These findings suggest possible use of machine learning models for real-world risk assessment as a guide for observation and/or treatment decision making that may potentially lead to improved outcomes in hyperkalemic patients while retaining the benefit of life-saving therapies.Hyperkalemia is associated with increased risks of mortality and adverse clinical outcomes. The treatment of hyperkalemia often leads to the discontinuation or restriction of beneficial but potassium-increasing therapy such as renin-angiotensin-aldosterone inhibitors (RAASi) and high-potassium diet including fruits and vegetables. To date, limited evidence is available for personalized risk evaluation in this heterogeneous and multifactorial pathophysiological condition. We developed risk prediction models using extreme gradient boosting (XGB), multiple logistic regression (LR), and deep neural network. Models were derived from a retrospective cohort of hyperkalemic patients with either heart failure or chronic kidney disease stage ≥3a from a Japanese nationwide database (1 April 2008–30 September 2018). Studied outcomes included all-cause death, renal replacement therapy introduction (RRT), hospitalization for heart failure (HHF), and cardiovascular events within three years after hyperkalemic episodes. The best performing model was further validated using an external cohort. A total of 24,949 adult hyperkalemic patients were selected for model derivation and internal validation. A total of 1452 deaths (16.6%), 887 RRT (10.1%), 1,345 HHF (15.4%), and 621 cardiovascular events (7.1%) were observed. XGB outperformed other models. The area under receiver operator characteristic curves (AUROCs) of XGB vs. LR (95% CIs) for death, RRT, HHF, and cardiovascular events were 0.823 (0.805–0.841) vs. 0.809 (0.791–0.828), 0.957 (0.947–0.967) vs. 0.947 (0.936–0.959), 0.863 (0.846–0.880) vs. 0.838 (0.820–0.856), and 0.809 (0.784–0.834) vs. 0.798 (0.772–0.823), respectively. In the external dataset including 86,279 patients, AUROCs (95% CIs) for XGB were: death, 0.747 (0.742–0.753); RRT, 0.888 (0.882–0.894); HHF, 0.673 (0.666–0.679); and cardiovascular events, 0.585 (0.578–0.591). Kaplan–Meier curves of the high-risk predicted group showed a statistically significant difference from that of the low-risk predicted groups for all outcomes ( Hyperkalemia, characterized by abnormally elevated serum potassium levels, is a common electrolyte abnormality that is often found in patients with heart failure (HF) and chronic kidney disease (CKD) ,3,4,5,6.Numerous studies have shown that hyperkalemia is associated with increased risks of mortality and adverse clinical outcomes, suggesting the possibility that hyperkalemia can be a marker for the worsening of patients’ general conditions or even the cause of adverse outcomes in certain conditions . Direct Artificial intelligence (AI) in combination with electronic health records has been thought to have the potential to address risks for pathological conditions with heterogenous backgrounds by predicting one-dimensional outcomes based on patients’ multifactorial conditions . In factThis study aimed to develop and validate novel AI risk prediction models for hyperkalemic patients with a heterogeneous clinical background using two independent real-world databases. The new machine learning algorithms can assess the risk of mortality and cardiovascular and renal outcomes. The combination of machine learning technology and high-dimensional real-world data has the potential to provide practical predictive accuracy for the personalized detection of hyperkalemic patients at high risk of adverse clinical outcomes and may lead to the improvement of prognosis with more timely and appropriate treatment.Data used in this study were extracted from the databases provided by Medical Data Vision Co., Ltd.  and Real World Data Co., Ltd. . These databases include extensive data on prescriptions, procedures, examinations, laboratory data, and hospital diagnoses based on ICD-10 codes from clinical practice, covering hundreds of medical institutions across most geographic regions and all age groups in Japan. Detailed explanations of these data sources are described in the We selected subjects with hyperkalemia from individuals with at least one serum potassium measurement and aged ≥18 years. Patients with hyperkalemia were defined as those with at least two episodes of elevated serum potassium levels ≥5.1 mmol/L within 12 months. Subjects who were already on dialysis prior to their first hyperkalemic episode, or who had cancer, or who had no history of either HF or CKD stage ≥3a were excluded to ensure substantial patient background homogeneity. The index date was the date of the first hyperkalemic episode, defined as the measurement of serum potassium level ≥5.1 mmol/L. Patients were followed up until the time of death, exit from the dataset or the end of study period, whichever came first.The data handling flow of the internal dataset is depicted in We collected information on medications, medical history, and risk factors based on the information recorded during the 12 months prior to the index date. Risk factors included prescription of RAASi ) and other hyperkalemia-inducing drugs, the presence of high-risk conditions , and other comorbidities. We also collected information on laboratory values and typical therapies for hyperkalemia. Variables which were used as predictors for the model are listed in The occurrence of clinical outcomes was searched over three years from the first hyperkalemic episode. The studied outcomes were all-cause death, renal replacement therapy introduction (RRT) including dialysis or kidney transplantation, hospitalization for HF (HHF), and cardiovascular events . Detailed definitions of these outcomes are listed in We adopted three types of machine learning algorithms: multiple logistic regression (LR) with L1/L2 regularization , extremeFor hyperparameter optimizations of each model, the hyperparameter set that performed best under n-fold cross-validation (5-fold for LR/XGB and 3-fold for NN) was selected . All proOf 81 clinical variables used in the initial models, we selected 64 common variables that can predict the risks of pre-defined clinical outcomes while maintaining the model performance. We took a two-phase approach for the selection. In phase one, we included all the 81 variables, and evaluated prediction accuracy of the models by area under receiver operator characteristics curve (AUROC) within the training dataset. In phase two, we summarized each variable importance by summing the values for all the outcomes and selected candidate variables for deletion according to the following criteria: (1) the rank of summed variable importance lower than 20%, (2) variables that were clinically similar to each other, or (3) variables made of other variables combination. We then evaluated AUROC for the clinical outcomes using experimentally built models by excluding the candidate variables one by one. We finally determined to select the 64 variables set since the prediction accuracy could no longer be maintained when the number of variables was reduced further than the 64 variables .The performance of the optimized model was first tested on the internal validation set. For each combination of outcomes and machine learning algorithms, AUROC values, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) were calculated with the cut-off points of probability of outcomes, i.e., the point maximizing the sum of sensitivity + specificity − 1, herein defined as the best cut-off point. The best cut-off point was set as the cut-off value to the point on the ROC curve farthest from the diagonal line where AUC = 0.5. That is, (sensitivity + specificity − 1) was calculated to obtain the cut-off point that is the maximum value thereof. The point where this (sensitivity + specificity − 1) is the maximum value is defined as the Youden index that provides efficient tradeoff between sensitivity and specificity. An AUROC ≥ 0.80 was considered as an indicator of good prediction performance. To help interpret the instance, Shapley additive explanations (SHAP) values  were calpost hoc analysis, we performed the analysis in a subgroup of patients whose causal information of hospitalization events were available and applied the original definition used in the internal dataset. We also performed another condition of external validation analysis, by restricting the data collection period for input variables within one month after the first hyperkalemic episode for risk predictions of clinical outcomes that occurred after the data collection period, to assess the prediction performance for future adverse events based on the information collected shortly after hyperkalemic episodes. These external validation analyses were performed at an institution independent from the institution performing the model development to ensure reliability of results.The machine learning model which showed the best performance was subjected to external validation, where the model was applied to the external dataset extracted from RWD database. For each outcome, AUROCs, specificity, sensitivity, PPV, and NPV were calculated. The survival curve analysis was carried out based on the probability of clinical outcomes as a threshold. As a result, Kaplan–Meier curves layered in subgroups of high- and low-risk groups were drawn based on the best cut-off points. The survival probabilities between the two groups were verified by the log rank test. Since we could obtain the cause of hospitalization from part of patients (98.4%) in the external validation set, the outcome definitions of HHF and cardiovascular events were modified by counting all hospitalizations with relevant diagnostic codes used to define HF and cardiovascular events . Given lOut of 1,208,894 adult patients with at least one serum potassium measurement, we selected 24,949 hyperkalemic patients for model derivation. Among these patients, 4990 patients were held out for the internal validation set; after excluding 11,207 patients whose hospital records were not available during the 12 months prior to the hyperkalemic episode, we selected 8752 patients for the derivation set . For extDuring the study period, 1452 deaths (16.6%), 887 RRT (10.1%), 1345 HHF (15.4%), and 621 cardiovascular events (7.1%) were observed within three years after hyperkalemic episodes in the derivation set. The best cut-off point was set as the cut-off value to the point on the ROC curve that maximizes the sum of sensitivity + specificity – 1, i.e., the Youden index, that provides efficient tradeoff between sensitivity and specificity.p < 0.005; log-rank test)  . When wenk test) .The prediction performances were similar when the data collection period was restricted within one month after hyperkalemic episodes and were used to predict the risk of clinical outcomes that occurred after the data collection period. The AUROCs for death, RRT, HHF, and cardiovascular events were 0.711 (0.704–0.718), 0.867 (0.859–0.874), 0.662 (0.655–0.668), and 0.586 (0.579–0.593), respectively .We developed and tested the machine learning models for risk predictions of mortality and adverse clinical outcomes over three years after the first hyperkalemic episode. Risk models were built based on multifaceted information obtained from hyperkalemic patients. Among the machine learning models tested, XGB provided the best prediction performance, resulting in AUROCs over 0.8 for all outcomes. The XGB model was further tested on the external validation set and showed that the prediction performances were maintained for death and RRT, but decreased for HHF and cardiovascular events. The high-risk group based on stratification by the machine learning models showed higher incidences for all outcomes.The prediction models for similar types of outcomes were reported in several studies. A study in patients with HF with preserved ejection fraction showed AUROCs of 0.72 to predict mortality and 0.76 to predict HHF . AnotherThe important variables shown in the SHAP summary plots suggested that contributions of each clinical variable for risk predictions were identical by outcome types. HF diagnosis, history of emergency visit, high brain natriuretic peptide value, and older age positively related to the risk of HHF, while low eGFR value, advanced CKD stage, history of acute kidney injury, and younger age contributed to the risk of RRT. Likewise, history of cerebrovascular disease, atrial fibrillation or atrial flutter, and myocardial infarction contributed to the risk of cardiovascular events, while older age, history of chronic pulmonary disease, sepsis, and emergency room visit contributed to the risk of death. Interestingly, some variables provided interpretations inconsistent with the clinical knowledge. For instance, our results showed not having RAASi discontinuation after hyperkalemia contributed to the risk of clinical outcomes. Previous studies reported increased risk of adverse clinical outcomes in patients who discontinued RAASi treatment ,17. ThisRecent studies have shown that hyperkalemic patients are at high risk of long-term cardiovascular and renal outcomes and rapid kidney function decline ,14. On tOne important strength is that the model was tested on an external dataset including more than ten times the number of patients than the derivation set. The prediction performance for the all-cause death, and higher incidence of all clinical outcomes in the high-risk group suggested that the model would work on datasets collected under different settings. However, the prediction performance for HHF and cardiovascular events was decreased, suggesting the need for further attempts to improve the prediction performances. The modifications of outcome definition due to the lack of causal information for hospitalization events could lead to lower prediction performance; therefore, further studies are warranted using clinical outcomes with high specificity applicable across different datasets. Several other approaches may also be considered such as increasing sizes and variety of the training dataset. Advanced technologies such as transfer learning have proven successful to maintain good prediction performance of prediction models across different datasets ,38. In tThe external validation was performed at an independent institution from the institution that performed the model derivation to ensure the reliability of the results. Due to limitations in exchanging the detailed learning conditions, we did not optimize the model in the external dataset; and we did not compare the different machine learning models in the external dataset since the comparison of unoptimized models might not be an ideal condition. However, further studies are needed to externally validate the models in a distinct population or database. Building predictive models using real-world databases had the advantage of large sample sizes representing various clinical settings. However, available information was limited to structured data. Furthermore, MDV collects only deaths that occurred in hospital; therefore, we could not retrieve information on deaths that occurred outside of hospitals. There are some redundancies among the predictor variables used in the final model. For instance, both eGFR value and CKD stage were used as predictor variables. Although we made effort to reduce such redundancies in the variable selection process, they could not be fully removed for maintaining the satisfactory prediction performance of the model. The machine learning modeling algorithm such as the XGB modeling is effective when there are several types of relationships between explanatory variables and objective variables dependent on other variables. Therefore, the application of the machine learning algorithm can aid in the risk prediction based on the numerous types of clinical variables.Finally, it is important to note that the risk models did not explicitly nor implicitly provide information on the treatment effects of any therapeutic interventions. The treatment of high-risk patients would thoroughly be dependent on existing therapeutic guidelines and assessments by treating physicians based on their clinical knowledge.We report the development and validation of risk prediction models using novel machine learning technologies to detect hyperkalemic patients at high risk of mortality, and cardiovascular and renal outcomes, over three years after their first hyperkalemic episode. Although further studies are warranted to improve model applicability in different settings, these findings suggested a possible use of machine learning models for real-world risk assessment as a guide for observation and/or treatment decision making with the potential to lead to the improvement of long-term cardiovascular and renal outcomes, and mortality in patients with hyperkalemia, while retaining the benefit of life-saving therapies.


