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PubMed2003

Predictors of institutionalization in an older population during a 13-year period: the effect of urge incontinence.

BACKGROUND: Longitudinal data on predictors of institutionalization in random older populations are limited. The aim here was to identify predictors of institutionalization in an unselected older population during a period of 13 years with a special focus on the prognostic value of urge incontinence. METHODS: A population-based prospective survey was conducted involving 366 men and 409 women aged 60 years and older. Age-adjusted and multivariate Cox proportional hazards models were used to examine the predictive association of urge incontinence, living arrangements, neurological, cardiovascular, musculoskeletal, and other chronic diseases, activities of daily living (ADL) disability, and depressive symptoms with institutionalization separately in men and women. RESULTS: Adjusted for age, ADL disability and other chronic diseases predicted institutionalization in both men and women. Urge incontinence and depressive symptoms in men and living alone and cardiovascular diseases in women were also significant predictors. In multivariate analyses where all potential predictors were included simultaneously, age (RR [relative risk] 1.15; 95% CI [confidence interval] 1.10-1.19), urge incontinence (RR 3.07; 95% CI 1.24-7.59), and depressive symptoms (RR 1.22; 95% CI 1.00-1.48) remained significant predictors of institutionalization in men. In women, age (RR 1.15; 95% CI 1.12-1.19) and living alone (RR 2.02; 95% CI 1.27-3.21) were independent predictors. CONCLUSIONS: In addition to age, urge incontinence and depressive symptoms in men and living alone in women are significant prognostic indicators of institutionalization. The greater prognostic value of urge incontinence in men compared with women emphasizes the importance of interventions aimed at promoting continence and coping with the problem both at the individual and caregiver levels especially among older men.

Activities of Daily Living↗

PubMed1998

Predictors of lean body mass and total adipose mass in community-dwelling elderly men and women.

As part of an ongoing longitudinal study, we analyzed cross-sectional data to identify the predictors of lean body mass (LBM) and total adipose mass (TAM) in community-dwelling elderly men and women. Body composition analysis was done using dual energy x-ray absorptiometry. A total 262 subjects (118 women and 144 men), 60 to 80 years of age, from the urban and suburban communities of southeastern Wisconsin were studied. In women, the age (r = -.18), body mass index (BMI) (r = .43), and waist-to-hip ratio (WHR) (r = .30), and in men, BMI (r = .45) and insulin-like growth factor-1 (IGF-1) (r = .32) were identified as predictors (P < .05) of LBM. In women, the BMI (r = .87), WHR (r = .21), and functional work capacity (VO2 max) (r = -.47), and in men, the BMI (r = .83), WHR (r = .52), dehydroepiandrosterone sulfate (DHEAS) (r = -.27), total testosterone (TT) (r = -.35), free testosterone (FT) (r = -.23), physical activity (LTE) (r = -.32), and VO2 peak (r = -.59) were identified as predictors of TAM. After partialling out age in addition to the predictors identified earlier, the VO2 peak was identified as a predictor (P < .05) of LBM in both women and men, and TT, FT, and LTE as predictors (P < .05) of LBM in men. We conclude that the BMI, WHR, and VO2 peak influences LBM and TAM in both women and men. Additionally, in men LBM and TAM is influenced by hormone profile.

Absorptiometry, Photon↗

PubMed1992

Multicenter study of general anesthesia. III. Predictors of severe perioperative adverse outcomes.

Little information is available about the incidence of severe adverse outcomes, and even less information is available about the identification and quantification of independent predictors of severe perioperative adverse outcomes. The purpose of this study was to identify and quantitate independent predictors of severe perioperative adverse outcomes in a prospective randomized clinical trial of general anesthesia in 17,201 patients. Twenty-nine prognostic variables for 15 severe outcomes in 847 patients were tested by multiple stepwise logistic regressions from which 20 significant (P less than 0.05) predictors were identified. A history of cardiac failure or myocardial infarction less than or equal to 1 yr; ASA physical status 3 or 4; age greater than 50 yr; cardiovascular, thoracic, abdominal or neurologic surgery; and the study anesthetics were significant predictors of "any severe outcome, including death." There were 17 significant predictors for 10 severe cardiovascular outcomes in 608 patients, including a history of ventricular arrhythmia, hypertension, cardiac failure, myocardial ischemia, myocardial infarction less than or equal to 1 yr or myocardial infarction greater than 1 yr, and smoking; ASA physical status; age; cardiovascular, thoracic, abdominal, eyes-ears-nose-throat/endocrine, neurologic, musculoskeletal, or gynecologic surgery; and the study anesthetics. There were 9 significant predictors for 4 severe respiratory outcomes in 163 patients, including a history of cardiac failure, myocardial ischemia, or chronic obstructive pulmonary disease; obesity; smoking; male gender; ASA physical status; abdominal surgery; and the study anesthetics. Colinearity between related prognostic variables (such as disease and ASA physical status) was assessed using progressively segregated groups of variables in eight stepwise logistic regressions. We conclude that the comprehensive stepwise logistic regression of 29 prognostic variables reported here provides a valid estimate of the risks of severe perioperative outcomes associated with general anesthesia.

