Analysis of Unplanned Postoperative Admissions to the Intensive Care Unit

The elderly in the post-anesthesia care unit

It is increasingly conceivable that elderly patients will be treated in perioperative settings as the world's population shifts toward an older age distribution. They are more prone to a variety of unfavorable outcomes as a consequence of the physiological changes that accompany aging and the coexistence of multiple medical conditions. Postoperative complications in elderly patients are linked to a large increase in morbidity and mortality and the burden placed on the healthcare system. Our goal is to determine how elderly patients' recovery after anesthesia differs from that of younger patients. In addition, we will discuss the main postoperative complications experienced by elderly patients and the measures that are utilized to limit the risk of these complications developing.

Developing a reflection and analysis tool (We-ReAlyse) for readmissions to the intensive care unit: A quality improvement project

BACKGROUND

Readmissions to the intensive care unit are associated with poorer patient outcomes and health prognoses, alongside increased lengths of stay and mortality risk. To improve quality of care and patients' safety, it is essential to understand influencing factors relevant to specific patient populations and settings. A standardized tool for systematic retrospective analysis of readmissions would help healthcare professionals understand risks and reasons affecting readmissions; however, no such tool exists.

PURPOSE

This study's purpose was to develop a tool (We-ReAlyse) to analyze readmissions to the intensive care unit from general units by reflecting on affected patients' pathways from intensive care discharge to readmission. The results will highlight case-specific causes of readmission and potential areas for departmental- and institutional-level improvements.

METHOD

A root cause analysis approach guided this quality improvement project. The tool's iterative development process included a literature search, a clinical expert panel, and a testing in January and February 2021.

RESULTS

The We-ReAlyse tool guides healthcare professionals to identify areas for quality improvement by reflecting the patient's pathway from the initial intensive care stay to readmission. Ten readmissions were analyzed by using the We-ReAlyse tool, resulting in key insights about possible root causes like the handover process, patient's care needs, the resources on the general unit and the use of different electronic healthcare record systems.

CONCLUSIONS

The We-ReAlyse tool provides a visualization/objectification of issues related to intensive care readmissions, gathering data upon which to base quality improvement interventions. Based on the information on how multi-level risk profiles and knowledge deficits contribute to readmission rates, nurses can target specific quality improvements to reduce those rates.

IMPLICATIONS FOR CLINICAL PRACTICE AND RESEARCH

With the We-ReAlyse tool, we have the opportunity to collect detailed information about ICU readmissions for an in-depth analysis. This will allow health professionals in all involved departments to discuss and either correct or cope with the identified issues. In the long term, this will allow continuous, concerted efforts to reduce and prevent ICU readmissions. To obtain more data for analysis and to further refine and simplify the tool, it may be applied to larger samples of ICU readmissions. Furthermore, to test its generalizability, the tool should be applied to patients from other departments and other hospitals. Adapting it to an electronic version would facilitate the timely and comprehensive collection of necessary information. Finally, the tool's emphasis comprises reflecting on and analyzing ICU readmissions, allowing clinicians to develop interventions targeting the identified problems. Therefore, future research in this area will require the development and evaluation of potential interventions.

Dosage and clinical outcomes of medical emergency team and conventional referral mediated unplanned intensive care admissions

Background: Unplanned intensive care unit (ICU) admission occurs via activation of medical emergency team (MET) and conventional ICU referral (CIR), i.e., ICU consultation. We aimed to compare the dosage, association with unplanned ICU admissions and hospital mortality between MET and CIR systems. Methods: We performed a retrospective, single centre observational study on unplanned ICU admissions from hospital wards between July 2017 and June 2018. We evaluated the dosage (expressed per 1000 admissions) and association of CIR and MET system with unplanned ICU admission using Chi-square test. The relationship (unadjusted and adjusted to Australia and New Zealand risk of death (ANZROD) and lead time) between unplanned ICU admission pathway (MET vs CIR) and hospital mortality was tested by binary logistic regression analysis [Odds ratio (OR) with 95% confidence interval (CI)]. Results: Out of 38,628 patients hospitalised, 679 had unplanned ICU admission (2%) with an ICU admission rate of 18 per 1000 ward admissions. There were 2153 MET and 453 CIR activations, producing a dosage of 56 and 12 per 1000 admissions, respectively. Higher unplanned ICU admission was significantly associated with CIR compared to MET activation (324/453 (71.5%) vs 355/2153 (16.5%) p < 0.001). On binary logistic regression, MET system was significantly associated with higher hospital mortality on unadjusted analysis (OR 1.65 (95% CI: 1.09-2.48) p = 0.02) but not after adjustment with ANZROD and lead time (OR 1.15 (95% CI: 0.71-1.86), p = 0.58). Conclusions: Compared to CIR, MET system had higher dosage but lower frequency of unplanned ICU admissions and lacked independent association with hospital mortality.

