Cross‐sectional designs are often used to monitor the proportion of infections and other post‐surgical complications acquired in hospitals. However, conventional methods for estimating incidence proportions when applied to cross‐sectional data may provide estimators that are highly biased, as cross‐sectional designs tend to include a high proportion of patients with prolonged hospitalization. One common solution is to use sampling weights in the analysis, which adjust for the sampling bias inherent in a cross‐sectional design. The current paper describes in detail a method to build weights for a national survey of post‐surgical complications conducted in Israel. We use the weights to estimate the probability of surgical site infections following colon resection, and validate the results of the weighted analysis by comparing them with those obtained from a parallel study with a historically prospective design. Copyright © 2012 John Wiley & Sons, Ltd.

BACKGROUND:This analysis is part of a multicenter study conducted in Israel to evaluate survival of critically ill patients treated in and out of intensive care units (ICUs). OBJECTIVE:To assess the role of infection on 30-day survival among critically ill patients hospitalized in ICUs and regular wards. DESIGN:All adult inpatients were screened on four rounds for patients meeting ICU admission criteria. Retrospective chart review was used to detect presence and type of infection. Mortality was ascertained from day of meeting study criteria to 30 days thereafter. ANALYSIS:The effect of infection on mortality among patients, treated in and out of the ICU, was compared using Kaplan Meier survival curves. Multivariate Cox models were constructed to adjust interdepartmental comparisons for case-mix differences. RESULTS:Of 641 critically ill patients identified, 36.8% already had an infection on day 0. An additional 40.2% subsequently developed a new infection during the follow-up period, ranging from 64.6% in the ICU to 31.5% in regular wards (p < .001). Resistant infections were more prevalent in ICUs. Infection was independently associated with an increase in mortality, regardless of whether the patient was admitted to the ICU. There was no difference in the adjusted risk of mortality associated with an infection diagnosed on day 0 vs. an infection diagnosed later. Risk of dying was similar in resistant and nonresistant infections. Adjusting for infections, survival of ICU patients was better relative to patients in regular wards (adjusted hazard ratio = 0.7). Among the different types of infection, risk of mortality from pneumonia was significantly lower in ICUs relative to regular wards. There was a protective effect in ICUs among noninfected patients. CONCLUSION:The risk of acquiring a new infection is greater in the ICU. However, risk of mortality among ICU patients was lower for the most serious infections and for those without any infection.

Objective:A lack of intensive care units beds in Israel results in critically ill patients being treated outside of the intensive care unit. The survival of such patients is largely unknown. The present study's objective was to screen entire hospitals for newly deteriorated patients and compare their survival in and out of the intensive care unit. Design:A priori developed intensive care unit admission criteria were used to screen, during 2 wks, the patient population for eligible incident patients. A screening team visited every hospital ward of five acute care hospitals daily. Eligible patients were identified among new admissions in the emergency department and among hospitalized patients who acutely deteriorated. Patients were followed for 30 days for mortality regardless of discharge. Setting:Five acute care hospitals. Patients:A total of 749 newly deteriorated patients. Interventions:None. Measurements and Main Results:Crude survival of patients in and out of the intensive care unit was compared by Kaplan-Meier curves, and Cox models were constructed to adjust the survival comparisons for residual case-mix differences. A total of 749 newly deteriorated patients were identified among 44,000 patients screened (1.7%). Of these, 13% were admitted to intensive care unit, 32% to special care units, and 55% to regular departments. Intensive care unit patients had better early survival (0–3 days) relative to regular departments (p = .0001) in a Cox multivariate model. Early advantage of intensive care was most pronounced among patients who acutely deteriorated while on hospital wards rather than among newly admitted patients. Conclusions:Only a small proportion of eligible patients reach the intensive care unit, and early admission is imperative for their survival advantage. As intensive care unit benefit was most pronounced among those deteriorating on hospital wards, intensive care unit triage decisions should be targeted at maximizing intensive care unit benefit by early admitting patients deteriorating on hospital wards.

