Biomedical subjects

Jason S Haukoos

Publications and source records attributed to Jason S Haukoos.

23 records · Page 2Linked to original sources

PubMed2003

Carcinoembryonic antigen and albumin predict survival in patients with advanced colon and rectal cancer.

HYPOTHESIS: Patients with stage IV colon or rectal cancer at initial diagnosis have characteristics that will predict subsequent survival time. DESIGN: Retrospective cohort study. SETTING: Urban county teaching hospital providing tertiary care. PATIENTS: Patients who came to the study institution with stage IV colon or rectal cancer between 1991-1999. MAIN OUTCOME MEASURE: Survival duration (days) after diagnosis. RESULTS: One hundred five patients were identified, with a median survival of 225 days (interquartile range, 72-688 days). Univariate analysis identified carcinoembryonic antigen (CEA) and albumin (ALB) as possible predictors for survival. Classification and regression tree analysis, a form of binary recursive partitioning, was used to identify optimal cut points for CEA (275 ng/mL) and ALB (2.7 g/dL) levels. Based on the cut points, patients were stratified into the following groups: (1) low CEA, high ALB; (2) low CEA, low ALB; (3) high CEA, high ALB; and (4) high CEA, low ALB. The median survival times for the first group and the fourth group were 287 days (interquartile range, 150-851 days) and 39 days (interquartile range, 14-168 days), respectively. A Kaplan-Meier analysis was performed, and a statistically significant difference was identified across all strata (P =.004). Additionally, groups 1 and 4 demonstrated the largest overall survival difference (P<.001). CONCLUSIONS: Patients with stage IV colon and rectal cancer with a CEA level greater than or equal to 275 ng/mL and an ALB level less than 2.7 g/dL had a significantly shorter survival time. Conversely, patients with an ALB level greater than or equal to 2.7 g/dL and a CEA level less than 275 ng/mL had a longer survival time.

Adult↗

PubMed2003

An assessment of the severity of recurrent appendicitis.

BACKGROUND: This study examines the clinical characteristics of patients who developed recurrent appendicitis after previous nonoperative management of perforated appendicitis. METHODS: Retrospective chart review was performed, and data from the recurrent and initial episode of appendicitis were collected. RESULTS: In all, 237 patients from 1989 to 2001 were managed nonoperatively for perforated appendicitis and 32 (14%) were readmitted for recurrent appendicitis. Median white blood cell count at recurrence was 9.5 (interquartile range [IQR]: 6.6 to 13.2] versus 13.1 [IQR: 10.8 to 16.1] at initial presentation (P = 0.002). Maximum temperature was 98.6 degrees F [IQR: 98.2 to 100.5] at recurrence versus 100.3 degrees F [IQR: 99.5 to 101.5] (P = 0.008). Median time for intravenous antibiotics use was 3 [IQR: 3 to 7] days at recurrence versus 6 [IQR: 4 to 8] days initially (P = 0.01). Inpatient stay was also shorter; median length was 6 [IQR: 3 to 8] days compared with 7 [IQR: 5 to 9] days at initial presentation (P = 0.02). CONCLUSIONS: Patients managed nonoperatively for perforated appendicitis who later developed recurrent appendicitis exhibited a milder clinical course at recurrence. Elective interval appendectomy may be reserved until a recurrent episode.

Adult↗

PubMed2003

Volume regression of abdominal aortic aneurysms and its relation to successful endoluminal exclusion.

OBJECTIVES: Evaluating the success of endoluminal repair of abdominal aortic aneurysms (AAAs) is frequently based on diameter measurements and determining the presence of endoleaks. The use of three-dimensional volumetric data and observation of morphologic changes in the aneurysm and device have been proposed to be more appropriate for postdeployment surveillance. The purpose of this study was to analyze the long-term volumetric and morphologic data of 161 patients who underwent endovascular AAA exclusion and to assess the utility of volume measurements for determining successful AAA repair. METHODS: Patients with spiral computed tomography scans obtained preoperatively, within the first postoperative month, at 6 months, and annually thereafter, were included in this analysis. Computerized interactive three-dimensional reconstruction of each AAA scan was performed. Total aneurysm sac volume was measured at each time interval (mean preoperative volume 169.0 +/- 78.5 mL), and the significance of volume changes was determined by mixed linear modeling, a form of repeated measures analysis, to account for longitudinal data clustered at the individual level. Sixty-two patients (38%) developed endoleaks at some time during follow-up-15 type I leaks, 45 type II leaks, and 2 type III leaks. The patients with type I and type III leaks were treated with cuffs, and the type II leaks were treated either with observation, side-branch embolization, or required open conversion. RESULTS: Aneurysm sac volume increased slightly at 1-month follow-up (+3.3%), and then decreased steadily to -12.9% at 5 years (P <.0001). This effect remained unchanged after controlling for the three device types used in our study population. Patients who did not exhibit an endoleak (n = 99) showed a significant decrease in aneurysm volume across the entire follow-up duration when compared with those who did exhibit an endoleak (n = 62) (P <.0001). The presence of a 10% or greater decrease in volume at 6 months demonstrated a sensitivity of 64%, a specificity of 95%, a positive predictive value of 95%, a negative predictive value of 62%, and an accuracy of 75% for predicting primary clinical success defined by successful deployment of the device; freedom from aneurysm- or procedure-related death; freedom from endoleak, rupture, migration, or device malfunction; or conversion to open repair. CONCLUSIONS: Volumetric analysis may be used to predict successful endoluminal exclusion of AAAs. Volume regression appears to be device-independent and should be expected in most clinically successful cases. The presence of volume increases in the first 6 months is suspicious for an endoleak that is pressurizing the aneurysm sac and heralds the need for closer evaluation and possible intervention. A volume decrease of 10% or greater at 6 months and continuing regression over time is associated with successful endovascular repair.