Clinical Frailty Scale is a better predictor for adverse post-operative complications and functional outcomes than Modified Frailty Index and Charlson Comorbidity Index after total knee arthroplasty

PURPOSE

Studies have demonstrated correlations between frailty and comorbidity scores with adverse outcomes in total knee replacement (TKR). However, there is a lack of consensus on the most suitable pre-operative assessment tool. This study aims to compare Clinical Frailty Scale (CFS), Modified Frailty Index (MFI), and Charlson Comorbidity Index (CCI) in predicting adverse post-operative complications and functional outcomes following a unilateral TKR.

METHODS

In total, 811 unilateral TKR patients from a tertiary hospital were identified. Pre-operative variables were age, gender, body mass index (BMI), American Society of Anesthesiologists (ASA) class, CFS, MFI, and CCI. Binary logistic regression analysis was performed to ascertain odd ratios of pre-operative variables on adverse post-operative complications (length of stay < LOS >, complications, ICU/HD admission, discharge location, 30-day readmission, 2-year reoperation). Multiple linear regression analyses were used to estimate the standardized effects of pre-operative variables on the Knee Society Functional Score (KSFS), Knee Society Knee Score (KSKS), Oxford Knee Score (OKS), and 36-Item Short Form Survey (SF-36).

RESULTS

CFS is a strong predictor for LOS (OR 1.876, p < 0.001), complications (OR 1.83-4.97, p < 0.05), discharge location (OR 1.84, p < 0.001), and 2-year reoperation rate (OR 1.98, p < .001). ASA and MFI were predictors for ICU/HD admission (OR:4.04, p = 0.002; OR 1.58, p = 0.022, respectively). None of the scores was predictive for 30-day readmission. A higher CFS was associated with a worse outcome for 6-month KSS, 2-year KSS, 6-month OKS, 2-year OKS, and 6-month SF-36.

CONCLUSION

CFS is a superior predictor for post-operative complications and functional outcomes than MFI and CCI in unilateral TKR patients. This suggests the importance of assessing pre-operative functional status when planning for TKR.

LEVEL OF EVIDENCE

Diagnostic, II.

Association of immediate versus delayed extubation of patients admitted to intensive care units postoperatively and outcomes: A retrospective study

AIM OF THIS STUDY

This study seeks to investigate, whether extubation of tracheally intubated patients admitted to intensive care units (ICU) postoperatively either immediately at the day of admission (day 1) or delayed at the first postoperative day (day 2) is associated with differences in outcomes.

MATERIALS AND METHODS

We performed a retrospective analysis of data from an Austrian ICU registry. Adult patients admitted between January 1st, 2012 and December 31st, 2019 following elective and emergency surgery, who were intubated at the day 1 and were extubated at day 1 or day 2, were included. We performed logistic regression analyses for in-hospital mortality and over-sedation or agitation following extubation.

RESULTS

52 982 patients constituted the main study population. 1 231 (3.3%) patients extubated at day 1 and 958 (5.9%) at day 2 died in hospital, 464 (1.3%) patients extubated at day 1 and 613 (3.8%) at day 2 demonstrated agitation or over-sedation after extubation during ICU stay; OR (95% CI) for in-hospital mortality were OR 1.17 (1.01-1.35, p = 0.031) and OR 2.15 (1.75-2.65, p<0.001) for agitation or over-sedation.

CONCLUSIONS

We conclude that immediate extubation as soon as deemed feasible by clinicians is associated with favourable outcomes and may thus be considered preferable in tracheally intubated patients admitted to ICU postoperatively.

Preoperative Comorbidities Associated With Early Mortality in Hip Fracture Patients: A Multicenter Study

OBJECTIVE

Multiple comorbidities in hip fracture patients are associated with increased mortality and complications. The goal of this study was to characterize the relationship between specific patient factors including comorbidities and outcomes in geriatric hip fractures, including length of stay, unplanned ICU admission, discharge disposition, complications, and mortality.

METHODS

This is a retrospective review of a trauma database from five Level 1 and Level 2 trauma centers of patients with hip fractures of the femoral neck and intertrochanteric region who underwent treatment using hip pinning, hemiarthroplasty, total hip arthroplasty, cephalomedullary nailing, or dynamic hip screw fixation. Mortality was the primary outcome variable (including in-hospital mortality, 30-day mortality, 60-day mortality, and 90-day mortality). Secondary outcome variables included in-hospital adverse events, unplanned transfer to the ICU, postoperative length of stay, and discharge disposition. Regression analyses were used for evaluation of relationships between comorbidities as independent variables and primary and secondary outcomes as dependent variables.

