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A multivariate prediction model of schizophrenia.

Univariate prediction models of schizophrenia may be adequate for hypothesis testing but are narrowly focused and limited in predictive efficacy. Therefore, we used a multivariate design to maximize the prediction of schizophrenia from premorbid measures and to evaluate the relative importance of various predictors. Two hundred twelve Danish subjects with at least one parent diagnosed in the schizophrenia spectrum (high risk) and 99 matched subjects with no such parent (low risk) were assessed on 25 premorbid variables in seven domains (genetic risk, birth factors, autonomic responsiveness, cognitive functioning, rearing environment, personality, and school behavior) when the subjects averaged 15 years of age. Twenty-five years later, 33 subjects had received lifetime diagnoses of schizophrenia. Discriminant function analyses were used to discriminate schizophrenia outcomes from no mental illness and nonschizophrenia outcomes on the basis of premorbid measures. Regardless of the comparison group used, schizophrenia was predicted by the interaction of genetic risk with rearing environment, and disruptive school behavior. Within the high-risk group, two-thirds of schizophrenia outcomes were correctly predicted by these premorbid measures; three-quarters of those with no mental illness were also correctly predicted. Prediction was enhanced among those with two schizophrenia spectrum parents, lending support to a multiplicative gene x environment model. Implications for early identification/primary prevention efforts are discussed.

Adolescent↗

Predicting residue solvent accessibility from protein sequence by considering the sequence environment.

The solvent accessibility of each residue is predicted on the basis of the protein sequence. A set of 338 monomeric, non-homologous and high-resolution protein crystal structures is used as a learning set and a jackknife procedure is applied to each entry. The prediction is based on the comparison of the observed and the average values of the solvent-accessible area. It appears that the prediction accuracy is significantly improved by considering the residue types preceding and/or following the residue whose accessibility must be predicted. In contrast, the separate treatment of different secondary structural types does not improve the quality of the prediction. It is furthermore shown that the residue accessibility is much better predicted in small than in larger proteins. Such a discrepancy must be carefully considered in any algorithm for predicting residue accessibility.

Amino Acid Sequence↗

The use of clinical prediction formulas in the evaluation of obstructive sleep apnea.

STUDY OBJECTIVES: To prospectively study the utility of four clinical prediction models for either predicting the presence of obstructive sleep apnea (OSA, apnea-hypopnea index [AHI] > or = 10/hour), or prioritizing patients for a split-night protocol (AHI(3)20/hour). DESIGN: All patients presenting for OSA evaluation completed a research questionnaire that included questions from previously developed clinical prediction models. The probability of sleep apnea for each patient for each model was calculated based upon the equation used in the model. Based upon two cutoffs of apnea-hypopnea index, 10 and 20, the sensitivity, specificity, and positive predictive value were calculated. For the cutoffs AHI > or =10 and > or =20, receiver operating characteristic curves were generated and the areas under the curves calculated. Comparisons of demographic information and symptom response were compared between patients with and without OSA, and men vs. women. SETTING: Urban, accredited sleep disorders center. PATIENTS OR PARTICIPANTS: All patients referred for evaluation of OSA who underwent polysomnography. INTERVENTIONS: N/A. RESULTS: 370 patients (191 men, 179 women) completed the study. 248 of the 370 (67%) patients had an AHI(3)10; 180 of the 370 (49%) had an AHI> or =20. For AHI > or =10, the sensitivities ranged from 76 to 96%, specificities from 13%-54%, positive predictive values from 69%-77% using the probability cutoff of the original investigators; the areas under the curve from 0.669 to 0.736. For AHI(3)20, the areas under the ROC curves ranged from 0.700 to 0.757; using cutoffs to maximized specificity, the sensitivities ranged from 33%-39%, specificities from 87%-93%, and positive predictive values from 72%-85%. All the models performed better for men. CONCLUSIONS: The clinical prediction models tested are not be sufficiently accurate to discriminate between patients with or without OSA but could be useful in prioritizing patients for split-night polysomnography.

Adult↗

Prediction of movement during propofol/nitrous oxide anesthesia. Performance of concentration, electroencephalographic, pupillary, and hemodynamic indicators.

