Comparison of SAPS II, MPM II24 and SAPS in intensive care

OBJECTIVE: To compare the performance of the new SAPS II, new MPM2 and SAPS in a cohort of patients admitted to our polyvalent ICU. METHODS: Design: the ability of the SAPS II scoring system to predict the probability of hospital mortality was assessing calibration and discrimination (ROC curve) measures obtained using published coefficients and within relevant subgroups using formal statistic assessment (goodness of fit). Patients: from May 1997 to May 1998, 420 consecutive patients over 18 years old. RESULTS: When the parameters based on the standard model were applied, the SAPS II discrimination (area under ROC curve) was = 0.889 and calibration (chi square test) of SAPS II was = 4.448 with p = 0.879; MPM2 chi 2 = 0.9385, p = 0.402 and SAPS chi 2 = 27.089, p = 0.0001. The performance of SAPS II model was very good. Worst predictive accuracy was achieved in trauma and elective surgery patients. CONCLUSIONS: SAPS II model gave good results in terms of calibration and discrimination. SAPS II has better accuracy then SAPS and MPM2. Concerning the performance of models, large differences were apparent in relevant subgroups: trauma and sepsis patients. Moreover the choice of adequate statistic method to compare intensive care populations appeared to need more research.     

A first-level customization study of SAPS II with Norwegian Intensive Care and Pandemic Registry (NIPaR) data

Background

Severity scores and mortality prediction models (MPMs) are important tools for benchmarking and stratification in the intensive care unit (ICU) and need to be regularly updated using data from a local and contextual cohort. Simplified acute physiology score II (SAPS II) is widely used in European ICUs.

Methods

A first-level customization was performed on the SAPS II model using data from the Norwegian Intensive Care and Pandemic Registry (NIPaR). Two previous SAPS II models (Model A: the original SAPS II model and Model B: a SAPS II model based on NIPaR data from 2008 to 2010) were compared to the new Model C. Model C was based on patients from 2018 to 2020 (corona virus disease 2019 patients omitted; n = 43,891), and its performances (calibration, discrimination, and uniformity of fit) compared to the previous models (Model A and Model B).

Results

Model C was better calibrated than Model A with a Brier score 0.132 (95% confidence interval 0.130–0.135) versus 0.143 (95% confidence interval 0.141–0.146). The Brier score for Model B was 0.133 (95% confidence interval 0.130–0.135). In the Cox's calibration regression $\alpha \approx 0$ and $\beta \approx 1$ for both Model C and Model B but not for Model A. Uniformity of fit was similar for Model B and for Model C, both better than for Model A, across age groups, sex, length of stay, type of admission, hospital category, and days on respirator. The area under the receiver operating characteristic curve was 0.79 (95% confidence interval 0.79–0.80), showing acceptable discrimination.

Conclusions

The observed mortality and corresponding SAPS II scores have significantly changed during the last decades and an updated MPM is superior to the original SAPS II. However, proper external validation is required to confirm our findings. Prediction models need to be regularly customized using local datasets in order to optimize their performances.     

A comparison of SAPS II and SAPS 3 in a Norwegian intensive care unit population

Background: Simplified Acute Physiology Score (SAPS II) is the most widely used general severity scoring system in European intensive care medicine. Because its performance has been questioned in several external validation studies, SAPS 3 was recently released. To our knowledge, there are no published validation studies of SAPS II or SAPS 3 in the Scandinavian countries. We aimed to evaluate and compare the performance of SAPS II and SAPS 3 in a Norwegian intensive care unit (ICU) population.
Method: Prospectively collected data from adult patients admitted to two general ICUs at two different hospitals in Norway were used. Probability of mortality was calculated using the SAPS 3 global equation (SAPS 3 G), the SAPS 3 Northern European equation (SAPS 3 NE), and the original SAPS II equation. Performance was assessed by the standardized mortality ratio (SMR), area under receiving operating characteristic, and the Hosmer and Lemeshow goodness-of-fit Ĉ test.
Results: One thousand eight hundred and sixty-two patients were included after excluding readmissions, and patients who were admitted after coronary surgery or burns. The SMRs were SAPS 3 G 0.71 (0.65, 0.78), SAPS 3 NE 0.74 (0.68, 0.81), and SAPS II 0.82 (0.75, 0.91). Discrimination was good in all systems. Only the SAPS 3 equations displayed satisfactory calibration, as measured by the Hosmer–Lemeshow test.
Conclusion: The performance of SAPS 3 was satisfactory, but not markedly better than SAPS II. Both systems considerably overestimated mortality and exhibited good discrimination, but only the SAPS 3 equations showed satisfactory calibration. Customization of these equations based on a larger cohort is recommended.     