RESULTS

Two thousand three hundred patients were included. The mortality was 1.8%, 7.0%, 10.9%, and 14.1% for in-hospital, 30-day, 60-day, and 90-day mortality, respectively. Diabetes and cognitive impairment present on admission were associated with mortality at all-time intervals. COPD was the only comorbidity that signaled in-hospital adverse event with an odds ratio of 1.67 (P = 0.012). No patient factors, time to surgery, or comorbidities signaled unplanned ICU transfer. Patients with renal failure and COPD had longer hospital stays after surgery.

CONCLUSION

Geriatric hip fractures continue to have high short-term morbidity and mortality. Identifying patients with increased odds of early mortality and adverse events can help teams optimize care and outcomes. Patients with diabetes, cognitive impairment, renal failure, and COPD may benefit from continued and improved medical optimization during the perioperative period as well as being more closely managed by a medicine team without delaying time to the operating room.

Characteristics and outcomes of unplanned intensive care unit admission after general anesthesia

Background

Unplanned ICU admission after surgery has been validated as a measure of a quality indicator of perioperative management because it may put surgical patients at risk of increased morbidity and mortality. Postoperative unscheduled admission to the ICU is usually determined either in the post-anesthesia care unit (PACU) or in the general surgical ward; however, it could be expected patient outcomes after ICU admission would be affected by the circumstances. The purpose of this retrospective observational study was to investigate the clinical characteristics and the outcome of unplanned admission to the ICU directly from the PACU or from the ward within 7 days after PACU discharge.

Methods

Forty-three thousand, five hundred fifty-three patients admitted to the PACU after general anesthesia were included in the study. Unplanned ICU admission was defined as the admission which was not anticipated preoperatively but was due to adverse events in the PACU (PACU group) or the ward after discharge from the PACU (Ward group). The following parameters were compared between the groups: patient characteristics, surgical characteristics, length of ICU and hospital stay, the principal adverse event for ICU admission, treatments in the ICU, and in-hospital mortality. The primary outcome was in-hospital mortality and the second was the length of ICU and hospital stay.

Results

Among 43,553 patients, 109 patients underwent unplanned ICU admission directly from the PACU (n= 73, 0.17%) or subsequently from the ward (n= 36, 0.08%). The length of both ICU and hospital stay was significantly longer in the Ward group than in the PACU group (1.4 and 19 days vs. 2.5 and 39 days, respectively). There was no significant difference in in-hospital mortality between the groups (4.1% vs. 8.3%, respectively).

Conclusions

The incidence of unplanned ICU admission after PACU stay was low, however, delayed admission to the ICU from the ward may prolong the length of both ICU and hospital stay compared to those directly from the PACU.

Tanaka score predicts surgical intensive care admission following abdominal wall reconstruction

PURPOSE

With the advancement of abdominal wall reconstruction, more complex hernia patients are undergoing repairs that may require a postoperative surgical intensive care unit (SICU) admission. The volume ratio (VR) of the hernia sac to the abdominal cavity is an easily applied method to quantify disease severity and the ensuing physiologic insult. This study aimed to predict postoperative SICU admission using VR and other preoperative variables.

METHODS

A single-center retrospective review was conducted for patients undergoing large abdominal hernias (width ≥ 18 cm) repaired from September 2014 to October 2019. Patient demographics, comorbidities, abdominal surgical history, and VR were analyzed through univariate and multivariable methods to identify predictors of SICU admission within the first two postoperative days. A predictive model was generated and validated.

RESULTS

Of 434 patients meeting inclusion criteria, 127(29%) required a SICU admission within the first two postoperative days. VR was significantly higher in SICU patients (Median 30.6% [IQR 14.4-59.0] vs. 10.6% [IQR 4.35-23.6], P < 0.001). Male sex, history of chronic obstructive pulmonary disease, prior component separation, recurrent incisional hernia, hernia grade 3, and VR showed higher odds of SICU admission. When validated on a testing dataset, these variables showed strong SICU admission predictions, with an area under the curve, sensitivity, and specificity of 0.82, 81.7% and 68.5%, respectively.

CONCLUSIONS

The volume ratio in combination with preoperatively available variables can reliably predict postoperative SICU admission following abdominal wall reconstruction. Anticipating such events preoperatively allows for bed space allocation as well as optimizing postoperative care.