Norepinephrine showed a significant increase after the lowlanders had spent some time at high altitude (p < 0.001). With increasing altitude, a progressive increase in carotid-radial and carotid-femoral pulse wave velocity values was observed in lowlanders, showing a particularly significant increase (p < 0.001) after staying at high altitude  from 9.2 (7.9–10.0) to 11.2 (10.9–11.8) m/s and carotid-femoral pulse wave velocity from 8.5 (7.9–9.0) to 11.3 (10.9–11.8) m/s). At high altitudes (3400 and 5050 m above sea level), no significant differences were observed between highlanders and lowlanders in hemodynamic parameters . Conclusions: The progressive arterial stiffening with altitude observed in European lowlanders could explain the increase in systolic and pulse pressure values observed at high altitudes in this ethnic group. Further studies are needed to evaluate the role of aortic stiffening in the pathogenesis of acute mountain sickness.Background: Exposure to high altitudes determines several adaptive mechanisms affecting in a complex way the whole cardiovascular, respiratory, endocrine systems because of the hypobaric hypoxic condition. The aim of our study was to evaluate the circulatory adaptive mechanisms at high altitudes, during a scientific expedition in the Himalayas. Methods: Arterial distensibility was assessed measuring carotid-radial and carotid-femoral pulse wave velocity. Tests were carried out at several altitudes, from 1350 to 5050 m above sea level, on 8 lowlander European researchers and 11 highlander Nepalese porters. Results: In Europeans, systolic blood pressure and pulse pressure increased slightly but significantly with altitude ( Exposure to high altitudes determines several adaptive mechanisms which affect in a complex way the whole cardiovascular, respiratory, and endocrine systems because of the hypobaric hypoxic condition. Altitude may lead to detrimental effects on health, the most common of which is Acute Mountain Sickness (AMS). This condition is favoured by rapid ascent, exercise, cold, and individual predisposition ,2 and isDespite the large number of studies conducted on humans to study the pulmonary and cardiac adaptations to altitude, the adaptive mechanisms of the large elastic arteries at very high altitude are not yet clearly understood. Given the difficulty and complexity of performing clinical research in extreme hypoxic-hypobaric conditions, a very small number of studies evaluated a possible process of aortic stiffening induced by exposure at very high altitudes. Lewis et al.  assessedThe large arteries play an important role in blood pressure and peripheral flux regulation. It is well known that large arteries physiologically have not only a conduit function but also a buffering function, and owing to their distensibility, they are able to decrease the pulsatile systolic output of the left ventricle. Therefore, the large arteries have a regulation role, redeeming the pulsatility of the systolic ejection and transforming the regime of the cardiac pump from discontinuous to continuous. This buffering function results from the viscoelastic properties of the arterial wall, which depend on the arterial structure and tone. Structure is determined by the three arterial wall components: elastin, collagen, and smooth muscle cells. On the other hand, the arterial tone is mainly modulated by the autonomic nervous system’s activity and by other vasoactive systems  . The funThe aim of our research was to study the changes in blood pressure and haemodynamic parameters during the ascent and staying at high altitudes, in two groups of European lowlanders and Nepalese highlanders.This study was performed during the scientific expedition in the Himalayas “Circulatory adaptive mechanisms at high altitudes”, inside the research project Everest-K2 of the Italian National Research Council (CNR). Our scientific expedition involved a group of white European lowlander researchers, who lived permanently almost at sea level, and a group of Nepalese highlanders, of Rai ethnicity, born and residing in the Khumbu valley between 3400 and 4930 m a.s.l., on average at 4007 ± 583 m a.s.l. The presence of chronic disease involving habitual therapy was considered an exclusion criterion from the study. No chronic treatments were taken by the study participants, and no drugs were taken during the high-altitude ascension.The lowlanders, coming from Europe (Milan and Paris), after a 3-day stay in Kathmandu , were taken by air transport to Lukla airport (2840 m a.s.l.). Nepalese highlander porters were enrolled at Lukla airport. Enrolment was random, linked to the needs of the scientific expedition . After staying overnight in the nearby village of Phakding (2500 m a.s.l.), the group of lowlanders and highlanders trekked the next day to the village of Namche Bazaar (3400 m a.s.l.), where they stayed two full days for ac-climatization. From Namche Bazaar, the two groups of lowlanders and highlanders hiked together for 3 days to Lobuche (5050 m a.s.l.) on the Nepalese side of Everest at the “Pyramid International Laboratory” of the Italian National Research Council (CNR).Data were collected at Kathmandu and Namche Bazaar in hotel rooms and at Lobuche in the Pyramid International Laboratory. Barometric pressure was recorded by a microclimatic station at the time of each study. Ambient temperature was similarly recorded and kept constant throughout the study. Examinations were performed in the morning after at least 18 h of physical rest and after a stay of at least 1 h in a room with a constant temperature of 19 ± 1 °C.Participants were studied at different altitudes.In Italy, at sea level ;On the second day of permanence in Kathmandu, at 1350 m a.s.l.;On the second day of permanence in Namche Bazar, at 3400 m a.s.l.;On the second day of permanence in Lobuche, at 5050 m. a.s.l.;On the eighth day of stay in this high altitude laboratory.For the Europeans, measurements were performed :In ItalyFor Nepalese participants, the same measurements were performed the same day as for the Europeans at 3400 m a.s.l. and the second day after their arrival in Lobuche.The viscoelastic properties of large arteries were estimated by measuring PWV. Currently, carotid-femoral PWV (cf-PWV) is considered the most reliable non-invasive method for assessing aortic stiffness, while carotid-radial PWV (cr-PWV) reflects the stiffness of the muscular arteries in the upper limb . A MillaBlood pressure measurements were carried out by means of mercury sphygmomanometer and a validated oscillometric system . Blood pressure with the latter device was acquired every 2 min in the left arm, during the tonometric recording.Arterial oxygen saturation was measured by means of a Kontron Pulse Oximeter 7845  with finger clip sensor.The radioenzymatic assay was performed for the dopamine, epinephrine, and norepinephrine assays and the radioimmunoassay for the determination of the atrial natriuretic factor. These dosages were performed only at 1350 m a.s.l., at 5050 m a.s.l., and after stay at 5050 m a.s.l.t-test for unpaired data or with independent samples Mann–Whitney U test for variables not normally distributed. Levene’s test was used to assess equality of variances. Statistical analysis of parameter’s alterations with altitude was calculated using Friedman’s test and the subsequent two tailed Wilcoxon test for non-parametric paired data. Multivariate analysis using logistic regression models adjusted for age and body mass index were performed to assess differences in parameters between the European and Nepalese groups. Statistical analysis was performed by using the Statistical Package for the Social Sciences . A p value less than 0.05 was considered as significant.Results are expressed as median and interquartile range. Normal distribution of variables was assessed by Shapiro–Wilk test. Differences between two groups  for all variables were evaluated with Student’s All 8 European participants in the scientific expedition (6 men and 2 women) and 11 male Nepalese porters belonging to the Rai ethnic group agreed to participate in the study. Among the eight Europeans participating in this expedition, six reported headaches after 4000 m a.s.l. Three had moderate dyspnoea at rest, and one experienced vomiting at 5000 m a.s.l. Finally, upon arrival at Lobuche, one person in the lowlander group presented with signs of moderate cerebral oedema , which rapidly regressed after oxygen and corticoid therapy. None of the highlander porters reported any symptoms.p < 0.05). Diastolic blood pressure and mean blood pressure did not show significant changes with altitude. In the Nepalese participants, blood pressure values did not change between 3500 and 5050 m.In the European group, systolic blood pressure and pulse pressure increased slightly but significantly with altitude , reachinp < 0.001) on the eighth day in Lobuche  to 11.3 (10.9–11.8) m/s, carotid-radial: from 9.2 (7.9–10.0) to 11.2 (10.9–11.8) m/s). As for systolic blood pressure in the Nepalese, no changes in PWV were observed with altitude.Carotid-femoral and carotid-radial PWV increased in Europeans with altitude  showing p < 0.05): from median (interquartile range) 18 (9–45) pg/mL at 1350 m a.s.l. to 186 (158–222) pg/mL at 5050 m a.s.l., to 350 (193–833) pg/mL after 8 days of stay at 5050 m a.s.l. Nepalese people had higher levels of norepinephrine than the Europeans at the same altitude (428 (326–572) pg/mL at 5050 m a.s.l., p < 0.05). Epinephrine, dopamine, and atrial natriuretic factor tended to increase with altitude in lowlanders, without reaching statistical significance , especially on the eighth day compared to the values recorded at 1350 m a.s.l.  recorded in Nepalese highlanders were similar to those recorded in European lowlanders at the same altitude. These changes remained significant after adjusting for mean arterial pressure and heart rate changes with altitude.The viscoelastic properties of the aorta and of the large elastic arteries are guaranteed by an adequate ratio between elastic and collagen fibres of the arterial wall, as well as by a balance between these fibres, the extracellular matrix, and the smooth muscle cells. While changes in arterial wall structure may be evoked as an adaptation phenomenon for Nepalese highlanders, on the other hand, it is difficult to hypothesize that structural changes in the arterial wall can occur in the relatively short time of high-altitude ascension. A further element that makes PWV change at high altitude unlikely to be due to structural changes in the arterial wall comes from the results of the HIGHCARE Study. In agreement with results of our study, the HIGHCARE study showed, after an increase in PWV values at high altitudes, a rapid return of the PWV to baseline after returning to Europe at sea level .We can therefore hypothesize, at least in lowlanders, a prevalent role played by functional factors in the changes in arterial distensibility at high altitudes. The role of functional factors affecting arterial mechanical properties is complex, and their changes are transitory. The main functional factors determining changes in vascular distensibility include left ventricular systolic ejection function, heart rate, arterial smooth muscle, and mean arterial pressure . The symAs already emerged in the HIGHCARE Study ,24, and The trend of the norepinephrine increase curve is associated with a corresponding significant increase in PWV. The stiffening of the aorta at high altitudes, documented by the increase in cf-PWV, may justify the increase in systolic blood pressure and pulse pressure recorded at high altitudes. The PWV values which were registered in the native people are similar to those registered in the Europeans at the same altitude; therefore, it may be inferred that the modifications which were observed in the Europeans are chronically present in the natives.Muscular arteries should be much more sensitive to the activity of the sympathetic nervous system than the aorta and elastic arteries. We would therefore have expected a greater increase in cr-PWV compared to cf-PWV at high altitudes. Therefore, the weaker increase in carotid-radial PWV with altitude suggests that other factors besides sympathetic activation may influence the aortic stiffening. Among other factors that can contribute to increased aortic stiffness at high altitudes, we can consider haemoconcentration with consequent increase in blood viscosity , oxidatiAccording to our knowledge, only the study developed by Lewis et al. compared aortic PWV values in lowlanders and highlanders at the same altitude, above 5000 m a.s.l., and provided evidence of impaired vascular function in highlanders versus lowlanders at sea level, as indicated by significantly higher central PWV values . These oThe main limitation of our study was the relatively small number of enrolled individuals. However, the limit conditions in which the researchers worked must be taken into account. Materials were carried on back by Nepalese porters and yaks , the energy supply was scarce. In Namche, the electric power was available only for few hours a day and sometimes it was unsteady.These data demonstrate how altitude determines important and significant haemodynamic changes. The stiffening of the aorta at high altitudes, documented by the increase in cf-PWV, could justify the increase in systolic blood pressure and pulse pressure recorded at high altitudes ,35. Furt