Validation of SAPS 3 Admission Score and comparison with SAPS II

Background: The objective of this study was to validate the Simplified Acute Physiology Score SAPS 3 Admission Score (SAPS 3) and to compare its fit with that of SAPS II in an independent sample of patients admitted to a single-centre intensive care unit (ICU).
Methods: The data for all adult patients consecutively admitted to an eight-bed ICU of a 700-bed university hospital between 1 January 2006 and 2 September 2007 were collected. SAPS II and SAPS 3 were computed, as well as the predicted hospital mortality. The calibration of SAPS II and SAPS 3, according to the general equation (GE), and equations for Southern Europe and Mediterranean countries (SE&MC), and Central and Western Europe (C&WE), were assessed by the goodness-of-fit Hosmer–Lemeshow Ĥ and Ĉ statistics. Standardized mortality ratios (SMR) with 95% confidence interval (95% CI) were computed for SAPS II and SAPS 3 equations.
Results: Six hundred and eighty-four patients were studied (males 63%). The median age was 73 (quartiles 65–80) years. The fit of SAPS 3 using the C&WE equation (Ĥ 13.49, P =0.095; Ĉ 12.73, P =0.121) as well as that of SAPS II was acceptable (Ĥ 6.02, P =0.644; Ĉ12.08, P =0.147), while SAPS 3 GE (Ĥ 23.36, P =0.002; Ĉ 22.37, P =0.004) and S&MC (Ĥ 25.73, P =0.001; Ĉ 26.19, P =0.001) did not fit well. SAPS 3 GE, SAPS 3 SE&M Countries and the SAPS II significantly over estimated the mortality. Only 95% CI of SMR for SAPS 3 C&WE included 1 (SMR 0.97; 95% CI 0.89–1.05).
Conclusion: Each ICU should identify the SAPS 3 equation most suitable for its case mix. The SAPS II model tended to overestimate the mortality.     

SAPS 3 at dialysis commencement is predictive of hospital mortality in patients supported by extracorporeal membrane oxygenation and acute dialysis

Objective: This study examined the association between hospital mortality and five illness–severity scoring systems evaluated at different time points in the intensive care unit (ICU) as well as clinical variables as predictors in critically ill patients supported by extracorporeal membrane oxygenation (ECMO) and acute dialysis. Methods: This multicenter prospective observational study included 104 patients who received ECMO support and acute dialysis from January 2002 to December 2006. Patients’ demographic, clinical and laboratory variables were analyzed as predictors of survival. The SAPS 2, APACHE II, SOFA, MODS, and SAPS 3 scores upon ICU admission and at acute dialysis commencement were evaluated to predict the patient's hospital mortality. Results: Hospital mortality for the study group was 76% (79/104). Among the five scoring systems, only SAPS 3 score showed a significant difference between survivors and non-survivors either upon ICU admission (p = 0.038) or at dialysis commencement (p = 0.001). SAPS 3 score at dialysis commencement showed the best discrimination ability by using the area under the receiver operating characteristic curve (SOFA, 0.55; SAPS 2, 0.56; MODS, 0.58; APACHE II, 0.59; and SAPS 3, 0.73). Multiple logistic regression analysis indicated that SAPS 3 score at dialysis commencement (OR: 1.070, 95% CI: 1.016–1.216) and IABP usage before ECMO (OR: 4.181, 95% CI: 1.448–12.075) were two independent risk factors for hospital mortality. Conclusions: Among five common ICU scoring systems evaluated at different time points, SAPS 3 at dialysis commencement is the best risk adjustment systems to predict hospital mortality in critically ill patients supported by ECMO and acute dialysis. Furthermore, the SAPS 3 score at dialysis commencement and IABP usage before ECMO are two major independent predictors for hospital mortality in patients supported by ECMO and acute dialysis.     