Patient Deterioration on General Care Units: A Concept Analysis

Patient deterioration is a phenomenon that occurs from the inability to recognize it or respond to a change in condition. Despite the published reports on recognizing a deteriorating patient on general care floors, a gap remains in the ability of nurses to describe the concept, affecting patient outcomes. Walker and Avant's approach was applied to analyze patient deterioration. The aim of this article was to explore and clarify the meaning of patient deterioration and identify attributes, antecedents, and consequences. The defining attributes were compared to early warning scores. An operational definition was developed and its value to nurses established.

A clinical nomogram predicting unplanned intensive care unit admission after hip fracture surgery

BACKGROUND

Despite the improvement of surgical procedures and perioperative management, a portion of patients were still at high risk for intensive care unit admission owing to severe morbidity after hip fracture surgeries. The purpose of this study was to analyze influencing factors and to construct a clinical nomogram to predict unscheduled intensive care unit admission among inpatients after hip fracture surgeries.

METHODS

We enrolled a total of 1,234 hip fracture patients, with 40 unplanned intensive care unit admissions, from January 2011 to December 2018. Demographics, chronic coexisting conditions at admission, laboratory tests, and surgical variables were collected and compared between intensive care unit admission and nonadmission groups using univariate analysis. The optimal lasso model was refined to the whole data set, and multivariate logistic regression was used to assign relative weights. A nomogram incorporating these predictors was constructed to visualize these predictors and their corresponding points of the risk for unplanned intensive care unit admission. The model was validated temporally using an independent data set from January 2019 to December 2019 by receiver operating characteristic area under the curve analysis.

RESULTS

In the development group, we identified age, chronic heart failure, coronary heart disease, chronic obstructive pulmonary disease, Parkinson disease, and serum albumin and creatinine concentration were associated with unscheduled intensive care unit admission using multivariate analysis. The final model had an area under the curve of 0.854 (95% confidence interval, 0.742-0.966). The median calculated odds ratio of intensive care unit admission based on the nomogram was significantly higher for patients in the intensive care unit admission group than in the non-intensive care unit admission group (65.93% vs 0.02%, P < .01). The validation group proved its high predictive power with an area under the curve of 0.96 (95% confidence interval, 0.91-0.99).

CONCLUSION

In this study, we identified several independent factors that may increase the risk for unexpected intensive care unit admission after hip fracture surgery and developed a clinical nomogram based on these variables. Preoperative evaluation using this nomogram might facilitate advanced intensive care unit resource management for high-risk patients whose conditions might easily deteriorate if not closely monitored in general wards after surgeries.

Unplanned hospital admission after ambulatory surgery: a retrospective, single cohort study

PURPOSE

We estimated the rate of unplanned hospital and intensive care unit (ICU) admissions following ambulatory surgery centre (ASC) procedures, and identified factors associated with their occurrence.

METHODS

This retrospective cohort included adult patients who underwent ASC procedures within a large community practice from January 2010 to December 2014. Patients were categorized into two groups: unplanned postoperative hospital/ICU admission within 24 hr of procedure or uneventful discharge. Demographics, comorbidities, anesthesia type, procedure type, procedure group, and ASC facility were assessed.

RESULTS

Of the 211,389 patients included, there were 211,147 uneventful discharges (99.89%) and 242 unplanned hospital admissions (0.11%), of which 75 were ICU admissions (0.04%). The multivariable logistic regression model for hospital admission showed an increased risk associated with age > 50 yr (odds ratio [OR], 1.53); American Society of Anesthesiologists (ASA) physical status (III vs II: OR, 1.45; IV vs II: OR, 1.88), comorbidity (chronic obstructive pulmonary disease: OR, 2.63; diabetes mellitus: OR, 1.62; transient ischemic attack: OR, 2.48) procedure (respiratory: OR, 2.92; digestive: OR, 2.66; musculoskeletal system: OR, 2.53), anesthetic management (general anesthesia [GA] and peripheral nerve block vs GA: OR, 1.79), and ASC facility (189BB: OR, 2.29; 30E9A: OR, 7.41; and BD21F: OR, 1.69). The multivariable logistic regression model for ICU admission showed increased risk of unplanned ICU admission associated with ASA physical status (ASA III vs II: OR, 3.0; ASA IV vs II: OR, 8.52), procedure (musculoskeletal system: OR, 2.45), and ASC facility (00E6C: OR, 3.14; 189BB: OR, 2.77; 30E9A: OR, 2.59; and BD21F: OR, 3.71).

CONCLUSION

While a small percentage of adult patients who underwent ASC procedures required unplanned hospital admission (0.07%), approximately one-third of these admissions were to the ICU (0.04%). Facility was at least as strong a predictor of hospital admission as the patient- and/or procedure-specific variables.

