Risk Assessment

FRailty in Australian patients admitted to Intensive care unit after eLective CANCER-related SURGery: a retrospective multicentre cohort study (FRAIL-CANCER-SURG study)

BACKGROUND

The association between frailty and short-term and long-term outcomes in patients receiving elective surgery for cancer remains unclear, particularly in those admitted to the ICU.

METHODS

In this multicentre retrospective cohort study, we included adults ≥16 yr old admitted to 158 ICUs in Australia from January 1, 2018 to March 31, 2022 after elective surgery for cancer. We investigated the association between frailty and survival time up to 4 yr (primary outcome), adjusting for a prespecified set of covariates. We analysed how this association changed in specific subgroups (age categories [<65, 65-80, ≥80 yr], and those who survived hospitalisation), and over time by splitting the survival information at monthly intervals.

RESULTS

We included 35,848 patients (median follow-up: 18.1 months [inter-quartile range: 8.3-31.1 months], 19,979 [56.1%] male, median age 69.0 yr [inter-quartile range: 58.8-76.0 yr]). Some 3502 (9.8%) patients were frail (defined as clinical frailty scale ≥5). Frailty was associated with lower survival (hazard ratio: 1.72, 95% confidence interval [CI]: 1.59-1.86 compared with clinical frailty scale ≤4); this was concordant across several sensitivity analyses. Frailty was most strongly associated with mortality early on in follow-up, up to 10 months (hazard ratio: 1.39, 95% CI: 1.03-1.86), but this association plateaued, and its predictive capacity subsequently diminished with time up until 4 yr (1.96, 95% CI: 0.73-5.28). Frailty was associated with similar effects when stratified based on age, and in those who survived hospitalisation.

CONCLUSIONS

Frailty was associated with poorer outcomes after an ICU admission after elective surgery for cancer, particularly in the short term. However, its predictive capacity with time diminished, suggesting a potential need for longitudinal reassessment to ensure appropriate prognostication in this population.

Unexpected intensive care unit admission after surgery: impact on clinical outcome

PURPOSE OF REVIEW

This review is focused on providing insights into unplanned admission to the intensive care unit (ICU) after surgery, including its causes, effects on clinical outcome, and potential strategies to mitigate the strain on healthcare systems.

RECENT FINDINGS

Postoperative unplanned ICU admission results from a combination of several factors including patient's clinical status, the type of surgical procedure, the level of supportive care and clinical monitoring outside the ICU, and the unexpected occurrence of major perioperative and postoperative complications. The actual impact of unplanned admission to ICU after surgery on clinical outcome remains uncertain, given the conflicting results from several observational studies and recent randomized clinical trials. Nonetheless, unplanned ICU admission after surgery results a significant strain on hospital resources. Consequently, this issue should be addressed in hospital policy with the aim of implementing preoperative risk assessment and patient evaluation, effective communication, vigilant supervision, and the promotion of cooperative healthcare.

SUMMARY

Unplanned ICU admission after surgery is a multifactorial phenomenon that imposes a significant burden on healthcare systems without a clear impact on clinical outcome. Thus, the early identification of patient necessitating ICU interventions is imperative.

Team Approach: Perioperative Management of Pilon Fractures

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Tibial pilon fractures are devastating injuries requiring complexsurgical management resulting in a challenging postoperativecourse.

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A multidisciplinary approach is required to manage these injuries in addition to patients' medical comorbidities and concomitant injuries to achieve optimal outcomes.

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The case presented here demonstrates the importance of communication and teamwork between specialties in the management of a patient with a tibial pilon fracture that was medically optimized for surgery using a team-based approach.

Association between frailty and clinical outcomes in surgical patients admitted to intensive care units: a systematic review and meta-analysis

BACKGROUND

Preoperative frailty may be a strong predictor of adverse postoperative outcomes. We investigated the association between frailty and clinical outcomes in surgical patients admitted to the ICU.