Anesthesia, General↗

PubMedDate not supplied

Symptom predictors of acute coronary syndromes in younger and older patients.

BACKGROUND: Symptoms, a key element in the patient's decision to seek care, are critical to appropriate triage, and influence decisions to pursue further evaluation and initiation of treatment. Although many studies have described symptoms associated with acute coronary syndromes (ACS), few, if any, have examined symptom predictors of ACS and whether they differ by patients' age. OBJECTIVES: To explore symptom predictors of ACS in younger (< 70 years) and older (> or = 70 years) patients. To test the hypothesis that typical symptoms are predictive of ACS in younger patients, but are less predictive in older patients. METHOD: Secondary analysis of observational data gathered on 531 patients presenting to the emergency department of a regional cardiac referral center in New England with symptoms suggestive of ACS. RESULTS: Bivariate analyses revealed no symptoms significantly (p < .01) associated with ACS in older patients. In younger patients presence of chest symptoms and the total number of typical symptoms reported were significantly (p < .01) associated with ACS. After adjustment for age and gender, typical symptoms that were positive predictors of ACS in younger patients included chest symptoms (OR 2.37, 95% CI 1.32-4.27, p = .004) and arm pain (OR 1.78, 95% CI 1.03-3.09, p = .040). Additionally, the total number of typical symptoms reported (OR 1.68, 95% CI 1.31-2.15, p < .001) was a positive predictor of ACS in younger patients. The atypical symptom of fatigue (OR 2.52, 95% CI 1.10-5.81, p = .029) was a significant positive predictor of ACS, whereas dizziness/faintness (OR .50, 95% CI .26-.91, p = .024) was a significant negative predictor of ACS in younger patients. Logistic regression analysis using the entire sample revealed an interaction between age and number of typical symptoms indicating that younger patients had a 36% greater odds for ACS for each additional typical symptom present compared with older patients (OR 1.36, 95% CI 1.02-1.83, p = .038 for interaction between age and number of typical symptoms reported). The model with the interaction between age and chest symptoms revealed a borderline association (p = .10 for the interaction between age and chest symptoms), with younger patients being more likely than older patients to report chest symptoms. CONCLUSIONS: Typical symptoms are predictive of ACS in younger patients and less predictive in older patients.

Acute Disease↗

PubMed2002

Predictors of flexibility and pain patterns in thoracolumbar and lumbar idiopathic scoliosis.