Unplanned hospital admission after ambulatory surgery: a retrospective, single cohort study

PURPOSE

We estimated the rate of unplanned hospital and intensive care unit (ICU) admissions following ambulatory surgery centre (ASC) procedures, and identified factors associated with their occurrence.

METHODS

This retrospective cohort included adult patients who underwent ASC procedures within a large community practice from January 2010 to December 2014. Patients were categorized into two groups: unplanned postoperative hospital/ICU admission within 24 hr of procedure or uneventful discharge. Demographics, comorbidities, anesthesia type, procedure type, procedure group, and ASC facility were assessed.

RESULTS

Of the 211,389 patients included, there were 211,147 uneventful discharges (99.89%) and 242 unplanned hospital admissions (0.11%), of which 75 were ICU admissions (0.04%). The multivariable logistic regression model for hospital admission showed an increased risk associated with age > 50 yr (odds ratio [OR], 1.53); American Society of Anesthesiologists (ASA) physical status (III vs II: OR, 1.45; IV vs II: OR, 1.88), comorbidity (chronic obstructive pulmonary disease: OR, 2.63; diabetes mellitus: OR, 1.62; transient ischemic attack: OR, 2.48) procedure (respiratory: OR, 2.92; digestive: OR, 2.66; musculoskeletal system: OR, 2.53), anesthetic management (general anesthesia [GA] and peripheral nerve block vs GA: OR, 1.79), and ASC facility (189BB: OR, 2.29; 30E9A: OR, 7.41; and BD21F: OR, 1.69). The multivariable logistic regression model for ICU admission showed increased risk of unplanned ICU admission associated with ASA physical status (ASA III vs II: OR, 3.0; ASA IV vs II: OR, 8.52), procedure (musculoskeletal system: OR, 2.45), and ASC facility (00E6C: OR, 3.14; 189BB: OR, 2.77; 30E9A: OR, 2.59; and BD21F: OR, 3.71).

CONCLUSION

While a small percentage of adult patients who underwent ASC procedures required unplanned hospital admission (0.07%), approximately one-third of these admissions were to the ICU (0.04%). Facility was at least as strong a predictor of hospital admission as the patient- and/or procedure-specific variables.

Institution of Monthly Anesthesia Quality Reports Does Not Reduce Postoperative Complications despite Improved Metric Compliance

While quality programs have been shown to improve provider compliance, few have demonstrated conclusive improvements in patient outcomes. We hypothesized that there would be increased metric compliance and decreased postoperative complications after initiation of an anesthesiology quality improvement program at our institution. We performed a retrospective study of all adult inpatients having anesthesia for a twelve-month period that spanned six months before and after program implementation. The primary outcome was the rate of complications in the post-implementation period. Secondary outcomes included the change in proportion of complications and compliance with quality metrics. We studied a total of 9620 adult inpatient cases, subdivided into pre- and post-implementation groups (4832 vs 4788.) After multivariate model adjustment, the rate of any complication (our primary outcome) was not significantly changed (32% to 31%; adjusted P = 0.410.) Of the individual complications, only wound infection (2.0% to 1.5%; adjusted P = 0.020) showed a statistically significant decrease. Statistically and clinically significant increases in compliance were seen for the BP-02 Avoiding Monitoring Gaps metric (81% to 93%, P < 0.001), both neuromuscular blockade metrics (NMB-01 76% to 91%, P < 0.001; NMB-02 95% to 97%, P = 0.006), both tidal volume metrics (PUL-01 84% to 93%, P < 0.001; PUL-02 30% to 45%, P < 0.001), and the TEMP-02 Core Temperature Measurement metric (88% to 94%, P < 0.001). Implementation of a comprehensive quality feedback program improved metric compliance but was not associated with a change in postoperative complications.

Post-operative intensive care unit admission after elective non-cardiac surgery: A single-center analysis of the NSQIP database

BACKGROUND

Admission to the intensive care unit (ICU) after surgery can be associated with significant morbidity and mortality. This observational cohort study aims to identify perioperative factors associated with post-operative ICU admission in patients undergoing elective non-cardiac surgery.

METHODS

Data from the ACS NSQIP^® database at a tertiary care academic medical center were analyzed from January 2011 to September 2016. Univariable and multivariable logistic regression of patient and surgery-specific characteristics was performed to assess association with post-operative ICU admission. The Current Procedural Terminology (CPT) and International Classification of Diseases (ICD-9) billing codes, as well as associated outcomes, were reviewed.