Evaluation of intensive care unit performance in Lithuania using the SAPS II system

BACKGROUND AND OBJECTIVE: Outcome prediction and evaluation of intensive care unit (ICU) performance using severity of illness scoring is a tool for the estimation of effectiveness and quality of intensive care. We used the simplified acute physiology score (SAPS) II system to evaluate ICU performance. METHODS: The present study is a prospective observational study in an ICU at Vilnius University Emergency Hospital, Lithuania. The observed death rate was compared with the predicted death rate calculated using SAPS II system. The ability of the SAPS II prognostic system to predict the probability of hospital mortality was assessed with discrimination and calibration measures. RESULTS: Two-thousand-and-sixty-seven patients consecutively admitted to the ICU were studied. The median SAPS II score on the first ICU day was 29. The SAPS II system showed a good ability to separate those patients predicted to live from those predicted to die (an area under the receiver operating characteristic curve was 0.883). The calibration curve demonstrated under-prediction of the actual death rate (Hosmer-Lemeshow goodness-of-fit test, chi2 = 56.98; df = 8; P < 0.001). The observed mortality was higher than predicted by the SAPS II equation (observed to predicted ratio is 1.28). CONCLUSIONS: The SAPS II system is a useful tool for the assessment of ICU performance. This system demonstrated a good ability of discrimination, but an under-prediction of the actual mortality rate, in Lithuanian ICUs.     

Mortality Risk Factors and Validation of Severity Scoring Systems in Critically Ill Patients with Acute Renal Failure

Background. Risk stratification and prediction of outcome in acute renal failure patients in the intensive care unit are important determinants for improvement of patient care and design of clinical trials. Methods. In order to identify mortality risks factors and validate general and specific predictive models for acute renal failure (ARF) patients in the intensive care unit (ICU), 324 patients were prospectively evaluated. Multivariate analysis by logistic regression was utilized for identification of mortality risk factors. Discrimination and calibration were used to evaluate the performance of the following models at referral to nephrologist and at initiation of renal replacement therapy: APACHE II, SAPS II, LODS, and ATN-ISI. Organ failure was assessed by SOFA and OSF. Results. The hospital mortality rate was 85%. The identified mortality risk factors were: age ≥ 65 yr, BUN ≥ 70 mg/dL, ARF of septic origin, and previous hypertension. Serum creatinine ≥ 3.5 mg/dL, systolic blood pressure ≥ 100 mm Hg, and normal consciousness were associated with mortality risk reduction. Performance of all prognostic models was disappointing with unsatisfactory calibration and underestimation of mortality on the day of referral to the nephrologist and at initiation of renal replacement therapy. Conclusions. Cross-validation of prognostic models for ARF resulted in poor performance of all studied scores. Therefore, a specific model is still warranted for the design of clinical trials, comparison of studies, and for prediction of outcome in ARF patients, especially in the ICU.     

Mixed venous oxygen saturation is a prognostic marker after surgery for aortic stenosis

