Background and Objectives: The prospective study was conducted to evaluate humoral and cellular immune responses after two doses of BNT162b2 (Pfizer-BioNTech) vaccine and possible relation with other factors  in kidney transplant patients. Materials and Methods: Out of 167 vaccinated patients, 136 agreed to a follow-up visit three to six weeks after vaccination. Results: Only 39 patients (29%) developed antibody response against SARS-CoV-2 (≥35.2 binding antibody units (BAU)/mL) after full vaccination. Multivariate binary logistic regression analysis showed that predictive factors for good antibody response to the COVID-19 vaccine were better kidney function, higher hemoglobin level, and no use of mycophenolate mofetil for immunosuppression. For seropositive kidney transplant patients there was a significant negative correlation between anti-SARS-CoV-2 antibody titer and CD4/CD8 ratio , percentage of CD19+ cells , and a positive correlation with percentage of CD8+ cells . There was an increase of total leucocyte count after vaccination in the total studied population, and in the group of responders. Conclusions: Only one third of kidney transplant patients develop sufficient antibody responses after full COVID-19 vaccination with Pfizer-BioNTech. Better kidney function, higher hemoglobin level, and no use of mycophenolate mofetil for immunosuppression increases the adequacy of response. The antibody titers correlated positively with relative number of CD8+ cells and negatively with CD4/CD8 ratio in responders. Chronic kidney disease (CKD) patients have been significantly impacted during the coronavirus disease of 2019 (COVID-19) pandemic, resulting in a substantial decrease in transplant activity, an increased risk of COVID-19 disease, hospitalization and mortality ,4. PatieThe BNT162b2 (Pfizer-BioNTech) vaccine was the first available COVID-19 vaccine in Lithuania during this pandemia, and organ transplant recipients had vaccination priority. Kidney transplant recipients followed in our transplant center of the Hospital of the Lithuanian University of Health Sciences were able to receive full vaccination during January–February 2021. The aim of our study was to evaluate humoral and cellular immune responses after two doses of BNT162b2 (Pfizer-BioNTech) vaccine and possible relation with other factors  in kidney transplant patients.The prospective study was conducted for evaluation of the response to vaccination against SARS-CoV-2 in patients after renal transplantation in the Hospital of Lithuanian University for Health Sciences, Kauno klinikos. The study was approved by the Regional Bioethical Committee (5 February 2021 Nr. BE-2-43).Out of 317 patients, followed in our center, 167 were vaccinated with two doses of BNT162b2 (Pfizer-BioNTech) SARS-CoV-2 mRNA vaccine with an interval of 21 days as recommended by the manufacturer. Vaccination was recommended not earlier than three months after kidney transplantation. 136 patients agreed to participate in the study and signed written informed consent, and they came for a follow-up visit three to six weeks after vaccination (mean time 35 ± 11.5 days). None of these subjects had COVID-19 previously. Data about comorbid conditions and medications used were collected from their medical records. Anamnesis of angina pectoris, myocardial infarction, and stroke was counted as cardiovascular events. Levels of creatinine, estimated glomerular filtration rate , hemoglobin (Hb), albumin, C-reactive protein, parathyroid hormone (PTH), and vitamin D were evaluated as routine measurements before and after vaccination. Blood samples were taken for evaluation of anti-SARS-CoV-2 antibodies, lymphocyte subpopulations, and immunoglobulin (Ig)-G, M, A three to six weeks after vaccination. We continued follow-up for allograft rejection reactions after vaccination.Anti-SARS-CoV-2 antibodies were evaluated using QuantiVac ELISA assay (Euroimmun), which provides quantitative in vitro determination of human antibodies of the IgG class against SARS-CoV-2 spike proteins in serum, according to the manufacturer‘s recommendations. Values were given in BAU/mL (BAU—binding antibody units). A result ≥35.2 BAU/mL was interpreted as a seropositive.Quantification of lymphocyte subpopulations in blood was performed by flow cytometry . After blood incubation with a monoclonal antibodies mix  and erythrocytes lysis, prepared samples were acquired and analyzed on the BD FACSLyric system with BD FACSuite Clinical software . During data analysis, the lymphocyte region was gated and the absolute numbers (cells/L) of lymphocyte subpopulations in the sample were determined. T, B and NK cells were characterized by expression of CD3, CD4, CD8, CD19 and CD16/56.p < 0.05 was considered statistically significant for all analyses.Statistical analysis was performed using SPSS 22.0 . Continuous variables have been described as mean with standard deviation or median, according to data distribution. Parameter distribution was assessed using the Kolmogorov-Smirnov test. According to the level of antibodies against SARS-CoV-2 spike proteins, patients were divided into a seropositive group (anti-SARS-CoV-2 ≥ 35.2 BAU/mL), and a seronegative group (anti-SARS-CoV-2 < 35.2 BAU/mL). For comparison of seropositive and seronegative patients’ results, groups were analyzed by means of an independent t-test or the Mann-Whitney U test. Categorical variables have been described as absolute frequencies and percentages and analyzed by Fisher’s Exact test. Bivariate correlations of antibody titers with other variables were tested calculating Spearman’s coefficient. The significant variables that were found in univariate analysis were included into a binary logistic regression model for the risk of seronegativity. Changes in the variables before and after vaccination were assessed by paired t test and Wilcoxon signed-rank test for related samples. The median age of studied patients was 55 (21–82) years: 88 (62.4%) men, 53 (37.6%) women.Results of laboratory tests of kidney transplant patients before and after full vaccination against COVID-19 are summarized in Although there are statistically significant differences between eGFR, serum albumin before and after vaccination, these differences are not clinically significant. Differences in leucocyte and lymphocyte count obtained from SARS-CoV-2 seropositive and seronegative groups were studied in more detail.Only 39 patients (29%) with kidney transplant developed an antibody response against SARS-CoV-2 (≥35.2 BAU/mL) after full vaccination against COVID-19.Two groups of patients—with positive and negative antibody response—were compared according to the possible predictive factors .Out of all measures—creatinine level, eGFR, Hb before and after vaccination, and IgG after vaccination differed significantly between the groups. SARS-CoV-2 seropositive subjects with kidney transplants had higher levels of Hb, eGFR, IgG, and lower creatinine levels . HoweverComparison of SARS-CoV-2 antibody response in studied groups in relation to comorbid condition and concomitant medication is shown in Statistically significant difference was noticed for a use of immunosuppression: antibody response to COVID-19 vaccine was better in patients, who were using sirolimus, and did not use mycophenolate mofetil (MMF) .Multivariate binary logistic regression analysis was performed, including age and most potent factors, tested after vaccination for evaluation of predictive factors for good antibody response after COVID-19 vaccination in kidney transplant patients . Analysip = 0.02) in responders. Anti-SARS-CoV-2 antibodies titer significantly correlated with percentage of CD8+ cells  and negatively correlated with percentage of CD19+ cells , but there was no significant correlation with absolute numbers of lymphocyte subpopulations.Additional evaluation of kidney transplant patients with positive anti-SARS-CoV-2 antibodies after COVID-19 vaccination  showed that there is no correlation between anti-SARS-CoV-2 titer and patient’s age, level of IgA, M, G, vitamin D concentration, total leucocyte and lymphocyte count, MMF dose, and other routine laboratory test results before and after vaccination. However, there was a significant negative correlation between anti-SARS-CoV-2 antibody titer and CD4/CD8 ratio  biopsy proven rejection reactions during the nine months of follow-up (until November 2021): in one patient mixt  rejection diagnosed one month after second dose (this patient was known for non-compliance), in one patient cellular rejection diagnosed two months after second dose, and in another four patients rejection was diagnosed 6–9 months after second dose of vaccine. Out of 150 patients who were not vaccinated in our clinic, there were 6 rejection reactions (4%) during the same period. Therefore, there is no clear association between rejection reaction and vaccination.This study was conducted to evaluate the humoral and cellular immune responses induced by SARS-CoV-2 mRNA vaccine (Pfizer-BioNTech) in kidney transplant patients. Key findings of a study—measurable antibody response was detected only in one third of patients; level of antibodies was associated with a relative amount of CD8+ cells in antibody responders. Kidney function, level of anemia, mycophenolate mofetil use were important for antibody response.First data about the immunological response to SARS-CoV-2 in solid organ transplant (SOT) patients were received from those who recovered from COVID-19. Both T- and B-cell responses against SARS-CoV-2 were detected in the blood around 1 week after the onset of COVID-19 symptoms. In one of the studies , the autp = 0.003). These results contrast with the robust early immunogenicity observed in mRNA vaccine trials, including 100% anti-spike seroconversion by day 15 following vaccination with mRNA-12735 and by day 21 following vaccination with BNT162b2 [However, the situation after vaccination appeared to be different. Investigation of early serological response after first dose of COVID-19 Pfizer/BioNTech (BNT162b2) mRNA vaccines in 74 kidney transplant recipients showed a positive antibody level in only three transplant recipients at day 36 . In the BNT162b2 .p = 0.0001). In addition, the mean SARS-CoV-2 IgG titer of renal transplant recipients was significantly lower  [In our study we did not evaluate quantitative antibody response after the first dose of COVID-19 vaccine. That is why we can compare our study data with the reports of immune response after the second dose only. Our data showed that only 29% of kidney transplant recipients become SARS-CoV-2 positive three to six weeks after the second dose of the BNT162b2 (Pfizer-BioNTech) vaccine. Such a low response to COVID-19 vaccination of kidney transplant patients was confirmed in few already published studies. In a German study only 4 of 39 and 1 of 39 transplanted individuals showed IgA and IgG seroconversion 8 and 23 days after vaccination. Although most transplanted patients mounted spike-specific T helper cell responses, frequencies were significantly reduced compared with those in controls, and this was