RESULTS

Of 5254 database patient records, 1150 met our inclusion criteria. Elevated body mass index (BMI), longer procedure duration and a diagnosis of disseminated cancer were associated with post-operative ICU admission. Prostatectomy and morbid obesity were the most common CPT and ICD-9 codes identified. Patients who were admitted to the ICU after surgery had a longer hospital length of stay (LOS), had a higher frequency of readmission, re-operation, and in-hospital mortality.

CONCLUSION

Admission to the ICU after elective non-cardiac surgery is common. Our analysis of the ACS NSQIP^® database identified elevated BMI, longer duration of surgery and disseminated cancer as predictors of post-operative ICU admissions in patients undergoing elective non-cardiac surgery.

Severe odontogenic deep neck space infections: risk factors for difficult airways and ICU admissions

PURPOSE

The purpose of this retrospective study was to evaluate perioperative risk factors concerning difficult airway management, primary tracheostomy, and need for intensive care unit (ICU) admission in severe odontogenic space infections.

METHODS

Perioperative risk factors were retrospectively analyzed in 499 cases. Fisher's exact test and analysis of variance were performed to analyze associations between categorical and continuous variables. Univariate regression analysis was used for estimating predictors for ICU admission. A risk model for ICU admission was performed using multivariate regression analysis. Area-under-the-curve (AUC) was calculated by receiver-operating-characteristic (ROC) curve.

RESULTS

Airway securing in patients with restricted mouth opening led to significant use of the video laryngoscope (p < 0.001) or fiberoptic bronchoscope (p < 0.001). The use of fiberoptic bronchoscopy was significantly increased in patients with dysphagia (p = 0.005) and dyspnea (p = 0.04). Four patients (0.8%) needed primary tracheostomy. ICU admission was significantly associated with higher levels of C-reactive protein (CRP, p = 2.78 × 10^-5), white blood cell count (WBC, p = 0.003), dyspnea (p = 9.95 × 10^-6), and higher body mass index (BMI, p = 0.0003). American Society of Anesthesiologists physical status (ASA PS) class III patients (p = 0.04) and the need for the use of a video laryngoscopy (p = 0.003) or fiberoptic bronchoscopy (p = 6.58 × 10^-5) resulted in a more frequent ICU admission. The AUC of the model was 0.897.

CONCLUSION

Difficult airway management was mainly dependent on limited mouth opening and elevated CRP. Elevated CRP, BMI, ASA PS III, and dyspnea were important risk factors for ICU admission. These predictors should be considered preoperatively for proper planning and preparation.

The incidence of cardiac arrest in the intensive care unit: A systematic review and meta-analysis

The incidence of cardiac arrest in the intensive care unit (ICU-CA) has not been widely reported. We undertook a systematic review and meta-analysis of studies reporting the incidence of cardiac arrest in adult, general intensive care units. The review was prospectively registered with PROSPERO (CRD42017079717). The search identified 7550 records, which included 20 relevant studies for qualitative analysis and 16 of these were included for quantitative analyses. The reported incidence of ICU-CA was 22.7 per 1000 admissions (95% CI: 17.4-29.6) with survival to hospital discharge of 17% (95% CI: 9.5-28.5%). We estimate that at least 5446 patients in the UK have a cardiac arrest after ICU admission. There are limited data and significant variation in the incidence of ICU-CA and efforts to synthesise these are limited by inconsistent reporting. Further prospective studies with standardised process and incidence measures are required to define this important patient group.

Postoperative Respiratory Impairment Is a Real Risk for Our Patients: The Intensivist's Perspective

Postoperative respiratory impairment occurs as a result of a combination of patient, surgical, and management factors and contributes to both surgical and anesthetic risk. This complication is challenging to predict and has been associated with an increase in mortality and hospital length of stay. There is mounting evidence to suggest that patients remain vulnerable to respiratory impairment well into the postoperative period, with the vast majority of adverse events occurring during the first 24 hours following discharge from anesthesia care. At present, preoperative risk stratification scores may be able to identify patients who are particularly prone to respiratory complications but cannot consistently and globally predict risk in an ongoing fashion as they do not incorporate the impact of intra- and postoperative events. Current postoperative monitoring strategies are not always continuous or comprehensive and do not dependably identify all cases of respiratory impairment or mitigate their sequelae, which may be severe and require the use of increasingly limited intensive care unit resources. As a result, postoperative respiratory impairment has the potential to cause significant downstream effects that can increase cost and adversely impact the care of other patients.