Background: Adequate monitoring of the hemodynamic state is essential after cardiac surgery and is vital for medical decision making, particularly concerning hemodynamic management. Unfortunately, commonly used methods to assess the hemodynamic state are not well documented with regard to outcome. Mixed venous oxygen saturation (SvO₂) was therefore investigated after cardiac surgery. Methods: Detailed data regarding mortality were available on all patients undergoing aortic valve replacement for isolated aortic stenosis during a 5‐year period in the southeast region of Sweden (n=396). SvO₂ was routinely measured on admission to the intensive care unit (ICU) and registered in a database. A receiver operating characteristics (ROC) analysis of SvO₂ in relation to post‐operative mortality related to cardiac failure and all‐cause mortality within 30 days was performed. Results: The area under the curve (AUC) was 0.97 (95% CI 0.96–1.00) for mortality related to cardiac failure (P=0.001) and 0.76 (95% CI 0.53–0.99) for all‐cause mortality (P=0.011). The best cutoff for mortality related to cardiac failure was SvO₂ 53.7%, with a sensitivity of 1.00 and a specificity of 0.94. The negative predictive value was 100%. The best cutoff for all‐cause mortality was SvO₂ 58.1%, with a sensitivity of 0.75 and a specificity of 0.84. The negative predictive value was 99.4%. Post‐operative morbidity was also markedly increased in patients with a low SvO₂. Conclusion: SvO₂, on admission to the ICU after surgery for aortic stenosis, demonstrated excellent sensitivity and specificity for post‐operative mortality related to cardiac failure and a fairly good AUC for all‐cause mortality, with an excellent negative predictive value.     

Customization of SAPS II for the assessment of severity in Italian ICU patients. ARCHIDIA. Archivio Diagnostico

BACKGROUND: To assess the accuracy of SAPS II on the Italian population and to perform a customization of the model. Design: observational prospective study. Patients: 24 participating centers. 6794 patients out of 9185 enrolled in the cohort study. Measurements: the performance of SAPS II was assessed with calibration and discrimination. In the case of standard model not fitting the data, new logistic regression equation has been calculated using Archidia database. RESULTS: SAPS II showed a good discrimination, but a bad calibration. The new logit has been calculated on the population examined in 1995 and successively tested on the population collected during 1996. In both samples discrimination and calibration results were good. CONCLUSIONS: Our customized model reaches a high standard in calibration and discrimination. We suggest this model for future application in Italian ICU.     

Timely use of a CentriMag heart assist device improves survival in postcardiotomy cardiogenic shock

Abstract Background: Postcardiotomy cardiogenic shock (PCS) is often fatal despite inotropic and circulatory support. We compared our experience with the CentriMag left ventricular assist device (LVAD) for patients with PCS at two time periods: in the operating room (OR) after unsuccessful weaning from cardiopulmonary bypass (CPB) and after transfer to the intensive care unit (ICU). Methods: We reviewed 22 patients’ records (13 men, nine women; age, 65 ± 12 years) who underwent open heart surgery (January 2004 to September 2009) and required LVAD support for PCS despite maximal inotropic and intra‐aortic balloon pump (IABP) support. In ten patients who could not be weaned from CPB despite high‐dose inotropic therapy (≥ 3 agents) and IABP support, the CentriMag was implanted in the OR (immediate group). The other 12 patients were weaned from CPB with high‐dose inotropic therapy and IABP but became increasingly unstable or had a cardiac arrest in the ICU, and the CentriMag was implanted for circulatory support (delayed group). Results: Preoperatively, the average ejection fraction was 40%± 12%, the creatinine level was 1.6 ± 0.6 mg/dL, and the European Systematic Coronary Risk Evaluation was 13.1 ± 4.6. The duration of CentriMag support was 5 ± 3 days. The immediate group had significantly better survival (7/10 vs. 2/12, p = 0.027), higher cardiac index (2.4 ± 0.3 L/min/m² vs. 1.7 ± 0.3 L/min/m², p = 0.001), and lower pulmonary capillary wedge pressure (20 ± 6 mmHg vs. 29 ± 8 mmHg, p = 0.024) than the ICU group. No perioperative complications related to device implantation occurred. Conclusion: In patients with PCS, timely placement of a CentriMag LVAD may increase the chance of eventual recovery. (J Card Surg 2011;26:548‐552)     

Application of the Simplified Acute Physiology Score II (SAPS II) in a medical intensive care unit

OBJECTIVE: Our study was to assess the validity of SAPS II (New Simplified Acute Physiology Score) to predict the probability of in hospital mortality, in a cohort of patient admitted to a medical intensive care unit. STUDY DESIGN: Prospective study. PATIENTS AND METHODS: Out of 467 the 525 patients admitted were included. SAPS score and in hospital mortality prediction were calculated for each of them. RESULTS: In this group, SAPS II offered a satisfactory discrimination power with an area under the curve of 0.843. However, calibration showed a lack of fit (chi 2 = 28.5, P < 0.001), with an overall under prediction of mortality (observed versus expected ratio of 1.12). CONCLUSION: This SAPS II lower predicting accuracy in a specific population and for individual outcome prediction may reduce its interest in clinical decision-making.     