METHODS

PubMed, Embase, and Ovid MEDLINE were searched for relevant articles. We included full-text original English articles that used any frailty measure, reporting results of surgical adult patients (≥18 yr old) admitted to ICUs with mortality as the main outcome. Data on mortality, duration of mechanical ventilation, ICU and hospital length of stay, and discharge destination were extracted. The quality of included studies and risk of bias were assessed using the Newcastle Ottawa Scale. Data were synthesised according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.

RESULTS

Thirteen observational studies met inclusion criteria. In total, 58 757 patients were included; 22 793 (39.4%) were frail. Frailty was associated with an increased risk of short-term (risk ratio [RR]=2.66; 95% confidence interval [CI]: 1.99-3.56) and long-term mortality (RR=2.66; 95% CI: 1.32-5.37). Frail patients had longer ICU length of stay (mean difference [MD]=1.5 days; 95% CI: 0.8-2.2) and hospital length of stay (MD=3.9 days; 95% CI: 1.4-6.5). Duration of mechanical ventilation was longer in frail patients (MD=22 h; 95% CI: 1.7-42.3) and they were more likely to be discharged to a healthcare facility (RR=2.34; 95% CI: 1.36-4.01).

CONCLUSION

Patients with frailty requiring postoperative ICU admission for elective and non-elective surgeries had increased risk of mortality, lengthier admissions, and increased likelihood of non-home discharge. Preoperative frailty assessments and risk stratification are essential in patient and clinician planning, and critical care resource utilisation.

CLINICAL TRIAL REGISTRATION

PROSPERO CRD42020210121.

Risk assessment and risk stratification for perioperative complications and mitigation: Where should the focus be? How are we doing?

Various risk stratification tools are used to predict patients' risk of adverse outcomes. Most of these tools are based on type of surgery and patient comorbidities. Accuracy of risk prediction is improved when additional factors such as functional capacity are included. However, these tools are limited because data are obtained from specific patient populations, are simplified to aid ease of use, and do not account for improved treatment modalities that occur over time. Risk estimation allows for shared decision-making among the perioperative care team and the patient, for perioperative planning, and for opportunity for risk mitigation. Technological advancement in data collection will likely improve existing risk assessment and allow development of new options. Future research should focus on establishing and standardizing perioperative outcomes that include meaningful patient-centric considerations such as quality of life. We review available stratification tools and important risk assessment biomarkers that address the most common causes of adverse outcomes.

Inaccurate Risk Assessment by the ACS NSQIP Risk Calculator in Aortic Surgery

OBJECTIVES

The aim of this retrospective study was to assess the predictive performance of the American College of Surgeons (ACS) risk calculator for aortic aneurysm repair for the patient population of a Dutch tertiary referral hospital.

METHODS

This retrospective study included all patients who underwent elective endovascular or open aortic aneurysm repair at our institution between the years 2013 and 2019. Preoperative patient demographics and postoperative complication data were collected, and individual risk assessments were generated using five different current procedural terminology (CPT) codes. Receiver operating characteristic (ROC) curves, calibration plots, Brier scores, and Index of Prediction Accuracy (IPA) values were generated to evaluate the predictive performance of the ACS risk calculator in terms of discrimination and calibration.

RESULTS

Two hundred thirty-four patients who underwent elective endovascular or open aortic aneurysm repair were identified. Only five out of thirteen risk predictions were found to be sufficiently discriminative. Furthermore, the ACS risk calculator showed a structurally insufficient calibration. Most Brier scores were close to 0; however, comparison to a null model though IPA-scores showed the predictions generated by the ACS risk calculator to be inaccurate. Overall, the ACS risk calculator showed a consistent underestimation of the risk of complications.

CONCLUSIONS

The ACS risk calculator proved to be inaccurate within the framework of endovascular and open aortic aneurysm repair in our medical center. To minimize the effects of patient selection and cultural differences, multicenter collaboration is necessary to assess the performance of the ACS risk calculator in aortic surgery.

Risk assessment in aortic aneurysm repair by medical specialists versus the American College of Surgeons National Surgical Quality Improvement Program risk calculator outcomes

Objective

The aim of this online clinical vignette-based survey study was to compare risk assessments by vascular surgeons, anaesthesiologists and interventional radiologists involved in treating patients with aortic aneurysms in the Netherlands with the NSQIP risk calculator outcomes.