BACKGROUND: Movement in response to painful stimulation is the end point classically used to assess the potency of anesthetic agents. In this study, the ability of modeled propofol effect-site concentration to predict movement in volunteers during propofol/nitrous oxide anesthesia was tested, then it was compared with the predictive abilities of the Bispectral Index and 95% spectral edge frequency of the electroencephalogram, pupillary reflex amplitude, and systolic arterial blood pressure. In addition, the relationships between simple end points of loss and recovery of consciousness, and pupillary, hemodynamic, and propofol concentration indicators were studied. METHODS: Ten healthy volunteers were anesthetized with an infusion of propofol, which was increased in three equal steps to 21 mg.kg lean body mass-1.h-1. After loss of the ability to hold a syringe and of the eyelash reflex, 60% nitrous oxide was introduced and the trachea was intubated without the use of muscle relaxants. The propofol infusion rate then was decreased to 15.4 mg.kg lean body mass-1.h-1. Ten minutes later, tetanic electrical stimulation was administered to the thigh via needle electrodes: if movement was observed within 1 min, the propofol infusion rate was increased by 1.75 mg.kg lean body mass-1.h-1 5 min after the stimulus; if not, it was similarly decreased. This 15-min sequence was repeated until volunteers "crossed over" from movement to no movement (or vice versa) four times. The propofol infusion rate then was increased to 21 mg.kg lean body mass-1.h-1, nitrous oxide was discontinued, the trachea was extubated, and the infusion rate was decreased in five equal steps over 50 min. The times at which the eyelash reflex returned and the birth date was recalled were recorded. The electroencephalogram was monitored continuously (FP1, FP2, ref: nasion, ground: mastoid). Measurements of the pupillary response, arterial blood pressure, and heart rate were recorded during induction and awakening, just before and for 5 min after each stimulation. Arterial blood samples were obtained for propofol assay, and propofol effect-site concentrations were calculated at each time. The predictive value of indicators was compared using a new static, the prediction probability (PK). RESULTS: Loss and return of the eyelash reflex occurred at greater propofol effect-site concentrations than either dropping the syringe or recall of the birthday. The propofol effect-site concentration (in the presence of 60% nitrous oxide) predicted to prevent movement after a supramaximal stimulus in 50% of volunteers was 1.80 micrograms/ml (95% confidence limits: 1.40-2.34 micrograms/ml). The Bispectral Index (PK = 0.86), 95% spectral edge frequency (PK = 0.81), pupillary reflex amplitude (PK = 0.74), and systolic arterial blood pressure (PK = 0.78) did not differ significantly from modeled propofol effect-site concentration (PK = 0.76) in their ability to predict movement. CONCLUSIONS: Indicators of pharmacodynamic effect, such as the electroencephalogram, pupillary light reflex, and systolic arterial blood pressure, predict movement as well as effect-site concentration during propofol/nitrous oxide anesthesia. Loss and return of the eyelash reflex correspond to a deeper level of anesthesia than syringe-dropping or recall of the birth date.

Adult↗

Predicting follow-up functional outcomes in outpatient rehabilitation.

Functional outcomes at an average of six months after outpatient rehabilitation were investigated in a pilot study with a sample of 42 patients receiving physical therapy for low back, neck, and other musculoskeletal problems. Logistic regression analyses were used to study variables related to the achievement of a predetermined level of physical functioning or to whether improvement occurred from initial to follow-up assessment. Scales used in the analyses were obtained from two measures of functioning, the Medical Outcomes Trust Short Form 36 (SF-36) and the Medical Rehabilitation Follow Along (MRFA instrument). Demographic and program characteristic variables obtained from clinic records were also included in the analyses. The independent variables entered into two groups of regression equations included age, gender, presenting problem, workers' compensation coverage, functioning at initial assessment, number of visits, length of program, and intensity of program. For the SF-36, the General Health scale and presenting problem predicted above or below a level greater than one standard deviation less than the mean on the Physical Functioning scale at follow-up. The combination of the Role Physical and Role Emotional scales predicted follow-up level on the Physical Component Summary (PCS) scale. The interaction of age and intensity of treatment was predictive for both the Physical Functioning and PCS scales. For predicting improvement or no improvement using the SF-36 scales, General Health and the interaction between age and intensity were predictive of change on the Physical Functioning scale, whereas age and the interaction between age and number of visits were predictive of change on the PCS scale. For the MRFA instrument, the interaction between age and the intensity of treatment was predictive for both a predetermined level of physical functioning and amount of improvement in physical functioning at follow-up. An intensity rating of pain and a measure of affective distress at initial assessment both improved the identification of patients at risk for not reaching a given level of functioning, whereas treatment intensity improved the identification of those patients at risk for not showing improvement at follow-up. Length of time between the end of outpatient therapy and follow-up assessment was generally not related to follow-up physical functioning. Interpretation and implications of these findings, as well as applications of this analytic approach to outcomes assessment, are discussed.

