Clinicians inevitably encounter patients who meet the diagnostic criteria for the metabolic syndrome (MetS); these criteria include central obesity, hypertension, atherogenic dyslipidaemia, and hyperglycaemia. Regardless of the variations in its definition, MetS may be associated with adverse outcomes in patients undergoing both cardiac and non-cardiac surgery. There is a paucity of data concerning the anaesthetic management of patients with MetS, and only a few observational (mainly retrospective) studies have investigated the association of MetS with perioperative outcomes. In this narrative review, we consider the impact of MetS on the occurrence of perioperative adverse events after cardiac and non-cardiac surgery. Metabolic syndrome has been associated with higher rates of cardiovascular, pulmonary, and renal perioperative events and wound infections compared with patients with a non-MetS profile. Metabolic syndrome has also been related to increased health service costs, prolonged hospital stay, and a greater need for posthospitalization care. Therefore, physicians should be able to recognize the MetS in the perioperative period in order to formulate management strategies that may modify any perianaesthetic and surgical risk. However, further research is needed in this field.

The present work investigated the dynamic changes in stressed volume (Vs) and other determinants of venous return using a porcine model of hyperdynamic septic shock. Septicemia was induced in 10 anesthetized swine, and fluid challenges were started after the diagnosis of sepsis-induced arterial hypotension and/or tissue hypoperfusion. Norepinephrine infusion targeting a mean arterial pressure (MAP) of 65 mmHg was started after three consecutive fluid challenges. After septic shock was confirmed, norepinephrine infusion was discontinued, and the animals were left untreated until cardiac arrest occurred. Baseline Vs decreased by 7% for each mmHg decrease in MAP during progression of septic shock. Mean circulatory filling pressure (Pmcf) analogue (Pmca), right atrial pressure, resistance to venous return, and efficiency of the heart decreased with time (p < 0.001 for all). Fluid challenges did not improve hemodynamics, but noradrenaline increased Vs from 107 mL to 257 mL (140%) and MAP from 45 mmHg to 66 mmHg (47%). Baseline Pmca and post-cardiac arrest Pmcf did not differ significantly (14.3 ± 1.23 mmHg vs. 14.75 ± 1.5 mmHg, p = 0.24), but the difference between pre-arrest Pmca and post-cardiac arrest Pmcf was statistically significant (9.5 ± 0.57 mmHg vs. 14.75 ± 1.5 mmHg, p < 0.001). In conclusion, the baseline Vs decreased by 7% for each mmHg decrease in MAP during progression of hyperdynamic septic shock. Significant changes were also observed in other determinants of venous return. A new physiological intravascular volume existing at zero transmural distending pressure was identified, termed as the rest volume (Vr).

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Background:Mean systemic filling pressure (Pmsf) is a quantitative measurement of a patient's volume status and represents the tone of the venous reservoir. The aim of this study was to estimate Pmsf after severe hemorrhagic shock and cardiac arrest in swine anesthetized with propofol-based total intravenous anesthesia, as well as to evaluate Pmsf's association with vasopressor-free resuscitation. Methods: Ten healthy Landrace/Large-White piglets aged 10-12 weeks with average weight 20 ± 1 kg were used in this study. The protocol was divided into four distinct phases: stabilization, hemorrhagic, cardiac arrest, and resuscitation phases. We measured Pmsf at 5-7.5 seconds after the onset of cardiac arrest and then every 10 seconds until 1 minute postcardiac arrest. During resuscitation, lactated Ringers was infused at a rate that aimed for a mean right atrial pressure of ≤ 4 mm Hg. No vasopressors were used. Results: The mean volume of blood removed was 860 ± 20 ml (blood loss, ~61%) and the bleeding time was 43.2 ± 2 minutes while all animals developed pulseless electrical activity. Mean Pmsf was 4.09 ± 1.22 mm Hg, and no significant differences in Pmsf were found until 1 minute postcardiac arrest (4.20±0.22 mm Hg at 5-7.5 seconds and 3.72±0.23 mm Hg at 55-57.5 seconds; P=0.102). All animals achieved return of spontaneous circulation (ROSC), with mean time to ROSC being 6.1 ±1.7 minutes and mean administered volume being 394 ±20 ml. Conclusions: For the first time, Pmsf was estimated after severe hemorrhagic shock. In this study, Pmsf remained stable during the first minute post-arrest. All animals achieved ROSC with goal-directed fluid resuscitation and no vasopressors.