Sodium glucose co-transporter-2 (SGLT2) inhibitors reduce the risk of kidney and heart failure events independent of glycemic effects. We assessed whether initiation of the SGLT2 inhibitor canagliflozin guided by multivariable predicted risk based on clinical characteristics and novel biomarkers is more efficient to prevent clinical outcomes compared to a strategy guided by HbA1c or urinary-albumin-creatinine ratio (UACR) alone.2-statistic.We performed a post-hoc analysis of the CANVAS trial including 3713 patients with available biomarker measurements. We compared the number of composite kidney  and composite heart failure outcomes  death) prevented per 1000 patients treated for 5 years when canagliflozin was initiated in patients according to HbA1c ≥ 7.5%, UACR, or multivariable risk models consisting of: (1) clinical characteristics, or (2) clinical characteristics and novel biomarkers. Differences in the rates of events prevented between strategies were tested by ChiAfter a median follow-up of 6.1 years, 144 kidney events were recorded. The final clinical model included age, previous history of CV disease, systolic blood pressure, UACR, hemoglobin, body weight, albumin, estimated glomerular filtration rate, and randomized treatment assignment. The combined biomarkers model included all clinical characteristics, tumor necrosis factor receptor-1, kidney injury molecule-1, matrix metallopeptidase-7 and interleukin-6. Treating all patients with HbA1c ≥ 7.5% (n = 2809) would prevent 33.0 (95% CI 18.8 to 43.3 ) kidney events at a rate of 9.6 (95% CI 5.5 to 12.6) events prevented per 1000 patients treated for 5 years. The corresponding rates were 5.8 (95% CI 3.4 to 7.9), 16.6 (95% CI 9.5 to 22.0) (P < 0.001 versus HbA1c or UACR approach), and 17.5 (95% CI 10.0 to 23.0) . Findings were similar for the heart failure outcome.Initiation of canagliflozin based on an estimated risk-based approach prevented more kidney and heart failure outcomes compared to a strategy based on HbA1c or UACR alone. There was no apparent gain from adding novel biomarkers to the clinical risk model. These findings support the use of risk-based assessment using clinical markers to guide initiation of SGLT2 inhibitors in patients with type 2 diabetes.The online version contains supplementary material available at 10.1186/s12933-022-01619-0. Sodium glucose cotransporter-2 (SGLT2) inhibitors are developed and approved by regulatory agencies for the treatment of type 2 diabetes to improve glycemic control. Following regulatory requirements to establish cardiovascular (CV) safety of new anti-diabetic treatments, the CV safety of SGLT2 inhibitors was assessed in large clinical trials , 2. ThesAnalyses from CV and kidney outcome trials have demonstrated that the relative benefits of SGLT2 inhibitors are consistent across many patient subgroups including those with or without type 2 diabetes, severity of kidney disease or the presence of heart failure , 13. TheIn this study, we first assessed if a treatment strategy to initiate the SGLT2 inhibitor canagliflozin using the multivariable predicted risk of kidney outcome based on clinical risk markers is more efficient for preventing clinical outcomes compared to a strategy based on HbA1c or albuminuria alone. Secondly, we assessed whether the addition of novel biomarkers to predict kidney outcome further improve the efficiency of guiding SGLT2 inhibitor initiation. Because of shared pathophysiology between diabetic kidney disease and heart failure, we hypothesized that the kidney risk model would also stratify patients at risk for a clinically relevant heart failure event and therefore also report the effects of canagliflozin on heart failure outcome by baseline kidney risk.2 at baseline. For additional exploratory biomarker research, CANVAS patients provided separate informed consent form (excluding CANVAS-R patients). The CANVAS trial was conducted in accordance with the Declaration of Helsinki . The study protocol was approved by ethics committee at each participating site. All patients provided written informed consent before study specific procedures commenced [This study included data from the Canagliflozin Cardiovascular Assessment Study (CANVAS) program consisting of two multicentre, randomized, double-blind placebo-controlled trials (CANVAS and CANVAS-R) to assess the CV safety and kidney outcomes of canagliflozin in type 2 diabetes patients with an established CV disease or multiple CV risk factors. The CANVAS trial included a total of 4330 patients who were randomly assigned to canagliflozin 100 mg, 300 mg, or placebo in a 1:1:1 ratio, and the CANVAS-R included 5812 patients. The inclusion criteria for the CANVAS program were patients with type 2 diabetes , either 30 years of age or older with a history of symptomatic atherosclerotic CV disease, or 50 years of age or older with two or more of the following risk factors for CV disease; diabetes duration more than 10 years, systolic blood pressure (BP) > 140 mmHg while receiving one or more anti-hypertensive agents, current smoker, evidence of micro- or macroalbuminuria, high-density lipoprotein (HDL) cholesterol level < 1mmol/L, and eGFR of  ≥ 30 mL/min/1/.73mommenced .® GDF-15 electrochemiluminescence immunoassay . Plasma interleukin-6 (IL-6), serum Matrix Metallopeptidase-7 (MMP-7), urinary monocyte chemoattractant protein-1 (uMCP-1), and urinary epidermal growth factor (uEGF) were measured using the Mesoscale QuickPlex SQ 120 platform . All urinary measurements were standardized for urinary creatinine to correct for hydration status.Blood samples of eligible patients were measured at baseline. Plasma tumor necrosis factor receptor-1 (TNFR-1), TNFR-2, and kidney injury molecule-1 (KIM-1) were measured using the Mesoscale Quickplex SQ 120 platform , a high-performance electrochemiluminescence immunoassay . Plasma Growth Differentiation Factor-15 (GDF-15) was measured using the Elecsys2, or the need of dialysis, kidney transplantation, or kidney death) and the composite heart failure outcome .For model development, Cox proportional hazards regression models were used for prediction of the 5-year risk and treatment effect of canagliflozin on the composite kidney outcome , hemoglobin, body weight, HDL cholesterol, low-density-lipoprotein cholesterol (LDL), uric acid, potassium, eGFR according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, phosphorus, albumin level, and canagliflozin treatment (yes/no). Second, we added to the clinical model the following novel biomarkers as candidate predictors: TNFR-1, KIM-1, GDF-15, MMP-7, IL-6, uMCP-1 to creatinine ratio (uMCP-1/Cr) and uEGF to creatinine ratio (uEGF/Cr). To prevent overfitting, variables were selected based on a stepwise backward selection according to the Akaike’s Information Criterion . We deveWe tested the Cox proportional hazards assumptions using Schoenfeld residuals against log transformed time. The assumption was met for all included variables. We determined the Martingale distribution to visually inspect the linearity of the continuous variables, leading to log transformation of UACR, TNFR1, KIM-1, GDF-15, MMP-7, IL-6, uMCP-1/Cr and uEGF/Cr. To determine the internal validity of the final models, we generated 1000 bootstrap samples of the CANVAS dataset . CalibraTo account for missing data, multiple imputations by chained equation  was performed on all variables that had missing values. Imputations were performed by a predictive mean matching, a semi-parametric approach which replaces missing values according to a multivariable regression . Means aThe 5-year predicted risk for the composite kidney outcome for all patients was calculated by setting the treatment status to zero in the development model . The on-treatment risk  was estimated by applying the treatment efficacy estimate to the predicted 5-year risk of an individual for each endpoint in the CANVAS trial. The absolute risk reduction (ARR) (%) for every individual  was calculated as the difference between the predicted 5-year baseline risk and the on-treatment risk. The formula to compute predicted baseline risk according to multivariable risk strategies and OTR are provided in Additional file 2-statistics. In addition, we performed an analysis by comparing the events prevented and NNT in participants with UACR ≥ 30 mg/g for the HbA1c versus UACR or the two multivariable risk-based strategies. Two-sided P-values < 0.05 were considered statistically significant. All statistical analyses were conducted with R version 4.1.1 .To assess the efficacy of different treatment strategy, we ranked all patients by descending levels of baseline risk according to the HbA1c or UACR cut-offs, or the risk percentiles according to the clinical characteristics or the clinical/ novel biomarkers model. For each strategy, we assume that everyone above the threshold is treated and those below would be untreated. The number needed to treat (NNT) at a given threshold was estimated by using the reciprocal of the ARR at that threshold, with 95% CI calculated based on lower and upper limit of the original point estimate to account for statistical uncertainty. We assessed and compared the performance of each strategy at a given risk threshold by comparing the number of events prevented per 1000 patients treated for 5 years using Chi2 and median UACR was 11.7 mg/g. Demographic and clinical characteristics were balanced between the placebo and the treatment group. During a median follow-up of 6.1 years, 144 (3.9%) patients developed a composite kidney outcome, and 371 (10.0%) patients experienced a composite heart failure outcome.A total of 4330 patients were included in the CANVAS trial of whom 3713 (85.8%) patients had biomarkers measured at baseline. The mean age was 62.7 years and 67.0% were males. . For the composite heart failure outcome, the bootstrapped calibration showed Chi2-goodness of fit, P = 0.990 and C-statistics for discrimination was moderately good 0.73 (95% CI 0.70 to 0.76)   of the population in