Methods

Participants, recruited using purposive sampling, provided their estimation of the likelihood of postoperative complications and events following aortic surgery in five fictional cases. These cases were subsequently scored using the NSQIP calculator. The risk assessments were statistically analysed using the ANOVA and student t-test.

Results

All participating specialists i.e. twelve vascular surgeons, ten interventional radiologists and ten anaesthesiologists completed the survey. In the vast majority of outcomes and vignettes, no significant differences were found between various specialists, whereas significant differences were found between the NSQIP risk calculator outcomes and the combined risk assessments of the specialists. Overall, specialist risk assessments differ from the NSQIP, but neither particularly higher nor lower compared to the risk calculator.

Conclusions

Risk assessment by vascular surgeons, anaesthesiologists and interventional radiologists differs significantly with NSQIP risk calculator outcomes, within the framework of both endovascular and open aortic aneurysm repair. Based on these results, implementing the NSQIP risk calculator in preoperative workup could be of added value in both patient planning as well as adequately informing patients for obtaining consent.

Development and Validation of a Web-Based Prediction Model for AKI after Surgery

BACKGROUND

AKI after surgery is associated with high mortality and morbidity. The purpose of this study is to develop and validate a risk prediction tool for the occurrence of postoperative AKI requiring RRT (AKI-dialysis).

METHODS

This retrospective cohort study had 2,299,502 surgical patients over 2015-2017 from the American College of Surgeons National Surgical Quality Improvement Program Database (ACS NSQIP). Eleven predictors were selected for the predictive model: age, history of congestive heart failure, diabetes, ascites, emergency surgery, hypertension requiring medication, preoperative serum creatinine, hematocrit, sodium, preoperative sepsis, and surgery type. The predictive model was trained using 2015-2016 data (n=1,487,724) and further tested using 2017 data (n=811,778). A risk model was developed using multivariable logistic regression.

RESULTS

AKI-dialysis occurred in 0.3% (n=6853) of patients. The unadjusted 30-day postoperative mortality rate associated with AKI-dialysis was 37.5%. The AKI risk prediction model had high area under the receiver operating characteristic curve (AUC; training cohort: 0.89, test cohort: 0.90) for postoperative AKI-dialysis.

CONCLUSIONS

This model provides a clinically useful bedside predictive tool for postoperative AKI requiring dialysis.

Serum Albumin Levels: Who Needs Them?

OBJECTIVES

The purpose of this critical narrative review is to discuss common indications for ordering serum albumin levels in adult critically ill patients, evaluate the literature supporting these indications, and provide recommendations for the appropriate ordering of serum albumin levels.

DATA SOURCES

PubMed (1966 to August 2020), Cochrane Library, and current clinical practice guidelines were used, and bibliographies of retrieved articles were searched for additional articles.

STUDY SELECTION AND DATA EXTRACTION

Current clinical practice guidelines were the preferred source of recommendations regarding serum albumin levels for guiding albumin administration and for nutritional monitoring. When current comprehensive reviews were available, they served as a baseline information with supplementation by subsequent studies.

DATA SYNTHESIS

Serum albumin is a general marker of severity of illness, and hypoalbuminemia is associated with poor patient outcome, but albumin is an acute phase protein, so levels vacillate in critically ill patients in conjunction with illness fluctuations. The most common reasons for ordering serum albumin levels in intensive care unit (ICU) settings are to guide albumin administration, to estimate free phenytoin or calcium levels, for nutritional monitoring, and for severity-of-illness assessment.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

Because hypoalbuminemia is common in the ICU setting, inappropriate ordering of serum albumin levels may lead to unnecessary albumin administration or excessive macronutrient administration in nutritional regimens, leading to possible adverse effects and added costs.

CONCLUSIONS

With the exception of the need to order serum albumin levels as a component of selected severity-of-illness scoring systems, there is little evidence or justification for routinely ordering levels in critically ill patients.