Activities of Daily Living↗

Functional assessment in patients with chronic pain: can physicians predict performance?

OBJECTIVES: To determine the appropriateness of using physicians to estimate the functional abilities of patients with chronic pain. Specific objectives included the following: (1) to compare the physician's predicted performance on functional assessment with actual performance, and (2) to compare the physician's predicted effort during functional assessment with an objective measure of effort. DESIGN: A total of 201 outpatients with chronic pain completed this prospective, multicenter, cohort study. Fifteen physicians, who were trained to administer the standardized evaluation, performed the evaluations and predicted performance and effort on functional assessment. Therapists, blinded to the physician's evaluation, administered a functional assessment (maximal and sustained lifts [n = 3 types]; repetitive activities [n = 4 types]) and a grip dynamometry test (effort measure) on each subject. RESULTS: Pearson's correlation testing demonstrated significant correlations between the physician's predicted performance and the observed performance for all lifting items and repetitive activities in both men (0.52, 0.50, 0.55) and women (0.36, 0.40, 0.18). Analysis of variance and post hoc t tests showed agreement between the physician's predicted effort and the dynamometry effort measure in only a small subset of patients (men were predicted to put forth absolutely no effort; n = 4). CONCLUSIONS: A trained physician, performing a standardized evaluation, can estimate with reasonable accuracy the work-related functional ability in patients with chronic pain. The prediction of effort seems to be more problematic.

Activities of Daily Living↗

Molecular genetic predictive testing for Alzheimer's disease: deliberations and preliminary recommendations.

Forty-one participants representing diverse professional back-grounds attended a workshop on genetic predictive testing for familial Alzheimer's disease (FAD) on January 23, 1993 at Surrey Place Centre in Toronto, Canada. Rapidly emerging molecular genetic findings in AD indicate that predictive testing is now technologically feasible for selected individuals, although defining eligibility criteria remains problematic. Legal, ethical, biomedical, and psychosocial issues related to establishing predictive testing programs for AD were discussed at the workshop. This article reflects these discussions, provides the current biomedical background for them and examines the Huntington's disease (HD) predictive testing experience. Observations concerning molecular genetic predictive testing for AD in light of its genetic heterogeneity and clinical characteristics, such as usual later age of onset than HD, are presented. It is proposed that predictive testing for AD can now be cautiously offered in a research setting primarily according to the recommendations contained within the Ethical Issues Policy Statement on Huntington's Disease Molecular Genetics Predictive Test. However, in their application to AD, some points in the statement are considered to require emphasis, modification, or currently to be of uncertain applicability. This represents an initial step in an on-going process of debate concerning AD that will be required as new advances occur in genetic and clinical research and in bioethics.

Aged↗

Factors predicting pain reduction in chronic back and neck pain after multimodal treatment.