STUDY DESIGN: A retrospective evaluation of radiographs in patients with idiopathic scoliosis was undertaken to assess predictors of flexibility. OBJECTIVE: To evaluate potential predictors of flexibility in patients with thoracolumbar and lumbar scoliosis. SUMMARY OF BACKGROUND DATA: Curve flexibility is an important consideration in the operative management of idiopathic scoliosis. Flexibility of the major curve is a useful predictor of expected surgical correction, and flexibility of compensatory curves determines whether they are structural or nonstructural. An accurate assessment of curve flexibility has important implications on surgical approaches and planning for deformity correction. The role of age and curve magnitude in predicting curve flexibility has not been well defined. A quantitative assessment of changes in curve flexibility with age and progression of deformity may yield important insight into the change in surgical management options over time. METHODS: A retrospective review of 75 patients with idiopathic thoracolumbar and lumbar scoliosis (age range 13-78 years) was undertaken. Preoperative standing and side-bending radiographs of thoracolumbar and lumbar curves were evaluated. Cobb angles of structural and fractional curves, curve flexibility, presence of lateral listhesis, and axial and radicular pain were documented. Predictors of structural and fractional curve flexibility were evaluated with correlation and regression analysis. Correlation analysis was used to demonstrate an association between radiographic findings and the clinical presentation. RESULTS: Seventy-five patients had an average major curve magnitude of 56 degrees (range 34-82 degrees ) with flexibility averaging 55% (range 20-93%). Structural curve flexibility was highly inversely correlated with both curve magnitude (r = -0.7; P< 0.001) and with age (r = -0.6; P< 0.001). Lumbar fractional curve (L4-S1) flexibility showed a high inverse correlation with age (r = -0.65; P< 0.001) but did not show correlation with Cobb angle. Thoracic compensatory curves showed a moderate correlation with Cobb angle (r = 0.53). Structural and fractional curve flexibility showed high correlation with each other (r = 0.5-0.66). Regression analysis yielded a formula to predict the flexibility of the structural curve (FSC): FSC = 130 - (Cobb + Age/2). Axial pain was correlated with age (r = 0.63); however, it was not correlated with curve magnitude. CONCLUSION: We have shown that curve magnitude and patient age are the main predictors of structural flexibility. Every 10 degrees increase in curve magnitude over 40 degrees results in a 10% decrease in flexibility; every 10-year increase in age decreases flexibility of the structural curve by 5% and the lumbosacral fractional curve by 10%. Curve magnitude and age of the patients are significant predictors of curve flexibility. The demonstration of this association offers useful information in estimating how surgical options for deformity correction may change over time.

Adolescent↗

PubMed2002

Predictors of lower extremity injury among recreationally active adults.

OBJECTIVE: To identify gender-specific predictors of lower extremity injury among a sample of adults engaging in running, walking, or jogging (RWJ) for exercise. DESIGN: Prospective cohort study. SETTING: Cooper Clinic Preventive Medicine Center, Dallas, Texas. PARTICIPANTS: Participants were 2,481 men and 609 women who underwent a physical examination between 1970 and 1981 and returned a follow-up survey in 1986. Predictor variables measured at baseline included height, weight, and cardiorespiratory fitness. At follow-up, participants recalled information about musculoskeletal injuries, physical activity levels, and other predictors for lower extremity injury over two time periods, 5 years and 12 months. MAIN OUTCOME MEASURES: An injury was defined as any self-reported lower extremity injury that required a consultation with a physician. Cox proportional hazards regression (HR) was used to predict the probability of lower extremity injury for the 5-year recall period, and unconditional logistic regression was used for the 12-month recall period. RESULTS: Among men, previous lower extremity injury was the strongest predictor of lower extremity injury (HR = 1.93-2.09), regardless of recall period. Among women, RWJ mileage >20 miles/wk was the strongest predictor for the 5-year period (HR = 2.08), and previous lower extremity injury was the strongest predictor for the 12-month period (HR = 2.81). CONCLUSIONS: For healthy adults, walking at a brisk pace for 10-20 miles per week accumulates adequate moderate-intensity physical activity to meet national recommendations while minimizing the risk for musculoskeletal lower extremity injury. Clinicians may use this information to provide appropriate injury prevention counseling to their active patients.

Adult↗

PubMedDate not supplied

Time-varying predictors for clinical surveillance of small hepatocellular carcinoma.

PURPOSE: Prognosis of small hepatocellular carcinoma depends on a constellation of time-varying predictors in association with liver function. We aimed to elucidate the impact of these time-dependent predictors on survival. PATIENTS AND METHODS: A total of 108 patients with hepatocellular carcinoma smaller than 5 cm in diameter were recruited. Series of laboratory data and clinical assessments were retrieved from medical records. The time-dependent scoring system for the prediction of death was developed in accordance with a time-dependent Cox regression model. RESULTS: Time trends for biologic predictors parallel cumulative survival of small hepatocellular carcinoma cases. Higher serum alpha-fetoprotein level was identified as the most significant time-dependent predictor. Other significant predictors included aspartate transaminase, bilirubin, alkaline phosphatase, and albumin levels and prothrombin time. Time-dependent surveillance scoring system shows the cutoff points of scores at 6 months, 1 year, 2 years, and 3 years were 42, 21, 19, and 31, respectively; the estimates of sensitivity, 100%, 100%, 100%, and 87.5%, respectively; and the estimates of specificity, 91.26%, 67.02%, 60.27%, and 78.26%, respectively. Predictive validity for this time-dependent Cox regression model, particularly within 1-year of follow-up, is good. DISCUSSION: The dynamic relationships between time-dependent predictors and risk of death were illustrated. A time-dependent predictive scoring system using these dynamic relationships was developed for real-time surveillance.