accompanied by a broad impairment in effector cytokine production, memory differentiation, and activation-related signatures. Spike-specific CD8+ T cell responses were almost undetectable in transplant patients . In anotp = 0.003) and a cyclosporine-based immunosuppressive regimen (p = 0.0003). T cell counts were not associated with the detection or the magnitude of the antibody but were associated with T cell response to the vaccine in univariate analysis  [The up to date published studies are small, and only some of them tried to find the most important factors associated to non-responsiveness. In a study with 45 kidney transplant recipients, only 17.8% of patients developed anti-spike SARSCoV-2 antibodies after two injections of mRNA BNT162b2 vaccine. In univariate analysis, predictive factors for a positive antibody response were the duration of kidney transplantation (for CD8) . We did p = 0.006), receiving ATG during the last year , lymphopenia , time from transplant <1 year  and eGFR < 30 mL/min/1.73 m2 . At multivariable analysis, diabetes and treatment with anti-thymocytes globulins during the last year were associated with vaccine no-response [The prospective study evaluated 117 SARS-CoV-2-naïve recipients of either kidney or kidney-pancreas grafts with assessment of IgM/IgG spike (S) antibodies and ELISpot against the nucleocapside (N) and the S protein at baseline and two weeks after receiving the second dose of the mRNA-1273 (Moderna) vaccine. Thirty-five patients 29.9%) developed either IgG or IgM two weeks after the second dose of the mRNA-1273 vaccine. At multivariable analysis, only baseline immunosuppression was significantly associated with no-response to the vaccine. 65.0% of patients developed either humoral or cellular response, while 35.0% did not develop any kind of response. Both humoral (either IgG or IgM) and cellular response (S-ELISpot positivity) was observed in 23 patients (19.6%). Considering vaccine non-responders (both IgG/IgM and S(ELISPot)-negative), the factors that were associated with an absence of response at univariable analysis were diabetes . Participants with a positive anti-spike serology were significantly younger, had a shorter period of time on maintenance dialysis before transplantation, and had a higher prevalence of living donors. The main difference in immunosuppression between the two groups was a lower rate of treatment with MMF and a lower rate of triple maintenance immunosuppression in responders. Seropositive patients had a significantly higher eGFR, and higher mean hemoglobin and lymphocyte counts. A longer period of time since transplantation was significantly associated with positive response to the vaccination. When multivariate analysis was performed, variables associated with negative humoral response were: older age , high-dose corticosteroids in the last 12 months  in 136 kidney transplant recipients and compared it to 25 controls. All participants in the control group had a positive antibody response to spike protein, while only 51 of 136 transplant recipients (37.5%) had positive serology , lower mycophenolic acid dose , younger age  and lower calcineurin inhibitor (CNI) blood level  [The association of worse kidney function and mycophenolate mofetil use with non-responsiveness to vaccination was also observed in a study of 308 kidney transplant recipients. Only 112 (36.4%) tested positive for anti-S antibodies two to four weeks after receiving the second dose of the BNT162b2 vaccine. Factors associated with antibody response were higher eGFR (OR 1.025 per mL/min/1.73 mp 0.014) .A highest rate of response after full vaccination of kidney transplant patients until now is reported in a study from France. They published the follow-up data of 205 kidney transplant patients who received two doses of the mRNA-1273 SARS-CoV-2 vaccine. 48% of study patients responded to vaccination. Patients who received their first transplant had a longer duration from transplant, experienced better graft function, and experienced lower levels of overall immunosuppression mounted a stronger immune response. Patients treated with calcineurin inhibitors, mycophenolate mofetil, or steroids showed significantly lower anti–SARS-CoV-2 antibody titers .p = 0.01 for CD3, p = 0.05 for CD4, p = 0.03 for CD8) [Lymphocytopenia and decreased CD3, CD4, and CD8 counts were common in patients with COVID-19 and correlate with disease severity . Severe for CD8) .During clinical evaluation of lymphocyte subpopulations by immunophenotyping, the absolute number of cells are mostly used to assess immunosuppression or immunodeficiencies, but in our study we did not find a statistically significant difference between anti-SARS-CoV-2 seropositive and seronegative patient groups with kidney transplant. The relative number of lymphocyte subpopulations can be useful to determine effects induced by viral infection, especially in immunocompromised patients; relative changes of CD8+ and CD4+ cells are reflected on CD4/CD8 ratio and worsen prognosis, while the difference in absolute numbers of lymphocyte subpopulations may not be detected. Similar mechanisms of action of vaccines could be expected if specific T cell immunity is achieved, depending on vaccine type ,37,38.p = 0.02), and the relative number of CD8+ T cells  in responders to the COVID-19 vaccine. It could be explained by the recent finding from Rha et al. [p = 0.02). Changes in the proportion of lymphocyte subpopulations after vaccination could be explained by SARS-CoV-2-specific CD8+ T cells formation and might be related to B cell activity or their phenotypes. It can be hypothesized that due to enhanced chemotaxis, part of B cells migrate to the site of vaccination and other lymphoid tissues, where they are activated and transformed to plasma cells producing specific immunoglobulins; in such a way the proportion of B lymphocytes among other lymphocytes in peripheral blood may be reduced, but changes in absolute numbers of CD19+ cells are not significant enough to be detected [In our study, there was no correlation between anti-SARS-CoV-2 antibodies and the absolute number of lymphocytes or their subpopulations . However, there was a significant negative correlation between anti-SARS-CoV-2 antibody level and CD4/CD8 ratio  directly correlate, and for seroconversion only a small amount of B lymphocytes (<1%) is needed . TherefoIn summary, the current vaccination strategy for kidney transplant recipients may not provide effective protection against COVID-19. Individual vaccination strategies might be needed and evaluated in clinical trials in the immunosuppressive cohort. In the meantime, these studies reinforce the need to continue good public health measures, such as hand hygiene, mask wearing, and social distancing, as practical means to help limit the spread of COVID-19 in our renal communities. In light of the reduced response in patients who received a kidney transplant, strategies that promote vaccination of close household contacts to provide so-called “ring vaccination” of those closest to transplant recipients seem a logical approach to reduce the chance of direct household spread .According to the levels of anti-SARS-CoV-2 antibodies, only one third of patients with kidney transplants develop sufficient antibody response after full COVID-19 vaccination with Pfizer-BioNTech. Factors that may significantly influence the adequacy of response to the COVID-19 vaccine in these patients are: better kidney function, higher hemoglobin levels, and no use of mycophenolate mofetil for immunosuppression.Even though in kidney transplant patients the level of humoral response developed after COVID-19 vaccination with Pfizer-BioNTech was not related to the absolute number of different lymphocyte subpopulations, it correlates with the relative number of CD8+ cells and negatively with the CD4/CD8 ratio in responders. This fact let us hypothesize about the importance of the relation between cellular and humoral immunity as well as other factors in the development of specific responses after COVID-19 vaccination in kidney transplant patients and emphasized the necessity of further extended studies.


Reductions in LDL-cholesterol, total cholesterol and triglycerides during the first month were 51 ± 25%, 32 ± 25% and 11 ± 40%, respectively, levels that remained stable throughout the first year . During follow-up, proteinuria improved from 57 (9–481) to 30 (7–520) mg/g (p = 0.021). In addition, eGFR remained stable, and no adverse events were reported. In our cohort, dyslipidemia treatment with PCSK9i was associated with decreased proteinuria in CKD patients, an effect that might be due to reduced lipid nephrotoxicity. Clinical trials are needed to further investigate whether this impact on proteinuria can significantly slow CKD progression in the long term.Control of dyslipidemia in chronic kidney disease (CKD) is not always guaranteed with statins and/or ezetimibe. Proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) have opened up a new era in lipid control, but their effect on renal function and proteinuria in real life have not yet been evaluated. The aim of the present study was to analyze the evolution of renal function and proteinuria in a cohort of CKD patients treated with PCSK9i. This retrospective multicentric cohort study included CKD patients treated with PCSK9i. Baseline epidemiological data, comorbidities and laboratory findings  were collected. The evolution of renal function, proteinuria and lipid profile was analyzed during the 1-year follow-up. The cohort included 76 patients . The mean baseline creatinine was 1.55 ± 0.77 mg/dL, and the mean eGFR was 52 ± 22 mL/min/1.73 m Chronic kidney disease (CKD) is a leading cause of cardiovascular events, especially in advanced stages . Both cl2) CKD patients not on dialysis, independently of low-density lipoprotein cholesterol (LDL-C) levels and without further testing or dose adjustment. Contrary to these recommendations and based on more recent epidemiological studies, the latest European Society of Cardiology and European Atherosclerosis Society guidelines suggested a “the lower, the better” strategy [2) or very high cardiovascular risk (eGFR below 30 mL/min/1.73m2). LDL-C targets for these patients were recommended as below 70 and 55 mg/dL, respectively [Among classic factors, dyslipidemia is one of the least frequent treatment targets in CKD patients. Current recommendations for lipid management vary according to different guidelines. The latest dyslipidemia guidelines published by a nephrology society were the 2013 Kidney Disease Improving Global Outcomes (KDIGO) clinical practice guidelines [strategy . These gCurrently available drugs for lowering LDL-C levels to recommended targets include statins, fibrates, ezetimibe and omega-3 fatty acids. However, most have proven insufficient for reaching the recommended goals, and they may present adverse reactions such as muscle or liver toxicity .2) [In this setting, a new pharmacological group has emerged, targeting liver-derived circulating proprotein convertase subtilisin/kexin type 9 (PCSK9) . The