OBJECTIVES: To determine whether treatment related pain reduction on the short- and long-term is predicted by different baseline variables, and with different accuracy, in patients with chronic low back pain as compared with those with chronic neck pain. DESIGN AND METHODS: A single blinded prospective cohort study based on patients with chronic musculoskeletal pain in the lower back (N = 167) or the neck (N = 136) who completed a 4-week multimodal rehabilitation program. At admission, each patient was evaluated on 17 potential predictors, including pain characteristics and physical, sociodemographic, and psychosocial-behavioral variables. Changes in self-reported pain intensity in the lower back or the neck between the pretreatment evaluation and those performed immediately after, and 12 months after the rehabilitation program, were assessed. RESULTS: Logistic regression models revealed that change in pain intensity could be predicted with good specificity but with poor sensitivity both for patients with chronic low back pain and chronic neck pain. Significant predictors among the neck pain patients were high endurance, low age, high pain intensity, few other symptoms, low need of being social, to do things with others, and to be helped, along with optimistic attitudes on how the pain will interfere with daily life. Among the low back pain patients, high pain intensity, low levels of pain severity, and high affective distress were important predictors. Variables such as sex, sick leave history, working status, accident, pain duration, and depressive symptoms demonstrated no predictive value. Short- and long-term pain outcome was equally predictable and predicted by almost the same variables. CONCLUSIONS: Patients who reported unchanged or increased pain after multimodal treatment could be predicted with good accuracy, whereas those who reported decreased pain were more difficult to identify. Treatment-related pain alteration in chronic low back pain seems to be predicted by partly different variables than in chronic neck pain.

Adult↗

Accuracy of leg length prediction in children younger than 10 years of age.

In this study, the authors attempted to predict the ultimate leg length in normal children with normally growing legs, using Green-Anderson and Moseley techniques with chronologic and skeletal age. The predictions were based on serial growth studies of children between 5 and 10 years of age. Using skeletal age for prediction, the absolute mean error in predicting the ultimate leg length was 2.4 cm using the Green-Anderson method and 2.58 cm using the Moseley method. Using the Moseley method for length prediction in boys, the mean error was 3.8 cm using skeletal age and 1.5 cm using chronologic age. For girls, using the Moseley method of leg length prediction, the mean error was 1.55 cm with skeletal age and 2.46 cm with chronologic age. The significance of this study is that skeletal age, as determined by the Gruelich and Pyle Atlas, does not improve the accuracy of prediction of ultimate leg length in children younger than 10 years of age, except in girls with advanced bone age.

Age Determination by Skeleton↗

Stress test and gastric-arterial PCO2 measurement improve prediction of successful extubation.

OBJECTIVE: Correct early prediction of successful extubation decreases morbidity and mortality. The use of single time point measurements and surrogate markers of true extubation success limits weaning studies. Our aim was to determine whether a "stress test" improves prediction of extubation outcome and to determine the most predictive variables. DESIGN: Observational study. SETTING: Intensive care unit of a teaching hospital. PATIENTS: A convenience sample of 68 patients judged to be ready for extubation. INTERVENTIONS: We decreased pressure support from 5 to 0 cm H2O for 1 hr before extubation (stress test) while patients were on 5 cm H2O continuous positive airway pressure. MEASUREMENTS AND MAIN RESULTS: We measured respiratory frequency, tidal volume, ratio of respiratory frequency to tidal volume (f/VT), airway occlusion pressure after onset of inspiration (P0.1), and gastric-arterial PCO2 (deltaPg-aCO2 both on 5 cm H2O and 0 cm H2O pressure support. Then all patients were extubated. Failure of extubation was defined as reintubation within 24 hrs. Seventeen patients (25%) failed extubation. With pressure support of 5 cm H2O and continuous positive airway pressure of 5 cm H2O, most predictors were not different between patients who failed and patients who were successfully extubated. After the stress test, deltaPg-aCO2 was 2 (-5; 15) mm Hg (median; quartiles) in successfully extubated patients vs. 28 (-9; 48) in failures (p = .0003), tidal volume was 473 (387; 558) vs. 400 (323; 435) mL (p = .02), and P0.1 was 2.8 (2; 4.1) vs. 4.1 (2.7; 5.3) mm Hg (p = .03), respectively. The stress test increased specificity of deltaPg-aCO2 from 0.45 to 0.94 and positive predictive value from 0.85 to 0.97. The specificity and positive predictive values for f/VT after the stress test were 0.23 and 0.78. CONCLUSIONS: A simple stress test improves prediction of extubation outcome. deltaPg-aCO2 has superior specificity and positive predictive value compared with other variables. The use of true clinical outcome (i.e., extubation) instead of the use of surrogate markers (e.g., tachypnea) distinguishes these results from previous studies.

