PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients

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Methods A total of 63 patients admitted for sepsis-induced AKI in our Mangalore ICU were evaluated and baseline demographic and clinical/laboratory parameters, including serum creatinine (SCr), base excess (BE), Plethysmographic Variability Index (PVI), Caval Index, R wave variability index (RVI), mean arterial pressure (MAP) and renal resistivity index (RI) using renal doppler and need for inotropes were assessed on admission. Patients were managed as per standard protocol. After six hours of fluid resuscitation, patients were classified as volume responders or non-responders. Re-assessment was done at 24 hours and 72 hours after admission. Primary outcome was persistent AKI after 72 hours. Secondary outcome was initiation of dialysis or death within 15 days of admission. Results A total of 34 subjects recovered from AKI, of whom 32 patients were volume responders and 31 were non-responders. Response to fluid, MAP at admission and six hours, BE at admission, inotrope requirement, and PVI at admission did not correlate with recovery. Multiple logistic regression showed that SCr 14.45 and RI < 0.8 on admission correlated with recovery and they were evaluated further to model AKI recovery and develop PASS. PASS score = (SCr points × 5.4) + (RVI points × 4.0) + (RI points × 6.2). One point each was allotted if SCr was 14.45 and RI was 7.8 predicted recovery with a sensitivity of 79.4%, specificity of 72.4%, PPV 81.8%, NPV 76.7% and AuROC of 0.85. Conclusions The PASS score can be used to identify salvageable cases of sepsis-AKI, guiding fluid resuscitation and aiding early referral from rural to tertiary care centers for better management. 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F1000Research 2024, 12 :902 ( https://doi.org/10.12688/f1000research.134459.3 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Revised PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] Dattatray Prabhu https://orcid.org/0000-0002-6743-8432 1 , Sonali Dattatray Prabhu 2 , Chakrapani Mahabala https://orcid.org/0000-0002-0460-7913 3 , Mayoor V Prabhu https://orcid.org/0000-0003-1227-4837 4 Dattatray Prabhu https://orcid.org/0000-0002-6743-8432 1 , Sonali Dattatray Prabhu 2 , Chakrapani Mahabala https://orcid.org/0000-0002-0460-7913 3 , Mayoor V Prabhu https://orcid.org/0000-0003-1227-4837 4 PUBLISHED 16 Sep 2024 Author details Author details 1 Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India 2 Department Of Radiodiagnosis, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India 3 Department of Medicine, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India 4 Department of Nephrology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India Dattatray Prabhu Roles: Conceptualization, Data Curation, Investigation, Methodology, Project Administration, Writing – Review & Editing Sonali Dattatray Prabhu Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Chakrapani Mahabala Roles: Conceptualization, Formal Analysis, Methodology, Project Administration, Supervision, Visualization, Writing – Review & Editing Mayoor V Prabhu Roles: Data Curation, Investigation, Methodology, Resources, Supervision, Visualization OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Manipal Academy of Higher Education gateway. Abstract Background We evaluated if the course of recovery from sepsis-induced acute kidney injury (AKI) can be predicted using variables collected at admission. Methods A total of 63 patients admitted for sepsis-induced AKI in our Mangalore ICU were evaluated and baseline demographic and clinical/laboratory parameters, including serum creatinine (SCr), base excess (BE), Plethysmographic Variability Index (PVI), Caval Index, R wave variability index (RVI), mean arterial pressure (MAP) and renal resistivity index (RI) using renal doppler and need for inotropes were assessed on admission. Patients were managed as per standard protocol. After six hours of fluid resuscitation, patients were classified as volume responders or non-responders. Re-assessment was done at 24 hours and 72 hours after admission. Primary outcome was persistent AKI after 72 hours. Secondary outcome was initiation of dialysis or death within 15 days of admission. Results A total of 34 subjects recovered from AKI, of whom 32 patients were volume responders and 31 were non-responders. Response to fluid, MAP at admission and six hours, BE at admission, inotrope requirement, and PVI at admission did not correlate with recovery. Multiple logistic regression showed that SCr 14.45 and RI < 0.8 on admission correlated with recovery and they were evaluated further to model AKI recovery and develop PASS. PASS score = (SCr points × 5.4) + (RVI points × 4.0) + (RI points × 6.2). One point each was allotted if SCr was 14.45 and RI was 7.8 predicted recovery with a sensitivity of 79.4%, specificity of 72.4%, PPV 81.8%, NPV 76.7% and AuROC of 0.85. Conclusions The PASS score can be used to identify salvageable cases of sepsis-AKI, guiding fluid resuscitation and aiding early referral from rural to tertiary care centers for better management. READ ALL READ LESS Keywords AKI, Sepsis, AKI recovery, renal Resistive index, Persistent AKI scoring system, Critically ill, RVI, creatinine Corresponding Author(s) Sonali Dattatray Prabhu ( [email protected] ) Close Corresponding author: Sonali Dattatray Prabhu Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2024 Prabhu D et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Prabhu D, Prabhu SD, Mahabala C and Prabhu MV. PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.12688/f1000research.134459.3 ) First published: 28 Jul 2023, 12 :902 ( https://doi.org/10.12688/f1000research.134459.1 ) Latest published: 16 Sep 2024, 12 :902 ( https://doi.org/10.12688/f1000research.134459.3 ) Revised Amendments from Version 2 Version 1 was reviewed previously, and the reviewer had reservations about the study’s sample size. We acknowledged in the article that the small sample size was a limitation of the study. Certain parameters, such as R wave variability, Renal Resistive Index, and initial serum creatinine levels, showed a strong correlation with AKI recovery, and these parameters had strong statistical significance. Therefore, the conclusion was drawn based on these findings. However, a follow-up study with a larger sample size is needed for external validation. In response to the reviewer’s query about whether the AKI cases in the study were sepsis-related, we clarified that sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI is typically clinical or subclinical