Biomarkers, Tumor↗

PubMed2007

Early predictors for infection recurrence and death in patients with ventilator-associated pneumonia.

OBJECTIVE: Early recognition of predictors of unfavorable evolution of ventilator-associated pneumonia (VAP) might prompt therapeutic measures that might improve outcome. The objective of this study was to describe resolution of VAP variables and to determine early predictors of VAP recurrence and death. DESIGN AND SETTING: Description of the natural course of VAP resolution and multivariable analyses of predictors of VAP recurrence and death by day 28 after VAP onset based on the 401 patients included in the PNEUMA trial, a multiple-center, randomized study comparing 8 vs. 15 days of antibiotics for microbiologically proven VAP. Every patient included in that trial had received appropriate empirical antibiotics. MEASUREMENTS AND MAIN RESULTS: By day 28 after VAP onset, 27% of patients had VAP recurrence and 18% had died. On day 8 after VAP onset, predictors of VAP recurrence included intensive care unit admission Simplified Acute Physiology Score II (odds ratio [OR], 1.02), radiologic score (OR, 1.17), temperature (OR, 1.34), nonfermenting Gram-negative bacilli (OR, 2.00) or methicillin-resistant Staphylococcus aureus (OR, 2.50) as pathogens responsible for VAP, and mechanical ventilation dependency (OR, 2.08). Day 8 predictors of 28-day death were age (OR, 1.06), female sex (OR, 2.30), Sepsis-Related Organ Failure Assessment score (OR, 1.26), and nonfermenting Gram-negative bacilli (OR, 2.83) as pathogens responsible for VAP. However, the duration of antimicrobial therapy (8 vs. 15 days) was not associated with any of the studied adverse outcomes. CONCLUSIONS: For patients benefiting from appropriate empirical antibiotics for VAP, early predictors of infection recurrence or death included demographic characteristics, such as age or female sex, disease severity at VAP onset, nonfermenting Gram-negative bacilli or methicillin-resistant S. aureus as VAP-causative pathogens, prolonged mechanical ventilation dependency, persistent fever, and severity of lung injury. Future studies should attempt to determine whether specific diagnostic or therapeutic strategies could markedly improve VAP outcomes when early criteria for treatment failure are present.

APACHE↗

PubMed2005

Predictors of smoking cessation in patients admitted for acute coronary heart disease.

BACKGROUND: Smoking cessation is probably the most important single action after a coronary event. In order to increase the effectiveness of smoking cessation programs, it is important to have knowledge of the predictors of smoking cessation. Further, it is unknown whether smoking cessation programs have impact on these predictors. METHODS: Data were obtained from a randomized controlled trial of smoking cessation intervention in 240 smokers aged less than 76 years admitted for myocardial infarction, unstable angina, or cardiac bypass surgery. Baseline characteristics were prospectively recorded. Smoking cessation was determined by self report and biochemical verification at 12 months follow-up. RESULTS: In multivariate logistic regression analysis, a high level of nicotine addiction, low level of self-confidence in quitting and having previous coronary heart disease were significant negative predictors of smoking cessation at 12 months follow-up. Having previous coronary heart disease and a diagnosis other than acute myocardial infarction as a reason for admission were important negative predictors of abstinence in the usual care group, in contrast to the intervention group, although this did not reach a level of significance in the subgroup interaction analyses. A high level of nicotine addiction was a strong negative predictor in both groups. CONCLUSION: A high level of nicotine addiction is an important negative predictor of smoking cessation, even within an individualized smoking cessation program. Smoking cessation intervention seems to be especially effective in patients with previous coronary heart disease and in patients with unstable angina or coronary artery bypass surgery, compared to usual care.

Acute Disease↗

PubMed2004

Race is not a predictor of prostate cancer detection on repeat prostate biopsy.

