Unplanned Intensive Care Unit Research Articles

Rate of preventable early unplanned intensive care unit transfer for direct admissions and emergency department admissions.

Appropriate patient placement at the time of admission to avoid unplanned transfers to the ICU and codes outside of the ICU is an important safety goal for many institutions. The objective of this study was to determine if the overall rate of unplanned ICU transfers within 12 hours of admission to the inpatient medical/surgical unit was higher for direct admissions compared with emergency department (ED) admissions. This was a retrospective cohort study of all unplanned ICU transfers within 12 hours of admission to an inpatient unit at a tertiary care children's hospital from January 2010 to December 2012. Proportions of preventable unplanned transfers from the ED and from direct admission were calculated and compared. Over the study period, there were a total of 46,998 admissions; 279 unplanned ICU transfers occurred during the study period of which 101 (36%) were preventable. Preventable unplanned transfers from each portal of entry were calculated and compared with the total number of admissions from those portals. The portals of entry evaluated included admissions from our internal ED versus all outside facility transfers. The rates of early unplanned transfer (per 1000 admissions) by portal of entry were 3.50 for direct admissions and 3.18 for ED. There was no difference between direct admissions and ED admissions resulting in preventable unplanned transfers to the ICU (P=.64). Rates of unplanned ICU transfers within 12 hours of admission to an inpatient unit are not higher for direct admissions compared with ED admissions. Further studies are required to determine clinical risk factors associated with unplanned ICU transfer after admission, thus allowing for more accurate initial patient placement.

Effect of a 2-tier rapid response system on patient outcome and staff satisfaction

BackgroundRapid response systems (RRS) have been recommended as a strategy to prevent and treat deterioration in acute care patients. Questions regarding the most effective characteristics of RRS and strategies for implementing these systems remain. AimsThe aims of this study were to (i) describe the structures and processes used to implement a 2-tier RRS, (ii) determine the comparative prevalence of deteriorating patients and incidence of unplanned intensive care unit (ICU) admission and cardiac arrest prior to and after implementation of the RRS, and (iii) determine clinician satisfaction with the RRS. MethodA quasi-experimental pre-test, post-test design was used to assess patient related outcomes and clinician satisfaction prior to and after implementation of a 2-tier RRS in a tertiary metropolitan hospital. Primary components of the RRS included an ICU Outreach Nurse and a Rapid Response Team. Prevalence of deteriorating patients was assessed through a point prevalence assessment and chart audit. Incidence of unplanned admission to ICU and cardiac arrests were accessed from routine hospital databases. Clinician satisfaction was measured through surveys. ResultsPrevalence of patients who met medical emergency call criteria without current treatment reduced from 3% prior to RRS implementation to 1% after implementation; a similar reduction from 9% to 3% was identified on chart review. The number of unplanned admissions to ICU increased slightly from 17.4/month prior to RRS implementation to 18.1/month after implementation (p=0.45) while cardiac arrests reduced slightly from 7.5/month to 5.6/month (p=0.22) but neither of these changes were statistically significant. Staff satisfaction with the RRS was generally high. ConclusionThe 2-tier RRS was accessed by staff to assist with care of deteriorating patients in a large, tertiary hospital. High levels of satisfaction have been reported by clinical staff.

Laboratory tests to identify patients at risk of early major adverse events: a prospective pilot study.

To test whether commonly measured laboratory variables can identify surgical patients at risk of major adverse events (death, unplanned intensive care unit (ICU) admission or rapid response team (RRT) activation). We conducted a prospective observational study in a surgical ward of a university-affiliated hospital in a cohort of 834 surgical patients admitted for >24 h. We applied a previously validated multivariable model-derived risk assessment to each combined set of common laboratory tests to identify patients at risk. We compared the clinical course of such patients with that of control patients from the same ward who had blood tests but were identified as low risk. We studied 7955 batches and 73,428 individual tests in 834 patients (males 55%; average age 65.8 ± 17.6 years). Among these patients, 66 (7.9%) were identified as 'high risk'. High-risk patients were older (75.9 vs 61.8 years of age; P < 0.0001), had much greater early (48 h) mortality (6/66 (9%) vs 4/768 (0.5%); P < 0.0001) and greater overall hospital mortality (11/66 (16.7%) vs 9/768 (1.2%); P < 0.0001). They also had more early (8/66 (12.1%) vs 14/768 (1.8%); P = 0.0001) and overall in-hospital unplanned ICU admissions (12/66 (18.2%) vs 18/768 (2.3%); P < 0.0001) and more early (26/66 (39.3%) vs 50/768 (6.5%); P < 0.0001) and overall in-hospital RRT calls (26/66 (39.4%) vs 55/768 (7.2%); P < 0.0001). Commonly performed laboratory tests identify surgical ward patients at risk of early major adverse events. Further studies are needed to assess whether such identification system can be used to trigger interventions that help improve patient outcomes.