inh2) ,11.The relationship between lipids and kidney function is bidirectional. First, CKD patients present a dysregulated lipid profile ,13, in wSecond, dysregulated lipids can deposit in the kidney , causingGiven the absence of real-world data on the subject, we conducted a multicentric observational study to analyze changes in renal function and proteinuria in CKD patients treated with PCSK9i., the cohort included 76 patients; in total, 52 (68%) were male, and mean age was 66 ± 10 years. As regards comorbidities, 64 patients (84%) had hypertension and 52 (68%) were diabetic, while 15 patients (20%) had familial hypercholesterolemia. Turning to treatment, 68 (90%) patients were receiving statins prior to PCSK9i, 45 (59%) ezetimibe and 12 (16%) fibrates; 49 patients (65%) were receiving renin–angiotensin–aldosterone system (RAAS) inhibitors; and two (3%) selective sodium–glucose cotransporter 2 inhibitors (SGLT2i).As illustrated in Table 12. In total, 57 (75%) patients had a urine protein-to-creatinine ratio (UPCR), with a baseline median of 57 (interquartile range 9–481 mg/g) (The most frequent CKD etiology was hypertension (42%), followed by diabetic kidney disease (21%). The mean baseline creatinine was 1.55 ± 0.77 mg/dL, and the mean eGFR was 52 ± 22 mL/min/1.73 m81 mg/g) .Prior to PCSK9i initiation, lipid profile values were: total cholesterol (TC) 235 ± 71 mg/dL, LDL-C 154 ± 50 mg/dL, high-density lipoprotein cholesterol (HDL-C) 51 ± 12 mg/dL and triglycerides 160 (127–254) mg/dL . PCSK9i The lipid profiles improved during follow-up. TC, LDL-C and triglycerides decreased after PCSK9i initiation and during the first year. Mean reductions at the 1-month follow-up were 51 ± 25% for LDL-C, 11 ± 40% for triglycerides and 32 ± 25% for TC. In contrast, HDL-C showed no significant changes .p for trend = 0.021). UPCR reduction rates compared with baseline were 20 (−3–42) % at 1 month, 32 (−2–64) % at 3 months, 41 (8–65) % at 6 months and 38 (9–64) % at the end of follow-up. We divided the sample to test whether proteinuria reduction was higher in any patient subsets. Interestingly, patients with baseline UPCR below the median (57 mg/g) achieved significantly higher reductions (p = 0.04). As shown in Our study demonstrates that dyslipidemia treatment with PSCK9i safely improves lipid profiles in CKD patients, with a concomitant decrease in proteinuria (as assessed by UPCR). This is a novel observation with these agents, which can be explained by the classic hypothesis known as “lipid nephrotoxicity” .Our results invite the hypothesis that dyslipidemia control could decrease lipid-mediated damage in the kidney by the previously described mechanisms, which could explain the improvement in proteinuria seen in our series. This effect has previously been observed in treatment with statins, as shown in a meta-analysis by Palmer et al. , a studyThe effect of improving the lipid profile on the glomerular filtration rate is uncertain. Similar to our results, another meta-analysis conducted by Palmer et al. demonstrated no effect of statins use on eGRF . As suggThe beneficial effect of PCSK9i on proteinuria and glomerular filtration rate decline needs to be addressed. Evidence for a positive influence of PCSK9i on cardiovascular outcomes in CKD patients treated with statins has been published elsewhere . AlthougPCSK9i has been widely demonstrated to reduce LDL-C in patients at a high risk of cardiovascular events . This efThe safety profile of PCSK9i in our study was excellent. Previous studies in CKD have shown only a slightly higher rate of injection-site reactions, without evidence of severe adverse effects after PCSK9i prescription ,11. OccaThis study has some limitations; firstly, its retrospective design  and the lack of a control group. As a real-world study, however, follow-up assays were available in most patients, ensuring a sufficient sample size to demonstrate the effect of PCSK9i on eGFR and proteinuria. Moreover, although we included patients with diverse CKD etiologies whose proteinuria might be affected by multiple factors, we limited this impact by excluding those who had received treatments with an effect on this parameter. Unfortunately, the sample size was not big enough for an in-depth analysis of the changes in proteinuria by CKD etiology; and finally, follow-up was probably not sufficiently long to detect significant variations in kidney function. Nevertheless, the beneficial effect of PCSK9i on proteinuria was significant and clinically relevant from the first month of follow-up.We designed a multicenter retrospective cohort study. As the pilot center, we invited subjects to participate in the study via a memo sent to Spanish hospitals, finally including patients from five hospitals. Each center screened their CKD patients with PCSK9i, assessing criteria fulfilment and sending back information only on included subjects. Inclusion criteria were patients over 18 years with a CKD diagnosis according to KDIGO definitions  and an iWe collected baseline demographic data and data on comorbidities . Regarding CKD, baseline renal function was recorded as assessed by the CKD-EPI equation using creatinine and eGFR, UPCR and etiology . CKD etiInformation was collected on other treatments, including statins, ezetimibe and fibrates; antiproteinuric drugs such as RAAS blockers or SGLT2i and immunosuppressive therapy. Lipid profiles included LDL-C, triglycerides, HDL-C and TC levels. Regarding PCSK9i treatment, prescription indication, PCSK9i type  and starting dose were also registered.During follow-up, patients’ lipid and renal profiles were evaluated at 1, 3, 6 and 12 months after PCSK9i treatment initiation. The variation rates of lipids, eGFR and UPCR were calculated. UPCR variation was considered for analysis when it was higher than 10 mg/g at baseline. Adverse events were also collected.This study was approved by the Research Ethics Committee of La Princesa University Hospital  and was conducted in accordance with the ethical standards of the Declaration of Helsinki (as revised in Brazil 2013).Values are expressed as mean ± standard deviation or median (interquartile range), depending on their distribution. Comparisons between variables were performed using chi-square or t-tests for parametric variables and Fisher or Mann–Whitney tests for non-parametric variables. Repeat measures of lipid and kidney parameters during follow-up  were evaluated using linear models for repeated variables, providing estimations of significance for each trend. An additional analysis was performed regarding CKD etiology.p-values were <0.05.All statistical analyses were performed with SPSS 24.0 . Figures were drawn with GraphPad Prism 6.0 . Results were considered statistically significant when In summary, treatment of dyslipidemia with PSCK9i in patients with non-dialysis CKD is associated with a reduction in proteinuria, which could partially be explained by the mitigation of lipid nephrotoxicity. Large clinical trials with strict endpoints focused on kidney function are warranted to address the real effect of PCSK9i on glomerular filtration rate and proteinuria. Reducing the atherogenic effect of dyslipidemia is mandatory in CKD patients, as they are at high cardiovascular risk even in the absence of previous vascular events.


It is most important to measure blood pressure (BP) exactly in treating hypertension. Recent recommendations for diagnosing hypertension clearly acknowledge that an increase in BP attributable to the “whitecoat response” is frequently associated with manual BP recordings performed in community-based practice.However, there was no data about after-consult (AC) BP that could reduce whitecoat effect. So we evaluated before-consult (BC) and AC routine clinic BP and research based automated office blood pressure (AOBP) measured.The study population consisted of 82 consecutive patients with hypertension between April 2019 and December 2019. We measured routine clinic BP and AOBP before and after see a doctor, respectively. Seated blood pressure and pulse are measured at each time after a rest period using an automated device as it offers reduced potential for observer biases. AOBP was measured and measuring BP 3 times un-observed. We compared each BP parameter for identifying exact resting BP state.p = 0.015). However there was no difference in the BC and AC diastolic blood pressure . In the AOBP comparison, there was also significant difference .There was significant difference between BC and AC systolic BP (135.37 ± 16.90 vs. 131.95 ± 16.40 mmHg, In our study, AC AOBP was most lowest representing resting state. Although AC BP was higher than BC AOBP, it might be used as alternative measurement for reducing whitecoat effect in the routine clinical practice. The effect of blood pressure (BP) to cardiovascular disease is obvious . It has There is no concern that method of BP measurement is basic and important step in the hypertensive patient management. Hypertension guidelines described precisely BP measurement dividing conventional office BP, unattended office BP, out of office BP, Home BP, and ambulatory BP , 4. GeneHowever, an increase in BP attributable to the “white coat response” is frequently associated with manual office BP recordings performed in community-based practice –7. So, wWe evaluated before-consult (BC) and AC clinic BP and research based automated office blood pressure (AOBP) measured.Participants were required to meet all the following criteria: controlled hypertensive state with medication, older than 18 years, no medication change during recent 3 month. Detailed exclusion criteria are one or more of following below: patients with secondary hypertension, uncontrolled diabetes mellitus, chronic kidney disease needing dialysis, more 2 times of AST/ALT, drug sensitivity, atrial fibrillation or uncontrolled arrhythmia. All participants provided written informed consent.All major classes of antihypertensive agents were included in the formulary and we did not change medications during follow up period as possible as. Study investigators could also prescribe other antihypertensive medications.We measured three BP: office BP, AOBP and 24 h ambulatory BP (ABP). For office BP, an initial single observed BP measurement with non-invasive oscillometric system  was performed after 5 min of quiet rest period using appropriate cuff size for mid-arm circumference, seated in chair, cuff at mid sternal level, arm supported on a flat surface, feet flat on the floor, with no conversation during the measurement.AOBP was performed with another device  with the technique noted above but with the patient entirely alone in the exam room resting quietly and mean of three blood-pressure measurements was reported.Twenty-four-hour ABP was monitored using validated oscillometric arm devices . Measurements were performed at 15–30 min intervals for 24 h, and study participants were instructed to remain still with the forearm extended during each BP reading. Awake and night-time periods were defined 07:00 to 22:00, 22:01 to 06:59, repetitively. ABP recordings with less than 70 % usable