Interdisciplinary Care Model Independently Decreases Use of Critical Care Services After Corrective Surgery for Adult Degenerative Scoliosis

OBJECTIVE

Interdisciplinary management of elderly patients requiring spine surgery has been shown to improve short- and long-term outcomes. The aim of this study was to determine whether an interdisciplinary team approach mitigates use of intensive care unit (ICU) resources.

METHODS

A unique comanagement model for elderly patients undergoing lumbar fusion surgery was implemented at a major academic medical center. The Peri-operative Optimization of Senior Health Program (POSH) was launched with the aim of improving outcomes in elderly patients (>65 years old) undergoing complex lumbar spine surgery. In this model, a geriatrician evaluates elderly patients preoperatively, comanages daily throughout hospital course, and coordinates multidisciplinary rehabilitation, along with the neurosurgical team. We retrospectively reviewed the first 100 cases after the initiation of the POSH protocol and compared them with the immediately preceding 25 cases to assess the rates of ICU transfer and independent predictors of ICU admission.

RESULTS

A total of 125 patients undergoing lumbar decompression and fusion surgery were enrolled in this pilot program. Baseline characteristics and intraoperative variables, as well as number of fusion levels and duration of surgery, were similar between both cohorts. There was a significant difference in the use of ICU services (ICU admission rates) between both cohorts, with the non-POSH cohort having a 3-fold increase compared with the POSH cohort (P < 0.0001). In a multivariate analysis, lack of an interdisciplinary comanagement team approach was an independent predictor for ICU transfers in elderly patients undergoing corrective surgery (odds ratio 8.51, 95% confidence interval 2.972-24.37, P < 0.0001).

CONCLUSIONS

Our study suggests that an interdisciplinary comanagement model between geriatrics and neurosurgery is independently associated with reduced use of critical care services.

Processes of care in surgical patients who died with hospital-acquired infections in Australian hospitals

BACKGROUND

Infection may complicate surgical patients' hospital admission. The effect of hospital-acquired infections (HAIs) on processes of care among surgical patients who died is unknown.

AIM

To investigate the effect of HAIs on processes of care in surgical patients who died in hospital.

METHODS

Surgeon-recorded infection data extracted from a national Australian surgical mortality audit (2012-2016) were grouped into HAIs and no infection. The audit included all-age surgical patients, who died in hospital. Not all patients had surgery. Excluded from analysis were patients with community-acquired infection and those with missing timing of infection. Multivariate logistic regression was used to determine the adjusted effects of HAIs on the processes of care in these patients. Costs associated with HAIs were estimated.

FINDINGS

One-fifth of surgical patients who died did so with an HAI (2242 out of 11,681; 19.2%). HAI patients had increased processes of care compared to those who died without infection: postoperative complications [51.0% vs 30.3%; adjusted odds ratio (aOR): 2.20; 95% confidence interval (CI): 1.98-2.45; P < 0.001]; unplanned reoperations (22.6% vs 10.9%; aOR: 2.38; 95% CI: 2.09-2.71; P < 0.001) and unplanned intensive care unit admission (29.3% vs 14.8%; aOR: 2.18; 95% CI: 1.94-2.45; P < 0.001). HAI patients had longer hospital admissions and greater hospital costs than those without infection.

CONCLUSION

HAIs were associated with increased processes of care and costs in surgical patients who died; these outcomes need to be investigated in surgical patients who survive.

Unplanned Intensive Care Unit Admission following Elective Surgical Adverse Events: Incidence, Patient Characteristics, Preventability, and Outcome

Context:

Adverse events (AEs) are a persistent and an important reason for Intensive Care Unit (ICU) admission. They lead to death, disability at the time of discharge, unplanned ICU admission (UIA), and prolonged hospital stay. They impose large financial costs on health-care systems.

Aims:

This study aimed to determine the incidence, patient characteristics, type, preventability, and outcome of UIA following elective surgical AE.

Settings and Design:

This is a single-center prospective study.

Methods:

Analysis of 15,372 elective surgical procedures was performed. We defined UIA as an ICU admission that was not anticipated preoperatively but was due to an AE occurring within 5 days after elective surgery.

Statistical Analysis:

Descriptive analysis using SPSS software version 18 was used for statistical analysis.

Results:

There were 75 UIA (0.48%) recorded during the 2-year study period. The average age of patients was 54.64 ± 18.02 years. There was no sex predominance, and the majority of our patients had an American Society of Anesthesiologist classes 1 and 2. Nearly 29% of the UIA occurred after abdominal surgery and 22% after a trauma surgery. Regarding the causes of UIA, we observed that 44 UIA (58.7%) were related to surgical AE, 24 (32%) to anesthetic AE, and 7 (9.3%) to postoperative AE caused by care defects. Twenty-three UIA were judged as potentially preventable (30.7%). UIA was associated with negative outcomes, including increased use of ICU-specific interventions and high mortality rate (20%).