PURPOSE: We evaluated men undergoing repeat prostate biopsies for persistently increased serum prostate specific antigen (PSA) levels to determine if race was a predictor of cancer detection. MATERIALS AND METHODS: Between July 1995 and June 2002, 401 men had undergone 2 or more transrectal ultrasound guided prostate biopsies at our institutions. Clinical information was gathered using our prostate biopsy database and retrospectively reviewed. Race, age, serum PSA, PSA velocity, total number of biopsies performed, total number of previous negative cores and the presence of high grade prostatic intraepithelial neoplasia (HGPIN) or atypical small acinar proliferation (ASAP) on prior biopsy were evaluated to determine if they were predictors of subsequent cancer detection. Multivariate analysis was performed using a time dependent covariate Cox proportional hazards model. RESULTS: Of the 401 men undergoing repeat prostate biopsy, 91 (22.7%) were diagnosed with prostate cancer. In total there were 180 (44.9%) black men and 221 (55.1%) white men. Cancer was diagnosed in 49 black men (27.2%) and 42 white men (19.0%, p = 0.06). On multivariate analysis serum PSA, HGPIN, ASAP and PSA velocity were predictors of prostate cancer detection (p = 0.006, <0.0001, 0.001 and 0.0004, respectively). Race was not found to be a predictor of prostate cancer detection on repeat prostate biopsy (p = 0.16). In the evaluation of clinical data for racial differences, black men had a significantly higher incidence of HGPIN on prior biopsy compared to white men (p = 0.02). Serum PSA, PSA velocity, presence of ASAP on prior biopsy, age, number of biopsies performed and number of previous negative cores were not statistically different between black and white men. CONCLUSIONS: Race is not a predictor of prostate cancer detection in men undergoing repeat prostate biopsies. With the exception of HGPIN, all other clinical parameters were similar between black and white men. Serum PSA, PSA velocity, HGPIN and ASAP were found to be significant predictors of subsequent prostate cancer detection.

Biopsy↗

PubMedDate not supplied

Predictors of psychiatric comorbidity in medical outpatients.

OBJECTIVE: Psychiatric comorbidity in medical outpatients is associated with personal suffering and reduced psychosocial functioning. Simple clinical indicators are needed to improve recognition and treatment of psychiatric comorbidity. This study aimed to identify predictors of psychiatric comorbidity for diagnostic use in busy medical settings and to describe their criterion validity. METHODS: The SCID was adopted as the independent criterion standard for the presence of a psychiatric comorbidity in 357 patients (68% female; mean age, 43 years) of six internal medicine outpatient clinics and 12 general practices. Potential indicators of psychiatric comorbidity were investigated by means of patient and physician questionnaires. Logistic regression analyses were used to identify independent predictors of psychiatric comorbidity, and their operating characteristics were determined. RESULTS: Of 18 indicators, the four most important predictors of psychiatric comorbidity were identified: a screening question for nervousness, anxiety, or worries (odds ratio, 11.9; p <.001), a screening question for depressed mood (odds ratio, 8.8; p <.001), the self-report of three or more bothersome physical symptoms (odds ratio, 3.2; p =.001), and feeling distressed by partner difficulties (odds ratio, 2.7; p =.006). The combined assessment of the four predictors resulted in positive predictive values as high as 100%, negative predictive values as high as 91%, sensitivities as high as 86%, and specificities as high as 100%. CONCLUSIONS: The identification of mental disorders in medical outpatients could be substantially improved by the knowledge and use of four easily accessible predictors. When the presence of one or more of these predictors can be confirmed, it is suggested that the patient undergo further evaluation to determine more precisely the presence and specific type of psychiatric disorder being identified.

Adult↗

PubMed2025

Gene Specific Pathogenicity Predictor for Chromatin-Remodeling BAF Complex-Associated Neurodevelopmental Disorders.

Advancements in whole genome sequencing have increased the number of variants of uncertain significance (VUS) identified in patient genomes. This has created a diagnostic bottleneck for genetic counselors tasked with sifting through these variants and determining those most likely to be causative for a patient's clinical presentation. Machine learning (ML) tools can aid in identifying pathogenic variants from VUS, but there is a need for gene-specific algorithms that predict pathogenic variants with high accuracy. To address this need, we present a workflow for developing gene-specific, ensemble-learning ML tools, that leverage outputs from other algorithms, locations of variants within the gene, and evolutionary conservation data to make a prediction of pathogenicity. Variants in SMARCA2 and SMARCA4 that are associated with rare neurodevelopmental diseases were used to screen 15 ML algorithms. A random forest learner was tuned to yield a final accuracy of 0.93 on holdout data. Generalizing this predictor to other BAF complex proteins resulted in a sharp decline in performance. We trained a final predictor for all genes in the study to create a predictor that identifies pathogenic variants in these BAF subunits with an accuracy of 0.91 on holdout data. This predictor specific to BAF complex proteins performs with higher accuracy and AUROC than any other predictor. The decline in performance when generalized to other proteins emphasizes the need for the gene-specific calibration of predictors. Our workflow for the development of such models provides a quick, computationally inexpensive route for improving the ML tools available to genetic counselors.