BP readings were excluded. All valid awake and nighttime ABP readings were averaged to provide a single awake and nighttime ABP value per study participant.For office BP and AOBP, we repeated BP measurement after and before see a doctor with same method. We illustrated BP measurement pathway Fig. .Fig. 1BFor identifying target organ damage, we evaluated left ventricular hypertrophy, pulse wave velocity and microalbuminuria. Left ventricular hypertrophy (LVH) was defined by the increased left ventricular mass index (LVMI) in transthoracic echocardiography. (LVMI > 115 g/m2 in men and LVMI > 95 g/m2 in women), Pulse Wave Velocity (PWV) was measured by pulse waveform analyzer. , Urine Albumin-to-creatinine ratio (A/C ratio) was measured by a spot urine sample.Continuous variables are reported as mean ± standard deviation (SD). Frequencies are given as percentages. Differences between mean systolic and diastolic AOBP values and heart rate (HR) were assessed using paired t tests for “white coat effect” measurements. Similarly, differences between mean systolic and diastolic AOBP and 24-hour BP values were also assessed using t tests. We compared agreement between BP measurements in two ways: We used the method of Bland and Altman with bias  and 95 % limits of agreement with their confidence intervals. The analyses were performed using the software R, version 3.2.2 .A total of eighty two consecutive hypertensives fulfilling the criteria for enrollment were included in the study, 46 men and 36 women, with a mean age of 62.6 ± 13.7 years. Their clinical characteristics are shown in Tables P = 0.015)    unlike BC and AC diastolic BP. , 2.14 ± 7.65 mmHg (p = 0.023) in systolic BP and diastolic BP, respectively  Fig.  A Howeve15) Fig. B. Furthe06) Fig.  A. In thBP. Fig. B For clip = 0.001) representing resting state.When compare among all BP values, both systolic and diastolic AC AOBP was lowest .For BP variability analysis, we checked difference between BC BP and AC BP and defined as delta office BP and analyzed correlation between delta office BP and 24 h BP deviation. There was no significant association between delta office BP and 24 h BP variability , AC SBP  and BC and AC BP differences  between men and women.Lastly, we compared BC and AC BP difference between men and women. There was no significant difference in BC SBP (133.4 ± 15.3 vs. 137.8 ± 18.6 mmHg, To the best of our knowledge, this is first study to simultaneously compare BP values between before and after seeing a doctor for reducing white coat effect and examined for any differences in the mean AOBP when these readings were obtained before and after office consult. We also compared the office BP and AOBP values with 24 h ABP, which is generally accepted as a more sensitive risk predictor than office BP of CV events, in order to investigate any differences between AOBP and 24 h ABP values , 9.Our findings showed that based on the automated BP measurement device, AC systolic BP was lower when readings with after seeing a doctor were taken. Furthermore, AC systolic AOBP had further lower in the similar situation. The mild association between AC BP and 24 h ABP values was observed and the value was higher than other BP values. So, it should be highlighted that AC BP measurement should be considered as alternative routine practice.The overall prevalence of white coat hypertension in the general population is estimated to be approximately 10–15 %, and it amounts to 30 % in patients with increased clinic BP recordings . AlthougIn our study, white coat effect was about 9.8 % when we defined as 20mmHg difference between BC and AC systolic BP. So, AC BP that we measured BP after consult is fit to take a sufficient time and reduce white coat effect.Recently, a study was performed for reducing white coat effect . EmmanueWe still used 24 h ABP as reference standard. A recent meta-analysis showed that due to the significant heterogeneity it is believed that use of the AOBP should not replace daytime ABP.Interestingly, it should be highlighted that AC systolic AOBP value was lower than 24 h ABP. Our findings are inconsistent with those of others , 14 thatThis study has several limitations. First, it should be mentioned that the entrance of the study personnel into the examination room before recording before or after-consult BP with 5 min resting cannot completely eliminate noisy circumstance. However, we believe that situation reflected more real clinical practice. Second, the relatively small size of the study population may limit generalization of study results. Third, we could not check the long-term prognosis because we concentrated on method of BP measurement. We will identify the adverse event in the near future.In our study, AC AOBP was most lowest representing resting state. Overall AC BP including routine BP and AOBP was lower than BC BP. Based on the present results, although AC BP was higher than BC AOBP, it might be used as alternative measurement in the routine clinical practice for reducing white coat effect.


This study evaluated oxygen uptake (VOn = 21) and 12 months (n = 14) after transplantation and a control group of healthy young adults (n = 16) underwent cardiopulmonary exercise testing on cycle-ergometer. The protocol consisted in two subsequent constant, moderate-load exercise phases with a final incremental test until exhaustion.Two groups of KTRs enrolled 3 . Peak VO2 was lower in KTRs evaluated 3 months after transplantation compared to patients evaluated after 1 year . Blood haemoglobin (Hb) concentration was higher in KTRs evaluated at 12 months . Among KTRs, τ showed a moderate negative correlation with Peak VO2 (ρ = − 0.52) and Oxygen uptake efficiency slope (OUES) (r = − 0.57) while no significant correlation with Hb and peak heart rate.The time constant of VO2 kinetics compared to healthy controls. Hb and peak VO2 seem to improve during the first year after transplantation. VO2 kinetics were significantly associated with indices of cardiorespiratory fitness, but less with central determinants of aerobic capacity, thus suggesting a potential usefulness of adding this index of muscular oxidative metabolism to functional evaluation in KTRs.KTRs show slower VOThe online version contains supplementary material available at 10.1007/s00421-021-04672-x. Scientific evidence clearly shows that cardiorespiratory fitness is a strong predictor of all-cause and cardiovascular mortality independent of age, sex, ethnicity, and comorbidities , i.e., the rate of adjustment of the oxygen consumption to a sudden increase in workload during the transition from rest to constant, moderate intensity exercise, is thought to reflect the oxygen utilization at a peripheral muscular level . All procedures were conducted in accordance with the Declaration of Helsinki and patients provided written informed consent. The evaluation was performed during routine clinical exercise testing, as previously described for other patient population . To overcome the possible drop-outs that could have arisen testing patients on two different days, a specific protocol was designed to obtain both constant load and incremental exercise testing data in a single clinical evaluation Fig. . The pro2 kinetics during the transition from unloaded pedalling to moderate intensity exercise. First, the VO2 responses were linearly interpolated using a mathematical software  to provide one value of VO2 per second; thereafter the values of the two bouts were averaged. Iterative nonlinear regression (Levenberg–Marquardt procedure) was used to characterize the primary VO2 response after removing the first 20 s of data , fitting the resting 5 min in a mono-exponential function according to the following equation:2(t) is the VO2 at time t; VO2(bl) is the baseline VO2 measured in the 30 s preceding the transition to exercise; and Ap, TDp, and τ are the amplitude, time delay, and the time constant of the primary (phase 2) response of VO2 kinetics, respectively.The first two constant load bouts were used for the determination of the VO2 at peak exercise (peak VO2) was determined during a final, incremental ramp testing until patients’ exhaustion, defining peak VO2 as the highest average VO2 recorded during a 30-s period of testing. The first ventilatory threshold (VT1) was estimated using the V-slope method and evaluating the ventilatory equivalent of VO2  with post hoc analysis (Tuckey’s post hoc test) was performed on all normally distributed variables. For parameters that violated the assumption of homogeneity of variances, a Welch test was performed and Games-Howell post hoc tests were used for multiple comparisons. For variables that showed a non-normal distribution in at least one of the three groups, a Kruskal–Wallis H test was performed and pairwise comparisons were conducted using Dunn’s (1964) procedure with a Bonferroni correction for multiple comparisons. A statistical significance level of 0.05 was used for all tests; pairwise comparisons results were expressed as adjusted P values. Controlling data for outliers, the analysis was performed also removing the outliers and their presence was tolerated if they did not alter the significance of the results obtained. To assess correlations between variables, Pearson’s r or Spearman’s rho correlation indexes were used for normally and non-normally distributed variables, respectively. Statistical analysis was performed using SPSS .Normality of variables was checked using the Shapiro–Wilk test. For comparisons between two groups, a chi-square test was used to assess the differences between categorical variables. In the case expected cell frequencies were greater than five a Fisher’s exact test was used. For continuous variables, a 2, maximal power output, VO2 at the VT1 and peak heart rate. The VO2/Work Rate slope was, however, comparable between all groups , maximal power output  and OUES  were found higher 1 year post-surgery. This was also confirmed by a more efficient ventilation as shown by the lower VE/VCO2 slope 12 months after transplantation  , peak power output , VO2 at the VT1 , power output at the VT1  and the OUES . No significant correlation was found between τ and Hb  or percentage-predicted peak heart rate (HR) . Conversely, Hb was more strongly correlated with main parameters of cardiorespiratory fitness, similarly to what found for patients’ peak HR . This value seems to improve 1 year after transplant . These results confirm existing data on VO2 improvement after kidney transplant  , which were comparable for KTRs of the 12-month group  . Although these data cannot provide information regarding the underpinning pathophysiological mechanisms affecting VO2 kinetics, study outcomes may suggest that also peripheral adaptations occur after kidney transplantation. As previously mentioned, current evidence supports the hypothesis that slowed VO2 kinetics during moderate intensity cycling mainly reflect an impaired oxidative capacity of the muscle. Even if this assumption is still debated, particularly for patients with chronic diseases  Below is the link to the electronic supplementary material.