Conclusions:

Our analysis of UIA is a quality control exercise that helps identify high-risk patient groups and patterns of anesthesia or surgical care requiring improvement.

Random Survival Forests for Predicting the Bed Occupancy in the Intensive Care Unit

Predicting the bed occupancy of an intensive care unit (ICU) is a daunting task. The uncertainty associated with the prognosis of critically ill patients and the random arrival of new patients can lead to capacity problems and the need for reactive measures. In this paper, we work towards a predictive model based on Random Survival Forests which can assist physicians in estimating the bed occupancy. As input data, we make use of the Sequential Organ Failure Assessment (SOFA) score collected and calculated from 4098 patients at two ICU units of Ghent University Hospital over a time period of four years. We compare the performance of our system with a baseline performance and a standard Random Forest regression approach. Our results indicate that Random Survival Forests can effectively be used to assist in the occupancy prediction problem. Furthermore, we show that a group based approach, such as Random Survival Forests, performs better compared to a setting in which the length of stay of a patient is individually assessed.

Analysis of Unplanned Intensive Care Unit Admissions in Postoperative Pediatric Patients

BACKGROUND

Currently, there are only a few retrospective, single-institution studies that have addressed the prevalence and risk factors associated with unplanned admissions to the pediatric intensive care unit (ICU) after surgery. Based on the limited amount of studies, it appears that airway and respiratory complications put a child at increased risk for unplanned ICU admission. A more extensive and diverse analysis of unplanned postoperative admissions to the ICU is needed to address risk factors that have yet to be revealed by the current literature.

AIM

To establish a rate of unplanned postoperative ICU admissions in pediatric patients using a large, multi-institution data set and to further characterize the associated risk factors.

METHODS

Data from the National Anesthesia Clinical Outcomes Registry were analyzed. We recorded the overall risk of unplanned postoperative ICU admission in patients younger than 18 years and performed univariate and multivariate logistic regression analysis to identify the associated patient, surgical, and anesthetic-related characteristics.

RESULTS

Of the 324 818 cases analyzed, 211 reported an unexpected ICU admission. There was an increased likelihood of unplanned postoperative ICU in infants (age <1 year) and children who were classified as American Society of Anesthesiologists physical status classification of III or IV. Likewise, longer case duration and cases requiring general anesthesia were also associated with unplanned ICU admissions.

CONCLUSION

This study establishes a rate of unplanned ICU admission following surgery in the heterogeneous pediatric population. This is the first study to utilize such a large data set encompassing a wide range of practice environments to identify risk factors leading to unplanned postoperative ICU admissions. Our study revealed that patient, surgical, and anesthetic complexity each contributed to an increased number of unplanned ICU admissions in the pediatric population.

Delayed Recognition of Deterioration of Patients in General Wards Is Mostly Caused by Human Related Monitoring Failures: A Root Cause Analysis of Unplanned ICU Admissions

Background

An unplanned ICU admission of an inpatient is a serious adverse event (SAE). So far, no in depth-study has been performed to systematically analyse the root causes of unplanned ICU-admissions. The primary aim of this study was to identify the healthcare worker-, organisational-, technical,- disease- and patient- related causes that contribute to acute unplanned ICU admissions from general wards using a Root-Cause Analysis Tool called PRISMA-medical. Although a Track and Trigger System (MEWS) was introduced in our hospital a few years ago, it was implemented without a clear protocol. Therefore, the secondary aim was to assess the adherence to a Track and Trigger system to identify deterioration on general hospital wards in patients eventually transferred to the ICU.

Methods

Retrospective observational study in 49 consecutive adult patients acutely admitted to the Intensive Care Unit from a general nursing ward. 1. PRISMA-analysis on root causes of unplanned ICU admissions 2. Assessment of protocol adherence to the early warning score system.

Results

Out of 49 cases, 156 root causes were identified. The most frequent root causes were healthcare worker related (46%), which were mainly failures in monitoring the patient. They were followed by disease-related (45%), patient-related causes (7, 5%), and organisational root causes (3%). In only 40% of the patients vital parameters were monitored as was instructed by the doctor. 477 vital parameter sets were found in the 48 hours before ICU admission, in only 1% a correct MEWS was explicitly documented in the record.

Conclusions

This in-depth analysis demonstrates that almost half of the unplanned ICU admissions from the general ward had healthcare worker related root causes, mostly due to monitoring failures in clinically deteriorating patients. In order to reduce unplanned ICU admissions, improving the monitoring of patients is therefore warranted.