Pre and postoperative risk management: the role of scores and biomarkers

PURPOSE OF REVIEW

The goal of risk prediction is to identify high-risk patients who will benefit from further preoperative evaluation. Clinical scores and biomarkers are very well established tools for risk prediction but their accuracy remains a controversial issue.

RECENT FINDINGS

Current guidelines recommend one of the risk tools for preoperative cardiac risk assessment: American College of Surgeons National Surgical Quality Improvement Program (NSQIP) calculator or Revised Cardiac Risk Index. Although not as easy to use as risk scores, risk models are more accurate and can predict individual patient risk more precisely. A step forward in risk estimation was performed by introducing new risk models developed from the American College of Surgeons NSQIP database - NSQIP surgical risk calculator and Myocardial Infarction or Cardiac Arrest index. Although biomarkers, especially in cardiac risk assessment, are already present in current European and American guidelines, this use is still controversial. Novel biomarkers: microRNAs, heart-type fatty acid-binding protein and mid-regional proadrenomedullin, can be used as new potential biomarkers in clinical practice. Also some of the experimental biomarkers have not yet been introduced into clinical practice, preliminary results are encouraging.

SUMMARY

Different risk indices and biomarkers might lead to varying risk estimates. However, the importance of clinical judgment in risk assessment should not be underestimated.

Performance of cardiopulmonary exercise testing for the prediction of post-operative complications in non cardiopulmonary surgery: A systematic review

INTRODUCTION

Cardiopulmonary exercise testing (CPET) is widely used within the United Kingdom for preoperative risk stratification. Despite this, CPET's performance in predicting adverse events has not been systematically evaluated within the framework of classifier performance.

METHODS

After prospective registration on PROSPERO (CRD42018095508) we systematically identified studies where CPET was used to aid in the prognostication of mortality, cardiorespiratory complications, and unplanned intensive care unit (ICU) admission in individuals undergoing non-cardiopulmonary surgery. For all included studies we extracted or calculated measures of predictive performance whilst identifying and critiquing predictive models encompassing CPET derived variables.

RESULTS

We identified 36 studies for qualitative review, from 27 of which measures of classifier performance could be calculated. We found studies to be highly heterogeneous in methodology and quality with high potential for bias and confounding. We found seven studies that presented risk prediction models for outcomes of interest. Of these, only four studies outlined a clear process of model development; assessment of discrimination and calibration were performed in only two and only one study undertook internal validation. No scores were externally validated. Systematically identified and calculated measures of test performance for CPET demonstrated mixed performance. Data was most complete for anaerobic threshold (AT) based predictions: calculated sensitivities ranged from 20-100% when used for predicting risk of mortality with high negative predictive values (96-100%). In contrast, positive predictive value (PPV) was poor (2.9-42.1%). PPV appeared to be generally higher for cardiorespiratory complications, with similar sensitivities. Similar patterns were seen for the association of Peak VO2 (sensitivity 85.7-100%, PPV 2.7-5.9%) and VE/VCO2 (Sensitivity 27.8%-100%, PPV 3.4-7.1%) with mortality.

CONCLUSIONS

In general CPET's 'rule-out' capability appears better than its ability to 'rule-in' complications. Poor PPV may reflect the frequency of complications in studied populations. Our calculated estimates of classifier performance suggest the need for a balanced interpretation of the pros and cons of CPET guided pre-operative risk stratification.

Root causes and outcomes of postoperative pulmonary complications after abdominal surgery: a retrospective observational cohort study

Background

Postoperative pulmonary complications (PPCs) contribute significantly to overall postoperative morbidity and mortality. In abdominal surgery, PPCs remain frequent. The study aimed to analyze the profile and outcomes of PPCs in patients submitted to abdominal surgery and admitted in a Portuguese polyvalent intensive care unit.

Methods

From January to December 2017 in the polyvalent intensive care unit of Hospital Garcia de Orta, Almada, Portugal, we conducted a retrospective, observational study of inpatients submitted to urgent or elective abdominal surgery who had severe PPCs. We evaluated the perioperative risk factors and associated mortality. Logistic regression was performed to find which perioperative risk factors were most important in the occurrence of PPCs.

