ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo develop models in the Mortality Probability Model (MPM II) system to estimate the probability of hospital mortality at 48 and 72 hrs in the intensive care unit (ICU), and to test whether the 24-hr Mortality Probability Model (MPM24), developed for use at 24 hrs in the ICU, can be used on a daily basis beyond 24 hrs.DesignA prospective, multicenter study to develop and validate models, using a cohort of consecutive admissions.SettingSix adult medical and surgical ICUs in Massachusetts and New York adjusted to reflect 137 ICUs in 12 countries.PatientsConsecutive admissions (n = 6,290) to the Massachusetts/New York ICUs were studied. Of these patients, 3,023 and 2,233 patients remained in the ICU and had complete data at 48 and 72 hrs, respectively. Patients <18 yrs of age, burn patients, coronary care patients, and cardiac surgical patients were excluded.Outcome MeasureVital status at the time of hospital discharge.ResultsThe models consist of five variables measured at the time of ICU admission and eight variables ascertained at 24-hr intervals. The 24-hr model demonstrated poor calibration and discrimination at 48 and 72 hrs. The newly developed 48− and 72-hr models—MPM48and MPM72—contain the same 13 variables and coefficients as the MPM24. The models differ only in their constant terms, which increase in a manner that reflects the increasing probability of mortality with increasing length of stay in the ICU. These constant terms were adjusted by a factor determined from the relationship between the data from the six Massachusetts and New York ICUs and a more extensive data set, from which the ICU admission Mortality Probability Model (MPM0) and MPM24were developed. This latter data set was assembled from ICUs in 12 countries. The MPM48and MPM72calibrated and discriminated well, based on goodness-of-fit tests and area under the receiver operating characteristic curve.ConclusionsModels developed for use among ICU patients at one time period are not transferable without modification to other time periods. The MPM48and MPM72calibrated well to their respective time periods, and they are intended for use at specific points in time. The increasing constant terms and associated increase in the probability of hospital mortality exemplify a common clinical adage that if a patient's clinical profile stays the same, he or she is actually getting worse. (Crit Care Med 1994; 22:1351–1358)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo develop daily prognostic estimates for individual patients treated in adult intensive care units (ICU).DesignProspective, multicenter, inception cohort analysis.SettingForty-two ICUs at 40 U.S. hospitals with >200 beds including 20 ICUs in tertiary care centers with major teaching activities.PatientsA consecutive sample of 17,440 ICU admissions.Measurements and Main ResultsA series of multivariate equations were developed using the patient's primary reason for ICU admission, age, chronic health status, treatment before ICU admission, admission Acute Physiology Score, current day Acute Physiology Score, and change between the current and previous day's Acute Physiology Score. The equations were used to create daily risk predictions and cross-validated within the 17,440-patient sample. The single most important factor determining daily risk of hospital death during each of the initial 7 days of ICU care was the current day's Acute Physiology Score of the Acute Physiology and Chronic Health Evaluation (APACHE) III score. The admission Acute Physiology Score and change from previous to current day's Acute Physiology Score were also important, as were ICU admission diagnosis, age, chronic health status, and treatment before ICU admission. Equations incorporating these risk factors had receiver operating characteristics areas ranging from 0.9 on the first ICU day to 0.84 for patients remaining in the ICU for 7 days. The percent of cases with cross-validated predicted risks over 90% increased from 2.3% (n = 406) of cases on day 1 to 9% of all patients remaining in the ICU on ICU day 7 (n = 218). The 1,033 patients who had a daily risk estimate of >90% during any of their initial 7 ICU days had a 90% mortality rate and represented 47% of all ICU deaths and 31% of the total number of hospital deaths.ConclusionsEquations using initial and repeated physiologic measurements provide a high degree of explanatory power for subsequent hospital mortality rate. These daily prognostic estimates deserve evaluation for their potential role in improving the process and outcome from clinical decision-making. (Crit Care Med 1994; 22:1359–1372)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo develop predictive equations, estimating the probability that an individual intensive care unit (ICU) patient will receive life support within the next 24 hrs.DesignProspective, multicenter, inception cohort study.SettingForty-two ICUs in 40 U.S. hospitals, including 26 that were randomly selected and 14 volunteer hospitals, primarily university or large tertiary care centers.PatientsA consecutive sample of 17,440 ICU admissions.InterventionsNone.Measurements and Main ResultsA series of multivariate equations were developed to create daily estimates of probability of life support in the next 24 hrs. These equations used demographic, physiologic, and treatment information obtained at the time of ICU admission and during the first 7 ICU days. The most important determinants of next day risk for life support were the current day's therapy and Acute Physiology Score of the Acute Physiology and Chronic Health Evaluation (APACHE) III score. Other predictor variables included diagnosis, age, chronic health status, emergency surgery, previous day Acute Physiology Score, and hospital stay and location before ICU admission. The cross-validated ICU day 1, 2, and 3 predictive equations had receiver operating characteristic areas of 0.90. Survival, ICU readmission rate, and the number and type of therapies received by patients predicted at <10% risk for active treatment suggest that discharge of patients meeting these criteria to an intermediate care unit or hospital ward could reduce ICU bed demand without compromising patient safety.ConclusionsAccurate, objective predictions of next day risk for life support can be developed, using readily available patient information. Supplementing physician judgment with these objective risk assessments deserves evaluation for the role of these assessments in enhancing patient safety and improving ICU resource utilization. (Crit Care Med 1994; 22:1373–1384)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectivesTo present an approach for assessing intensive care unit (ICU) performance which takes into account both economic and clinical performance while adjusting for severity of illness. To present a graphic display which permits comparisons among a group of hospitals.DesignA multicenter, inception cohort study.SettingTwenty-five ICUs in U.S. hospitals that participated in the European and North American Study of Severity Systems for ICU Patients.PatientsConsecutive patients (n = 3,397) admitted to ICUs in participating hospitals between September 30, 1991 and December 27, 1991. Excluded were coronary care patients, burn patients, cardiac surgery patients and patients aged <18 yrs.Measurements and Main ResultsThe clinical performance index is the difference between observed hospital survival rate and survival rate predicted by the Mortality Probability Model measuring severity of illness at ICU admission. The economic performance (resource use) measure is a length of stay index, Weighted Hospital Days, which weights ICU days more heavily than non-ICU days. The economic performance index is the difference between actual mean resource use and the resource use predicted by a regression including severity of illness and percent of surgical patients. Both the clinical and economic performance indices are standardized to show how far a particular hospital is from the overall mean and are graphed together. Most of the 25 hospitals lie within 1 SD of the mean on both clinical and economic performance scales. The graph makes it easy to identify those hospitals that are outside this range. There is no evidence of a tradeoff between high clinical performance and high economic performance; i.e., it is possible to achieve both.ConclusionsCross-indexing of clinical and economic ICU performance is easy to calculate. It has potential as a research and evaluation tool used by physicians, hospital administrators, payers, and others. (Crit Care Med 1994; 22:1385–1391

