Personalizing renal replacement therapy initiation in the intensive care unit: a reinforcement learning-based strategy with external validation on the AKIKI randomized controlled trials.

OBJECTIVE: The timely initiation of renal replacement therapy (RRT) for acute kidney injury (AKI) requires sequential decision-making tailored to individuals' evolving characteristics. To learn and validate optimal strategies for RRT initiation, we used reinforcement learning on clinical data from routine care and randomized controlled trials. MATERIALS AND METHODS: We used the MIMIC-III database for development and AKIKI trials for validation. Participants were adult ICU patients with severe AKI receiving mechanical ventilation or catecholamine infusion. We used a doubly robust estimator to learn when to start RRT after the occurrence of severe AKI for three days in a row. We developed a "crude strategy" maximizing the population-level hospital-free days at day 60 (HFD60) and a "stringent strategy" recommending RRT when there is significant evidence of benefit for an individual. For validation, we evaluated the causal effects of implementing our learned strategies versus following current best practices on HFD60. RESULTS: We included 3748 patients in the development set and 1068 in the validation set. Through external validation, the crude and stringent strategies yielded an average difference of 13.7 [95% CI -5.3 to 35.7] and 14.9 [95% CI -3.2 to 39.2] HFD60, respectively, compared to current best practices. The stringent strategy led to initiating RRT within 3 days in 14% of patients versus 38% under best practices. DISCUSSION: Implementing our strategies could improve the average number of days that ICU patients spend alive and outside the hospital while sparing RRT for many. CONCLUSION: We developed and validated a practical and interpretable dynamic decision support system for RRT initiation in the ICU.

Continuous renal replacement therapy versus intermittent hemodialysis as first modality for renal replacement therapy in severe acute kidney injury: a secondary analysis of AKIKI and IDEAL-ICU studies.

BACKGROUND: Intermittent hemodialysis (IHD) and continuous renal replacement therapy (CRRT) are the two main RRT modalities in patients with severe acute kidney injury (AKI). Meta-analyses conducted more than 10 years ago did not show survival difference between these two modalities. As the quality of RRT delivery has improved since then, we aimed to reassess whether the choice of IHD or CRRT as first modality affects survival of patients with severe AKI. METHODS: This is a secondary analysis of two multicenter randomized controlled trials (AKIKI and IDEAL-ICU) that compared an early RRT initiation strategy with a delayed one. We included patients allocated to the early strategy in order to emulate a trial where patients would have been randomized to receive either IHD or CRRT within twelve hours after the documentation of severe AKI. We determined each patient's modality group as the first RRT modality they received. The primary outcome was 60-day overall survival. We used two propensity score methods to balance the differences in baseline characteristics between groups and the primary analysis relied on inverse probability of treatment weighting. RESULTS: A total of 543 patients were included. Continuous RRT was the first modality in 269 patients and IHD in 274. Patients receiving CRRT had higher cardiovascular and total-SOFA scores. Inverse probability weighting allowed to adequately balance groups on all predefined confounders. The weighted Kaplan-Meier death rate at day 60 was 54·4% in the CRRT group and 46·5% in the IHD group (weighted HR 1·26, 95% CI 1·01-1·60). In a complementary analysis of less severely ill patients (SOFA score: 3-10), receiving IHD was associated with better day 60 survival compared to CRRT (weighted HR 1.82, 95% CI 1·01-3·28; p < 0.01). We found no evidence of a survival difference between the two RRT modalities in more severe patients. CONCLUSION: Compared to IHD, CRRT as first modality seemed to convey no benefit in terms of survival or of kidney recovery and might even have been associated with less favorable outcome in patients with lesser severity of disease. A prospective randomized non-inferiority trial should be implemented to solve the persistent conundrum of the optimal RRT technique.

Personalization of renal replacement therapy initiation: a secondary analysis of the AKIKI and IDEAL-ICU trials.

