean age 67.7 years) with anterior circulation strokes within 6 h of symptom onset. 657 patients (61 %) had an occlusion of the internal carotid artery or the M1/M2 segment of the middle cerebral artery. Best cut-off value of the total NIHSS score to predict LVO was 7 (PPV 84.2 %, sensitivity 81.0 %, specificity 76.6 %, NPV 72.4 %, ACC 79.3 %). Receiver operating characteristic curves of various combinations of NIHSS subitems and published scores were equally or less predictive to show LVO than the total NIHSS score. At intersection of sensitivity and specificity curves in all scores, at least 1/5 of patients with LVO were missed. Best odds ratios for LVO among NIHSS subitems were best gaze (9.6, 95 %-CI 6.765-13.632), visual fields (7.0, 95 %-CI 3.981-12.370), motor arms (7.6, 95 %-CI 5.589-10.204), and aphasia/neglect (7.1, 95 %-CI 5.352-9.492). There is a significant correlation between clinical scores based on the NIHSS score and LVO on arteriography. However, if clinically relevant thresholds are applied to the scores, a sizable number of LVOs are missed. Therefore, clinical scores cannot replace vessel imaging.

Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

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Current tools for prediction of arteriovenous fistula outcomes

It remains challenging to accurately predict whether an individual arteriovenous fistula (AVF) will mature and be useable for haemodialysis vascular access. Current best practice involves the use of routine clinical assessment and ultrasonography complemented by selective venography and magnetic resonance imaging. The purpose of this literature review is to describe current practices in relation to pre-operative assessment prior to AVF formation and highlight potential areas for future research to improve the clinical prediction of AVF outcomes.

Clinical decision rules and D-Dimer in venous thromboembolism: current controversies and future research priorities

Venous thromboembolism (VTE) is a potentially lethal clinical condition that is suspected in patients with common clinical complaints, in many and varied, clinical care settings. Once VTE is diagnosed, optimal therapeutic management (thrombolysis, IVC filters, type and duration of anticoagulants) and ideal therapeutic management settings (outpatient, critical care) are also controversial. Clinical prediction tools, including clinical decision rules and D-Dimer, have been developed, and some validated, to assist clinical decision making along the diagnostic and therapeutic management paths for VTE. Despite these developments, practice variation is high and there remain many controversies in the use of the clinical prediction tools. In this narrative review, we highlight challenges and controversies in VTE diagnostic and therapeutic management with a focus on clinical decision rules and D-Dimer.

Automated prediction of deterioration of infants in paediatric intensive care using SpO2

Acute life-threatening events are mostly predictable in adults and children. Despite real-time monitoring these events still occur at a rate of 4%. This paper describes an automated prediction system based on the feature space embedding and time series forecasting methods of the SpO2 signal; a pulsatile signal synchronised with heart beat. We develop an age-independent index of abnormality that distinguishes patient-specific normal to abnormal physiology transitions. Two different methods were used to distinguish between normal and abnormal physiological trends based on SpO2 behaviour. The abnormality index derived by each method is compared against the current gold standard of clinical prediction of critical deterioration. Copyright © 2013 Inderscience Enterprises Ltd.

Soveltuvuuskokeella täydennetty opiskelijavalinta : Seurantatutkimus eräiden sosiaali- ja terveysalan teknisluonteisten koulutusohjelmien (apuvälinetekniikka, hammastekniikka ja optometria) opiskelijavalinnan toteuttamisesta

Aptitude-based student selection: A study concerning the admission processes of some technically oriented healthcare degree programmes in Finland (Orthotics and Prosthetics, Dental Technology and Optometry). The data studied consisted of conveniencesamples of preadmission information and the results of the admission processes of three technically oriented healthcare degree programmes (Orthotics and Prosthetics, Dental Technology and Optometry) in Finland during the years 1977-1986 and 2003. The number of the subjects tested and interviewed in the first samples was 191, 615 and 606, and in the second 67, 64 and 89, respectively. The questions of the six studies were: I. How were different kinds of preadmission data related to each other? II. Which were the major determinants of the admission decisions? III. Did the graduated students and those who dropped out differ from each other? IV. Was it possible to predict how well students would perform in the programmes? V. How was the student selection executed in the year 2003? VI. Should clinical vs. statistical prediction or both be used? (Some remarks are presented on Meehl's argument: "Always, we might as well face it, the shadow of the statistician hovers in the background; always the actuary will have the final word.") The main results of the study were as follows: Ability tests, dexterity tests and judgements of personality traits (communication skills, initiative, stress tolerance and motivation) provided unique, non-redundant information about the applicants. Available demographic variables did not bias the judgements of personality traits. In all three programme settings, four-factor solutions (personality, reasoning, gender-technical and age-vocational with factor scores) could be extracted by the Maximum Likelihood method with graphical Varimax rotation. The personality factor dominated the final aptitude judgements and very strongly affected the selection decisions. There were no clear differences between graduated students and those who had dropped out in regard to the four factors. In addition, the factor scores did not predict how well the students performed in the programmes. Meehl's argument on the uncertainty of clinical prediction was supported by the results, which on the other hand did not provide any relevant data for rules on statistical prediction. No clear arguments for or against the aptitude-based student selection was presented. However, the structure of the aptitude measures and their impact on the admission process are now better known. The concept of "personal aptitude" is not necessarily included in the values and preferences of those in charge of organizing the schooling. Thus, obviously the most well-founded and cost-effective way to execute student selection is to rely on e.g. the grade point averages of the matriculation examination and/or written entrance exams. This procedure, according to the present study, would result in a student group which has a quite different makeup (60%) from the group selected on the basis of aptitude tests. For the recruiting organizations, instead, "personal aptitude" may be a matter of great importance. The employers, of course, decide on personnel selection. The psychologists, if consulted, are responsible for the proper use of psychological measures.

Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

Background: Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods: This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results: In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better. Conclusions: Five clinical predictors easily available in the ED, and also in the primary care setting, can be used to create a simple and easily obtained score that allows clinicians to stratify patients with eCOPD upon ED arrival and guide the medical decision-making process.

Preoperative radial artery volume flow is predictive of arteriovenous fistula outcomes

Objective: Guidelines recommend the creation of a wrist radiocephalic arteriovenous fistula (RAVF) as initial hemodialysis vascular access. This study explored the potential of preoperative ultrasound vessel measurements to predict AVF failure to mature (FTM) in a cohort of patients with end-stage renal disease in Northern Ireland

.Methods: A retrospective analysis was performed of all patients who had preoperative ultrasound mapping of upper limb blood vessels carried out from August 2011 to December 2014 and whose AVF reached a functional outcome by March 2015.

Results: There were 152 patients (97% white) who had ultrasound mapping andan AVF functional outcome recorded; 80 (54%) had an upper arm AVF created, and 69 (46%) had a RAVF formed. Logistic regression revealed that female gender (odds ratio [OR], 2.5; 95% confidence interval [CI], 1.12-5.55; P = .025), minimum venous diameter (OR, 0.6; 95% CI, 0.39-0.95; P = .029), and RAVF (OR, 0.4; 95% CI, 0.18-0.89; P = .026) were associated with FTM. On subgroup analysis of the RAVF group, RAVFs with an arterial volume flow <50 mL/min were seven times as likely to fail as RAVFs with higher volume flows (OR, 7.0; 95% CI, 2.35-20.87; P < .001).

Conclusions: In this cohort, a radial artery flow rate <50 mL/min was associated with a sevenfold increased risk of FTM in RAVF, which to our knowledge has not been previously reported in the literature. Preoperative ultrasound mapping adds objective assessment in the clinical prediction of AVF FTM.