Journal Article↗

PubMed2006

Copeptin, a fragment of the vasopressin precursor, as a novel predictor of outcome in heart failure.

BACKGROUND: Natriuretic peptides, particularly brain natriuretic peptide (BNP), are elevated in heart failure and therefore considered to be excellent predictors of outcome. Vasopressin is also known to be related to the severity of heart disease. Copeptin--an inactive fragment of the vasopressin precursor--has not been previously investigated in the context of heart failure. MATERIALS AND METHODS: We prospectively studied 268 patients with advanced heart failure after they had been discharged from the hospital. We investigated the ability of BNP and copeptin to predict death, re-hospitalization due to heart failure, and a combination of the two endpoints. RESULTS: Over a mean follow-up period of 15.8 months (up to 24 months), 83 patients died, 122 patients experienced worsening of heart failure, and 145 patients achieved the combined endpoint. Univariate predictors of death were copeptin, BNP, age and impaired kidney function. In multivariate analysis, copeptin (chi(2) = 16, P < 0.0001) and age (chi(2) = 4, P < 0.05) were independent predictors. Univariate predictors of re-hospitalization due to heart failure were copeptin, BNP, age and impaired kidney function. Furthermore, in multivariate analysis BNP (chi(2) = 18, P < 0.0001), age (chi(2) = 11.8, P < 0.001) and copeptin (chi(2) = 4.2, P < 0.05) were found to be independent predictors. CONCLUSION: Our study is the first to show that copeptin is an excellent predictor of outcome in advanced heart failure patients. Its value is superior to that of BNP in predicting death and a combined endpoint, although BNP is still suitable for predicting chronic heart failure (CHF) re-hospitalization. Our data imply that vasopressin antagonism might be a new target to improve outcome in this population.

Aged↗

PubMed1984

Predictors of success in a cohort of medical students.

Secondary school results were compared with personality test scores as predictors of achievement in medical school in a study of a cohort of students, using simple correlation and multiple linear regression. The cohort of 151 students completed 28 courses in the 6 years. We have previously reported that the scores obtained could be reduced to five independent factors: 'physical science'; 'biological science'; 'paraclinical science'; 'basic clinical science'; and 'clinical science'. Both secondary school scores and personality test scores correlated with medical school achievement factors, but school scores correlated best with 'physical' and 'biological' science. Considering secondary school scores, English was the best predictor of 'clinical science', physics was the best predictor of 'basic clinical science' and scores obtained in physics and languages were better predictors of medical school 'biological science' than was school biology. Personality factors were better predictors of 'biological', 'paraclinical' and 'clinical science' than secondary school scores and the combined secondary school score (CSS) was the best predictor of 'physical science' and of 'overall achievement'. We conclude that incorporation of personality measurement with school academic achievement could be of value in selection procedures for applicants for medical school.

Achievement↗

PubMed2005

Clinical predictors for delirium tremens in alcohol dependence.

BACKGROUND AND AIMS: This study was aimed to find clinical predictors for developing delirium tremens (DT) in alcohol dependence. METHODS: This cohort study was retrospectively carried out among patients who were diagnosed as having alcohol dependence between January 2001 and July 2004. Fifteen parameters were compared between patients who developed DT and ones who did not. We identified clinical predictors for DT by using multivariate analysis. RESULTS: A total of one hundred and seventy-eight consecutive admission cases from 147 patients were analyzed. The mean age was 47.8 years, and 95.5% were male. Delirium tremens developed in 59 cases (33%) during hospitalization. On multiple logistic regression analysis, a previous history of DT (odds ratio (OR) 3.990; 95% CI 1.631, 9.759) and high pulse rate above 100 b.p.m. (OR 4.158; 95% CI 2.032, 8.511) were significant predictors for developing DT. When combined, DT developed in just 20.4% of cases without any predictors; however, if one predictor was present, DT developed in 45.6%, and if two predictors were present, DT developed in all cases (100%). CONCLUSIONS: A simple assessment using the past history of DT and the pulse rate, which may be easily evaluated in clinical settings, can allow physicians to readily identify the patients who are at a high risk of developing DT during an alcohol dependence period and reserve more intensive therapies for the selected cases.

