Mild hypoglycemia is strongly associated with increased intensive care unit length of stay

Background: Hypoglycemia is associated with increased mortality in critically ill patients. The impact of hypoglycemia on resource utilization has not been investigated. The objective of this investigation was to evaluate the association of hypoglycemia, defined as a blood glucose concentration (BG) <70 mg/dL, and intensive care unit (ICU) length of stay (LOS) in three different cohorts of critically ill patients. Methods: This is a retrospective investigation of prospectively collected data, including patients from two large observational cohorts: 3,263 patients admitted to Stamford Hospital (ST) and 2,063 patients admitted to three institutions in The Netherlands (NL) as well as 914 patients from the GLUCONTROL trial (GL), a multicenter prospective randomized controlled trial of intensive insulin therapy. Results: Patients with hypoglycemia were more likely to be diabetic, had higher APACHE II scores, and higher mortality than did patients without hypoglycemia. Patients with hypoglycemia had longer ICU LOS (median [interquartile range]) in ST (3.0 [1.4-7.1] vs. 1.2 [0.8-2.3] days, P <0.0001), NL (5.2 [2.6-10.3] vs. 2.0 [1.3-3.2] days, P <0.0001), and GL (9 [5-17] vs. 5 [3-9] days, P <0.0001). For the entire cohort of 6,240 patients ICU LOS was 1.8 (1.03.3) days for those without hypoglycemia and 3.0 (1.5-6.7) days for those with a single episode of hypoglycemia (P <0.0001). This was a consistent finding even when patients were stratified by severity of illness or survivor status. There was a strong positive correlation between the number of episodes of hypoglycemia and ICU LOS among all three cohorts. Conclusions: This multicenter international investigation demonstrated that hypoglycemia was consistently associated with significantly higher ICU LOS in heterogeneous cohorts of critically ill patients, independently of severity of illness and survivor status. More effective methods to prevent hypoglycemia in these patients may positively impact their cost of car

Computer-assisted glucose control in critically ill patients

Objective: Intensive insulin therapy is associated with the risk of hypoglycemia and increased costs of material and personnel. We therefore evaluated the safety and efficiency of a computer-assisted glucose control protocol in a large population of critically ill patients. Design and setting: Observational cohort study in three intensive care units (32 beds) in a 1,300-bed university teaching hospital. Patients: All 2,800 patients admitted to the surgical, neurosurgical, and cardiothoracic units; the study period started at each ICU after implementation of Glucose Regulation for Intensive Care Patients (GRIP), a freely available computer-assisted glucose control protocol. Measurements and results: We analysed compliance in relation to recommended insulin pump rates and glucose measurement frequency. Patients were on GRIP-ordered pump rates 97% of time. Median measurement time was 5 min late (IQR 20 min early to 34 min late). Hypoglycemia was uncommon (7% of patients for mild hypoglycemia, <3.5 mmol/l; 0.86% for severe hypoglycemia, <2.2 mmol/l). Our predefined target range (4.0 - 7.5 mmol/l) was reached after a median of 5.6h (IQR 0.2 - 11.8) and maintained for 89% (70 - 100%) of the remaining stay at the ICU. The number of measurements needed was 5.9 (4.8 - 7.3) per patient per day. In-hospital mortality was 10.1%. Conclusions: Our computer-assisted glucose control protocol provides safe and efficient glucose regulation in routine intensive care practice. A low rate of hypoglycemic episodes was achieved with a considerably lower number of glucose measurements than used in most other schemes

Hypoglycemia in Non-Diabetic In-Patients: Clinical or Criminal?

BACKGROUND AND AIM: We wished to establish the frequency of unexpected hypoglycemia observed in non diabetic patients outside the intensive care unit and to determine if they have a plausible clinical explanation. METHODS: We analysed data for 2010 from three distinct sources to identify non diabetic hypoglycaemic patients: bedside and laboratory blood glucose measurements; medication records for those treatments (high-strength glucose solution and glucagon) commonly given to reverse hypoglycemia; and diagnostic codes for hypoglycemia. We excluded from the denominator admissions of patients with a diagnosis of diabetes or prescribed diabetic medication. Case notes of patients identified were reviewed. We used capture-recapture methods to establish the likely frequency of hypoglycemia in non-diabetic in-patients outside intensive care unit at different cut-off points for hypoglycemia. We also recorded co-morbidities that might have given rise to hypoglycemia. RESULTS: Among the 37,898 admissions, the triggers identified 71 hypoglycaemic episodes at a cut-off of 3.3 mmol/l. Estimated frequency at 3.3 mmol/l was 50(CI 33-93), at 3.0 mmol/l, 36(CI 24-64), at 2.7 mmol/l, 13(CI 11-19), at 2.5 mmol/l, 11(CI 9-15) and at 2.2 mmol/l, 8(CI 7-11) per 10,000 admissions. Admissions of patients aged above 65 years were approximately 50% more likely to have an episode of hypoglycemia. Most were associated with important co-morbidities. CONCLUSION: Significant non-diabetic hypoglycemia in hospital in-patients (at or below 2.7 mmol/l) outside critical care is rare. It is sufficiently rare for occurrences to merit case-note review and diagnostic blood tests, unless an obvious explanation is found