order to prevent 33.0 (95% CI 18.8 to 43.3) kidney events. Treating 2809 patients according to the UACR cut-offs, clinical or clinical/ novel biomarker approach resulted in the prevention of 20.0 (95% CI 11.6 to 27.2), 57.0 (95% CI 32.7 to 75.4) and 60.0 (95% CI 34.2 to 78.7) kidney events , 134 (95% CI 100.9 to 233.8), 49.0 (95% CI 37.3 to 85.9), and 47.0 (95% CI 35.7 to 82.2), respectively  are consistent with previous studies showing the micro- and macrovascular complications in patients with type 2 diabetes are determined by multiple risk markers, and support the measurement of biomarker panels to adequately capture individual risk and guide individualized treatment decisions , 37. TheSeveral limitations should be considered when interpreting the findings. Firstly, there were only few patients who had HbA1c ≥ 10.5% (n = 54), and albuminuria (n = 1037) at baseline, thus the risk prediction and ARR estimation in this group are based upon small samples. Secondly, we note that the model was developed and tested in the same trial and was not externally validated. However, the model was internally validated and was corrected for optimism. Our main aim was not to generate a model for external use but to demonstrate the utility of a multivariable model with known predictors versus HbA1c and UACR alone for the initiation of SGLT2 treatment. Thirdly, we used NNT as a metrics of risk-benefit assessment in this study. Future studies could use other measures of effectiveness including assessment of cost-effectiveness for the different strategies. Finally, it is important to note that although SGLT2 inhibitors have shown strong beneficial effects on the kidney and heart failure outcomes, canagliflozin did not statistically significantly decrease the risk of all-cause mortality in the CANVAS program. Therefore we did not include all-cause mortality in the current analyses.In conclusion, this post-hoc analysis of the CANVAS trial suggests that the use of a clinical risk-based assessment is more efficient to guide the initiation of SGLT2 inhibitors for patients with type 2 diabetes instead of using HbA1c or UACR alone. This would result in the prevention of more kidney and heart failure event for the same number of patients treated compared to the HbA1c or UACR guided initiation of SGLT2 inhibitors across a broad range of potential thresholds to initiate treatment. Validation in an independent study would support clinical implementation.Additional file 1: Box S1. Prediction of the effect ofcanagliflozin on the composite kidney risk for individual patients with type 2diabetes in the CANVAS trial according to clinical and novel markers model.  Table S1. Hazard ratios and P-for-interactions between predictedbaseline risk and treatment variable for both the composite kidney and thecomposite of heart failure or cardiovascular death outcomes. Figure S1. (A) The number of events prevented in patientswith albuminuria  based on the HbA1c (red line), urinary-albumin-creatinineratio (UACR) (purple line), clinical markers (green line), or clinical andnovel biomarkers (blue line) strategy for the composite kidney outcome,and C-statistics obtained for the respective model. Numbers at each curve arespecific HbA1c, UACR cut-offs or based on 5th to 95th percentiles of predicted5-year risk at specific treatment threshold. (B) The number needed to treat inpatients with albuminuria  in order to avoid onecomposite heart failure outcome according to the HbA1c (red line), UACR (purpleline), clinical markers (green line) or the clinical and novel markers (blueline) strategies are shown in the same figure. The intersection points at thevertical dashed-lines indicate the corresponding events prevented and thenumber needed to treat for the different strategies for the same number ofpatients treated with UACR ≥30mg/g and UACR≥300mg/g (n = 214). Figure S2. (A)The number of events prevented in patients with albuminuria  based on the HbA1c (red line), urinary-albumin-creatinine ratio (UACR)(purple line), clinical markers (green line), or clinical and novel biomarkers(blue line) strategy for the composite heart failure outcome  outcome, and C-statistics obtained for therespective model. Numbers at each curve are specific HbA1c, UACR cut-offs orbased on 5th to 95th percentiles of predicted 5-year risk at specific treatmentthreshold. (B) The number needed to treat in patients with albuminuria  in order to avoid one composite heart failure outcomeaccording to the HbA1c (red line), UACR (purple line), clinical markers (greenline) or the clinical and novel markers (blue line) strategies are shown in thesame figure. The intersection points at the vertical dashed-lines indicate thecorresponding events prevented and the number needed to treat for the differentstrategies for the same number of patients treated with UACR ≥30mg/g and UACR≥300mg/g(n = 214).


Extracorporeal membrane oxygenation (ECMO) is a form of circulatory support used in patients with refractory cardiac and/or respiratory failure. The main role of such support is to allow the lungs and heart to rest and heal while providing adequate oxygenation to vital organs. During extracorporeal support, the venous blood removed is decarboxylated, oxygenated, warmed, and infused back into the circulation. Physicians and nursing staff should be familiar with ECMO in order to provide the best care for critically ill patients. The aim of this paper is to review the technical aspects, indications, contraindications, complications, and management of both veno-venous (VV) and veno-arterial (VA) ECMO. Extracorporeal membrane oxygenation (ECMO) is a form of circulatory support used in patients with cardiac failure, respiratory failure, or both, in whom conventional therapies have been exhausted. The venous blood removed is decarboxylated, oxygenated, warmed, and infused back into the venous (veno-venous (VV) ECMO) or arterial  ECMO) circulation. While the role of mechanical support during a respiratory failure is to allow the lungs to rest and recover while minimizing iatrogenic ventilator-induced lung injury (VILI), the goal of mechanical support in cardiac failure is to preserve end-organ perfusion while allowing myocardial rest and healing. Nowadays, there has been more interest in ECMO due to modernized equipment and experience. Consequently, its use has a 400% increase between the years 2006 and 2011 [Despite the emergence of newer ventricular assist devices that are more suitable for long-term support, ECMO is simple to install, cost-effective, and widely available. However, it should only be performed by experienced clinicians familiar with its technical aspects, indications, and complications. This review describes the ECMO circuit and discusses its indications, contraindications, patient selection, and weaning.Technical aspectsThe fundamentals of ECMO have not changed during the past three decades. The circuit consists of a blood pump, oxygenator, and heat exchanger connected by drainage and return cannulas. The drainage cannula facilitates blood drainage from the patient into the pump, while the return cannula facilitates its return from the oxygenator into the patient. Drainage cannulation can be performed peripherally or centrally, whereas a return cannula is usually installed into a large central vein or the femoral artery, depending on the support indication. The resistance to blood flow depends on both the length and the diameter of the cannula. Shorter and broader cannulas decrease resistance, while longer and narrower ones increase resistance. The tubing system can be coated with biocompatible lining to limit the activation of the immune system and decrease the risk of inflammation, thrombosis, and bleeding .During ECMO support, either roller or centrifugal blood pumps are the used mechanisms. Centrifugal pumps, although they carry an increased risk of hemolysis, have replaced roller pumps in most centers . CentrifThe amount of oxygen provided via the artificial lung is a function of the blood flow, and its effects on systemic oxygenation depend on the type of cannulation and the function of the native lungs. In a veno-venous configuration Figure , primariThe VA approach Figure , mainly The removal of CO2 is primarily a function of gas flow. The extracorporeal CO2 removal abolishes the need for ventilation and allows the lungs to rest . Indeed,Indications for veno-venous ECMOVeno-venous ECMO is an “artificial lung” that provides oxygenation and removes carbon dioxide. It is used in cases of severe respiratory failure and requires a functional native heart as it does not provide any cardiac support. The interest in this modality of respiratory support has increased since the H1N1 pandemic in the year 2009 ,9.Hypoxemic Respiratory FailureIn 2009, the Conventional ventilatory support versus Extracorporeal membrane oxygenation for Severe Acute Respiratory failure (CESAR) trial randomly assigned 180 patients with severe acute respiratory distress syndrome (ARDS) to an ECMO center or conventional ventilatory treatment. The authors defined severe ARDS as hypercapnic respiratory acidosis with an arterial pH < 7.20 or a Murray score greater than 3.0. It was concluded that referral to the ECMO center had significantly improved survival and recovery at six months compared to standard management (63% versus 47%) .In 2018, the ECMO to rescue lung injury in severe ARDS (EOLIA) trial was conducted on 249 patients with severe ARDS. The patients received early veno-venous ECMO or conventional low-tidal volume low-pressure ventilation (which could introduce late ECMO as a rescue therapy). Severe ARDS was defined as partial arterial pressure of oxygen/fraction of inspired oxygen ratio (PaO2:FiO2) < 50 mmHg for >3 hours or PaO2:FiO2 < 80 mmHg for >6 hours. ECMO resulted in improved oxygenation, less chance of renal failure compared to other modalities of treatment (46% versus 21%), and fewer cases of ischemic stroke (0% versus 5%). The final analysis concluded that the 11% difference in 60-day mortality, while favoring early ECMO, was not significant (35% versus 46%) [The Berlin consensus report on acute respiratory distress syndrome (ARDS) suggests ECMO in severe respiratory failure (PaO2:FiO2 < 70) despite optimization of ventilatory settings . In addiHypercapnic Respiratory FailureECMO can facilitate the removal of carbon dioxide and reduce ventilator-induced lung injury caused by barotrauma. The SUPERNOVA trial assessed the usefulness of extracorporeal carbon dioxide removal as a component of ultra-protective ventilation . The primary outcome was the number of patients who successfully achieved a tidal volume of 4 mL/kg of predicted body weight with arterial carbon dioxide not increasing more than 20% from baseline, in addition to an arterial pH > 7.30. It was evident that protective ventilation supported by extracorporeal carbon dioxide removal is feasible in moderate ARDS. However, there has been a relatively high incidence of circuit clotting, hemolysis, and bleeding .Bridge to Lung TransplantOther studies showed that ECMO could serve as a bridge for lung transplantation. In a study of 40 patients with interstitial lung disease and respiratory failure, 21 were treated with ECMO. Eventually, six patients treated with support were bridged to lung transplant .Table Indications for veno-arterial ECMOWhen applied in the veno-arterial configuration, the ECMO bypasses the pulmonary circulation while providing cardiac support. This allows for organ perfusion while the heart rests and recovers. Such an approach is a bridge to “recovery, decision, or transplant” Table .Cardiopulmonary ArrestNot uncommonly, the VA-ECMO is used during resuscitation from cardiac arrest. Extracorporeal cardiac