| 1. |
- Gualandro, Danielle M. M., et al.
(författare)
-
Acute heart failure after non-cardiac surgery: incidence, phenotypes, determinants and outcomes
- 2023
-
Ingår i: European Journal of Heart Failure. - : WILEY. - 1388-9842 .- 1879-0844. ; 25:3, s. 347-357
-
Tidskriftsartikel (refereegranskat)abstract
- Aims Primary acute heart failure (AHF) is a common cause of hospitalization. AHF may also develop postoperatively (pAHF). The aim of this study was to assess the incidence, phenotypes, determinants and outcomes of pAHF following non-cardiac surgery.Methods and results A total of 9164 consecutive high-risk patients undergoing 11 262 non-cardiac inpatient surgeries were prospectively included. The incidence, phenotypes, determinants and outcome of pAHF, centrally adjudicated by independent cardiologists, were determined. The incidence of pAHF was 2.5% (95% confidence interval [CI] 2.2-2.8%); 51% of pAHF occurred in patients without known heart failure (de novo pAHF), and 49% in patients with chronic heart failure. Among patients with chronic heart failure, 10% developed pAHF, and among patients without a history of heart failure, 1.5% developed pAHF. Chronic heart failure, diabetes, urgent/emergent surgery, atrial fibrillation, cardiac troponin elevations above the 99th percentile, chronic obstructive pulmonary disease, anaemia, peripheral artery disease, coronary artery disease, and age, were independent predictors of pAHF in the logistic regression model. Patients with pAHF had significantly higher all-cause mortality (44% vs. 11%, p < 0.001) and AHF readmission (15% vs. 2%, p < 0.001) within 1 year than patients without pAHF. After Cox regression analysis, pAHF was an independent predictor of all-cause mortality (adjusted hazard ratio [aHR] 1.7 [95% CI 1.3-2.2]; p < 0.001) and AHF readmission (aHR 2.3 [95% CI 1.5-3.7]; p < 0.001). Findings were confirmed in an external validation cohort using a prospective multicentre cohort of 1250 patients (incidence of pAHF 2.4% [95% CI 1.6-3.3%]).Conclusions Postoperative AHF frequently developed following non-cardiac surgery, being de novo in half of cases, and associated with a very high mortality.
|
|
| 2. |
- Lurati Buse, Giovanna A., et al.
(författare)
-
Risk assessment for major adverse cardiovascular events after noncardiac surgery using self-reported functional capacity : international prospective cohort study
- 2023
-
Ingår i: British Journal of Anaesthesia. - : Elsevier. - 0007-0912 .- 1471-6771. ; 130:6, s. 655-665
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Guidelines endorse self-reported functional capacity for preoperative cardiovascular assessment, although evidence for its predictive value is inconsistent. We hypothesised that self-reported effort tolerance improves prediction of major adverse cardiovascular events (MACEs) after noncardiac surgery.METHODS: This is an international prospective cohort study (June 2017 to April 2020) in patients undergoing elective noncardiac surgery at elevated cardiovascular risk. Exposures were (i) questionnaire-estimated effort tolerance in metabolic equivalents (METs), (ii) number of floors climbed without resting, (iii) self-perceived cardiopulmonary fitness compared with peers, and (iv) level of regularly performed physical activity. The primary endpoint was in-hospital MACE consisting of cardiovascular mortality, non-fatal cardiac arrest, acute myocardial infarction, stroke, and congestive heart failure requiring transfer to a higher unit of care or resulting in a prolongation of stay on ICU/intermediate care (≥24 h). Mixed-effects logistic regression models were calculated.RESULTS: In this study, 274 (1.8%) of 15 406 patients experienced MACE. Loss of follow-up was 2%. All self-reported functional capacity measures were independently associated with MACE but did not improve discrimination (area under the curve of receiver operating characteristic [ROC AUC]) over an internal clinical risk model (ROC AUCbaseline 0.74 [0.71-0.77], ROC AUCbaseline+4METs 0.74 [0.71-0.77], ROC AUCbaseline+floors climbed 0.75 [0.71-0.78], AUCbaseline+fitnessvspeers 0.74 [0.71-0.77], and AUCbaseline+physical activity 0.75 [0.72-0.78]).CONCLUSIONS: Assessment of self-reported functional capacity expressed in METs or using the other measures assessed here did not improve prognostic accuracy compared with clinical risk factors. Caution is needed in the use of self-reported functional capacity to guide clinical decisions resulting from risk assessment in patients undergoing noncardiac surgery.CLINICAL TRIAL REGISTRATION: NCT03016936.
|
|
| 3. |
- Meister, Rebecca, et al.
(författare)
-
Prediction of perioperative myocardial infarction/injury in high-risk patients after noncardiac surgery
- 2023
-
Ingår i: European Heart Journal. - : OXFORD UNIV PRESS. - 2048-8726 .- 2048-8734. ; 12:11, s. 729-739
-
Tidskriftsartikel (refereegranskat)abstract
- Aims Perioperative myocardial infarction/injury (PMI) is a surprisingly common yet difficult-to-predict cardiac complication in patients undergoing noncardiac surgery. We aimed to assess the incremental value of preoperative cardiac troponin (cTn) concentration in the prediction of PMI. Methods and results Among prospectively recruited patients at high cardiovascular risk (age >= 65 years or >= 45 years with preexisting cardiovascular disease), PMI was defined as an absolute increase in high-sensitivity cTnT (hs-cTnT) concentration of >= 14 ng/L (the 99th percentile) above the preoperative concentration. Perioperative myocardial infarction/injury was centrally adjudicated by two independent cardiologists using serial measurements of hs-cTnT. Using logistic regression, three models were derived: Model 1 including patient- and procedure-related information, Model 2 adding routinely available laboratory values, and Model 3 further adding preoperative hs-cTnT concentration. Models were also compared vs. preoperative hs-cTnT alone. The findings were validated in two independent cohorts. Among 6944 patients, PMI occurred in 1058 patients (15.2%). The predictive accuracy as quantified by the area under the receiver operating characteristic curve was 0.73 [95% confidence interval (CI) 0.71-0.74] for Model 1, 0.75 (95% CI 0.74-0.77) for Model 2, 0.79 (95% CI 0.77-0.80) for Model 3, and 0.74 for hs-cTnT alone. Model 3 included 10 preoperative variables: age, body mass index, known coronary artery disease, metabolic equivalent >4, risk of surgery, emergency surgery, planned duration of surgery, haemoglobin, platelet count, and hs-cTnT. These findings were confirmed in both independent validation cohorts (n = 722 and n = 966). Conclusion Preoperative cTn adds incremental value above patient- and procedure-related variables as well as routine laboratory variables in the prediction of PMI.
|
|