Cyclosporine Microemulsion (Neoral®) Absorption Profiling and Sparse-sample Predictors During the First 3 Months after Renal Transplantation

Recent data suggest that optimal cyclosporine (CsA) exposure early post‐transplant significantly reduces the risk of acute graft rejection. They indicate that trough level monitoring is inadequate for precise concentration‐controlled therapy, and suggest that absorption profiling may offer a superior approach for guiding clinical immunosuppression with Neoral. An international, prospective, multicenter study examined the feasibility, accuracy, precision and clinical utility of cyclosporine microemulsion (Neoral^®) absorption profiling in de novo renal transplant recipients receiving basiliximab immunoprophylaxis and cyclosporine microemulsion maintenance immunosuppression. The nested pharmacokinetic study reported here was conducted in 4 study centers in which full (11‐point) pharmacokinetic profiles were performed on days 3, 7, 14 and 84 post‐transplant to examine absorption profile and absorption efficiency, and to determine optimal sparse‐sampling pharmacokinetic methods to predict Neoral exposure. Twenty‐four patients had complete 12‐h pharmacokinetic (PK) data on all 4 sampling days. Area under the time‐concentration curve (AUC) over the first 4 h of the 12‐h dosage interval (AUC[0–4]) and AUC over the entire 12‐h dosage interval (AUC[0–12]) reached 3803 ± 1033 and 7462 ± 2120 μg.h/L, respectively, by day 3, remained stable throughout the first 2 weeks, and declined to 2310 ± 698 and 4062 ± 1158 μg.h/L by day 84 (p < 0.001). AUC[0–4], capturing the drug absorption phase, represented 52% of the AUC[0–12] values across the four PK study days (mean R² > 0.90). Between‐patient variability was highest for C0 and C1 (mean coefficient of variation [c.v.] 36–47%), and lower for C2 (mean c.v. 28%) and subsequent time‐points during the dosing interval. Mean relative CsA absorption, measured by dose‐ and weight‐adjusted AUC[0–4] and AUC[0–12], increased significantly over time. The dose‐ and weight‐corrected AUC[0–4h] (DWC.AUC[0–4]) rose by over 100% (p < 0.001) from 753 ± 202 at day 3 to 905 ± 232 at day 7, 1080 ± 330 at day 14 and 1521 ± 316 by day 84, while the dose‐ and weight‐corrected AUC[0–12h] (DWC.AUC[0–12]) rose by over 80% (p < 0.001) from 1477 ± 390 μg.h/L/mg/kg on day 3, to 1721 ± 426 on day 7, 2086 ± 478 on day 14 and 2690 ± 602 on day 84 (p < 0.001). Relative CsA absorption varied over 5‐fold between patients at day 3, but patients tended to remain within the same quartiles over time. Sparse‐sample modeling identified optimum 3‐point, 2‐point and 1‐point predictors for AUC[0–4] and AUC[0–12]. C2 was the most accurate and robust 1‐point predictor for AUC[0–4] (mean R²: 0.80), while C3 was superior for AUC[0–12] (mean R²: 0.75). C0 was not a good predictor of either AUC[0–4] or AUC[0–12] (mean R²: 0.13 and 0.24, respectively). Conclusion: Absorption profiling defines the heterogeneity in CsA exposure and relative absorption post‐transplant. A 2‐h post‐dose blood sample is the most consistent, accurate and robust single‐point predictor of the absorption phase measured by AUC[0–4] and should replace trough level monitoring for accurate concentration‐control of Neoral therapy in the clinical setting. The use of additional samples at 1 and 3 h is more complex and costly, but increases prediction accuracy and may be valuable in selected patients with erratic absorption.     

