Superior predictive ability for death of a basic metabolic profile risk score

Predicting postdischarge hospital-associated venous thromboembolism among medical patients using a validated mortality risk score derived from common biomarkers

BACKGROUND

Discharged medical patients are at risk for venous thromboembolism (VTE). It is difficult to identify which discharged patients would benefit from extended duration thromboprophylaxis. The Intermountain Risk Score is a prediction score derived from discrete components of the complete blood cell count and basic metabolic panel and is highly predictive of 1-year mortality. We sought to ascertain if the Intermountain Risk Score might also be predictive of 90-day postdischarge hospital-associated VTE (HA-VTE).

METHODS

We applied the Intermountain Risk Score to 60 064 medical patients who survived 90 days after discharge and report predictiveness for HA-VTE. Area under the receiver operating curve analyses were performed. We then assessed whether the Intermountain Risk Score improved prediction of 2 existing VTE risk assessment models.

RESULTS

The Intermountain Risk Score poorly predicted HA-VTE (area under the curve = 0.58; 95% confidence interval [CI], 0.56-0.60). Each clinical risk assessment model was superior to the Intermountain Risk Score (UTAH area under the curve, 0.63; Kucher area under the curve, 0.62; Intermountain Risk Score area under the curve, 0.58; P < .001 for each comparison). Adding the Intermountain Risk Score to these scores did not substantially improve the performance of either risk assessment model (UTAH + Intermountain Risk Score, 0.65; Kucher + Intermountain Risk Score, 0.64).

CONCLUSION

The Intermountain Risk Score demonstrated poor predictiveness for HA-VTE when compared to existing risk assessment models. Adding the Intermountain Risk Score to existing risk assessment models did not improve upon either risk assessment model alone to justify the added complexity.

Predictive value of a profile of routine blood measurements on mortality in older persons in the general population: the Leiden 85-plus Study

Background

Various questionnaires and performance tests predict mortality in older people. However, most are heterogeneous, laborious and a validated consensus index is not available yet. Since most older people are regularly monitored by laboratory tests, we compared the predictive value of a profile of seven routine laboratory measurements on mortality in older persons in the general population with other predictors of mortality; gait speed and disability in instrumental activities of daily living (IADL).

Methodology/Principal Findings

Within the Leiden 85-plus Study, a prospective population-based study, we followed 562 participants aged 85 years for mortality over five years. At baseline (age 85 years) high-density lipoprotein cholesterol, albumin, alanine transaminase, hemoglobin, creatinin clearance, C-reactive protein and homocysteine were measured. Participants were stratified based on their number of laboratory abnormalities (0, 1, 2–4 and 5–7). The predictive capacity was compared with gait speed (6-meter walking test) and disability in IADL (Groningen Activity Restriction Scale) by C-statistics. At baseline, 418 (74%) 85-year old participants had at least one laboratory abnormality. All cause mortality risk increased with increasing number of laboratory abnormalities to a hazard ratio of 5.64 [95% CI 3.49–9.12] for those with 5–7 laboratory abnormalities (p<0.001) compared to those without abnormalities. The c-statistic was 0.66 [95% CI 0.59–0.69], similar to that of gait speed and disability in IADL.

Conclusions/Significance

In the general population of oldest old, the number of abnormalities in seven routine laboratory measurements predicts five-year mortality as accurately as gait speed and IADL disability.

Panoptic total cardiovascular risk prediction using all predictors versus optimized risk assessment using variable subsets

Cardiovascular disease remains the primary cause of mortality and morbidity in the developed world. Risk scores can provide clinical risk stratification and many exist for use in cardiovascular disease prevention and treatment. Cardiovascular risk scores predict mortality, coronary heart disease and other vascular disease using risk predictors such as patient age, sex, BMI, smoking history, cholesterol level, blood pressure, glucose level or diabetes diagnosis, family history of cardiovascular disease and creatinine. While the risk scores in existence are excellent for risk stratification, actual use in a clinical environment is lagging behind the rate of new risk score creation. Future research should focus on how to utilize risk scores most effectively and efficiently in clinical practice.

Use of desirability functions to evaluate health status in patients with cirrhosis

BACKGROUND & AIMS

There is a need for methods that provide a quantitative assessment of a patient's global health status, especially as regards quality of life, prognosis, and impact of therapeutic interventions. We propose that desirability functions, widely used in industrial quality control, can be adapted to obtain a numerical "wellness" score, incorporating numerous easily measured clinical parameters, that reflects a patient's overall clinical status and prognosis on a scale from 0 (worst) to 1 (best).

METHODS

In this pilot study, we used this approach to develop a Cirrhosis Relative Wellness Index for use with patients with liver disease. We relied on expert opinion to select 10 parameters of interest and to determine the desirability function for each parameter. A composite index was then developed and tested using data from 109 cirrhotic subjects enrolled in the North American Study for the Treatment of Refractory Ascites (NASTRA). The index was independently validated using a separate database obtained from a review of records of 1342 cirrhotic patients referred for liver transplantation candidacy in the Veterans Health System between 1997 and 2008.

RESULTS

In both datasets, the Cirrhosis Relative Wellness Index was significantly associated with transplant-free survival using either a proportional hazards model or a logrank test (where the index was dichotomised).

CONCLUSION

Desirability function modelling represents a promising new approach to quantitatively estimating global health status.