pulmonary resuscitation (ECPR) utilizes VA-ECMO in patients who are unable to achieve a sustained return of spontaneous circulation, which is defined as 20 consecutive minutes without a need for chest compressions . It is sCardiogenic Shock2 of the body surface area, and a pulmonary-capillary wedge pressure of 15 mmHg and above [Extracorporeal support has also been employed in the context of cardiogenic shock (CS), which is clinically defined as systemic hypoperfusion caused by acute or acute on top of chronic heart failure. Hemodynamically speaking, it is described as a systolic blood pressure < 90 mmHg (or the need for supportive measures to maintain it above 90 mmHg), a cardiac index below 2.2 L/minute/mnd above . The etind above ; thus, Vnd above ,23 and ind above .Ventricular TachycardiaMoreover, extracorporeal life support (ECLS) has been applied successfully to patients with refractory ventricular tachycardia (VT). In a study conducted from January 2002 to December 2004, a total of 11 patients were enrolled, from which nine patients received veno-arterial mode ECLS support in an attempt to terminate refractory ventricular arrhythmias. Ventricular tachycardias terminated rapidly following ECLS deployment in all patients, and nine were discharged with no evident recurrent VT or the need for internal cardiac defibrillator implantation .Table Contraindications for ECMOThere are no absolute contraindications for ECMO, but its use should be based on a case-by-case decision . HoweverRelative contraindications include uncontrollable bleeding, severe coagulopathy, or contraindication to anticoagulation, in addition to limited vascular access such as obesity and severe peripheral vascular disease Table .ComplicationsComplications during ECMO treatment are frequent. The main complications reported are failure of the oxygenation membrane, intracranial hemorrhage (ICH), acute kidney injury (AKI), infections, limb ischemia, differential hypoxia, and ECMO lung.Oxygenation Membrane FailureIt is reported that the incidence of failure of the oxygenation membrane in adult patients is 5.8% in VV-ECMO and 2.8% in VA-ECMO . The priIntracranial HemorrhageAccording to the Extracorporeal Life Support Organization (ELSO) report, the incidence of intracranial hemorrhage (ICH) and ischemic stroke in adult patients on VV-ECMO is 2.1% and 3.1%, respectively, while it is 1.6% and 3.1%, respectively, in patients on VA-ECMO . AlteratAcute Kidney InjuryThe incidence of acute kidney injury(AKI) in adults managed with ECMO is 78% in patients with respiratory failure  and 81% The pathophysiology of such an insult is not well understood. Rapid hemodynamic fluctuations caused by the ECMO and pressors that alter renal blood flow leading to ischemia-reperfusion-associated AKI is a proposed hypothesis , in addiInfectionsPatients supported with ECMO usually have a complicated and prolonged hospitalization. ECMO itself, as a foreign body, increases the risk of nosocomial infections. In addition, such patients frequently require invasive hemodynamic monitoring and interventions. Indeed, they become susceptible to septic complications, commonly bloodstream and surgical site infections.Candida, and Pseudomonas [Analysis of the Extracorporeal Life Support Organization (ELSO) registry concluded that older age, longer duration of ECMO support, and longer post-ECMO ventilation increase the risk of infections. Only 6.1% of patients requiring bypass for ≤7 days had an infection, whereas 30.3% of those requiring ECMO for >14 days were diagnosed with an infection. The most common causative organisms were coagulase-negative staphylococci, udomonas . Treatmeudomonas .Limb IschemiaCannulation of the femoral artery while securing the VA-ECMO access carries a risk of lower extremity ischemia . The risOther complications include dissection, pseudoaneurysm, and retroperitoneal bleeding. Complications can also occur during the ECMO support or while performing ECMO separation.Differential HypoxiaDuring VA-ECMO support maintenance via the femoral artery, there is a risk of differential hypoxia in which the brain and upper extremities are perfused by deoxygenated blood ejected from the native left ventricle while the lower extremities are perfused by fully oxygenated blood provided by the ECMO . This diECMO LungThe retrograde ejection of blood through the femoral artery and aorta during VA-ECMO support increases the left ventricular afterload. In patients with cardiogenic shock, this worsens the myocardial contractility, increases the filling pressures, and decreases cardiac output. Eventually, pulmonary congestion will develop or worsen, leading to a more systemic inflammatory response that promotes more acute lung injury and even alveolar hemorrhage.The ECMO lung can be treated using inotropes to overcome the increased afterload by improving cardiac contractility. Intra-aortic balloon pump (IABP) or Impella can be deployed to unload the left ventricle. If all measures fail, percutaneous atrial septostomy or surgical decompression cannula can be attempted .Adjustment of ECMO settingsPatients on ECMO support should be medically managed similar to patients not on any circulatory assistance. This includes inotropes, vasopressors, vasodilators, crystalloids, and blood product transfusions.The initial blood flow should be maximized and then lowered to maintain an oxygen saturation of 80% and above. While applying VA support, hemodynamics are a function of blood flow and vascular resistance. Thus, organ perfusion is achieved by determining the adequate circuit blood flow needed and optimizing the cardiac function in this setting.Systemic perfusion is guided based on venous oxygen saturation (SvO2) measures with a target of 70%. Supposing the mixed venous oxygen level is below the target, blood flow should be enhanced by increasing the VA-ECMO circuit blood flow, improving the native cardiac output using inotropes/pressors or unloading methods (IABP). If more intravascular volume is needed to achieve adequate flow, infusing crystalloids and blood products should be considered. In contrast, there is no cardiac support provided by the VV-ECMO circuit; therefore, there is no need to assess the perfusion using SvO2 in this setting.As for the partial pressure of carbon dioxide (PaCO2), it is controlled by the sweep gas flow. CO2 diffuses 20-fold faster than O2; thus, large amounts of CO2 can be exchanged through the membrane lung even when the flow through the circuit is low. When the “sweep gas” flow rate is the same as the blood flow rate, the amount of oxygen added and the CO2 removed are approximately equal, but when the ratio of gas flow to blood flow is increased, there is no increase in oxygenation, but CO2 clearance increases in proportion to the gas flow. Thus, when blood decarboxylation is desired, the higher the gas/blood ratio, the more CO2 is removed. The gas flow is then adjusted to maintain a pH close to 7.40 and a partial pressure of carbon dioxide (PaCO2) of 40 mmHg. Hence, in patients with refractory hypercapnic respiratory failure, low extracorporeal blood flow is sufficient .Ventilation during ECMO supportWhen VV configuration is used, some of the venous blood is pumped into the circuit. As the blood passes through the oxygenator, it becomes fully saturated. This portion of the blood is then infused back into the native venous circulation and becomes mixed with desaturated blood in the right atrium, pumped into the lungs, left ventricle, and then native arterial circulation. The goal is arterial oxygen saturation of 80%. This will maintain tissue oxygenation even with mild-to-moderate hypoxemia if the cardiac output is adequate and there is enough hemoglobin to deliver the oxygen. Therefore, there is no need for pulmonary gas exchange, and the ventilator setting should be adjusted to allow lung recovery and prevent iatrogenic ventilator-induced lung injury (VILI). For this purpose, the ELSO guidelines recommend ventilator “rest settings” for patients on VV-ECMO support: pressure-controlled ventilation, inspiratory pressure of 25 cm H2O, positive end-expiratory pressure of 15 cm H2O, inspiratory to expiratory (I:E) ratio of 2:1, below 40% FiO2, and a respiratory rate of five breaths/minute. The usual tidal volume is 4 mL/kg of predicted body weight. However, a tidal volume of less than 1.5 mL/kg of predicted body weight has been used . The patIn contrast, during the VA-ECMO support, the oxygenation of the coronary arteries, aortic root, upper extremities, and brain is more dependent on the patient’s native cardiopulmonary function, while the perfusion of the organs distal to the mid aorta is maintained mainly by the ECMO circuit. Therefore, using “rest ventilation” as in VV support will put the patient at risk of “differential hypoxia syndrome“ causing myocardial hypoxia and anoxic brain injury. Ventilator settings should be adjusted to achieve adequate pulmonary gas exchange, and a higher PEEP and FiO2 may be necessary. In central subclavian artery cannulation, the risk of this complication is eliminated.Weaning from ECMOIn patients on VV support, improvements in radiographic appearance, pulmonary compliance, and arterial oxyhemoglobin saturation indicate that the patient might maintain satisfactory gas exchange and is ready to be weaned from ECMO. The blood flow should be decreased gradually and slowly over hours until 2 L/minute while assessing the patient. Once the blood flow is 2 L/minute, the sweep rate of the gas across the oxygenator should be decreased slowly to zero. This will eliminate the ECMO contribution to gas exchange. During the weaning trial, the optimal ventilator settings  should be determined to facilitate pulmonary gas exchange. If the patient remains hemodynamically stable and the arterial partial pressure of carbon dioxide is below 50 mmHg, the weaning is completed, and decannulation can be attempted .For patients on VA-ECMO, the decision to proceed with weaning depends on the clinical and hemodynamic evidence of improvement and recovery. Recovery of the cardiac function can be assessed by echocardiography, decrease in the need for inotropes/pressors, mean arterial pressure of more than 60 mmHg, and stable heart rate and rhythm. The combination of improved radiographic parameters, lung compliance, and (PaO2)/fraction of inspired oxygen (FiO2) > 200 mmHg on 30%-40% FiO2 predicts pulmonary improvement. If those criteria are fulfilled, a weaning trial can be initiated by decreasing the ECMO support by reducing the flow over hours to 2 L/minute. If vital signs and hemodynamic parameters remain stable, flow can be decreased to 1 L/minute. After one hour, the parameters should be reassessed. The patient can be removed from ECMO support if the left ventricular ejection fraction is >20% with adequate right ventricular function, central venous blood oxygen content (CVO2) is >60%, pH is >7.30 on a sweep rate of 1-2 L/minute, and PaO2:FiO2 is >200 with FiO2 of <60% [Extracorporeal membrane oxygenation is currently being increasingly used as a support device in critically ill patients with refractory cardiac and/or respiratory failure. It is simple to install, cost-effective, and widely available. However, it should only be performed by experienced clinicians familiar with its technical aspects, indications, and complications. The main goal of ECMO support is to allow the heart/lungs to recover while maintaining oxygenation/perfusion to vital organs. Patient selection is important in order to determine the ECMO configuration, and it is crucial that intensive care unit staff be familiar with this type of circulatory support since its management is a collaboration between physicians, technicians, perfusionists, and nurses.