Blood Gas Analysis↗

The role of a baseline casual blood pressure measurement and of blood pressure changes in middle age in prediction of cardiovascular and all-cause mortality occurring late in life: a cross-cultural comparison among the European cohorts of the Seven Countries Study.

OBJECTIVE: The first objective was to study the long-term association of a casual measurement of systolic blood pressure (SBP) with cardiovascular deaths (CVD) and all causes of death (ALL) occurring during 35 years of follow-up in different population samples of men aged 40-59 years in five European countries. The second objective was to study the predictive power of early change in SBP levels (years 0-10) in relation to late fatal events (years 10-35). DESIGN, SETTING AND PARTICIPANTS: A single measurement of SBP was considered in cohorts in Finland, The Netherlands, Italy, Serbia and Greece for a total of 6507 men. Three partitioned proportional hazards models were solved, one for each independent and subsequent time block of 10 years, after excluding data from the first 5 years, to predict the risk of cardiovascular disease deaths of atherosclerotic origin (CVD) and all cause mortality (ALL). Independently, the predictive power of SBP changes (Delta-SBP) occurred during the first 10 years of follow-up was explored as a possible additional risk factor in relation to CVD and ALL deaths occurring between year 10 and year 35 of follow-up. RESULTS: Partitioned hazard scores derived from the three partitioned functions were cumulated. The resulting curves showed a continuous and significant association of baseline SBP with CVD and ALL deaths during three decades, although the strength of association declined significantly from the first to the third decade. The relative risk for 20 mmHg of SBP (and its 95% confidence intervals) in predicting CVD deaths was 1.65 (1.54-1.77) for the first 10-year block; 1.33 (1.24-1.42) for the second block; and 1.22 (1.13-1.31) for the last 10-year block. The corresponding levels of ALL deaths were 1.41 (1.34-1.49), 1.26 (1.19-1.32) and 1.11 (1.05-1.17). Changes in SBP during 10 years (Delta-SBP) added predictive power to baseline measurements in a direct and significant way, with a relative risk for a change of 10 mmHg of 1.14 (1.10-1.17) for CVD deaths and 1.11 (1.09-1.13) for ALL deaths. CONCLUSION: A single measurement of systolic blood pressure in middle-aged men maintains a strong relationship with fatal CVD and ALL deaths during the next 35 years, although for late events the strength of the association definitely declines. Changes in systolic blood pressure levels during the first 10 years of follow-up add predictive power, while baseline measurements retain their predictive power.

Adult↗

Predicting survival from head trauma 24 hours after injury: a practical method with therapeutic implications.

OBJECTIVE: To develop a method to predict long-term outcome after head injury and determine if outcome can be accurately predicted 24 hours after injury. DESIGN: A retrospective review was performed on a study cohort of 672 head-injured patients admitted in coma (Glascow Coma Scale score < or = 8) who remained comatose for at least 6 hours, survived more than 24 hours, and had 6-month outcome data available. Stepwise logistic regression analysis was used to determine which clinical variables predicted 6-month outcome. Statistically significant clinical predictors were combined into a single examination variable (MPX score), which reflected a rank-ordering of examinations from worst to best, which was then further weighted by patient age. The relation between 6-month outcome and MPX score at admission and 24 hours was plotted and analyzed. MEASUREMENT AND MAIN RESULTS: Age, best motor score, and pupillary reactivity at admission and 24 hours were significant predictors of outcome; extraocular motility was predictive at 24 hours only. Age was the most important independent predictor, followed by best motor score, pupillary reactivity, and extraocular motility. Combining these predictors into MPX score resulted in a set of graphs that reliably predicted long-term outcome. The 24-hour MPX data were better predictors of 6-month outcome and were more specific in predicting negative outcomes than admission data. CONCLUSIONS: The method is simple to use, relying on bedside neurologic examination and a single graph, but appears to predict long-term outcome accurately as early as 24 hours after head injury. If validated on other large series of patients, this method could provide an objective and practical basis for terminating care in patients unlikely to survive a head injury.