Using the Rothman index to predict early unplanned surgical intensive care unit readmissions.

The Rothman index (RI) is a numerical score calculated hourly from 26 data points in the electronic medical record by a commercial software package. Although it is purported to serve as an indicator of change in a patient's condition, it has not been extensively evaluated in the literature. Our objective was to determine whether the RI can be used to predict early surgical intensive care unit (SICU) readmissions. This is a single-institution, retrospective 12-month period review of all patients transferred from the SICU to the surgical floor. Patients readmitted to the SICU within 48 hours were compared with patients who did not require readmission during this time (control). Demographics and continuous RI scores were collected at admission, 24 hours before SICU transfer, and for the first 48 hours on the surgical floor or until readmission to the SICU. A total of 1,152 SICU patients were transferred to the surgical floor; 27 patients were readmitted within 48 hours of transfer. Demographics were similar in both groups. The SICU length of stay was longer in the readmission group (mean [SD], 4.7 [8.1] vs. 16.5 [15.2]; p < 0.001). The RI immediately before SICU transfer was higher in the control group (70.4 [20.3] vs. 49.1 [20.9], p < 0.001) and was uniformly improved from the RI at the initial SICU admission. In comparison, readmitted patients had more variable RI trends from admission to SICU transfer (mean Δ, 6.51; range, -54.10 to 48.6), and 40.74% of readmitted patients actually had a decreased RI score on transfer. No patient with a RI score greater than 82.90 required readmission within 48 hours. An increased RI score or a score greater than 82.90 correlates with appropriateness for SICU transfer to the surgical floor. A decreased RI score is strongly associated with SICU readmission within 48 hours and should be explored as a potential quality metric. Epidemiologic/prognostic study, level III.

Multidimensional frailty score for the prediction of postoperative mortality risk.

The number of geriatric patients who undergo surgery has been increasing, but there are insufficient tools to predict postoperative outcomes in the elderly. To design a predictive model for adverse outcomes in older surgical patients. From October 19, 2011, to July 31, 2012, a single tertiary care center enrolled 275 consecutive elderly patients (aged ≥65 years) undergoing intermediate-risk or high-risk elective operations in the Department of Surgery. The primary outcome was the 1-year all-cause mortality rate. The secondary outcomes were postoperative complications (eg, pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned intensive care unit admission), length of hospital stay, and discharge to nursing facility. Twenty-five patients (9.1%) died during the follow-up period (median [interquartile range], 13.3 [11.5-16.1] months), including 4 in-hospital deaths after surgery. Twenty-nine patients (10.5%) experienced at least 1 complication after surgery and 24 (8.7%) were discharged to nursing facilities. Malignant disease and low serum albumin levels were more common in the patients who died. Among the geriatric assessment domains, Charlson Comorbidity Index, dependence in activities of daily living, dependence in instrumental activities of daily living, dementia, risk of delirium, short midarm circumference, and malnutrition were associated with increased mortality rates. A multidimensional frailty score model composed of the above items predicted all-cause mortality rates more accurately than the American Society of Anesthesiologists classification (area under the receiver operating characteristic curve, 0.821 vs 0.647; P = .01). The sensitivity and specificity for predicting all-cause mortality rates were 84.0% and 69.2%, respectively, according to the model's cutoff point (>5 vs ≤5). High-risk patients (multidimensional frailty score >5) showed increased postoperative mortality risk (hazard ratio, 9.01; 95% CI, 2.15-37.78; P = .003) and longer hospital stays after surgery (median [interquartile range], 9 [5-15] vs 6 [3-9] days; P < .001). The multidimensional frailty score based on comprehensive geriatric assessment is more useful than conventional methods for predicting outcomes in geriatric patients undergoing surgery.