Machine learning methods, such as hierarchical clustering and logistic regression, were used. Clustering resulted in the identification of two clusters, one including all individuals with CKD (n = 17), while the second one included all the healthy volunteers (n = 10) and the remaining individuals with CKD (n = 13), resulting in 100% specificity. Logistic regression identified five radiomic features to classify participants as with CKD vs. healthy volunteers, with a sensitivity and specificity of 93% and 70%, respectively, and an AUC of 0.95. Similarly, four radiomic features were able to classify participants as rapid vs. non-rapid CKD progressors among the 30 individuals with CKD, with a sensitivity and specificity of 71% and 43%, respectively, and an AUC of 0.75. These promising preliminary data should support future studies with larger numbers of participants with varied disease severity and etiologies to improve performance.Given the central role of interstitial fibrosis in disease progression in chronic kidney disease (CKD), a role for diffusion-weighted MRI has been pursued. We evaluated the feasibility and preliminary efficacy of using radiomic features to phenotype apparent diffusion coefficient (ADC) maps and hence to the clinical classification(s) of the participants. The study involved 40 individuals (10 healthy and 30 with CKD (eGFR < 60 mL/min/1.73 m Approximately 15% of adults in the United States have chronic kidney disease (CKD) , but the2), we found lower levels of ADC in individuals with CKD compared to age-matched healthy controls, but the difference did not reach statistical significance [Kidney tubulointerstitial fibrosis is recognized as a hallmark of progressive CKD . By asseificance . While tificance ,7,8,9,10ificance . Such meificance , kidney ificance , and kidificance . Based oificance , we now 2. Healthy volunteers took no prescribed medications and had no history of CKD, diabetes mellitus, hypertension, coronary artery disease, congestive heart failure, liver disease, or autoimmune disease. Exclusion criteria were (1) significant co-morbid conditions that led the investigator to conclude that life expectancy was less than 1 year; (2) expected to progress to end-stage kidney disease, requiring the initiation of dialysis or a kidney transplant in the subsequent 24 months; (3) pregnant or nursing; (4) involved in any other interventional research protocol; (5) decompensated heart failure; (6) previous diagnosis of renal artery stenosis or ureteral obstruction; (7) CKD of other etiologies, such as glomerular disease, interstitial disease, and polycystic kidney disease; (8) chronic use of non-steroidal anti-inflammatory agents (NSAIDs); and (9) patients treated for anemia with ferumoxytol. Participants were recruited from NorthShore University HealthSystem and the University of Chicago. All participants provided written informed consent. The study protocol was approved by the Institutional Review Boards at NorthShore University HealthSystem and the University of Chicago and is in accordance with the principles of the Declaration of Helsinki. We enrolled 41 individuals with CKD and 13 healthy volunteers. We excluded 14 individuals for image analysis due to the presence of cysts  and 2 who were missing MRI data , which yielded a total sample size of 40 for this study .We performed kidney diffusion-weighted MRI on individuals with and without CKD, as previously described . We incl2. Acquisitions were repeated 5 times and averaged to improve signal-to-noise ratio and to minimize motion artifact.All MRI procedures were performed on a 3 Tesla whole-body scanner  using body array coils after an overnight fast. Participants were instructed to hold NSAIDs for 3 days prior, angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers for 1 day prior, and loop diuretics on the day of the MRI. Medications were restarted following MRI data acquisition. Participants were scanned in a feet-first supine position. A spin-echo echo-planar imaging (EPI) technique with 3 directions of diffusion-sensitizing gradients were used to acquire diffusion-weighted images in five coronal planes during free breathing . Diffusi−5 for a range of ADC values from 0 to 4 × 10−3 mm2/s was used for all individual datasets. A total of 54 radiomics features were generated for left and right kidney ADC maps and averaged for a single representative value for each participant. The radiomic features from the right and left kidneys were highly correlated (Spearman ρ = 0.986 and p << 0.01), supporting their combination. FV software includes several categories of radiomic features. The radiomic features are separated into first-order (histogram features), such as central tendency parameters , gray level co-occurrence matrix (GLCM), and gray level run length matrix (GLRLM) textural features [The image analysis workflow is shown in features . A recenfeatures  document2 per year), respectively.In analyses that compared the 54 radiomic features in healthy volunteers and individuals with CKD, the exposure variable was CKD status . In analyses that investigated the associations of the 54 radiomic features with CKD status and CKD progressor status, the exposure variables were the radiomic features, and the outcomes were CKD status and rapid progressor status , and eGFR. Blood pressure, proteinuria, and additional eGFR measurements were collected from the electronic medical record for CKD patients. We used the creatinine-based CKD Epidemiology Collaboration 2009 equation to calculate eGFR . Proteint-test for normally distributed continuous variables and a Wilcoxon rank-sum test for non-normally distributed continuous variables. We used Spearman correlation coefficients to determine associations between non-normally distributed continuous variables.Descriptive statistics were summarized as count with percentages for categorical variables and mean ± standard deviation (SD) or median with interquartile range for normally distributed continuous variables or non-normally distributed continuous variables, respectively. To evaluate differences in radiomic parameters and clinical variables by CKD status, we used a u and v was calculated using distance correlation: t-test for normally distributed continuous variables and a Wilcoxon rank-sum test for non-normally distributed continuous variables.We performed a hierarchical cluster analysis to identify distinct clusters of radiomic features using the Seaborn Clustermap module in Python 3.7 . We tran−mean)SD . Clinicav−v¯)‖2  . We creav−v¯)‖2  . We utilp-values < 0.05 were considered significant. In additional analyses, in individuals with CKD, we created 3 models using radiomics, clinical features, and a combination of both, to predict rapid versus non-rapid progressors.We also performed logistic regression to identify the most prominent features that distinguish those individuals with known CKD from the controls . The regp = 0.05). The mean eGFR was lower in the individuals with CKD compared to the healthy volunteers (51.5 ± 12.2 vs. 88.6 ± 12.6) mL/min/1.73 m2; p < 0.001). The median urine protein excretion was 0.16 (IQR 0.02–0.25) g/day in individuals with CKD. The individuals with CKD had a higher BMI than the healthy volunteers . During a mean follow-up time of 4.4 years, the mean annual eGFR slope was −0.5 ± 3.7 mL/min/1.73 m2 per year in the individuals with CKD. Seven participants (23%) experienced rapid CKD progression, defined as a mean annual loss of eGFR > 3 mL/min/1.73 m2 per year.Baseline characteristics of the study cohort are shown in p < 0.001).ρ = 0.58 and p < 0.001). LongRunLowGLEmph had the strongest correlation with BMI (ρ = 0.47 and p = 0.002). SecMeasInfoCor had the strongest correlation with SBP (ρ = −0.51 and p = 0.004). p = 0.001).2, respectively (p = 0.002). There were no significant differences in eGFR slope, BMI, SBP, DBP, age, or blood glucose by cluster. There were 39 radiomic parameters that differed between the clusters. There were three measurements that were significantly different between the CKD and healthy groups that were not different between clusters, including 0.5, FirstMeasInfoCor, and LongRunHighGLEmph. There were five measurements that were significantly different between clusters that were not different between the CKD and healthy groups, including skewness, 0.99, JointMax, GLCMCor, and ClstProm.n = 40), the stepwise inclusion of the following features improved the AUC-ROC: GLNU, ShortRunHighGLEmph, GLCMContr, kurtosis, and skewness. For predicting CKD, the model’s sensitivity was 93%, specificity was 70%, and the AUC-ROC was 0.95.To predict CKD vs. healthy volunteers in the entire cohort . To predict rapid progressor vs. non-rapid progressor status among individuals with CKD (n = 30), we created three models using radiomics, baseline clinical features, and both radiomics and baseline clinical features (The rapid and non-rapid progressors had a mean annual eGFR slope of −5.27 ± 2.61 and 0.92 ± 2.57 mL/min/1.73 mfeatures . In the In this preliminary feasibility study, we identified significant differences in radiomic features derived from kidney ADC maps in individuals with mild to moderate CKD and healthy volunteers. Using unsupervised hierarchical clustering, a machine learning approach, we were able to identify two clusters with distinct radiomic signatures and clinical phenotypes—one cluster included individuals with CKD and another cluster that had a mixture of individuals with CKD and healthy volunteers. Finally, a logistic regression model was able to identify five radiomic features that distinguished individuals with CKD from healthy volunteers. Our modeling approach that included four radiomic features had a limited ability to classify individuals who experienced rapid CKD progression from individuals without rapid CKD progression. Proteinuria was the strongest clinical variable associated with rapidly progressive CKD, which was previously reported . In thisKidney cortical fibrosis is recognized as a hallmark of progressive CKD ,23. QuanPrior studies have demonstrated promise for the use of radiomics to identify signatures of disease independent of clinical variables . A recenThe strengths of our study include the use of individuals with CKD and age-matched healthy volunteers and the use of advanced image processing tools to generate radiomic features from kidney ADC maps. We also used kidney ADC parametric maps that have less inter-study variability than signal intensity, which can be influenced by instrument and acquisition parameters specific to each collection. Our study has several limitations that warrant consideration, as well. Our preliminary feasibility study utilized existing data in a small number of individuals, and future studies that include more individuals across the spectrum of CKD severity, with longer follow-ups, are needed to fully evaluate the efficacy of these approaches by allowing for appropriate size for cross validation, external validation, and comprehensive multivariable adjustment of potential confounders. We only used the 54 radiomic features available in FV, while many other encoding methods exist , which wIn conclusion, a number of radiomic features showed significant differences between individuals with CKD and healthy volunteers on kidney ADC maps, even though mean ADC values were not significantly different. Importantly, our preliminary data support the use of machine learning-based clustering techniques of radiomic features of quantitative MRI parametric maps to provide additional phenotyping of individuals with CKD. Our findings suggest the need for larger prospective studies that incorporate radiomics-based approaches to analyze kidney MRI as a tool to identity individuals at high risk of rapid CKD progression, in an effort to improve upon existing prediction models.