Anxiety and depression can negatively affect the management of asthma. The study aimed to assess the psychosocial effects of asthma patients during COVID-19 and analyze potential risk factors and interventions.In June 2022, the “Questionnaire Star” electronic questionnaire system was used to collect data. A total of 98 asthma patients from the affiliated hospital of the medical school of Ningbo University were invited to complete the questionnaires. According to our study, the prevalence of symptoms of anxiety and depression in the asthma patients in the institution was 91.8 and 77.6%, respectively. Patients who had an asthma exacerbation in the previous two months were more likely to have anxiety symptoms (OR = 0.142 95%CI 0.025–0.820), while patients who did not participate in asthma day activities were more likely to have anxiety symptoms than those who did (OR = 0.130 95%CI 0.022–0.762).This study found that routine disease educational lectures on asthma day can successfully alleviate asthma sufferers' anxiety and depression. In late March 2022, when the Omicron strain of COVID-19 hit Shanghai, the local government began two-month silent management (from 1 April to 31 May 2022),which included closing public places, canceling large events, and discouraging crowds from gathering [The capacity of Ningbo patients with asthma to visit their physicians or general practitioners has been seriously affected. It has been reported that anxiety and depression have increased significantly during the new coronavirus pandemic , 3, meanWe distributed online questionnaires to 120 asthma patients in the outpatient department. Subsequently, we received 98 responses accordingly with an effective recovery rate of 81.6%. At the beginning of the questionnaire, we informed participants that they would sign the consent by default if they completed the survey. All of the patients were invited to voluntarily participate in the online survey. Ethics approval was obtained from the Clinical Ethics Committee of the Affiliated Hospital of the medical school of Ningbo University.We used “Questionnaire Star” to collect data as previously described . The conWe employed the Chinese version of GAD-7 to assess the anxiety symptoms of patients . The GADPatients' depressive symptoms were assessed using the PHQ-9. The milWe designed the characteristics of the participants on the questionnaire, including gender, age, weight, smoking history, occupational status, and asthma history.Categorical variable statistics were used in this statistical analysis. The categorical variables were reported as percentages, and the chi-square test was used to determine statistical significance. To evaluate the results of the chi-square test p 0.05 in categorical variables, the binary logistic regression analysis was performed. The Hosmer–Lemeshow goodness-of-fit statistic was used to assess model discrimination and calibration. P = 0.05 on both sides was judged statistically significant. To acquire statistical data, these statistical instruments included SPSS v25.0 (IBM) and "questionnaire star."A total of 98 patients were investigated, including 52 males (53.06%) and 46 females (46.94%); 0 (0%) under the age of 18, and 4 (4.08%) between 18 and 25 years old. 20 (20.41%) aged 26–30; 28 (28.57%) aged 31–40, 23 (23.47%) aged 41–50, 18 (18.37%) aged 51–65; 5 aged over 65 (5.1%); 36 (36.73%) weighed 50–60 kg, 23 (23.46%) weighed 61-70 kg, 26 (26.53%) weighed 71–80 kg, 12 (12.24%) weighed 81-90 kg, 1 (1.02%) weighed 100 kg;7(7.14%) are students,5(5.10%) are in sales,7(7.14%) are public relations personnel,1(1.02%) is in the service industry,5(5.1%) are administrative staff, 20 (20.4%)are in professional jobs ,53(54.08%) 53(54.08%) are retirees or farmers; 24 (24.48%)had a smoking history, 74 (75.52%) had no smoking history, the 24 patients with a history of smoking were in the age group over 26 years, mainly in the 31–65 years age group; 36(36.73%) had an acute asthma attack in the last two months, and 62 (63.27%) had no attack, the 36 patients with acute attack of asthma ranged in age from 18 to 65 years, mainly in the 26–65 years age group.The questionnaire showed that 90 91.8%) people in this survey had anxiety-related symptoms, and the questionnaire showed that 76 (77.6%) people in this survey had depression-related symptoms , while patients who did not participate in asthma day activities were more likely to have anxiety symptoms than those who did (OR = 0.130 95 percent range 0.022–0.762)  and asthma day activities , and those who felt that they were Patients whose self-management was disrupted by the epidemic  were more likely to have depressive symptoms (Fig. Asthma, as a chronic heterogeneous illness, has been linked to psychiatric symptoms and mental problems. There is substantial evidence that persons with asthma have a worse quality of life and a higher frequency of mental problems , 12. EmoFour essential components of asthma management include patient education, monitoring of symptoms, control of triggering factors, and pharmacologic therapy. Patient education on asthma decreases exacerbations and improves control, and is a necessary and critical component . Asthma There was increased stress under lockdown, especially for patients with chronic diseases , and theThe asthma patients of Ningbo experienced high levels of anxiety and depression during the shanghai epidemic, and doctors' sharing and interpretation of chronic disease self-management knowledge eased patients' stress and depression levels. During the pandemic, doctors have mainly used the Internet or other media to disseminate knowledge about asthma to the general public. At the same time, they also provide personalized treatment for patients offline and spiritual support for those with psychological disorders.Therefore, during the COVID-19 epidemic, doctors are encouraged to provide professional education by different means to help patients.


To compare the level of exercise self-efficacy, symptoms, functional capacity and health status and investigate the association between these variables in patients with chronic obstructive pulmonary disease (COPD) and chronic heart failure (CHF). Additionally, to investigate how diagnosis, symptoms and patient characteristics are associated with exercise self-efficacy in these patient groups.Cross-sectional study.Primary care.n = 150) with COPD (n = 60), CHF (n = 60) and a double diagnosis (n = 30).Patients , fatigue score, pain severity score, Hospital Anxiety and Depression Scale, functional capacity measured as six-minute walking distance and health status measured by a Visual Analogue Scale.Levels of exercise self-efficacy, health status and symptoms were alike for patients with COPD and patients with CHF. Functional capacity was similar after correction for age. Associations with exercise self-efficacy were found for slight dyspnea (mMRC = 1) , moderate dyspnea (mMRC = 2) , severe dyspnea (mMRC ≥ 3) , fatigue , moderate pain  and severe pain , symptoms of depression  and anxiety , after adjustment for diagnosis, sex and age.Exercise training is an important part of self-management in patients with COPD and chronic heart failure (CHF). High exercise self-efficacy is required for optimal exercise training.Patients with COPD and CHF have similar symptoms and similar levels of exercise self-efficacy, functional capacity and health status.Not the diagnosis, but symptoms of dyspnea, fatigue, pain, depression and anxiety are important factors influencing exercise self-efficacy and need to be addressed.When forming self-management groups with a focus on exercise self-efficacy, it seems more relevant to consider the level of symptoms than the specific diagnosis of COPD or CHF.Patients with COPD or CHF have similar levels of exercise self-efficacy, symptoms, functional capacity and health status. More severe symptoms are associated with lower levels of exercise self-efficacy regardless of diagnosis, sex and age. When forming self-management groups with a focus on exercise self-efficacy, it seems more relevant to consider level of symptoms than the specific diagnosis of COPD or CHF. Chronic heart failure (CHF) and chronic obstructive pulmonary disease (COPD) are common chronic diseases in elderly people and mainly managed in primary health care . PatientPulmonary and cardiac rehabilitation programs, aimed at helping the patient to improve self-management, are well-established in hospital settings but less common in primary health care ,9. LatelSelf-efficacy is defined as the confidence that one has in the ability to perform a specific action in a specific situation . ReachinAccording to the self-efficacy theory, four factors influence an individual's level of self-efficacy: past successful or unsuccessful performance, verbal persuasion by a trusted person, emotions caused by physiological response to the exercise and ‘modeling’ ,14. ModePatients with COPD and CHF share symptomatology, the diseases often coexist, and the exercise recommendations are similar ,6,15. ThThe aim of this study is to explore the feasibility of joint self-management groups with a focus on exercise self-efficacy for patients with COPD and CHF by comparing the level of exercise self-efficacy, symptoms, functional capacity and health status and investigating the correlation between these variables in primary health care. Additionally, to investigate how symptoms and patient characteristics are associated with exercise self-efficacy in these patient groups.This study used the baseline data collected from 150 patients enrolled in the Symptoms and Function Study (SAFS), an intervention study testing a joint self-management group-intervention for patients with COPD and CHF recruited in primary health care, with the goal to increase the patient’s self-efficacy. The SAFS study has been described in detail earlier . PatientData from the written questionnaire contained information about age, sex, whether they lived alone, level of physical activity and smoking habits. For patients with CHF, the New York Heart Association Classification Scale (NYHA) was included. The NYHA classification has four points ranging from 1 = no symptoms to 4 = symptoms in rest.Exercise self-efficacy was measured using the Swedish validated version of the SCI Exercise Self-Efficacy Scale (S-ESES) . This scDyspnea was assessed by the modified Medical Research Council Dyspnea Scale (mMRC). The mMRC has five points ranging from 0 = I only get breathless with strenuous exercise, to 4 = too breathless to leave the house or breathless when dressing or undressing .Fatigue was assessed with three questions and calculated into a total score for frequency, duration and severity (range 0–9) . The freSymptoms of depression and anxiety were assessed by the Swedish version of the Hospital Anxiety and Depression Scale (HAD). It consists of seven items in two subscales (score range 0–21) and measures the degree of anxiety (HAD-A) and depression (HAD-D). A higher score indicates higher level of depressive or anxiety symptoms. In clinical practice, a HAD score over 8 can be indicative of the presence of the respective mood disorder [Severity of pain was assessed by using the patient’s answer to the question about their current level of pain or discomfort from the questionnaire that was developed by the EuroQol group (EQ5D5L). The question was answered on a five-point Likert scale ranging from 0 = I have no