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BACKGROUND: The incidence of postoperative microcirculatory flow alterations and their effect on outcome have not been studied extensively. OBJECTIVE: This systematic review and meta-analysis was designed to investigate the presence of sublingual microcirculatory flow alterations during the immediate and early postoperative period and their correlation with complications and survival. METHODS: A systematic search of PubMed, Scopus, Embase, PubMed Central, and Google Scholar was conducted for relevant articles from January 2000 to March 2021. Eligibility criteria were randomized controlled and non-randomized trials. Case reports, case series, review papers, animal studies and non-English literature were excluded. The primary outcome was the assessment of sublingual microcirculatory alterations during the immediate and early postoperative period in adult patients undergoing surgery. Risk of bias was assessed with the Ottawa-Newcastle scale. Standard meta-analysis methods (random-effects models) were used to assess the difference in microcirculation variables. RESULTS: Thirteen studies were included. No statistically significant difference was found between preoperative and postoperative total vessel density (p = 0.084; Standardized Mean Difference (SMD): –0.029; 95%CI: –0.31 to 0.26; I2 = 22.55%). Perfused vessel density significantly decreased postoperatively (p = 0.035; SMD: 0.344; 95%CI: 0.02 to 0.66; I2 = 65.66%), while perfused boundary region significantly increased postoperatively (p = 0.031; SMD: –0.415; 95%CI: –0.79 to –0.03; I2 = 37.21%). Microvascular flow index significantly decreased postoperatively (p = 0.028; SMD: 0.587; 95%CI: 0.06 to 1.11; I2 = 86.09%), while no statistically significant difference was found between preoperative and postoperative proportion of perfused vessels (p = 0.089; SMD: 0.53; 95%CI: –0.08 to 1.14; I2 = 70.71%). The results of the non-cardiac surgery post-hoc analysis were comparable except that no statistically significant difference in perfused vessel density was found (p = 0.69; SMD: 0.07; 95%CI: –0.26 to 0.39; I2 = 0%). LIMITATIONS: The included studies investigate heterogeneous groups of surgical patients. There were no randomized controlled trials. CONCLUSIONS: Significant sublingual microcirculatory flow alterations are present during the immediate and early postoperative period. Further research is required to estimate the correlation of sublingual microcirculatory flow impairment with complications and survival.

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Background COVID‐19 disease progression is characterized by hyperinflammation and risk stratification may aid in early aggressive treatment and advanced planning. The aim of this study was to assess whether suPAR and other markers measured at hospital admission can predict the severity of COVID‐19. Methods The primary outcome measure in this international, multi‐centre, prospective, observational study with adult patients hospitalized primarily for COVID‐19 was the association of WHO Clinical Progression Scale (WHO‐CPS) with suPAR, ferritin, CRP, albumin, LDH, eGFR, age, procalcitonin, and interleukin‐6. Admission plasma suPAR levels were determined using the suPARnostic ® ELISA and suPARnostic ® Turbilatex assays. Results Seven hundred and sixty‐seven patients, 440 (57.4%) males and 327 (42.6%) females, were included with a median age of 64 years. Log‐suPAR levels significantly correlated with WHO‐CPS score, with each doubling of suPAR increasing the score by one point ( p < .001). All the other markers were also correlated with WHO‐CPS score. Admission suPAR levels were significantly lower in survivors (7.10 vs. 9.63, 95% CI 1.47–3.59, p < .001). A linear model (SALGA) including suPAR, serum albumin, serum lactate dehydrogenase, eGFR, and age can best estimate the WHO‐CPS score and survival. Combining all five parameters in the SALGA model can improve the accuracy of discrimination with an AUC of 0.80 (95% CI: 0.759–0.836). Conclusions suPAR levels significantly correlated with WHO‐CPS score, with each doubling of suPAR increasing the score by one point. The SALGA model may serve as a quick tool for predicting disease severity and survival at admission.