Left ventricular stroke volume (LV SV) and right ventricular ejection fraction (RV EF) improved significantly with CPAP therapy . All other cardiac parameters did not change significantly while mean systolic and diastolic blood pressure improved significantly (p < 0.01). 21 patients were assigned to the non-compliance group and were considered as a control group. There were no relevant differences in cardiac parameters between baseline and follow up examination in these patients. CPAP therapy seems to improve LV SV, RV EF, systolic and diastolic blood pressure in OSAS patients, but reproducibility of our results need to be confirmed in a larger patient population.The obstructive sleep apnoea syndrome (OSAS) is a disorder with a high prevalence and is associated with an elevated cardiovascular risk and increased morbidity and mortality. For longitudinal studies and functional analysis cardiac MRI is regarded as the gold standard. Aim of this study was to evaluate the long-term effect of continuous positive airway pressure (CPAP) therapy on cardiac functional parameters with cardiac Magnetic Resonance Imaging (cMRI). 54 patients with OSAS (mean apnea hypopnea index-AHI: 31) were prospectively enrolled in this study and cMRI was performed before and after 7 months of CPAP therapy. Data were acquired on a 1.5 T MRI and right and left ventricular cardiac function were analysed. CPAP treatment was considered compliant when used Obstructive sleep apnea syndrome (OSAS) is a common sleep-related breathing disorder associated with heart failure –3. PeoplThe purpose of this study was to investigate the long-term effects of CPAP therapy on cardiac morphology and function in OSAS using cMRI and the long-term effect on blood pressure.54  patients were included in this prospective study. Patients with atrial fibrillation, moderate to severe valvular heart disease, known coronary artery disease (CAD), previous cardiac surgery or any contraindication to cMRI or CPAP were excluded from the study.All study subjects underwent a complete medical work-up including medication, clinical chemistry and physical examination. Use of medication was assessed at baseline and at follow-up measurements. Before OSAS treatment diagnostic polysomnography was performed. In this setting, the degree of OSAS and the sleep disturbance was quantified. The apnea hypopnea index (AHI) was assessed. Sleep stages were scored according to the standard criteria of the American Academy of Sleep Medicine . ObstrucOnly in CPAP-naive patients newly diagnosed with OSAS based on the overnight polysomnographic (PSG) exam (AHI > 5/h) baseline cMRI and 24 h blood pressure monitoring was performed.After baseline cMRI all patients initiated CPAP treatment with CPAP machines equipped with compliance monitors that measured CPAP use. The prescribed CPAP pressure was based on a titration study that eliminated respiratory events and improved oxyhemoglobin saturation during sleep. Adequate compliance to the prescribed pressure of CPAP was defined as more than 4 h of CPAP use per night on a routine basis , 17. PatWritten informed consent was obtained from all patients and the institutional review board approved the study.2, matrix 126 × 256, repetition time 9.9 ms, echo time 4.8 ms, flip angle 30°, slice thickness 8 mm) with a temporal resolution of 45 ms per image phase.CMRI analysis was an average of independent readings performed by two observers (W.W. and A.S.) with more than 10 and 20 years of experience in cMRI, respectively, who were blinded to patient and other imaging data. Only patients examined at baseline and after 7 months of CPAP therapy were included in the final analysis. All patients were examined with a 1.5 T scanner  and a 4-channel phased array body coil in supine position. Short, long axis and axial cine imaging was performed during breath-hold employing segmented 2D spoiled GRE sequences , enddiastolic volume (EDV), endsystolic volume (ESV), stroke volume (SV), and LV myocardial mass (MM).The nonparametric Wilcoxon’s matched-pairs test was used to evaluate differences between baseline and follow-up examination results. To compare baseline values between the study and control group student`s t-test was used. A p-value of < 0.05 was considered statistical significant. All parameters are given as mean ± standard deviation. Statistical analysis was performed using the software package SPSS Statistics version 21 .54 patients underwent both baseline and follow-up cMRI and were included in the data analysis. 33 patients  were assigned to the compliance group and 21 patients  to the non-compliant (control) group.See Tables CPAP therapy was used 5.6 ± 1.2 h/night.2, at follow up 33 ± 6 kg/m2. Baseline AHI was 34 ± 24 h, the minimum oxygen saturation was 72 ± 10%.At baseline, the mean BMI was 33 ± 7 kg/m24 h blood pressure monitoring results could be retrieved in 25/33 (76%) patients.At time of enrollment, the mean systolic and diastolic BP was 135 ± 12 mmHg and 83 ± 9 mmHg, respectively. At follow up the mean systolic and diastolic BP improved significantly .7/33 (21%) patients were on antihypertensive drugs . In 2/33 (6%) patients antihypertensive medication was started during CPAP therapy.CPAP therapy was used 1.9 ± 1.2 h/night.2, at follow up 30 ± 5 kg/m2. Baseline AHI was 27 ± 19 h, the minimum oxygen saturation was 75 ± 10%.At baseline, the mean BMI was 31 ± 5 kg/m24 h blood pressure monitoring results could be retrieved in 13/21 (62%) patients.At time of enrollment, the mean systolic and diastolic BP was 131 ± 13 mmHg and 83 ± 10 mmHg, respectively. At follow up the mean systolic and diastolic BP improved but only the diastolic pressure significantly .6/21 (28%) patients were on antihypertensive drugs and antihypertensive medication was not changed during CPAP therapy.Baseline AHI and blood pressure results did not differ significantly between the study and non compliant group.Baseline cardiac parameters did not differ significantly between the study and control group. See Tables Image quality was diagnostic in all patients and the examination could be completed in all cases.LV SV and RV EF improved significantly after CPAP therapy (93 ± 19 ml vs. 99 ± 20 ml—p = 0.02 and 50 ± 6% vs. 52 ± 6% at follow up—p = 0.04). All other LV and RV cardiac parameters did not change significantly. In 3/33 patients (9%) LV EF improved by 15% and in 1/33 patients (3%) RV EF increased by 15%.There was no significant difference between baseline and follow up examination in the control group.We investigated cardiac effects of CPAP-therapy on 54 patients with OSAS after 7 months of treatment. LV SV, RV EF and systolic as well as diastolic blood pressure improved significantly in the compliance group using CPAP masks at least 4 h per night.In OSAS recurrent episodes of complete obstruction (apnea) or partial obstruction (hypopnea) of the upper airway lead to intermittent hypoxia during sleep. Sleep can be divided in different stages and heart rate and systemic blood pressure are reduced and reach its lowest levels during the early periods of slow-wave sleep , 20. ReaNot only the systemic pressure alters during sleep but also there is evidence that pulmonary artery pressure also changes during the obstructive sleep apnea cycle . The strApart from our study there are only two other previous reports using cMRI to examine the longitudinal effect of CPAP on cardiac functional parameters in OSAS patients.In the first study, Magalang et al.  investigIn the second published study by Colish et al.  47 patieSome of the previously published studies using echocardiography report a positive effect of CPAP therapy on LV functional parameters associated with OSAS , some doEchocardiography data on the RV is sparse and only some papers are available. Bayram et al.  for examOne reason for discrepancy between the results of cMRI and echocardiography studies could be that MR imaging enables more accurate morphologic analyses than does echocardiography . CMRI isOur study has several limitations.First, the number of patients included is rather small but within the range of previous reported studies.Second, not all 24-h blood pressure monitoring results could be retrieved (76% in the compliant and 62% in the non compliant group).Third, there was a change of medication  in 2 patients (study group) between baseline and follow up cMRI. However in 31/33 (94%) patients medication was not altered thus we believe our results are representative for the effect of CPAP therapy.Fourth, due to the small but significant differences found between RV and LV functional parameters the clinical significance needs to be confirmed in a larger patient cohort.Using CPAP therapy > 4 h/night seems to improve LV SV and RV EF as measured with cMRI. It also seems to lower diastolic blood pressure even when used for less than 4 h/night.


The blood pressure (BP) is regulated by multiple neurophysiologic elements over multiple temporal scales. The multiscale dynamics of continuous beat-to-beat BP series, which can be characterized by “BP complexity”, may, thus, capture the subtle changes of those elements, and be associated with the level of functional status in older adults. We aimed to characterize the relationships between BP complexity and several important functions in older adults and to understand the underlying factors contributing to BP complexity.A total of 400 older adults completed a series of clinical and functional assessments, a finger BP assessment of at least 10 min, and blood sample and vessel function tests. Their hypertensive characteristics, cognitive function, mobility, functional independence, blood composition, arterial stiffness, and endothelial function were assessed. The complexity of systolic (SBP) and diastolic (DBP) BP series was measured using multiscale entropy.p < 0.005), cognitive function , and diminished mobility . Greater arterial stiffness , decreased endothelial function , and excessed level of blood lipids (p < 0.03) were the main contributors to BP complexity.We observed that lower SBP and DBP complexity was significantly associated with poorer functional independence (β > 0.17, Blood pressure complexity is closely associated with the level of multiple functional statuses and cardiovascular health in older adults with and without hypertension, providing novel insights into the physiology underlying BP regulation. The findings suggest that this BP complexity metric would serve as a novel marker to help characterize and manage the functionalities in older adults. Cardiovascular health is critical to maintaining functional independence in everyday activities in older adults. The conditions in the cardiovascular system have been linked to diminished functionalities. Hypertension, for example, a condition related to abnormal blood pressure (BP) regulation, is highly prevalent in older adults  and has multiple, not single, scales of time , as quantified using multiscale entropy (MSE) , is assoIn this study, we assessed multiple functions  in a group of older adults, measured their BP complexity, and assessed the characteristics of blood samples and vessels. We hypothesized that: (1) lower BP complexity would be associated with poorer functions and (2) with the alterations in blood composition  and in vessel function , suggesting the disruption in multiscale dynamics of BP fluctuation.via the data repository in the Department of Gerontology, Shenzhen People's Hospital, Shenzhen, China. Older adults who had a clinical visit for primary care/annual physical examination within the previous year and expressed interests in participating in future studies were contacted. The inclusion criteria were: (1) age greater than 60 years and (2) with the ability to walk for at least 1 min without physical assistance. The exclusion criteria were: (1) inability to understand the study protocol; (2) the diagnosis of terminal disease ; (3) the