Validation of a Paediatric Early Warning Score: first results and implications of usage.

Timely recognition of deterioration of hospitalised children is important to improve mortality. We developed a modified Paediatric Early Warning Score (PEWS) and studied the effects by performing three different cohort studies using different end points. Taking unplanned Paediatric Intensive Care Unit admission as end point and only using data until 2 h prior to end point, we found a sensitivity of 0.67 and specificity of 0.88 to timely recognise patients. This proves that earlier identification is possible without a loss of sensitivity compared to other PEWS systems. When determining the corresponding clinical condition in patients with an elevated PEWS dichotomously as 'sick' or 'well', this resulted in a total of 27 % false-positive scores. This can cause motivational problems for caregivers to use the system but is a consequence of PEWS design to minimise false-negative rates because of high mortality associated with paediatric resuscitation. Using the need for emergency medical interventions as end point, sensitivity of PEWS is high and it seems, therefore, that it is also fit to alert health-care professionals that urgent interventions may be needed. These data show the effectiveness of a modified PEWS in identifying critically ill patients in an early phase making early interventions possible and hopefully reduce mortality.

ABSTRACT 972

Background and aims: Unplanned Pediatric Intensive Care Unit (PICU) readmission is associated with greater length of ICU stay and mortality. Identifying children at risk of ICU readmission will enable earlier interventions for high-risk populations. The Pediatric Early Warning Score (PEWS), developed to identify children at risk of clinical deterioration, combines risk factors found previously to be associated with unplanned PICU readmission. Aims: Our primary aim is to evaluate association of PEWS with unplanned PICU readmission. Methods: Institutional Review Board approval included waiver of informed consent for this single-center case-control study. Children ≤ 18 years transferred from the PICU to the Pediatric Ward from 1/10 to 3/13 were screened. Cases had unplanned PICU readmission within 48 hours of transfer. Controls were not readmitted. PEWS scores assigned in the PICU (≤4 hours prior to transfer) and first PEWS scores assigned on the Pediatric Ward (≤4 hours after transfer) were collected for cases and controls. Multivariate logistic regression was used to generate odds ratios and 95% confidence intervals and test association of PEWS with unplanned PICU readmission, adjusted for age. Results: PEWS prior to PICU discharge and first PEWS on the Pediatric Ward were higher for readmitted vs. non-readmitted patients [median(IQR), 2(1,3) vs. 1(1,2);P=0.005] and [2(2,3) vs. 1(1,2);P=0.005], respectively. PEWS prior to PICU discharge and first PEWS on the Pediatric Ward were significantly associated with PICU readmission [adjusted OR (95%CI), 2.2(1.3-3.5);P=0.002] and [2.4(1.5-4.0);P<0.001], respectively. Conclusions: PEWS prior to PICU discharge and first PEWS on the Pediatric Ward can help identify children at high risk of PICU readmission.

Financial consequences of the implementation of a rapid response system on a surgical ward.

Rapid response systems (RRSs) are recommended by the Institute for Healthcare Improvement and implemented worldwide. Our study on the effects of an RRS showed a non-significant decrease in cardiac arrest and/or unexpected death from 0.5% to 0.25%. Unplanned intensive care unit (ICU) admissions increased significantly from 2.5% to 4.2% without a decrease in APACHE II scores. In this study, we estimated the mean costs of an RRS per patient day and tested the hypothesis that admitting less severely ill patients to the ICU reduces costs. A cost analysis of an RRS on a surgical ward, including costs for implementation, a 1-day training programme for nurses, nursing time for extra vital signs observation, medical emergency team (MET) consults and differences in unplanned ICU days before and after RRS implementation. To test the hypothesis, we performed a scenario analysis with a mean APACHE II score of 14 points instead of the empirical 17.6 points for the unplanned ICU admissions, including 33% extra MET consults and 22% extra unplanned ICU admissions. Mean RRS costs were €26.87 per patient-day: implementation €0.33 (1%), training €0.90 (3%), nursing time spent on extended observation of vital signs €2.20 (8%), MET consults €0.57 (2%) and increased number of unplanned ICU days after RRS implementation €22.87 (85%). In the scenario analysis mean costs per patient-day were €10.18. The costs for extra unplanned ICU days were relatively high but the remaining RRS costs were relatively low. The 'APACHE II 14' scenario confirmed the hypothesis that costs for the number of unplanned ICU days can be reduced if less severely ill patients are referred to the ICU. Based upon these findings, our hospital stimulates earlier referral to the ICU, although further implementation strategies are needed to achieve these aims.