BACKGROUND:There is a dearth of organs for liver transplantation in Israel. Enhancing our understanding of factors affecting graft survival in this country could help optimize the results of the transplant operation. OBJECTIVES:To report 3 years national experience with orthotopic liver transplantation, and to evaluate patient and perioperative risk factors that could affect 1 year graft survival. METHODS:The study related to all 124 isolated adult liver transplantations performed in Israel between October 1997 and October 2000. Data were abstracted from the medical records. One-year graft survival was described using the Kaplan-Meier survival curve and three multivariate logistic regression models were performed: one with preoperative case-mix factors alone, and the other two with the addition of donor and operative factors respectively. RESULTS:Of the 124 liver transplantations performed, 32 failed (25.8%). The 1 year survival was lower than rates reported from both the United States and Europe but the difference was not significant. Of the preoperative risk factors, recipient age > 60 years, critical condition prior to surgery, high serum bilirubin and serum hemoglobin < or = 10 g/dl were independently associated with graft failure, adjusting for all the other factors that entered the logistic regression equation. Extending the model to include donor and operative factors raised the C-statistic from 0.79 to 0.87. Donor age > or = 40, cold ischemic time > 10 hours and a prolonged operation (> 10 hours) were the additional predictors for graft survival. A MELD score of over 18 was associated with a sixfold increased risk for graft failure (odds ratio = 6.5, P = 0.001). CONCLUSIONS:Graft survival in Israel is slightly lower than that reported from the U.S. and Europe. Adding donor and operative factors to recipient characteristics significantly increased our understanding of 1 year survival of liver grafts.

Objectives: The goal of this paper was to examine the added effect of operative and post-operative variables on 30 days mortality, in addition to patients' case-mix factors. Setting and design: A prospective study of 4835 patients, 95% of all Israeli patients who underwent coronary artery bypass grafting (CABG) in 1994. Information related to risk of death was collected at admission to hospital (preceding the operation), at time of the operation and in the immediate post-operative period. Deaths were independently ascertained. Method: Data collectors followed every patient from admission to discharge. Sequential logistic models were constructed for the ‘case-mix’, ‘operative’ and the ‘post-operative’ periods in chronological order. Each model incorporated and adjusted for the risk estimated at the previous point in time, by forcing individual risk scores. Results: Significant pre-operative risk factors for 30 days mortality, in the case- mix model included mainly severity of illness characteristics, such as, left ventricular dysfunction and emergency admission, (c-statistic 78.8%). Model 2 (the ‘operation’ model) included in addition to the case-mix score, excessive duration of the operation per graft, bleeding, etc. (c-statistic 85.3%). The post-operative model showed the added effect of the post-operative factors such as low haemoglobin, additional surgery, and excessive time on respirator, (c-statistic 92.4%). Conclusions: The sequential analysis was an efficient method for updating patients' risk over time, where the number of events was small, relative to the number of risk factors. The addition of peri-operative factors increased significantly the predictive power of the model, adding clinical insights to the role of the hospital experience on 30 days mortality.

In a prospective follow-up of 2846 patients who underwent hernia repair in 22 general surgery departments in Israel, factors affecting early or late infections were explored. Risk factors included inherent patient characteristics such as old age, ethnic group, and type of hernia prior to the surgery. Patient management factors included duration of the operation, use of urinary catheters, and use of drains. Of the 12 variables studied, only three had a constant effect during the entire 30-day follow-up. The other factors affected the occurrence of either early or late infections, but not both. For example, patients undergoing long operations, or from ethnic minorities, had a high rate of early infection, while those with special wound treatment (such as evacuation of hematomas) had high rates of late infection. It is postulated that factors present at the time of the operative incision tend to "cause" early infections, while factors that accumulate over time, or develop after leaving the operating theater, tend to affect late infections.

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