diagnosis of overt neurological diseases ; (4) history of brain trauma or injury; (5) hospitalization within past 6 months; (6) uncontrolled hypertension; (7) chronic kidney disease and dyslipidemia; and (8) other cardiovascular diseases  or targeted organ damage. All the experimental methods and protocols were approved by the Institutional Review Board of Shenzhen People's Hospital and carried out in accordance with the guidelines in the Declaration of Helsinki. All the participants provided a written consent in order to participate in this study.The participants were recruited After the screening, a total of 400 eligible older adults were eligible for the following tests. Each eligible participant completed two study visits separated by one day. On the first visit, they completed a series of questionnaires to assess the clinical characteristics, the functional dependence of daily activities, the Mini-Mental State Examination (MMSE) for general cognitive function, and the timed-up-and-go (TUG) test for mobility. On the second study visit, they completed the assessment of continuous BP, the blood sample test, and the assessment of arterial stiffness and vascular endothelial function. One study personnel monitored all the procedures for each visit to ensure the safety of participants.Hypertension is the main condition in this population and affects BP regulation. We thus here carefully assessed the characteristics related to hypertension following the clinical diagnosis of each participant. Specifically, hypertension was characterized as the systolic BP (SBP) ≥ 140 mm Hg and/or diastolic BP (DBP) ≥ 90 mm Hg by measuring the brachial artery of the right arm using a digital sphygmomanometer . The duration of hypertension  was recorded. In hypertensive participants, hypertension had been controlled using the antihypertension medication. The antihypertension medication consisted of calcium channel blockers (CCBs), angiotensin-converting enzyme inhibitors (ACEI), angiotensin-II receptor blockers (ARB), beta-blockers (BBs), and diuretics. The number of participants using each type of medication, and the number of antihypertensive medications each participant used at the same time were recorded.Barthel index for activities of daily living (ADL)  was usedThe Chinese version of MMSE , 15 was The mobility of participants was assessed using a timed-up-and-go test (TUG). The TUG measures the time taken to stand from a chair, walk forward three meters, turn around, walk back, and return to a seated position . The timParticipants completed the blood sample test in the early morning of the second visit. They were asked to not eat before the visit. One experienced and trained nurse dropped the blood of 3 milliliters from the left arm of each participant when he/she was sitting in the chair. Multiple blood composition metrics, including those related to blood lipids , blood protein , blood sugar , and the kidney function , were analyzed by two analyzers . We then constructed a composite score of blood lipids using CHOL, HDL, and LDL. We also calculated the BUN/Cr ratio, an important marker for kidney function . Both thAfter at least 30 min of resting, each participant then completed a BP assessment when sitting in a quiet assessment room with one study staff. During the BP assessment, the participant was instructed to not talk and to keep motionless . The objects which may interfere with the testing, such as the mobile phone, were saved outside the room. The continuous SBP and DBP series were recorded using the Finometer PRO system  at the middle finger of the left hand in a supine position for 10 to 15 min. The sampling frequency was 100 Hz . All then = 140) was greater than that is recommended for reliable estimation of sample entropy with the parameters we used  . The sample entropies of each “coarse-grained” series were then calculated by using the negative natural logarithm of the conditional probability that a time series, having repeated itself within a tolerance r for m points (pattern length), will also repeat itself for m + 1 points without self-matches , 20, 21.100–289) .In addition, the mean and variability  of beat-to-beat SBP and DBP were calculated and used in the following analyses.Following the standard testing procedures as suggested in the previous studies –24, the p < 0.05.Statistical analyses were performed with JMP Pro. 15 software  and Mplus 8.4 . Data distribution and missing values were checked for all the variables. The significance level was set at We first examined the effects of hypertension on demographics, functionalities, vascular function, BP complexity, mean, and variability of BP by using ANOVA models. The factor of each model was hypertensive status , and the dependent variable was each of those outcomes.Then to examine the relationships between BP complexity  and the functionalities, linear regression models were used. The relationship of BP complexity with functional independence in daily activities , mobility , and cognitive function  was examined in the separate models. Similarly, linear regression analyses were also used to examine the relationship between traditional BP measures  and those functional characteristics. Age, sex, body mass index (BMI), the status of regular use of alcohol  and smoking  and hypertensive status , the use of antihypertension medication, and the duration of hypertension were included as covariates in these regression models. Secondarily, within the hypertensive group, we also explored the relationship between BP complexity and the duration of hypertension using the regression model, in which age, sex, BMI, smoking, and alcohol status were included as covariates.To examine the relationship between characteristics of blood lipids and vessel and BP complexity, we first used confirmatory factor analysis (CFA) with maximum likelihood estimation to derive the separate composite scores for blood lipids and vessels. Each composite score had a mean of 0 and a variance of 1. The relationships between each of the composite scores and BP complexity were examined using separate regression models. We then further used separate linear regression models to explore the relationship of BP complexity with each metric of blood composition related to proteins, lipids, and kidney function, and the metrics of vessel function. All these models were adjusted for age, sex, BMI, the status of regular use of alcohol  and smoking , and hypertensive status , the use of antihypertension medication, and the duration of hypertension. To enhance the interpretability of the regression coefficients, BP complexity was standardized for models.p < 0.03). Meanwhile, it was also observed that compared with the normotensive, the hypertensive group had significantly lower BP complexity (p < 0.004), which was consistent with our previous studies (p = 0.28–0.55).All the participants completed the tests of this study. A total of 247 participants were identified as hypertensive and the other 153 were normotensive.  studies . No signp = 0.001; DBP: β = −0.57, p = 0.003; p = 0.002; DBP: β = 0.17, p = 0.005), and MMSE score  (p = 0.21–0.91) (p = 0.01) and/or DBP  complexity, and such relationships were independent of age, sex, BMI, smoking, and alcohol status. = 0.01) . Specifi = 0.01) . No such21–0.91) . All thep < 0.001) and DBP  complexity. After adjusting for covariates, the association was attenuated but remained significant for both SBP  and DBP complexity  (p > 0.05).In unadjusted models, the composite score of vessel characteristics had a significant association with SBP  . Meanwhip = 0.02; DBP: β = −0.42, p = 0.01) and right  baPWV. Participants with greater baPWV  had lower complexity of SBP and/or DBP. A significant association between FMD and BP complexity was also observed, that is, participants with lower FMD had lower SBP  and/or DBP  complexity , higher LDL , CHOL , and/or TG  had lower BP complexity (p = 0.02) and/or DBP  complexity. No significant association was observed between BP complexity and other blood composition metrics , and between the mean BP level and the blood composition metrics  and/or diminished endothelial function  had lower BP complexity, suggesting the disrupted patterns of the BP fluctuations. Blood lipids are important to our vascular circulation system. For example, cholesterol is needed to build artery walls and to make hormones and vitamin D , and theOn the other hand, the alterations in the characteristics of blood lipids and vessels are highly prevalent in the older adults with hypertension and have been closely linked to the risk of cardiovascular events  , 41, 42.Another significant pathological condition in older adults is the kidney disease, which can be assessed by an abnormal level of BUN, Cr, or UA in blood. More recently, studies have shown that the ratio of BUN to Cr  is sensitive to the renal dysfunction , 44. In One important limitation is that this study only examined the cross-sectional relationship between BP complexity and functional status. Therefore, future longitudinal studies are highly demanded to examine the casual relationship between BP complexity and the changes in those functional statuses and the pathology of the conditions related to abnormal regulation of BP . The use of antihypertension medication in the hypertensive group may potentially contribute to BP complexity and other functions. Though we included the medication information in our analyses, we here did not explicitly examine the effects of medication on BP complexity, and on the relationship between BP complexity and functions because of the uneven number of medications . Therefore, it is worthwhile to explore how the use of antihypertensive medication influences the regulation of BP and its relationship with important functions in older adults in future studies. The BP was measured only in a short term at resting state in this study. While this suggests that this BP complexity metric can be obtained conveniently, previous studies, on the contrary, showed that the ambulatory BP across hours or days was also associated with important functional status  in older adults , 46. It The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Institutional Review Board of Shenzhen People's Hospital. The patients/participants provided their written informed consent to participate in this study.XJ, YCa, YG, and JZ contributed to study conception and design. XW, BH, YCh, LZ, and XG contributed to data collection. XJ, YCa, XW, BH, YCh, LZ, XG, YG, and JZ contributed to data acquisition, analysis, and interpretation of results. XJ, YCh, YG, and JZ drafted the manuscript. All authors contributed to the article and approved the submitted version.This study was supported by Sustainable Development Science and Technology Project of Shenzhen Science and Technology Innovation Commission (KCXFZ20201221173411032 and KCXFZ20201221173400001), the Basic Research Project of Shenzhen Natural Science Foundation, the Shenzhen Science and Technology planning project (JCYJ20190807145209306), the Natural Science Foundation of Guangdong Province (2021A1515010983), and the Shenzhen Key Medical Discipline Construction Fund (Nos. SZXK012 and SZXK005).