pain or discomfort to 4 = I have extreme pain or discomfort .The functional capacity of the patients was assessed by testing the six-minute walking distance (6MWD), when the patient had to walk as far as possible during 6 min, after receiving standardized instructions .To assess health status, we used the Visual Analogue Scale from the EuroQol group (EQ5D5L-VAS). The patients were asked to score their perceived health today on a vertical VAS from 0 to 100, in which 0 is the worst and 100 the best imaginable health .This study was approved by the Research Ethics Committee in Uppsala (2012/189/1). Written informed consent was obtained from all participants.n = 21), fatigue total score (n = 16) HAD-D (n = 14) and HAD-A (n = 14) were excluded from the analyses including these variables. Spearman correlation coefficients were used to analyze the correlation between the different variables separately. This analysis was performed for the whole group (n = 150) and separately for the patients with COPD (n = 60) or CHF (n = 60). Bonferroni–Holm method was used to correct for the use of multiple variables [Categorical and nominal data are presented as frequencies and percentages, median and inter-quartile range; for continuous data, mean and standard deviations (SD) are used. Patients with a double diagnosis were excluded from the comparative analyses but included in the merged analysis. Differences between patients with COPD and CHF were analyzed with the chi-square test for proportions, Mann–Whitney U-test for non-parametric data or student’s t-test for parametric averages. Analyses were repeated with stratification for sex and age group. The age groups used were ≤73 and > 73 years; being the mean age in this study population. Patients with incomplete data on S-ESES , linear regression analysis was performed with the S-ESES as dependent variable and the different symptoms and patient characteristics as independent variables. These analyses were performed unadjusted and adjusted for diagnosis group , sex and age. Diagnosis groups, mMRC, physical activity and pain were modeled as a series of binary dummy variables. The groups with mMRC = 3 and mMRC = 4 were merged for this analysis, since there were only three patients in the latter group. For our analyses, IBM SPSS statistics version 26 was used. A p value of <.05 was considered statistically significant.To analyze what variables are associated with the level of exercise self-efficacy in the study population (n = 29) in the COPD group than in the CHF group (n = 46) and patients with COPD were, on average, younger. There were more daily smokers in the COPD group .There was no statistically significant difference in the VAS score for perceived health between patients with CHF and COPD  nor betwn = 150), significant but mainly weak correlation coefficients were found between most of the variables within the model, but no significant association was found for functional capacity with fatigue and anxiety  showed that higher age, living alone, a mMRC ≥1, higher level of fatigue, moderate and severe pain, symptoms of depression and anxiety were associated with a lower level of exercise self-efficacy. Patients who were physically active for 30 min or more daily had a better physical capacity, health status and a higher level of exercise self-efficacy. Diagnosis of CHF and/or COPD did not influence the level of exercise self-efficacy, neither did sex or daily smoking. When adjusted for age, sex and diagnosis, the significant associations were unaltered except that age and living alone were no longer found to be significant factors associated with exercise self-efficacy (The unadjusted analysis of the group with complete S-ESES scores (efficacy .The primary findings of our study are that patients with COPD and CHF have similar levels of exercise self-efficacy, health status, symptoms and age-adjusted functional capacity. However, the strength of the associations between these variables seems to differ between the two diagnosis groups. Our secondary finding is that dyspnea, fatigue, pain and symptoms of depression or anxiety are important factors that decrease the level of exercise self-efficacy, regardless of diagnosis, sex and age.A strength of this study is that this patient sample is representative for patients in primary health care. The age and sex difference and the frequency and level of symptoms in both groups are comparable to those found earlier in Swedish primary care . Even thA limitation is that we have no doctor’s diagnosis for those with a double diagnosis. The self-reported data were considered insufficiently reliable, so we did not analyze these patients as a separate group. Another limitation of this study is the relatively small number of patients in the separate diagnosis groups, which probably caused that only few significant and mainly weak correlation coefficients were found within the model for COPD and CHF separately. The fact that more and stronger significant correlation coefficients were found in the group as a whole strengthens this assumption and indicates that our conceptual model is applicable for both COPD and CHF patients. The fact that we found less and weaker associations within the model for patients with CHF might, on the other hand, indicate that other factors, like comorbidity and social and environmental factors, that are not included in our model, play a larger role in patients with CHF ,27. HoweThis is, to our knowledge, the first study comparing levels of exercise self-efficacy between patients with COPD and CHF in primary health care. Self-efficacy in patients with COPD and CHF has been compared before, but in a hospital-selected patient group and using a scale including a broader variation of behavior related to health . Our resA clinically important finding is that dyspnea, fatigue, pain and depressive and anxiety symptoms influence the level of exercise self-efficacy. Focus is often on dyspnea and fatigue, as these symptoms are directly linked to the pathophysiology of both COPD and CHF. However, pain, depression and anxiety are not directly linked to the pathophysiology of the diseases but present in many patients with COPD and CHF and are often undertreated . We founIn our study, age was found to be associated with the level of exercise self-efficacy in the unadjusted regression analysis but not after adjustment for sex and diagnosis. We found though that functional capacity decreased with age, which is in line with prior studies , and thaThis study focused on the similarities between patients with COPD and CHF. There are, of course, differences between these patient groups, including, for example, the use of diuretics or sensitivity to cold or damp air, that need different coping strategies and make ‘modeling’ more difficult. Further research on effectiveness of joint self-management groups and qualitative research on patient and care-giver experiences is needed for further evaluation of the feasibility of these groups.In summary, the similar levels of exercise self-efficacy, symptoms, functional capacity and health status that we found in patients with COPD and CHF create the conditions for a beneficial effect of ‘modeling’ when utilized in a self-management group with a focus on increasing exercise self-efficacy. When forming self-management groups with a focus on exercise self-efficacy, it seems more relevant to consider the level of symptoms than the specific diagnosis of COPD or CHF.


This study aimed to assess the efficacy and safety of various neoadjuvant regimens for patients diagnosed with early-stage or locally advanced triple-negative breast cancer (TNBC).Medline, EMBASE, Cochrane Library, and Web of Science were searched in May 2020 to identify randomized controlled trials (RCTs). Bayesian network meta-analysis (NMA) was performed (Registration: PROSPERO CRD42020223012).A total of 35 RCTs involving 8,424 participants were reviewed, of which 22 RCTs with 5,203 patients were included in this NMA focusing on pathologic complete response (pCR). An anthracycline-taxane-based (AT) regimen combined with a platinum (ATPt)  regimen, and a docetaxel regimen combined with a carboplatin  regimen improved pCR beyond that with AT only. AT and ATPt combined with targeted therapy  also improved pCR. Five RCTs included in this NMA reported serious adverse events (SAEs) or grade ≥ 3 AEs. TCb was associated with fewer grade ≥ 3 AEs than was AT  alone. In contrast, ATPt, AT + Bev, ATPt + Bev, ATPt + veliparib, and ATPt + pembrolizumab were associated with more SAEs than was AT alone.In patients with TNBC, platinum-based neoadjuvant regimens ATPt and TCb increase pCR beyond that with AT alone, but TCb appears to be better tolerated than either AT or ATPt. Platinum-based regimens combined with targeted therapies  also improve the pCR rate beyond that with AT alone, but this benefit is accompanied by greater toxicity. Although many studies have been conducted on TNBC, its prognosis remains poor in the long term. Approximately 25%–30% of patients with early-stage TNBC are estimated to develop distant metastases within 3–5 years after diagnosis2. Although adjuvant therapy remains commonly used, neoadjuvant chemotherapy is now recognized as the standard of care for patients with TNBC4.Triple-negative breast cancer (TNBC) is defined by cancer cells that lack estrogen receptors, progesterone receptors, and human epidermal growth factor receptor type 2 (HER2) expression. TNBC is a genetically heterogeneous, aggressive molecular subgroup of breast cancer (BC) that accounts for approximately 15%–20% of all BCs and often occurs in younger women6. Pathologic complete response (pCR) is used to interpret prognostic information, predict overall outcomes, and guide adjuvant therapy selection and decision-making7. Minckwitz et al.8 have reported a pooled analysis exploring the association between pCR and long-term clinical benefits in TNBC. The results indicated that patients who achieve a pCR have significantly better event-free survival and overall survival outcomes than those who do not; however, a similar difference was not observed in hormone receptor (HP)-positive patients. Achieving a pCR is thus highly prognostic in TNBC, because such patients have better survival in the long term. Although the Create-X9 study has recently shown that adding the adjuvant capecitabine after standard neoadjuvant chemotherapy prolongs overall survival in patients with TNBC with residual invasive disease on pathological testing, gaps exist in the medical knowledge regarding how best to increase the pCR rate for TNBC. Therefore, more individualized therapy strategies are needed for patients without pCR.Neoadjuvant therapy, consisting of systemic therapy before surgical tumor removal, can downstage tumors, thus allowing for breast-conserving surgery and offering a valuable opportunity to monitor individual tumor responses10.Several studies combining standard neoadjuvant regimens with platinum or targeted agents, such as bevacizumab (Bev), PARP inhibitors (PARPi), and PD-1/PD-L1 inhibitors, have been shown to improve pCR rates in TNBC11. Common AEs of neoadjuvant regimens include thrombocytopenia, neutropenia, anemia, myelogenous leukemia, alopecia, stomatitis, anorexia, pyrexia, conjunctivitis, cardiac disorder, and pigmentation12.Most drugs used in neoadjuvant regimens can cause serious adverse effects (AEs) that may lead to poorer prognosis or death. Several studies have reported that participants withdrew or discontinued treatment because of severe toxicity13 has shown that a platinum-based regimen may be an option in the neoadjuvant setting; however, the regimen providing the best benefit/risk ratio when combined with targeted agents such as Bev, PARPi, and PD-1/PD-L1 inhibitors remains unknown. The toxicity of neoadjuvant regimens may be a barrier for clinicians, who might prefer to select better tolerated agents and dosages for patients with TNBC. To help clinicians choose appropriate treatments for patients with TNBC, we conducted a network meta-analysis (NMA) to assess the efficacy and safety of various neoadjuvant regimens for patients diagnosed with early-stage or locally advanced TNBC.Because of the heterogeneity of TNBC and the variety of neoadjuvant regimens, finding the optimal neoadjuvant regimen to improve long-term outcomes in patients with early-stage TNBC remains a challenge in clinical practice. A previous meta-analysis14. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-NMA checklist15.This study was registered with the International Prospective Register of Systematic Reviews Medline, EMBASE, Cochrane Library, and Web of Science were searched from inception to September 2020, without limitations on the date/time, language, or document type. The reference lists of the included studies were examined to identify any additional relevant published or unpublished material not retrieved by the electronic search. Search strategies for all databases are described in detail in Online Appendix 1.Randomized controlled trials (RCTs) fulfilling the following criteria were included: 1) patients with early or locally advanced TNBC ; 2) any neoadjuvant regimen  including a single drug or a combination of any of the following drugs: paclitaxel, docetaxel, platinum/cisplatin/carboplatin/oxaliplatin, albumin paclitaxel, capecitabine/gemcitabine/5-fluorouracil, doxorubicin/epirubicin, cyclophosphamide, pembrolizumab/nivolumab/atezolizumab, veliparib/olaparib, or everolimus; and 3) any outcomes of interest, namely pCR (ypT0/is ypN0 or ypT0 ypN0), serious AEs (SAEs), or grade ≥ 3 AEs.Patients in studies with subgroup analysis of TNBC were included only if they were stratified according to receptor status when randomized. Randomized controlled trials (RCTs) published only as abstracts without full articles or detailed reports were excluded from the analysis. Studies in a language other than English were excluded.16 were evaluated, comprising sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome reporting, and other bias. More details have been presented in our protocol14.Four reviewers were divided into 2 groups to independently screen the articles , perform data extraction , and assess the risk of bias . Disagreements were resolved by discussion, with assistance from a third party (ZW or ZS) if necessary. The 7 domains of the Cochrane Risk of Bias tool17. The pooled estimation and the probability of a given drug being optimal were obtained according to the Markov chain Monte Carlo method. The model convergence was assessed with trace plots and Brooks-Gelman-Rubin plots18. The results of dichotomous outcomes are reported as odds ratios (ORs) and credible intervals (CrIs). The ranking probabilities for all neoadjuvant regimens were estimated and are reported as the area under the cumulative ranking curve (SUCRA). Evidence inconsistency and clinical similarities in patient characteristics and settings across trials were carefully assessed before analysis. Network geometry was performed in STATA 16.0 software.The primary objective was to compare pCR among all included RCT regimens in the network. The second objective was to compare aggregated AEs  among all included RCT regimens in the network. A fixed-effect NMA within a Bayesian framework was performed in R 3.6.2 software (gemtc package)Figure 1). Thirty-five RCTs (with 47 references) were eligible according to the inclusion criteria; of these, 22 RCTs (with 29 references) were included in the NMA.A total of 2,205 articles were identified . After removal of duplicates, 1,719 articles were identified for screening. An additional 1,566 articles were excluded after inspection of the titles and abstracts. The remaining 153 articles were read in full, and 106 articles were subsequently excluded for various reasons (further details in Table 1 (Online Appendix 4) and Online Appendix 2 (Supplementary Tables S1 and S2) provide more details on the study and population characteristics.A total of 35 RCTs (published from 2012 to 2020) involving 8,424 participants met the inclusion criteria for this review. A total of 28 RCTs (80%) were multicenter trials. Participants were recruited from South America , Mexico, the United States, Canada, Australia, Europe , and Asia . The average age of the included participants was approximately 50 years. Supplementary Tables S3 and S4). A detailed risk of bias assessment is reported in Online Appendix 3 .All included RCTs reported pCR outcomes (neoadjuvant regimens in 22 RCTs were connected for NMA); 11 RCTs reported SAEs or grade ≥ 3 AEs (neoadjuvant regimens in 5 RCTs were connected for NMA). Data were extracted from subgroup analyses for TNBC in 15 RCTs. More details are presented in Online Appendix 2 . An improved pCR was detected for the taxane-platinum-anthracycline  and docetaxel-carboplatin (TCb)  chemotherapy regimens compared with the anthracycline-taxane-based (AT) regimen. The addition of Bev also improved pCR outcomes in patients receiving AT + Bev  and the ATPt + Bev . Combination with PARP inhibitors improved pCRs only for the ATPt + veliparib  regimens. Adding PD-1/PD-L1 inhibitors improved pCRs in the AT + atezolizumab , the AT + pembrolizumab , and the ATPt + pembrolizumab  regimens. .A total of 22 RCTs and 5,203 patients were included in the NMA, and a network plot is shown in Table 2. A total of 5 RCTs with 2,965 patients were connected in the NMA, and a network plot is shown in Figure 2B (more details are shown in Online Appendix 6: Supplementary Tables S11–14). The incidence of aggregated AEs was lower with TCb than with AT , but the difference was not statistically significant. In contrast, a significantly higher incidence of aggregated AE was observed with ATPt , AT + Bev , ATPt + Bev , ATPt + veliparib , and ATPt + pembrolizumab  than with AT .The incidence of aggregated AEs reported in RCTs is summarized in Supplementary Figure S4 and Online Appendix 6: Supplementary Figure S6). Except for interventions in which the loop could not be constructed, we observed no significant inconsistencies between the direct and indirect results [inconsistency test results in Online Appendix 5 ]. Online Appendix 5 and Online Appendix 6 show the mean SUCRA values for providing the hierarchy ranking of the different neoadjuvant regimens in terms of pCR  and aggregated AEs . The ranking might be highly biased, and interpretation should be made with caution. Funnel plots were not constructed because the number of included studies in one comparison was less than 10.The trace plot and density plot showed a good degree of convergence . The network inconsistency was also low in this analysis. In addition, we performed a comprehensive search with no limitations on language, date, document type, or publication status to identify all relevant published or unpublished RCTs. Four reviewers divided into 2 groups performed the screening, data extraction, and assessment independently to minimize possible bias in the review process.As a surrogate for long-term survival20 recommend AC  followed by biweekly or weekly paclitaxel as the preferred regimens for HER2-negative breast cancer. AC-T (where T indicates docetaxel) (q3w) or TAC are both commonly used regimens for neoadjuvant/adjuvant therapy in clinical practice. The combination of carboplatin with paclitaxel/docetaxel can be used in patients with TNBC in preoperative settings but is not routinely recommended for most patients.NCCN guidelinesSupplementary Figure S8). An improvement effect of pCR was detected for chemotherapy regimens including AC-nabP , TCb , and PCb-AC , as compared with AC-P (where P indicates paclitaxel) . Including a platinum agent in TNBC neoadjuvant therapy appears to be important to improve pCR benefits, and TCb appears to be effective but better tolerated than an ATPt regimen.In this NMA, we found that adding platinum to an AT-based regimen resulted in a significantly greater pCR than observed with the AT regimen alone. Removing anthracycline from the taxane-platinum regimen showed a pCR benefit comparable to that of ATPt, but with a relatively better safety profile, possibly because it combines only 2 chemotherapeutic agents. We additionally conducted an analysis without combining similar regimens .The VEGF inhibitor Bev combined with chemotherapy has demonstrated an improvement over chemotherapy alone, with respect to patient outcomes in several cancers, such as NSCLCSupplementary Table S9). Head-to-head trials are needed to confirm these data. In all reported studies, the chemotherapy regimens combined with PD-1/PD-L1 inhibitors were paclitaxel- or nab-paclitaxel-based dose dense regimens, but this combination was associated with a high incidence of aggregated AEs (Table 2)31. Additional clinical trials are thus needed to define the optimal chemotherapy regimen to be combined with a PD-1/PD-L1 inhibitor. The superiority of TCb vs. AT supports future clinical trials combining TCb with immunotherapy. The results of the NeoPACT (NCT03639948) study, an ongoing phase II single-arm clinical trial combining TCb with pembrolizumab in neoadjuvant treatment of TNBC, are awaited. Immunotherapy may also result in different responses according to the PD-L1 expression level, and patients with PD-L1-positive expression have been found to have higher pCR rates32. Therefore, additional research is needed to define which patients would benefit most from immunotherapy.This NMA also suggests that the use of PD-1/PD-L1 inhibitors  combined with various chemotherapy regimens, compared with AT alone, significantly improves pCR in patients with TNBC. However, no clear difference was identified between AT plus durvalumab and AT alone. In addition, none of the regimens including a PD-1/PD-L1 inhibitor showed superiority to TCb  were not always adequately reported in the included studies; thus, the risk was unclear for several domains of bias risk. Second, owing to a lack of head-to-head evidence and insufficient data in the included studies, we were unable to explore the comparative effects in some subgroups, such as BRCA mutation, dosage, and treatment duration. Third, owing to limited reports on survival data, long-term survival outcomes should be further assessed.In conclusion, the key messages of this NMA are as follows. First, adding platinum to TNBC neoadjuvant therapy (ATPt and TCb) significantly increases pCR beyond that with AT alone. TCb and ATPt show comparable pCR rates, but TCb is better tolerated than ATPt. Second, adding Bev, veliparib, and PD-1/PD-L1 inhibitors to AT and ATPt improves pCR rates. We observed no significant differences between regimens, including PD-1/PD-L1, but ATPt plus PD-1/L1 inhibitor led to relatively higher rates of aggregated AEs. The increased efficacy of regimens should be balanced with patients’ quality of life.Click here for additional data file.