Inflammatory response after out-of-hospital cardiac arrest—Impact on outcome and organ failure development

Background

Post-cardiac arrest syndrome that occurs in out-of-hospital cardiac arrest (OHCA) patients is characterized by inflammatory response. We conducted a scoping review of current evidence regarding several inflammatory markers' usefulness for assessment of patient outcome and illness severity. We also discuss the proposed underlying mechanisms leading to inflammatory response after OHCA.

Methods

We searched the MEDLINE, PubMed Central, Cochrane CENTRAL and Web of Science Core Collection databases with the following search terms: (“inflammation” OR “cytokines”) AND “out-of-hospital cardiac arrest.” Each inflammatory marker found was combined with “out-of-hospital cardiac arrest” using “AND” to find further relevant studies. We included original studies measuring inflammatory markers in adult OHCA patients that assessed their prognostic capabilities for mortality, neurological outcome, or organ failure severity.

Results

Fifty-nine studies met the inclusion criteria, covering in total 65 different markers. Interleukin-6 (IL-6), procalcitonin (PCT) and C-reactive protein (CRP) were the most studied markers, and they were associated with poor outcomes in 13/15, 13/14 and 11/17 studies, respectively. Based on area under the receiver operating characteristic curve (AUC) value, the time point of best discriminatory capacity for poor outcome was ICU admission for IL-6 (median AUC 0.78, range 0.71–0.98) and day one after OHCA for PCT (median AUC 0.84, range 0.61–0.98). Seven studies reported AUCs for CRP (range 0.52–0.76) with no measurement time point being superior to others. The association of IL-6 and PCT with outcome appeared stronger in studies with more severely ill patients. Studies reported conflicting results regarding each marker's association with organ failure severity.

Conclusion

Inflammatory markers are potentially useful for early risk stratification after OHCA. PCT and IL-6 have moderate prognostic value during the first 24 h of the ICU stay. Predictive accuracy appears to be associated with the study overall event rate.     

Prognostic Impact and Late Evolution of Untreated Moderate (2/4+) Functional Tricuspid Regurgitation in Patients Undergoing Aortic Valve Replacement

Objectives

The aim of the present study was to evaluate the prognostic impact and late evolution of associated tricuspid regurgitation (TR) 2/4+ after aortic valve replacement (AVR).

Methods

We evaluated 61 patients who underwent AVR between 2003 and 2012 (35 for aortic stenosis [AS], 26 for aortic regurgitation [AR]) with associated untreated TR 2/4+. Patients with concomitant mitral disease were excluded. Median follow‐up was 3.2 years. Serial echocardiographic and clinical data were collected and analyzed.

Results

Mean age was 65 ± 13 years; 26% of the patients were in NYHA class III–IV. Left ventricular ejection fraction was 53 ± 11%. Comorbidity included: chronic obstructive pulmonary disease in 5%, chronic renal failure in 13%, coronary artery disease in 20%, history of stroke/TIA in 8%. Thirty‐day mortality was 1.6%. Overall actuarial survival was 83 ± 6% at 6.5 years, with a freedom from cardiac death of 90 ± 5%. Freedom from TR ≥3+ was 86 ± 6% at 6.5 years. At last follow‐up, 82% of the patients had TR 0–1/4+, 9% had TR 2/4+, 4.5% had TR 3/4+ and 4.5% had TR 4/4+. Occurrence of TR ≥ 3+ at follow‐up was associated with increased cardiac mortality (HR 10.5; p = 0.009).

Conclusions

preoperative untreated TR 2/4+ improves or remains stable in the majority of patients. The poor outcomes associated with TR > 2+ suggest the need for better methods to identify subjects at risk for TR progression. doi: 10.1111/jocs.12656 (J Card Surg 2016;31:9–14)     

Diaphragm Valves Reduce Gastroesophageal Reflux following Cardiomyotomy for Patients with Achalasia

Background : This study was designed to investigate the effect of a novel surgical method on cardia sphincter function and complication rates after Heller’s cardiomyotomy for patients with achalasia.