Implementing glucose control in intensive care: a multicenter trial using statistical process control

Glucose control (GC) with insulin decreases morbidity and mortality of critically ill patients. In this study we investigated GC performance over time during implementation of GC strategies within three intensive care units (ICUs) and in routine clinical practice. All adult critically ill patients who stayed for >24 h between 1999 and 2007 were included. Effects of implementing local GC guidelines and guideline revisions on effectiveness/efficiency-related indicators, safety-related indicators, and protocol-related indicators were measured. Data of 17,111 patient admissions were evaluated, with 714,141 available blood glucose levels (BGL) measurements. Mean BGL, time to reach target, hyperglycemia index, sampling frequency, percentage of hyperglycemia events, and in-range measurements statistically changed after introducing GC in all ICUs. The introduction of simple rules on GC had the largest effect. Subsequent changes in the protocol had a smaller effect than the introduction of the protocol itself. As soon as the protocol was introduced, in all ICUs the percentage of hypoglycemia events increased. Various revisions were implemented to reduce hypoglycemia events, but levels never returned to those from pre-implementation. More intensive implementation strategies including the use of a decision support system resulted in better control of the process. There are various strategies to achieve GC in routine clinical practice but with variable success. All of them were associated with an increase in hypoglycemia events, but GC was never stopped. Instead, these events have been accepted and managed. Statistical process control is a useful tool for monitoring phenomena over time and captures within-institution change

Design and implementation of GRIP: a computerized glucose control system at a surgical intensive care unit

BACKGROUND: Tight glucose control by intensive insulin therapy has become a key part of critical care and is an important field of study in acute coronary care. A balance has to be found between frequency of measurements and the risk of hypoglycemia. Current nurse-driven protocols are paper-based and, therefore, rely on simple rules. For safety and efficiency a computer decision support system that employs complex logic may be superior to paper protocols. METHODS: We designed and implemented GRIP, a stand-alone Java computer program. Our implementation of GRIP will be released as free software. Blood glucose values measured by a point-of-care analyzer were automatically retrieved from the central laboratory database. Additional clinical information was asked from the nurse and the program subsequently advised a new insulin pump rate and glucose sampling interval. RESULTS: Implementation of the computer program was uneventful and successful. GRIP treated 179 patients for a total of 957 patient-days. Severe hypoglycemia (< 2.2 mmol/L) only occurred once due to human error. With a median (IQR) of 4.9 (4.2 – 6.2) glucose measurements per day the median percentage of time in which glucose fell in the target range was 78%. Nurses rated the program as easy to work with and as an improvement over the preceding paper protocol. They reported no increase in time spent on glucose control. CONCLUSION: A computer driven protocol is a safe and effective means of glucose control at a surgical ICU. Future improvements in the recommendation algorithm may further improve safety and efficiency

Asian dust-storm activity dominated by Chinese dynasty changes since 2000 BP

The Asian monsoon (AM) played an important role in the dynastic history of China, yet it remains unknown whether AM-mediated shifts in Chinese societies affect earth surface processes to the point of exceeding natural variability. Here, we present a dust storm intensity record dating back to the first unified dynasty of China (the Qin Dynasty, 221–207 B.C.E.). Marked increases in dust storm activity coincided with unified dynasties with large populations during strong AM periods. By contrast, reduced dust storm activity corresponded to decreased population sizes and periods of civil unrest, which was co-eval with a weakened AM. The strengthened AM may have facilitated the development of Chinese civilizations, destabilizing the topsoil and thereby increasing the dust storm frequency. Beginning at least 2000 years ago, human activities might have started to overtake natural climatic variability as the dominant controls of dust storm activity in eastern China