Adolescent↗

Early prediction of prolonged ventilator dependence in thermally injured patients.

BACKGROUND: Recent studies suggest that when prolonged ventilator dependence (PVD) can be predicted in trauma or intensive care unit patients, early tracheostomy may reduce hospital stay and improve utilization of resources. This study was performed to develop criteria predictive of PVD (> 14 days) in burn patients. METHODS: We reviewed burn patients aged > or =16 years admitted between 1990 and 1994 who required ventilator support for > or =3 days. Using the variables full-thickness burn size, age, inhalation injury, and worst PaO2/FiO2 on ventilator day 3, an equation predicting PVD was created using logistic regression. The equation was tested by applying it to 1995 patients. RESULTS: When a probability of >0.5 was considered predictive of PVD, the equation correctly predicted PVD in 82% of 1990 to 1994 patients (n = 110) and 90% of 1995 patients (n = 29). CONCLUSION: PVD in burn patients can be predicted using objective variables in the early postburn period. Predictions can be used to select patients for prospective studies of early tracheostomy.

Adult↗

The use of polynomial neural networks for mortality prediction in uncontrolled venous and arterial hemorrhage.

BACKGROUND: The ability to rapidly and accurately triage, evacuate, and utilize appropriate interventions can be problematic in the early decision-making process of trauma care. With current methods of prehospital data collection and analysis, decisions are often based upon single data points. This information may be insufficient for reliable decision-making. To date, no studies have attempted to utilize data at multiple time points for purposes of enhancing prediction, nor have studies attempted to synthesize prediction models with data reflecting both large-vessel venous and arterial injuries. Therefore, we performed a retrospective study to examine the potential utility of dynamic neural networks in predicting mortality using highly discretized uncontrolled hemorrhagic shock data. METHODS: One hundred forty-three swine with either grade V liver injuries or 2.8-mm aortotomies had hemodynamic data collected every minute throughout injury and resuscitation. The independent variables used as inputs to the polynomial neural networks (PNNs) included systolic blood pressure and mean arterial pressure (MAP). These inputs were used to predict mortality in individual swine 1 hour after injury using data up to 20 minutes after injury. Survival models were compared based on discrimination power (DP), i.e., where specificity equals sensitivity, and area under the receiver operating characteristic (ROC) curve (c-statistic). The Hosmer-Lemeshow (H-L) statistic was used to measure model calibration. RESULTS: The best PNN model predicted mortality at 60 minutes utilizing data from injury to 20 minutes after injury. This model produced a ROC area of 0.919, a DP of 0.857, and a H-L value of 16.47. A DP of 0.857 means that 85.7% of the survivors are correctly predicted to survive, and 85.7% of the nonsurvivors are predicted to die. MAP of survivors and nonsurvivors were graphed for comparative purposes. As this graph illustrates, the use of MAP alone cannot discriminate survivors from nonsurvivors. CONCLUSION: This study demonstrates that PNN models can effectively harness the dynamic nature of uncontrolled hemorrhagic shock data, despite utilizing data from large-vessel arterial and venous injuries. Utilizing the dynamic nature of hemorrhagic shock data in PNNs may ultimately allow the development of novel decision assist devices.

Animals↗

Are nuclear texture features a suitable tool for predicting non-organ-confined prostate cancer?

PURPOSE: We investigated the possibility of determining organ confinement of prostate cancer using multiple nuclear texture features determined by fully automated high resolution image analysis combined with preoperative serum PSA levels. MATERIALS AND METHODS: The study population consisted of 145 patients (61 organ confined and 84 non-organ-confined cases). Nuclear texture features were determined using single cell preparations of radical prostatectomy specimens. Nuclear texture features were extracted and analyzed by multivariate logistic regression analysis in order to build a classifier for distinguishing between organ confined and non-organ-confined tumors. The classifier was designed in a cell by cell model and tested on a case by case analysis. RESULTS: The predictive probability of the trained classifier in the cell by cell analysis had a sensitivity of 63%, a specificity of 53%, a positive predictive value of 75% and a negative predictive value of 38% and an area under the ROC curve of 0.58. In the case by case analysis the sensitivity was 70%, the specificity was 54%, positive predictive value 78%, negative predictive value 74%, area under the ROC curve 0.62. When preoperative PSA was included in the algorithm, sensitivity raised to 80%, specificity to 60%, the positive predictive value raised to 79%, the negative predictive value to 52% and the area under the ROC curve to 0.70. CONCLUSIONS: In contrast to former studies using tissue sections, our results suggest that nuclear texture features extracted from single cell preparations cannot be used as a reliable parameter for the determination of organ confinement in prostatic adenocarcinomas.