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Cardiac surgery is associated with a substantial risk of major adverse events. Although carbon dioxide (CO2)-derived variables such as venous-to-arterial CO2 difference (ΔPCO2), and PCO2 gap to arterial–venous O2 content difference ratio (ΔPCO2/C(a−cv)O2) have been successfully used to predict the prognosis of non-cardiac surgery, their prognostic value after cardiopulmonary bypass (CPB) remains controversial. This hospital-based study explored the relationship between ΔPCO2, ΔPCO2/C(a−cv)O2 and organ dysfunction after CPB.Methods: We prospectively enrolled 114 intensive care unit patients after elective cardiac surgery with CPB. Patients were divided into the organ dysfunction group (OI) and non-organ dysfunction group (n-OI) depending on whether organ dysfunction occurred or not at 48 h after CPB. ΔPCO2 was defined as the difference between central venous and arterial CO2 partial pressure.Results: The OI group has 37 (32.5%) patients, 27 of which (23.7%) had one organ dysfunction and 10 (8.8%) had two or more organ dysfunctions. No statistical significance was found (P = 0.84) for ΔPCO2 in the n-OI group at intensive care unit (ICU) admission , and at 4 , 8 , and 12 h post admission . In the OI group, ΔPCO2 also showed the same trend . No statistical difference was found for ΔPCO2/C(a−cv)O2 in the n-OI group (P = 0.46) and OI group (P = 0.39). No difference was detected in ΔPCO2, ΔPCO2/C(a−cv)O2 between groups during the first 12 h after admission (P > 0.05). Subgroup analysis of the patients with two or more failing organs compared to the n-OI group showed that the predictive performance of lactate and Base excess (BE) improved, but not of ΔPCO2 and ΔPCO2/C(a−cv)O2. Regression analysis showed that the BE at 8 h after admission  was a risk factor for organ dysfunction 48 h after CBP.Conclusion : ΔPCO2 and ΔPCO2/C(a−cv)O2 cannot be used as reliable indicators to predict the occurrence of organ dysfunction at 48 h after CBP due to the pathophysiological process that occurs after CBP. Althougon (VO2) , 5 and pon (VO2) , 7, the oversial , 9. CO2-patients . Hyperlapatients . Organ dly small , 13.2-derived variables and organ dysfunction occurring during the early phases after elective cardiac surgery with CPB. The secondary objective was to compare these variables with BE and lactate, which are usually associated with tissue hypoperfusion.The main objective of this study was to investigate relationship between COWe conducted a prospective observational study in a 39-bed mixed intensive care unit (ICU) of a university-affiliated Hospital. Our clinical trial was registered in the China Clinical Trial Registry (registration number: ChiCTR-ROC-17010727). Ethics approval was obtained from the Ethics Committee of Taizhou Hospital, Zhejiang Province. Written informed consent was obtained from all patients. The clinical trial started in February 2017 and ended in August 2018.Adults (≥18 years old) admitted to ICU immediately after CBP, were included if an arterial line and a central venous catheter (confirmed by X-ray) had been inserted. After initiation of the trial, we removed one of the eligibility criteria: “Factors affecting the accuracy of cardiac output monitoring: aortic regurgitation, atrial fibrillation, aortic balloon counter pulsation, high dose norepinephrine,” because it was not necessary and would have reduced our sample size. The exclusion criteria were: emergency surgery, pregnancy, chronic renal insufficiency with dialysis, preoperative acute or chronic liver failure, hematologic diseases, misplacement of the central venous catheter, and death within 48 h.2O, respirations 14–16 times/min, fraction of inspired oxygen 40%. Analgesia was achieved with continuous infusion of fentanyl (0.5–10 mg/kg/h) targeting Critical Care Pain Observation Tool scores of 0–2. Anesthesia was maintained with a continuous infusion of propofol (1–4 mg/kg/h) targeting Richmond Agitation-Sedation Scale scores of−2–0. Vasoactive drugs and fluid infusions were adjusted according to mean arterial pressure of 60–70 mmHg. Infusion of red blood cells was prescribed as needed to maintain hemoglobin (Hb) concentration ≥9.0 g/dL. Crystalloid solution  or 20% albumin was added for volume expansion if necessary.Intraoperative and ICU management was conducted according to local protocols and international guidelines. Ventilator settings were as follows: control mode, tidal volume 6–8 mL/kg, positive end-expiratory pressure ≤ 5 cmHWe prospectively collected preoperative, intraoperative, and postoperative variables, including clinical characteristics, duration of surgery, CBP duration, vital signs, fluid balance, vasoactive-inotropic score, routine blood tests, blood gas results, and clinical biochemistry. The specific data collection time points were at ICU admission and 4 h (H4), 8 h (H8), 12 h (H12), 24 h (H24), and 48 h (H48) after ICU admission. White blood cell count, hemoglobin concentration, platelet count, clinical biochemistry, chest X-rays, or CT scans were reviewed to evaluate organ function at ICU admission, H24, and H48. The length of stay in ICU, length of ventilator use, European System for Cardiac Operative Risk Evaluation II, Acute Physiology and Chronic Health Evaluation Score II (APACHE-II), and sequential organ failure score were recorded at ICU admission, H24, and H48. Paired arterial and central venous blood gases, arterial blood lactate, base excess (BE), and Hb levels were measured at ICU admission, H4, H8, and H12 using an automated analyzer .2-derived and O2-derived variables were calculated as follows:Vasoactive-inotropic score  and CO2-Vasoactive-inotropic score = dopamine (μg/kg/min) + dobutamine (μg/kg/min) + 10 × milrinone (μg/kg/min)+ 100 × epinephrine (μg/kg/min) + 100 × norepinephrine (μg/kg/min) + 10,000 × vasopressin (μg/kg/min)2/fraction of inspired oxygen <300 mmHg or PaO2 <60 mmHg requiring non-invasive ventilation or invasive mechanical ventilation support), acute kidney injury [Kidney Disease Improving Global Outcomes (KDIGO) level ≥1], acute tissue hypoperfusion , cardiac arrest  was used to compare categorical variables. GraphPad prism version 8.0.2 statistical software was used for boxplot charts.According to the occurrence of organ dysfunction at H48, the patients were divided into n-OI and OI groups, with the OI group being further subdivided into OI-1 and OI-2 subgroups according to the number of organs with evidence of dysfunction at H48. Comparisons took place within the OI group, within the n-OI group, between the OI and n-OI groups, and between the n-OI and OI-2 subgroups. The ROC curve analysis was carried out to assess the predictive performance of the variables independently associated with H48 organ dysfunction. The area under the curve (AUC) was calculated based on their 95% confidence intervals (CIs).P-value was < 0.05. A Hosmer–Lemeshow test was used to assess the goodness of fit of the model.In a subsequent analysis, variables were introduced into the logistic regression model if significantly associated with H48 organ dysfunction at the univariate analysis, when P = 0.01], shorter length of ICU stay , and lower H24 and H48 sequential organ failure scores  and . No statistical difference in the duration of mechanical ventilation was detected between the two groups of patients   h. In order to reduce the influence of spontaneous breathing on CO2 of the n-OI group at the four time points were 9.0 (7.0–11.0), 9.0 (7.0–11.0), 9.0 (7.0–11.0), and 9.0 (7.0–11.0) mmHg (P = 0.84), and those of the OI group were 9.0 (8.0–12.8), 10.0 (7.0–11.0), 10.0 (8.5–12.5), and 9.0 (7.3–11.0) mmHg (P = 0.37). The ΔPCO2/C(a−cv)O2 of the n-OI group at the four time points were 2.0 (1.6–2.7), 2.1 (1.7–2.8), 2.0 (1.5–2.3), and 2.0 (1.7–2.4) mmHg/mL (P = 0.46), and those of the OI group were 2.1 (1.7–2.9), 2.2 (1.8–2.5), 2.1 (1.8–2.6), and 1.8 (1.6–2.5) mmHg/mL (P = 0.39) (2-derived variables at any of the four time points (P > 0.05) between the n-OI and OI groups  , respectI groups . Statiste points .2, ΔPCO2/C(a−cv)O2, lactate and BE had no predictive value (P = 0.009) was a risk factor for H48 organ dysfunction after CPB.Regarding specific time point variables, ΔPCOve value . Comparive value . After a2/C(a−cv)O2 and ΔPCO2 did not differ significantly between the two groups at different time points during the first 12 h after ICU admission. Elevated ΔPCO2 and ΔPCO2/C(a−cv)O2 were common phenomena after CPB. The ΔPCO2/C(a−cv)O2 and ΔPCO2 cannot be used to predict H48 organ dysfunction. The predictive performance of lactate and BE was significantly enhanced as the number of dysfunctioning organs increased, although it was limited.We found that the ΔPCO2 and ΔPCO2/Ca−cvO2 on 48 h-organ dysfunction after adult cardiac surgery. In our study, the ΔPCO2 value, CPB time, aortic clamping time, and sequential organ failure score at ICU admission were similar to Guinot et al. study , at a 6.8 mmHg cut off with a sensitivity of 72.0% and specificity of 70.6%. Complications are defined as MMOM  (2 could be predictive of outcome (2/C(a−cv)O2 is not associated with respiratory quotient (2/C(a−cv)O2 was not associated with the existence of tissue hypoxia effectively because of its poor relationship with lactate (R2=0.067). ΔPCO2/C(a−cv)O2 was grouped according to whether it was ≥1.4 mmHg/mL, and no statistical significance were detected in the length of the ventilator, LOS in ICU, or the 24 h and 48 h sequential organ failure score (data not provided). That is probably largely because of the influence of CPB on the activation of inflammation in vivo, ischemia-reperfusion injury, myocardial suppression, and other factors, thus, a microcirculation disorder exists that can last for 72 h  , as foll outcome . A previquotient . In our for 72 h . From ouP itself , transloP itself , 29, andP itself  may dire2 and ΔPCO2/C(a-cv)O2, lactic acid has a moderate ability to predict two or more organ dysfunction. In addition, BE is the amount of base in mmol required to titrate 1 L of whole arterial blood to a pH of 7.40, with the sample fully saturated with oxygen at 37°C and a PaCO2 of 40 mmHg. We also found that BE was a more robust predictor of H48 organ dysfunction than lactic acid, and H8 BE was a risk factor for dysfunction of two or more organs (odds ratio = 1.37), whereas lactic acid was not. A high negative value of BE may be associated with renal dysfunction, metabolic acidosis, and shock, but the factors associated with the reduced systemic BE in patients after cardiac surgery are yet to be clarified , which could also explain the low susceptibility of BE to interference from other factors.Hyperlactatemia is common after cardiopulmonary bypass, and it can be influenced by many factors. Patients undergoing CPB are exposed to the “elution effect,” i.e., the release of lactic acid from the lungs  and the larified . We speccv−aCO2/C(a−cv)O2 cannot replace Pmv−aCO2/C(a−cv)O2 (mv: mixed venous blood) and might have underestimated the CO2 exchange from splanchnic circulation. Finally, it was not easy to detect when the outcome of interest, i.e., organ dysfunction, first occurred relative to the measurement. Continuous measurements or change over time may have more prognostic value than a single time point. However, the dynamic changes of ΔPCO2 at t0 and T6 time points were not found to be associated with postoperative complications or mortality in children after CPB O2 cannot be used as reliable indicators to predict the occurrence of organ dysfunction at 48 h after CBP, which is due to the complex pathophysiological processes after CBP.In conclusion, ΔPCOThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by Ethics Committee of Taizhou Hospital, Zhejiang Province. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.SZ: data curation, investigation, resources, writing—original draft, validation, and funding acquisition. DZ: data curation, investigation, and methodology. X-QC: data curation, investigation, methodology, and software. Y-PJ, L-ZQ, W-YY, and W-YZ: data curation, investigation, and resources. C-GW: data curation and formal analysis. Q-MZ: data curation and resources. T-HT: design of the study and performed data synthesis of the revised stage. R-HL: conceptualization, data curation, formal analysis, funding acquisition, software, validation, writing—review, and editing. All authors have read and approved the manuscript.This study was supported by the Medical and Health Science and Technology Project, Zhejiang Province (2017KY163). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.