Review of unplanned Intensive Care Unit (ICU) admissions through in-hospital referrals at Tertiary Referral Centre University Hospital

Review of unplanned Intensive Care Unit (ICU) admissions through in-hospital referrals at Tertiary Referral Centre University Hospital

Characteristics of patients readmitted to intensive care unit: a nested case-control study

To evaluate the pattern of unplanned readmissions to the intensive care unit and identify patients at risk of readmission. Nested case-referent study. Tertiary hospital, Hong Kong. A total of 146 patients with unplanned intensive care unit readmission were compared with 292 control patients who were discharged from the intensive care unit alive and never readmitted. Cases and controls were matched for age, gender, and disease severity. Patient demographics, initial and pre-discharge clinical parameters, reasons for readmission, and outcomes were studied. During the 30-month study period, the readmission rate was 5.1%. Readmitted patients had significantly higher mortality and longer mean hospital lengths of stay (both P<0.001). Most patients in this cohort (36.3%) were readmitted for a respiratory cause. Based on classification tree analysis, postoperative patients with sepsis (adjusted P=0.043), non-operative septic patients with fluid gain 24 hours pre-discharge (adjusted P=0.013), and non-septic patients with increased sputum quantity on discharge (adjusted P=0.006) were significantly associated with intensive care unit readmission. Incomplete resolution of respiratory conditions remained an important reason for potentially preventable intensive care unit readmission. Attention to fluid balance and sputum quantity before intensive care unit discharge might prevent unplanned intensive care unit readmission.

Feasibility of using the predisposition, insult/infection, physiological response, and organ dysfunction concept of sepsis to predict the risk of deterioration and unplanned intensive care unit transfer after emergency department admission

BackgroundRecognizing patients at risk for deterioration and in need of critical care after emergency department (ED) admission may prevent unplanned intensive care unit (ICU) transfers and decrease the number of deaths in the hospital. The objective of this research was to study if the predisposition, insult, response, and organ dysfunction (PIRO) concept of sepsis can be used to predict the risk of unplanned ICU transfer after ED admission. MethodsThe ICU transfer group included 313 patients with unplanned transfer to the ICU within 48 hours of ED admission, and the control (non-transfer) group included 736 randomly sampled patients who were not transferred to the ICU. Two-thirds of the total 1049 patients in this study were randomly assigned to a derivation group, which was used to develop the PIRO model, and the remaining patients were assigned to a validation group. ResultsIndependent predictors of deterioration within 48 hours after ED admission were identified by the PIRO concept. PIRO scores were higher in the ICU transfer group than in the non-transfer group, both in the derivation group [median (mean ± SD), 5 (5.7 ± 3.7) vs. 2 (2.5 ± 2.5); p < 0.001], and in the validation group [median (mean ± SD), 6 (6.0 ± 3.4) vs. 2 (2.4 ± 2.6); p < 0.001]. The proportion of ICU transfer patients with a PIRO score of 0–3, 4–6, 7–9, and ≥10 was 14.1%, 46.5%, 57.3%, and 83.8% in the derivation group (p < 0.001) and 12.8%, 37.3%, 68.2%, and 70.0% in the validation group (p < 0.001), respectively. The proportion of inpatient mortality in patients with a PIRO score of 0–3, 4–6, 7–9, and ≥10 was 2.6%, 10.1%, 23.2%, and 45.9% in the derivation group (p < 0.001) and 3.3%, 12.0%, 18.2%, and 20.5% in the validation group (p < 0.001), respectively. ConclusionThe PIRO concept of sepsis may be used in undifferentiated medical ED patients as a prediction system for unplanned ICU transfer after admission.