Adenocarcinoma↗

Ability of a computerized geriatric assessment to predict need for change in living status among elderly living at home.

The objective of this study was to determine the ability of a software program used in a primary care physician's office to predict the need for alternate living arrangement in a cohort of community-dwelling elderly. An analysis was conducted involving 124 consecutive patients between February 10, 1990, and December 20, 1991, in my private medical practice. These patients, all older than 65 years, underwent a computer-assisted geriatric assessment. Two scales--the Geriatric Functional Rating Scale (GFRS) and the Functional Assessment Screening Questionnaire (FASQ)--were compared for their accuracy at predicting change in living status during the 12- to 24-month period following the assessment. Similar analysis of the Tinetti gait and balance test was also performed. Ten and one-half percent of subjects (n = 13) required a change in living status during the study period. Ten went to nursing homes and three joined relatives' households. The GFRS was 62% accurate (8/13) and the FASQ was 54% (7/13) accurate in predicting this change. Abnormality in both gait and balance was predictive 77% (10/13) of the time. Combining all three parameters raised the successful prediction rate to 85% (11/13). Neither GFRS, FASQ, nor gait/balance testing was predictive of death. A computer software program designed to facilitate performance of geriatric assessments in primary care physicians' offices has a high rate of predictive capability relative to future need for change in living status among community-dwelling elderly. Further studies comparing this software program with traditional geriatric assessment protocols are suggested.

Activities of Daily Living↗

Prediction of the clinical course of low-back trouble using multivariable models.

The inability to predict outcome in patients with low-back pain seriously impedes clinical trials and leads to inappropriate or unnecessary treatment. This prospective study investigated the value of multivariable mathematical models to predict the 1-year clinical course of 109 patients with low-back trouble (LBT). Discriminant analysis was used to determine predictive models for outcome groups at 1 month, 3 months and 1 year. The variables selected in the analyses were subsets of 29 items from a clinical interview at presentation. These included anamnestic features of the first episode as well as symptomatic details and results from clinical tests for the current spell. The derived models successfully discriminated outcome groups with estimates of sensitivity and specificity ranging from 63 to 99%. When models from one set of patients were tested for predictive accuracy by the application of them to a different set, nonrecovery and satisfactory improvement were predicted with a 76-100% success rate. The results affirmed the importance of considering combinations of interrelated variables for prediction and discrimination in LBT. This work has demonstrated that outcome can be predicted successfully by the use of mathematic models based just on presentation data. The ability to determine homogenous groups in respect to outcome is seen as an important aid to therapeutic research; further work will enable refinement of these models for general clinical use and for incorporation into computer-based interview systems.

Adult↗

Identifying patients at risk of becoming disabled because of low-back pain. The Vermont Rehabilitation Engineering Center predictive model.

A predictive risk model of low-back pain (LBP) disability was developed by a panel of six experts in the fields of chronic pain and disability. It comprised 28 factors organized into eight categories: job, psychosocial, injury, diagnostic, demographic, medical history, health behaviors, and anthropometric characteristics and was administered as a 15-minute written questionnaire. The model was tested prospectively on 250 patients (age range, 18-65 years) attending two secondary-care low-back clinics. Disability, as predicted by the model, was compared with 1) actual disability assessed 3 and 6 months later; 2) predictions of disability made by the attending physicians; and 3) predictions obtained from an empirically derived model. These results showed that 1) the expert-generated risk model had a predictive accuracy of 89% and did better in predicting disability than the physicians across all samples and 2) the empirically weighted model did best of all (91% predictive accuracy), suggesting that the expert model used appropriate factors but that the weights assigned to these factors by the panel of experts could be improved.

Adult↗