Methods : Forty-eight patients (19 males, mean age 34.0 ± 10.5 years, range, 12–58) were included in this study. A spindle diaphragm valve was used in the surgery to rebuild the cardiac sphincter function. The efficacy of the surgery was determined by clinical assessment of symptoms and lower esophageal sphincter pressure (LESP) measurements. Barium meal examination was also used to evaluate the efficacy.

Results : The mean LESP before surgery was 41.3 ± 11.6 mmHg. It was reduced to 16.8 ± 3.7 mmHg and 17.5 ± 2.5 mmHg 3 and 12 months after surgery (P < 0.01). All patients were free of symptoms such as swallow difficulties or acid reflux during the follow up. However, barium swallow examination showed that 1 patient had mild reflux after the surgery. Clinical symptom scores on swallow difficulties/obstruction was reduced from 2.5 ± 0.65 before surgery to 0.06 ± 0.24 12 months after the surgery (P < 0.01).

Conclusion : A spindle diaphragm valve used with Heller’s cardiomyotomy was associated with a very low incidence of post-surgical complications, such as gastroesophageal reflux. This technique may be used in treating all patients with achalasia.     

Predicting serious complication risks after bariatric surgery: external validation of the Michigan Bariatric Surgery Collaborative risk prediction model using the Dutch Audit for Treatment of Obesity

BackgroundRisk-prediction tools can support doctor–patient (shared) decision making in clinical practice by providing information on complication risks for different types of bariatric surgery. However, external validation is imperative to ensure the generalizability of predictions in a new patient population.ObjectiveTo perform an external validation of the risk-prediction model for serious complications from the Michigan Bariatric Surgery Collaborative (MBSC) for Dutch bariatric patients using the nationwide Dutch Audit for Treatment of Obesity (DATO).SettingPopulation-based study, including all 18 hospitals performing bariatric surgery in the Netherlands.MethodsAll patients registered in the DATO undergoing bariatric surgery between 2015 and 2020 were included as the validation cohort. Serious complications included, among others, abdominal abscess, bowel obstruction, leak, and bleeding. Three risk-prediction models were validated: (1) the original MBSC model from 2011, (2) the original MBSC model including the same variables but updated to more recent patients (2015–2020), and (3) the current MBSC model. The following predictors from the MBSC model were available in the DATO: age, sex, procedure type, cardiovascular disease, and pulmonary disease. Model performance was determined using the area under the curve (AUC) to assess discrimination (i.e., the ability to distinguish patients with events from those without events) and a graphical plot to assess calibration (i.e., whether the predicted absolute risk for patients was similar to the observed prevalence of the outcome).ResultsThe DATO validation cohort included 51,291 patients. Overall, 986 patients (1.92%) experienced serious complications. The original MBSC model, which was extended with the predictors “GERD (yes/no),” “OSAS (yes/no),” “hypertension (yes/no),” and “renal disease (yes/no),” showed the best validation results. This model had a good calibration and an AUC of .602 compared with an AUC of .65 and moderate to good calibration in the Michigan model.ConclusionThe DATO prediction model has good calibration but moderate discrimination. To be used in clinical practice, good calibration is essential to accurately predict individual risks in a real-world setting. Therefore, this model could provide valuable information for bariatric surgeons as part of shared decision making in daily practice.     