Acute kidney injury—epidemiology, outcomes and economics

Acute kidney injury (AKI) is a widespread problem of epidemic status. Compelling evidence indicates that the incidence of AKI is rapidly increasing, particularly among hospitalized patients with acute illness and those undergoing major surgery. This increase might be partially attributable to greater recognition of AKI, improved ascertainment in administrative data and greater sensitivity of consensus diagnostic and classification schemes. Other causes could be an ageing population, increasing incidences of cardiovascular disease, diabetes mellitus and chronic kidney disease (CKD), and an expanding characterization of modifiable risk factors, such as sepsis, administration of contrast media and exposure to nephrotoxins. The sequelae of AKI are severe and characterized by increased risk of short-term and long-term mortality, incident CKD and accelerated progression to end-stage renal disease. AKI-associated mortality is decreasing, but remains unacceptably high. Moreover, the absolute number of patients dying as a result of AKI is increasing as the incidence of the disorder increases, and few proven effective preventative or therapeutic interventions exist. Survivors of AKI, particularly those who remain on renal replacement therapy, often have reduced quality of life and consume substantially greater health-care resources than the general population as a result of longer hospitalizations, unplanned intensive care unit admissions and rehospitalizations.

Data mining of common laboratory tests can be used to identify patients at risk

In deteriorating hospital patients, delayed intervention is associated with increased risk. Common laboratory tests may help identify such patients earlier. We studied the relationship between commonly measured laboratory variables and the occurrence within the next day of a rapid response team (RRT) call or unplanned intensive care unit (ICU) admission or death in patients admitted to hospital for >24h or presenting to the Emergency Department (ED) over a 6 year period. We analysed 5.9 million individual measurements and 559,612 multi-test batches of laboratory tests. We specifically studied 405,826 batches in 41,417 ward patients (average age 64.8 ± 17.5 years) and 153,786 batches in 65,363 ED patients (average age 58.1 ±20.7 years). Among 106,780 patients admitted to hospital, 1024 had at least one RRT call, 142 at least one unplanned ICU admission and 1286 died. In ward patients, total CO 2 (bicarbonate equivalent) had an AUC-ROC of 0.713 for imminent unplanned ICU admission and plasma urea had an AUC-ROC of 0.774 for imminent death. In ED patients, pH had an AUC-ROC of 0.819 for imminent unplanned ICU admission and creatinine had an AUC-ROC of 0.756 for imminent death. In addition, combinations of variables resulted in AUC-ROC values in the 0.80-0.88 range. Laboratory tests could, on average, predict an RRT call 10.2 (ward) or 11.9 (ED) hours before it occurred. In conclusion, data mining of common laboratory tests can be used to quantify risk and assist in the identification of high risk ward or ED patients

Rapid Response Team Implementation on a Burn Surgery/Acute Care Ward

To date there is limited evidence of efficacy for rapid response teams (RRT) in burns despite widespread their implementation in U.S. hospitals. The burn surgery/acute care ward at the Harborview Medical Center, Seattle, Washington, primarily treats burns, acute wounds, and pediatric trauma patients, but also accepts overflow surgical and medical patients. The authors hypothesize that institutional RRT implementation in 2006 has reduced code blue activations, unplanned intensive care unit (ICU) transfers, and mortality on the acute care ward of this hospital. The authors retrospectively analyzed all patients treated in our acute care unit before (2000-2004) and after RRT implementation (2007-2011). Patient, injury, and treatment outcomes information were collected and analyzed. The authors specifically examined clinical signs that triggered RRT activation and processes of care after activation. They compared code blue activation rates, unplanned ICU transfers, and mortality between the two periods by Poisson regression. The acute care unit treated 7092 patients before and 9357 patients after RRT implementation. There were 409 RRT activations in 329 patients, 18 of whom ultimately died during hospitalization. Those who died had higher rates of stridor (P = .03), tachypnea (P = .001), and low oxygen saturations (P = .02) compared with survivors. Fewer burn and surgical patients died after implementation (seven patients; 22% of all deaths) compared with patients who died pre-RRT (27 patients; 53% of all deaths). After adjustment for case-mix index, age, and medical service differences between the two periods, code blue calls decreased from 1.4/1000 to 0.4/1000 admissions (P = .04), unplanned ICU transfer rates decreased from 65/1000 to 50/1000 admissions (P < .01), and hospital deaths decreased from 4.5/1000 to 3.3/1000 admissions (P = .11). Since its implementation, RRT activation has been frequently used in the acute care ward of this hospital. Respiratory symptoms distinguish RRT patients who die during hospitalization compared with survivors. RRT implementation was associated with fewer code blue activations, unplanned ICU transfers, and a trend toward reduced in-hospital deaths, particularly in burn and surgical patients.