BACKGROUND: Trials comparing early and delayed strategies of renal replacement therapy in patients with severe acute kidney injury may have missed differences in survival as a result of mixing together patients at heterogeneous levels of risks. Our aim was to evaluate the heterogeneity of treatment effect on 60-day mortality from an early vs a delayed strategy across levels of risk for renal replacement therapy initiation under a delayed strategy. METHODS: We used data from the AKIKI, and IDEAL-ICU randomized controlled trials to develop a multivariable logistic regression model for renal replacement therapy initiation within 48 h after allocation to a delayed strategy. We then used an interaction with spline terms in a Cox model to estimate treatment effects across the predicted risks of RRT initiation. RESULTS: We analyzed data from 1107 patients (619 and 488 in the AKIKI and IDEAL-ICU trial respectively). In the pooled sample, we found evidence for heterogeneous treatment effects (P = 0.023). Patients at an intermediate-high risk of renal replacement therapy initiation within 48 h may have benefited from an early strategy (absolute risk difference, - 14%; 95% confidence interval, - 27% to - 1%). For other patients, we found no evidence of benefit from an early strategy of renal replacement therapy initiation but a trend for harm (absolute risk difference, 8%; 95% confidence interval, - 5% to 21% in patients at intermediate-low risk). CONCLUSIONS: We have identified a clinically sound heterogeneity of treatment effect of an early vs a delayed strategy of renal replacement therapy initiation that may reflect varying degrees of kidney demand-capacity mismatch.

Kidney Histopathology Can Predict Kidney Function in ANCA-Associated Vasculitides with Acute Kidney Injury Treated with Plasma Exchanges.

BACKGROUND: Data from the PEXIVAS trial challenged the role of plasma exchange (PLEX) in ANCA-associated vasculitides (AAV). We aimed to describe kidney biopsy from patients with AAV treated with PLEX, evaluate whether histopathologic findings could predict kidney function, and identify which patients would most benefit from PLEX. METHODS: We performed a multicenter, retrospective study on 188 patients with AAV and AKI treated with PLEX and 237 not treated with PLEX. The primary outcome was mortality or KRT at 12 months (M12). RESULTS: No significant benefit of PLEX for the primary outcome was found. To identify patients benefitting from PLEX, we developed a model predicting the average treatment effect of PLEX for an individual depending on covariables. Using the prediction model, 223 patients had a better predicted outcome with PLEX than without PLEX, and 177 of them had >5% increased predicted probability with PLEX compared with without PLEX of being alive and free from KRT at M12, which defined the PLEX-recommended group. Risk difference for death or KRT at M12 was significantly lower with PLEX in the PLEX-recommended group (-15.9%; 95% CI, -29.4 to -2.5) compared with the PLEX not recommended group (-4.8%; 95% CI, 14.9 to 5.3). Microscopic polyangiitis, MPO-ANCA, higher serum creatinine, crescentic and sclerotic classes, and higher Brix score were more frequent in the PLEX-recommended group. An easy to use score identified patients who would benefit from PLEX. The average treatment effect of PLEX for those with recommended treatment corresponded to an absolute risk reduction for death or KRT at M12 of 24.6%. CONCLUSIONS: PLEX was not associated with a better primary outcome in the whole study population, but we identified a subset of patients who could benefit from PLEX. However, these findings must be validated before utilized in clinical decision making.

Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: Is There a Relevant Experimental Model? A Systematic Review of Preclinical Literature.