Bicarbonate can improve the prognostic value of the MELD score for critically ill patients with cirrhosis

The prognosis of critically ill patients with cirrhosis is poor. Our aim was to identify an objective variable that can improve the prognostic value of the Model of End-Stage Liver Disease (MELD) score in patients who have cirrhosis and are admitted to the intensive care unit (ICU). This retrospective cohort study included 177 patients who had liver cirrhosis and were admitted to the ICU. Data pertaining to arterial blood gas-related parameters and other variables were obtained on the day of ICU admission. The overall ICU mortality rate was 36.2%. The bicarbonate (HCO₃) level was found to be an independent predictor of ICU mortality (odds ratio, 2.3; 95% confidence interval [CI], 1.0–4.8; p?=?0.038). A new equation was constructed (MELD-Bicarbonate) by replacing total bilirubin by HCO₃ in the original MELD score. The area under the receiver operating characteristic curve for predicting ICU mortality was 0.76 (95% CI, 0.69–0.84) for the MELD-Bicarbonate equation, 0.73 (95% CI, 0.65–0.81) for the MELD score, and 0.71 (95% CI, 0.63–0.80) for the Acute Physiology and Chronic Health Evaluation II score. Bicarbonate level assessment, as an objective and reproducible laboratory test, has significant predictive value in critically ill patients with cirrhosis. In contrast, the predictive value of total bilirubin is not as prominent in this setting. The MELD-Bicarbonate equation, which included three variables (international normalized ratio, creatinine level, and HCO₃ level), showed better prognostic value than the original MELD score in critically ill patients with cirrhosis.     

Outcome after catheter ablation for left atrial flutter

Objectives. Left atrial flutter has been reported in up to 10% of patients following pulmonary vein isolation or cardiac surgery. Left atrial flutter is typically highly symptomatic, responds poorly to medical antiarrhythmic treatment, and is often treated by catheter ablation. We aimed to investigate midterm freedom from recurrent arrhythmia after catheter ablation for left atrial flutter.

Design. In the National Danish Ablation Registry, we identified consecutive patients, who had undergone catheter ablation for left atrial flutter between 1 January 2014 and 1 April 2017 at our centre.

Results. A total of 53 patients (median age 68 years (IQR 60–71) 37 (70%) male) were included. Forty-two patients had prior left atrial catheter ablation procedures (79%), one patient prior ablation for classic atrial flutter (2%), four patients had prior surgery for congenital heart disease (8%), and six patients (11%) had no previous cardiac intervention. Acute procedural success, defined as non-inducibility of any atrial arrhythmia, was achieved in 45 of 53 patients (85%). During midterm follow-up (mean 20?±?12 months), 26 patients experienced an episode of recurrent atrial arrhythmia. Median EHRA-score was 3 (range 2–4) before catheter ablation and reduced to median 1 (range 1–3) evaluated at follow-up visits after three and twelve months (both p?Conclusion. Left atrial flutter is preceded by catheter ablation or cardiac surgery in 89% of patients. Acute procedural success is achieved in majority of patients and ablation reduces symptoms effectively. During midterm follow-up, almost half the patients experience recurrent atrial arrhythmia.     

Preoperative expiratory and inspiratory muscle weakness to predict postoperative outcomes in patients undergoing elective cardiac surgery

Background: Few studies have evaluated preoperative respiratory muscle strength as a risk factor for postoperative morbidity and mortality. The objective of this study was to evaluate the association of preoperative inspiratory muscle weakness (IMW) and preoperative expiratory muscle weakness (EMW) with duration of mechanical ventilation, length of stay in the intensive care unit (ICU), incidence of postoperative pulmonary complications (PPCs), and mortality in patients undergoing elective cardiac surgery. Materials and methods: This was a prospective observational study. Patients admitted for elective cardiac surgery were recruited. Maximal inspiratory and expiratory pressure were measured before surgery. A multivariate regression model was used to adjust for possible confounding variables and test the association of IMW and EMW with the duration of mechanical ventilation, length of stay in the ICU, PPCs, and hospital mortality. Results: Two hundred and fifty-five patients were included in this study. The presence of IMW was associated with an increase in the duration of mechanical ventilation (P = .012). The presence of EMW was associated with a reduction in the incidence of PPCs (P = .005). IMW had no significant association with length of stay in the ICU, PPCs, or hospital mortality. EMW had no significant association with the duration of mechanical ventilation, length of stay in the ICU, or hospital mortality. Conclusions: In patients undergoing elective cardiac surgery, preoperative IMW is associated with the duration of mechanical ventilation while preoperative EMW is associated with a decrease in PPCs.