Characteristics and Risk Factors of Trauma Patients Readmitted to the ICU Within the Same Hospitalization

There is little evidence about the characteristics and outcomes of unplanned intensive care unit (ICU) readmission for adult trauma patients. This retrospective study examined the characteristics, risks factors, and outcomes for trauma patients with and without ICU readmission. With 5 years of data, 1117 patients met inclusion criteria for the study. Patient characteristics for readmission included increased age and diabetes, while identified risk factors included increased time between injury and ICU admission, admission from surgery or outside hospital, higher Injury Severity Score, along with glucose, albumin, and lower Glasgow Coma Scale values on the day of ICU discharge.

The Impact of a Nurse Practitioner Rapid Response Team on Systemic Inflammatory Response Syndrome Outcomes

Early recognition of systemic inflammatory response syndrome (SIRS) can significantly alter outcomes such as mortality, unplanned intensive care unit admissions, and cost. Through utilization of a nurse practitioner rapid response team (NP-RRT) and a revised database query, earlier identification of SIRS patients and consistent implementation of early goal-directed therapy (EGDT) on the medical-surgical units would positively impact SIRS outcomes. A database query that indicated when patients had 2 or more of the SIRS criteria and anion gap acidosis was initiated. The NP-RRT reviewed the triggered patients, and if blood cultures, lactic acid levels, volume resuscitation, or antibiotics were not in place, they were either ordered or recommended to the physicians. All 4 components of EGDT were more frequently discussed with physicians at a statistically significant level. Individual components of EGDT had high levels of implementation. Unplanned intensive care unit admissions were reduced by 3.25% after intervention with a cost savings of approximately $250 000. After initiation of the database query, patients seen by the NP-RRT were more acutely ill, with a statistically higher mean anion gap acidosis, and as a result, mortality was essentially unchanged. Improved detection of SIRS and successful implementation of EGDT led to a bridging of the evidence-to-practice gap. Future recommendations on earlier detection of lactic acidosis were rendered as a consequence of this study. The NP-RRT will continue to use the database query to identify SIRS patients in a timely manner and expedite EGDT.

Comparison of Risks Factors for Unplanned ICU Transfer after ED Admission in Patients with Infections and Those without Infections

Background. The objectives of this study were to compare the risk factors for unplanned intensive care unit (ICU) transfer after emergency department (ED) admission in patients with infections and those without infections and to explore the feasibility of using risk stratification tools for sepsis to derive a prediction system for such unplanned transfer. Methods. The ICU transfer group included 313 patients, while the control group included 736 patients randomly selected from those who were not transferred to the ICU. Candidate variables were analyzed for association with unplanned ICU transfer in the 1049 study patients. Results. Twenty-four variables were associated with unplanned ICU transfer. Sixteen (66.7%) of these variables displayed association in patients with infections and those without infections. These common risk factors included specific comorbidities, physiological responses, organ dysfunctions, and other serious symptoms and signs. Several common risk factors were statistically independent. Conclusions. The risk factors for unplanned ICU transfer in patients with infections were comparable to those in patients without infections. The risk factors for unplanned ICU transfer included variables from multiple dimensions that could be organized according to the PIRO (predisposition, insult/infection, physiological response, and organ dysfunction) model, providing the basis for the development of a predictive system.