Results

Sixty patients (75% male) with a median age of 64.5 [47-81] years who were submitted to urgent or elective abdominal surgery were included in the analysis. Thirty-six patients (60%) developed PPCs within 48 h and twenty-four developed PPCs after 48 h. Pneumonia was the most frequent PPC in this sample. In this cohort, 48 patients developed acute respiratory failure and needed mechanical ventilation. In the emergency setting, peritonitis had the highest rate of PPCs. Electively operated patients who developed PPCs were mostly carriers of digestive malignancies. Thirty-day mortality was 21.7%. The risk of PPCs development in the first 48 h was related to the need for neuromuscular blocking drugs several times during surgery and preoperative abnormal arterial blood gases. Median abdominal surgical incision, long surgery duration, and high body mass index were associated with PPCs that occurred more than 48 h after surgery. The American Society of Anesthesiologists physical status score 4 and COPD/Asthma determined less mechanical ventilation needs since they were preoperatively optimized. Malnutrition (low albumin) before surgery was associated with 30-day mortality.

Conclusion

PPCs after abdominal surgery are still a major problem since they have profound effects on outcomes. Our results suggest that programs before surgery, involve preoperative lifestyle changes, such as nutritional supplementation, exercise, stress reduction, and smoking cessation, were an effective strategy in mitigating postoperative complications by decreasing mortality.

Cardiovascular Risk Assessment for Noncardiac Surgery: Are We Ready for Biomarkers?

Biomarkers aided perioperative cardiac assessment is a relatively new concept. Cardiac biomarkers with historical significance (aspartate transaminase, dehydrogenase, creatinine kinase and myoglobin) have paved the way for traditional biomarkers (cardiac troponin, C-reactive protein, lipoprotein). Contemporary biomarkers like natriuretic peptides (BNP and ProBNP) are validated risk markers in both acute and chronic cardiac diseases and are showing remarkable promise in predicting serious cardiovascular complications after non-cardiac surgery. This review is intended to provide a critical overview of traditional and contemporary biomarkers for perioperative cardiovascular assessment and management. This review also discusses the potential utility of newer biomarkers like galectin-3, sST-2, GDF-15, TNF-alpha, MiRNAs and many others that can predict inflammation, cardiac remodeling, injury and endogenous stress and need further investigations to establish their clinical utility. Though promising, biomarker led perioperative care is still in infancy and it has not been determined that it can improve clinical outcomes.

Preoperative Assessment of Older Adults

Older patients undergoing surgery have reduced physiologic reserve caused by the combined impact of physiologic age-related changes and the increased burden of comorbid conditions. The preoperative assessment of older patients is directed at evaluating the patient's functional reserve and identifying opportunities to minimize any potential for complications. In addition to a standard preoperative evaluation that includes cardiac risk and a systematic review of systems, the evaluation should be supplemented with a review of geriatric syndromes. Age-based laboratory testing protocols can lead to unnecessary testing, and all testing should be requested if indicated by underlying disease and surgical risk.

Prehabilitation is better than cure

PURPOSE OF REVIEW

With a continuously growing number of older patients undergoing major surgical procedures, reliable parameters practicable in perioperative routine revealing those patients at risk are urgently needed. Recently, the concept of 'prehabilitation' with its key elements exercise, nutrition and psychological stress reduction especially in frail patients is attracting increasing attention.

RECENT FINDINGS

Literature search revealed a huge amount of publications in particular within the last 12 months. Although a single definition of both frailty and prehabilitation is still to be made, various players in the perioperative setting obviously are becoming increasingly convinced about a possible benefit of the program - referring to different components and measures performed. Although physiologically advantages seem obvious, there is hardly any reliable data on clinical outcomes resulting from properly performed studies. This applies especially to octogenarians; thus those at risk for adverse events the concept originally addresses.

SUMMARY

Identifying high-risk patients at the earliest possible stage and increasing their physiological reserve prior to surgery is a promising approach that seems to result in remarkable improvements for older patients. However, further studies on effectiveness in a highly heterogeneous population and agreement on a common concept are mandatory before a final judgement can be given.