Alcohol Withdrawal Delirium↗

PubMed2005

Secondary predictors of preterm labour.

In addition to primary predictors of preterm birth which are used to estimate the baseline risk of preterm birth, secondary predictors (based on examinations done during the current pregnancy) allow a more accurate assessment of the risk of preterm birth in individual women. Screening for early signs of spontaneous preterm labour has always been an important topic in obstetric care. During the last two decades, the detection of fetal fibronectin (FFN) from cervicovaginal secretions and cervical shortening diagnosed by transvaginal ultrasonography have emerged as the major secondary predictors of preterm birth. Both markers have been extensively studied and consistently shown to be strong short term predictors of preterm birth across a wide range of gestational ages. Other secondary predictors that confirm the role of intrauterine infection in the pathogenesis of preterm birth are bacterial vaginosis (BV) and elevated levels of interleukin (IL)-6, IL-8, ferritin and granulocyte colony-stimulating factor. Apart from BV, inflammatory markers are still not routinely used. The sensitivity of single markers in predicting preterm birth is only moderate and serial examinations of markers, combinations of different markers and multiple marker tests have been studied, with limited results. Studies of interventions in order to prevent preterm birth have also yielded mixed benefits, as a consequence of which the use of these markers to screen low risk pregnancies is generally not recommended. Currently, secondary predictors of preterm birth are used mainly to design new intervention studies tailored to specific high risk populations and to avoid unnecessary interventions in the management of high risk women.

Biomarkers↗

PubMed1995

Predictors of patient-perceived quality.

Larrabee's model of quality proposes a relationship between quality and value. This study tested the relationship by identifying predictors of patient-perceived quality for nursing care. Data were obtained from interviews and records of 199 adult patients. Candidate predictors of patient-perceived quality included patient goal achievement, nurse-perceived quality, and nurse goal achievement. Candidate predictors also included seven demographic, seven financial, six illness, and six hospital variables. Predictors of both patient-perceived quality global and patient-perceived quality total were pain severity on exit interview, clinic referral, unit, and patient goal achievement. Medicare nonrecipient was a predictor of patient-perceived quality global. Worry score on admission was a predictor of patient-perceived quality total. The results support the relationship between quality and value and between quality and beneficence postulated by Larrabee's model of quality. Additional investigation of these relationships in other populations and using other operationalizations of the model concepts is needed to provide further support for the model. This model is potentially useful for investigating quality in diverse cultures because the operationalization of the model concepts can be designed to reflect local, regional, or national values.

Adult↗

PubMed1996

Predictors of outcome of epilepsy surgery: multivariate analysis with validation.

PURPOSE: To identify predictors of outcome of epilepsy surgery, using the Duke experience, applying multivariate analysis and validation techniques. To compare the results of different modeling algorithms. Few previous studies have reported multivariate analysis, or validated their results. METHODS: Records of 116 patients with focal resections for intractable epilepsy from January 1, 1980 through June 30, 1989 were analyzed. Primary outcome variable was patient's condition in second postoperative year: seizure free (except auras), or not. Three predictors of biologic interest were specified a priori for confirmatory analysis. Additional predictors were considered within exploratory analysis. Logistic regression techniques were applied to assess relations with pre- and postoperative predictors. Internal validity was assessed by repeated random selection of training and validation samples, used in conjunction with bootstrap techniques. RESULTS: By using multivariate analysis, percentage of epileptic EEG activity arising from the site of resection and either imaging localization or lack of use of invasive monitoring were the only statistically significant preoperative predictors for good outcome at 2 years. Presence of seizures within 2 months of surgery was a significant postoperative predictor for a poor outcome. Adding more variables did not result in significantly improved models. Use of validation techniques reduced the degree of optimism in the predictive value of the models. CONCLUSIONS: Pooling of data from multiple institutions is needed to attain the large sample sizes needed for multivariate analysis with validation.

Adolescent↗