Post-operative outcomes in adult obstructive sleep apnea patients undergoing non-upper airway surgery: a systematic review and meta-analysis

With the current obesity epidemic, obstructive sleep apnea (OSA) has become increasingly common. Several studies have reported on the risk of post-operative complications in OSA patients undergoing non-upper airway surgeries. The objective of our study was to systematically review the medical literature reporting the incidence of post-operative complications in patients with OSA. We conducted a systematic review using the Cochrane Collaboration Methodology. We searched Medline via Ovid, Pubmed, Embase, and Evidence-Based Medicine Reviews databases from 1950 to 2012. We rated the quality of evidence for each outcome using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Meta-analysis was done using Review Manager Version 5.0.20. Our search resulted in 18 eligible studies. OSA was found to be associated with a significantly increased incidence of post-operative hypoxemia (odds ratio [OR] = 3.06; 95% confidence interval [CI] 2.35-3.97), respiratory complications (OR = 2.77, 95% CI 1.73-4.43), cardiac complications (OR = 1.76 95% CI 1.16-2.67), neurological complications (OR = 2.65, 95% CI 1.43-4.92), and unplanned intensive care unit (ICU) transfer (OR = 2.97, 95% CI 1.90-4.64). Re-intubation (OR = 1.37, 95% CI 0.65-2.91) was not significantly increased in patients with OSA. The association between OSA and post-operative outcomes remained unchanged with sub-group analysis including only studies that used polysomnography (PSG) for diagnosis. OSA patients are at increased risk of post-operative complications from non-upper airway surgeries. Early diagnosis and treatment of OSA might decrease post-operative complications in these patients. There is a need for further studies to assess the benefit of peri-operative treatment of OSA on post-operative outcomes.

Unplanned pediatric intensive care unit readmissions: A single-center experience

PurposeThe purpose of the study was to compare patients readmitted to the pediatric intensive care unit (PICU) unexpectedly within 48 hours (early), more than 48 hours from transfer (late), or not readmitted during the same hospitalization. Materials and MethodsA retrospective study (2007-2009) was performed at a tertiary care pediatric academic hospital. Readmitted at-risk patients were grouped by timing of readmission, and a sample of nonreadmitted patients was randomly selected. Early readmissions were compared to late readmissions and to nonreadmissions. ResultsOf 3805 eligible patients, 3.9% had an unplanned PICU readmission with almost half occurring within 48 hours. Median times to readmission were 21.5 hours (early) and 7 days (late). Compared with late readmissions, early readmissions were more often admitted from and transferred to a surgical service, transferred on a weekend, and readmitted with the same primary diagnosis. Compared with nonreadmitted patients, independent risk factors for early readmission were admission source and respiratory support at PICU transfer. Readmitted patients had longer total PICU and hospital lengths of stay than nonreadmitted patients. Late readmissions had a higher mortality than early readmissions. ConclusionsPatients requiring an unplanned PICU readmission had worse outcomes than those without a readmission. Future studies should focus on identifying modifiable risk factors for targeted interventions.

Update in Hospital Medicine: Evidence Published in 2012

UpdatesJuly 16, 2013Update in Hospital Medicine: Evidence Published in 2012A. Scott Keller, MD, MS, Tamara E. Buechler, MD, MHA, and James S. Newman, MDA. Scott Keller, MD, MSFrom Mayo Clinic, Rochester, Minnesota.Search for more papers by this author, Tamara E. Buechler, MD, MHAFrom Mayo Clinic, Rochester, Minnesota.Search for more papers by this author, and James S. Newman, MDFrom Mayo Clinic, Rochester, Minnesota.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-159-2-201307160-00103 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail This year's Update in Hospital Medicine summarizes 10 influential studies published in 2012. Three studies focus on perioperative myocardial infarction (MI) and emphasize the morbidity and mortality of at-risk patients, and 2 studies look at issues associated with long-term anticoagulation. Other important studies highlight outcomes for patients with unplanned intensive care unit (ICU) transfer within 24 hours of ward admission, show that decreased length of stay (LOS) in Veterans Affairs patients is not associated with increased readmission rates, indicate that discharges against medical advice are associated with increased mortality and readmission, and note that longer efforts at cardiopulmonary resuscitation may ...