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo compare the ability of two methods—Acute Physiology and Chronic Health Evaluation (APACHE II) and Mortality Prediction Model (MPM)—to predict hospital outcome for a large group of intensive care patients from Britain and Ireland.DesignProspective, multicenter, cohort study.SettingTwenty-six general intensive care units in Britain and Ireland.PatientsA total of 8,724 patients admitted to the study.InterventionsNone.Measurements and Main ResultsProbabilities of hospital death for patients were estimated by applying APACHE II and MPM. Predicted risks of hospital death were compared with observed outcomes using four methods of assessing the overall goodness of fit. APACHE II performed better than MPM; the calibration curve for APACHE II lay closer to the line of perfect predictive ability. Lemeshow-Hosmer chi-square statistics were 81 and 57 for APACHE II, and 2515 and 1737 for MPM. The overall correct classification rate for APACHE II was 79%, and this classification rate was 74% for MPM, applying a decision criterion of 50%. The area under the receiver operating characteristic curve was 0.83 with APACHE II and 0.74 with MPM. Even after modifications to the MPM for the assessment of coma, the performance of APACHE II was superior.ConclusionsAPACHE II demonstrated a higher degree of overall goodness of fit, which was superior to MPM for groups of intensive care patients from Britain and Ireland. (Crit Care Med 1994; 22:1392–1401)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo evaluate the use of daily Acute Physiology and Chronic Health Evaluation (APACHE) II scoring in the prediction of individual mortality rates for intensive care unit (ICU) patients.DesignA prospective study of consecutive patients admitted to four university-affiliated ICUs.SettingMedical-surgical ICUs of four tertiary care academic hospitals.PatientsDaily data from 3,350 consecutive ICU admissions, excluding postoperative cardiac patients, were collected from January to December 1991.Measurements and Main ResultsDaily APACHE II scores were calculated for all patients and correlated with both ICU and hospital mortality. The ability of an absolute level or a predetermined algorithm, based on these scores, to predict mortality was examined. Day 1 APACHE II scores ranged from 0 to 55 (mean 18). We were unable to replicate the suggestion by Chang et al. that 100% hospital mortality was predicted by the following APACHE II scores: a) >35 at admission; b) 30 to 35 at admission, with a decrease of ≤3 from day 1 to day 2; or c) >27 on any day, with an increase of >2 from the previous day. We were unable to adjust these criteria to avoid a false prediction of death with any remaining useful sensitivity. Mortality rates of 158 (69%) deaths per 229 patients, 68 (62%) deaths per 110 patients, and 110 (48%) deaths per 230 patients were obtained, respectively, for these criteria.ConclusionsAdmission or daily APACHE II scores do not predict individual patient mortality. The adjustments needed in the algorithm that was used to avoid a false prediction of death render sensitivity so low that it would be impractical to limit therapy on this basis alone. (Crit Care Med 1994; 22:1402–1405)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo modify the Therapeutic Intervention Scoring System (TISS) for intermediate and floor care nursing units.DesignProspective study.SettingUniversity teaching hospital.PatientsIn-patients on medical and surgical nursing units.InterventionsNone.Measurements and Main ResultsIntermediate TISS retains 49 Original TISS items, adds 26 Intermediate TISS items, deletes 18 Original TISS items, and reweights 10 Original TISS items. Intermediate TISS score sums up the monitoring and therapeutic modalities used within the previous 24 hrs, each of which is assigned a weighted score from 1 to 4 points. A total of 3,073 patient days for 1,013 patients were simultaneously scored for Original TISS and Intermediate TISS over a 4-month period. A random sample of 435 patients was examined to identify those patients for whom Intermediate TISS added information over and above that obtained from Original TISS.Original TISS and Intermediate TISS correlated well, regression equation: Intermediate TISS = 4.4 + 1.4 x Original TISS (r2= .83). We identified two groups of outliers, together constituting 96 of 435 patients: a) patients whose sum of new TISS items was unusually high relative to the sum of old TISS items included those patients with diabetes mellitus, those patients receiving serial electrocardiograms to rule out myocardial infarction and patients requiring cardiac or pulmonary therapy; b) those patients whose sum of new TISS items was low relative to the sum of old TISS items were largely surgical patients outside the intensive care unit (ICU), in whom Original TISS still worked well because it had been designed for surgical ICU patients.ConclusionsIntermediate TISS is useful to score medical patients receiving intermediate or floor care in non-ICU nursing units within the hospital. (Crit Care Med 1994; 22:1406–1411)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID

摘要:

ObjectiveTo determine the applicability of the Acute Physiology and Chronic Health Evaluation (APACHE) II scoring system in predicting outcome in a subgroup of critically ill obstetrical patients.DesignRetrospective data collection.SettingA multidisciplinary intensive care unit (ICU) in a university hospital.PatientsAll patients (n = 1,670) admitted for >24 hrs to the ICU during an 8-yr period, of whom 58 were obstetrical patients and 120 were nonobstetrical young women.Measurements and Main ResultsThe mean APACHE II score in the obstetrical group was 11, with a mortality risk of 16.6%. In this group, the mortality ratio, which is the ratio between actual and predicted mortality rate, was low (0.416) and significantly (p= .021) different from the expected mortality ratio of 1. The mean APACHE II score in the group of nonobstetrical young women was 10, with a mortality risk of 10.17%. In all nonobstetrical ICU patients including all the admitted patients excluding the obstetrical patients, the mean APACHE II score was 15, with a mortality risk of 24.18%. The mortality ratio in the nonobstetrical young women group and in the nonobstetrical ICU patient group was 0.986 and 1.006, respectively, which was nonsignificantly different from the expected mortality ratio.ConclusionsObstetrical patients requiring intensive care in our ICU had a better outcome than predicted, as expressed by a low mortality ratio. Various explanations that may be applicable to any subgroup of critically ill patients with a different mortality ratio are presented. The subgroup itself may be uniquely different, similar to our obstetrical patients with their physiologic changes of pregnancy. Another explanation may relate to an improvement in care of the subgroup and therefore a better outcome. (Crit Care Med 1994; 22:1412–1414)

ISSN:0090-3493    

出版商:OVID    

年代:1994

数据来源: OVID