Delayed cerebral ischemia (DCI) is one of the main prognosis factors for disability after aneurysmal subarachnoid hemorrhage (SAH). The lack of a consensual definition for DCI had limited investigation and care in human until 2010, when a multidisciplinary research expert group proposed to define DCI as the occurrence of cerebral infarction (identified on imaging or histology) associated with clinical deterioration. We performed a systematic review to assess whether preclinical models of SAH meet this definition, focusing on the combination of noninvasive imaging and neurological deficits. To this aim, we searched in PUBMED database and included all rodent SAH models that considered cerebral ischemia and/or neurological outcome and/or vasospasm. Seventy-eight publications were included. Eight different methods were performed to induce SAH, with blood injection in the cisterna magna being the most widely used (n = 39, 50%). Vasospasm was the most investigated SAH-related complication (n = 52, 67%) compared to cerebral ischemia (n = 30, 38%), which was never investigated with imaging. Neurological deficits were also explored (n = 19, 24%). This systematic review shows that no preclinical SAH model meets the 2010 clinical definition of DCI, highlighting the inconsistencies between preclinical and clinical standards. In order to enhance research and favor translation to humans, pertinent SAH animal models reproducing DCI are urgently needed.

Fold-stratified cross-validation for unbiased and privacy-preserving federated learning.

OBJECTIVE: We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs). MATERIALS AND METHODS: Fold-stratified cross-validation complements cross-validation with an initial stratification of EHRs in folds containing patients with similar characteristics, thus ensuring that duplicates of a record are jointly present either in training or in validation folds. Monte Carlo simulations are performed to investigate the properties of fold-stratified cross-validation in the case of a model data analysis using both synthetic data and MIMIC-III (Medical Information Mart for Intensive Care-III) medical records. RESULTS: In situations in which duplicated EHRs could induce overoptimistic estimations of accuracy, applying fold-stratified cross-validation prevented this bias, while not requiring full deduplication. However, a pessimistic bias might appear if the covariate used for the stratification was strongly associated with the outcome. DISCUSSION: Although fold-stratified cross-validation presents low computational overhead, to be efficient it requires the preliminary identification of a covariate that is both shared by duplicated records and weakly associated with the outcome. When available, the hash of a personal identifier or a patient's date of birth provides such a covariate. On the contrary, pseudonymization interferes with fold-stratified cross-validation, as it may break the equality of the stratifying covariate among duplicates. CONCLUSION: Fold-stratified cross-validation is an easy-to-implement methodology that prevents data leakage when a model is trained on distributed EHRs that contain duplicates, while preserving privacy.

The Fragility and Reliability of Conclusions of Anesthesia and Critical Care Randomized Trials With Statistically Significant Findings: A Systematic Review.

OBJECTIVES: The Fragility Index, which represents the number of patients responsible for a statistically significant finding, has been suggested as an aid for interpreting the robustness of results from clinical trials. A small Fragility Index indicates that the statistical significance of a trial depends on only a few events. Our objectives were to calculate the Fragility Index of statistically significant results from randomized controlled trials of anesthesia and critical care interventions and to determine the frequency of distorted presentation of results or "spin". DATA SOURCES: We systematically searched MEDLINE from January 01, 2007, to February 22, 2017, to identify randomized controlled trials exploring the effect of critical care medicine or anesthesia interventions. STUDY SELECTION: Studies were included if they randomized patients 1:1 into two parallel arms and reported at least one statistically significant (p < 0.05) binary outcome (primary or secondary). DATA EXTRACTION: Two reviewers independently assessed eligibility and extracted data. The Fragility Index was determined for the chosen outcome. We assessed the level of spin in negative trials and the presence of recommendations for clinical practice in positive trials. DATA SYNTHESIS: We identified 166 eligible randomized controlled trials with a median sample size of 207 patients (interquartile range, 109-497). The median Fragility Index was 3 (interquartile range, 1-7), which means that adding three events to one of the trials treatment arms eliminated its statistical significance. High spin was identified in 42% (n = 30) of negative randomized controlled trials, whereas 21% (n = 20) of positive randomized controlled trials provided recommendations. Lower levels of spin and recommendations were associated with publication in journals with high impact factors (p < 0.001 for both). CONCLUSIONS: Statistically significant results in anesthesia and critical care randomized controlled trials are often fragile, and study conclusions are frequently affected by spin. Routine calculation of the Fragility Index in medical literature may allow for better understanding of trials and therefore enhance the quality of reporting.