Aged↗

PubMed2003

Is the ACLS score a valid prediction rule for survival after cardiac arrest?

UNLABELLED: The ACLS (advanced cardiac life support) Score was previously developed to predict survival from out-of-hospital cardiac arrest. Whether the arrest was witnessed, initial cardiac rhythm, performance of bystander cardiopulmonary resuscitation (CPR), and the response time of the paramedic unit were determined to be predictive of survival. However, the ACLS Score has not been validated in other emergency medical services systems. OBJECTIVES: The purpose of this study was to externally validate the ACLS Score in one patient population. METHODS: This was a retrospective cohort study performed at an urban county teaching hospital. The study population consisted of consecutive adult patients treated for out-of-hospital, nontraumatic cardiac arrest, and transported to the authors' institution between November 1, 1994, and September 30, 2001. Patient records for all cardiac arrests during the study period were reviewed. Study variables included witnessed arrest, initial arrest rhythm, bystander CPR, paramedic response time, and survival to hospital discharge. Predicted probability of survival to hospital discharge was calculated for each patient using the ACLS Score. The overall predicted and observed survival rates were compared using Flora's Z score. The Hosmer-Lemeshow test was used to evaluate the model's goodness-of-fit over a range of survival probabilities. RESULTS: Of 754 cardiac arrest patients enrolled in the study period, 575 (76%) patients had documentation that allowed scoring using the ACLS Score. Twenty-five (4%) patients survived to hospital discharge. The predicted number of survivors based on the ACLS Score was 104 (18%), yielding a Flora's Z statistic of -4.46 (p < 0.0001). After categorizing predicted survival probabilities into four categories, the resulting Hosmer-Lemeshow statistic was 210 (p << 10(-6)). Both goodness-of-fit statistics demonstrated extremely poor fit of the model. A receiver operating characteristic (ROC) curve was created, yielding an area under the ROC curve of 0.33 (95% CI = 0.19 to 0.47), signifying extremely poor discrimination. CONCLUSIONS: The previously published ACLS Score was not valid when applied to an external cohort of out-of-hospital cardiac arrest patients. An externally valid model is needed to predict survival to hospital discharge following out-of-hospital cardiac arrest.

Advanced Cardiac Life Support↗

PubMed2002

Emergency department triage of patients infected with HIV.

OBJECTIVE: The emergency department (ED) and HIV specialty clinics are primary sources of care for persons infected with HIV. HIV disease may be complicated by vague and complex symptomatology, and determining the degree of illness at triage is often difficult. The goals of this project were to characterize the ED presentation of HIV-related conditions, to develop a clinical decision rule to triage HIV-infected patients, and to validate the rule in clinical practice. METHODS: The study population consisted of ambulatory patients with self-reported HIV infection who presented for care to the ED of a 553-bed public hospital that serves a medically indigent, minority population. An Illness Severity Instrument was developed by an expert panel to serve as the criterion standard for defining medical urgency for HIV-infected patients presenting to the ED for care. Two phases of the study were conducted. Data from the first phase, a noninterventional cohort study, were used to develop a clinical decision rule for the ED triage of HIV-infected patients. The second phase was a prospective validation of the clinical decision rule. RESULTS: During phase I, data from 542 patient visits were collected. Data from 441 (81%) patient visits were used in a classification and regression tree (CART) analysis to produce a decision rule, the Clinical Triage Instrument. During phase II, the prospective validation of the Clinical Triage Instrument, 156 patient visits occurred. Of these, 88 (56%) patient visits were triaged using the Clinical Triage Instrument and could be scored using the Illness Severity Instrument. The Clinical Triage Instrument accurately triaged 45 [51%; 95% confidence interval (95% CI) = 40% to 62%] patient visits, undertriaged 11 (13%; 95% CI = 6% to 21%) patient visits, and overtriaged 32 (36%; 95% CI = 26% to 47%) patient visits. Sensitivities and specificities for determining emergent, urgent, and nonurgent medical conditions by the Clinical Triage Instrument were 56% (95% CI = 31% to 75%) and 84% (95% CI = 74% to 92%), 71% (95% CI = 55% to 84%) and 39% (95% CI = 25% to 55%), and 18% (95% CI = 6% to 37%) and 93% (95% CI = 84% to 98%), respectively. The positive and negative predictive values for determining an emergent medical condition using the Clinical Triage Instrument were 48% (95% CI = 26% to 70%) and 88% (95% CI = 78% to 95%), respectively. The positive and negative predictive values for determining a nonurgent medical condition using the Clinical Triage Instrument were 56% (95% CI = 21% to 86%) and 71% (95% CI = 60% to 81%), respectively. CONCLUSIONS: The Clinical Triage Instrument was not sufficiently accurate for clinical use. Until accurate and reliable triage methods are developed, all patients infected with HIV who present to the ED for care should receive timely evaluation and care.

Adult↗