at admission. This study included patients with sepsis-related AKI. Any cases of AKI later identified as associated with non-sepsis-related causes were excluded from the study. The term SA-AKI operationally defines the presence of AKI (based on clinical, biochemical, and functional criteria) within the context of sepsis as a distinct disease phenotype with a specific trajectory and outcome. We also addressed the reviewer’s request for clarification regarding the AKI definition by referencing the KDIGO criteria. Version 2 was reviewed and approved by the reviewer, who requested that we mention the study by Chaudhary et al. on sepsis-related AKI in the discussion section. Version 1 was reviewed previously, and the reviewer had reservations about the study’s sample size. We acknowledged in the article that the small sample size was a limitation of the study. Certain parameters, such as R wave variability, Renal Resistive Index, and initial serum creatinine levels, showed a strong correlation with AKI recovery, and these parameters had strong statistical significance. Therefore, the conclusion was drawn based on these findings. However, a follow-up study with a larger sample size is needed for external validation. In response to the reviewer’s query about whether the AKI cases in the study were sepsis-related, we clarified that sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI is typically clinical or subclinical at admission. This study included patients with sepsis-related AKI. Any cases of AKI later identified as associated with non-sepsis-related causes were excluded from the study. The term SA-AKI operationally defines the presence of AKI (based on clinical, biochemical, and functional criteria) within the context of sepsis as a distinct disease phenotype with a specific trajectory and outcome. We also addressed the reviewer’s request for clarification regarding the AKI definition by referencing the KDIGO criteria. Version 2 was reviewed and approved by the reviewer, who requested that we mention the study by Chaudhary et al. on sepsis-related AKI in the discussion section. See the authors' detailed response to the review by Hernando Gómez See the authors' detailed response to the review by Dhruva Chaudhry READ REVIEWER RESPONSES Introduction Many patients admitted in intensive care unit (ICU), present with acute kidney injury (AKI) caused by ischemia, hypoxia or nephrotoxicity, resulting in rapidly declining glomerular filtration rate (GFR), leading to an increased risk of morbidity and mortality. The prevalence of AKI in critically ill ICU patients is high, particularly in those with sepsis (20-50% rate of prevalence). 1 Reversibility of AKI is influenced by the recovery response, which is in turn affected by the extent of renal damage and potential for renal cell regeneration. 2 Hence, for such patients, rapid restoration of circulation as well as optimal perfusion pressure is of paramount importance. Persistent AKI, exceeding 48 hours, is shown to significantly increase mortality. 2 The clinical definition of AKI sums it up as a rapid decrease of GFR, leading to retention of nitrogenous waste products. AKI is diagnosed and staged using the RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease) classification and AKIN (Acute Kidney Injury Network) criteria. 1 , 3 Severity and causes of AKI vary and have direct effects on mortality. 1 , 3 The RIFLE criteria are one of the most commonly used criteria to define and diagnose AKI, developed by the Acute Dialysis Quality Initiative (ADQI); they determine AKI severity on the basis of serum creatine (SCr), GFR, and urine output. 4 Despite best efforts, AKI does not resolve in many cases. 5 The major challenge to clinicians is in prognostication and patient counseling. Many studies have proposed different models for this purpose. Some studies have used numerous biomarkers for prompt detection and predicting severity of AKI and thereby categorizing into appropriate risk groups at risk for progressive renal decline, requirement of RRT, or death. 5 – 7 Biomarkers like interleukin-18 (IL-18), cystatin C (Cys C), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1) and liver-type fatty acid binding protein (L-FABP) are being used for prediction of AKI and probable recovery. 6 – 8 Most of the tools to measure these biomarkers are expensive and not routinely available in all healthcare facilities. Our objective was to use easily available parameters and variables to predict the course of the disease in AKI. Ryo Matsuura et al. have published a scoring system called PARI (Persistent AKI Risk Index) to predict low risk persistent AKI in critically ill adult patients. 9 However, PARI does not enable assessment of patients at admission to decide on resuscitation. Hence this study included variables routinely collected at admission to predict the course of AKI and guide fluid resuscitation sepsis AKI. 9 , 10 Methods Study design, data source and participants This prospective cross-sectional study commenced after institutional ethics committee approval (see Ethical considerations at the end of the manuscript). Patients admitted to ICU during 2019-2020 with were included in this study, after informed written consent from all patients or their next of kins were obtained. This study utilized non-random sampling, with inclusion criteria being age > 18 years and patients with AKI and septic shock admitted to the ICU. 11 Exclusion criteria included pregnant women, patients diagnosed with renal artery stenosis, end-stage renal disease (ESRD) or chronic kidney disease (CKD), patients < 18 years, patients taking angiotensin-converting enzyme inhibitor (ACEI) or non-steroidal anti-inflammatory drugs (NSAID), patients with cirrhosis with hepatorenal syndrome, cardiorenal syndrome and patients with AKI secondary to urinary tract obstruction (diagnosed on imaging). KIDGO criteria do not recommend gender specific definitions for AKI. RI and RVI do not have gender specific cut offs. Methodology A total of 63 patients were included in over an eight-month period. We assessed parameters like serum creatinine (SCr), base excess (BE) in arterial blood gas (ABG) analysis, Plethysmographic Variability Index (PVI), Caval Index (CI), R wave variability in ECG, Mean arterial blood pressure (MAP), and renal resistive index (RI) using renal doppler screening on admission in patients presenting with sepsis. CI was calculated using IVC diameters obtained by trans-abdominal ultrasound using formula the formula (IVC maximum diameter during expiration − IVC minimum diameter during inspiration)/IVC maximum diameter × 100 and expressed as percentage. R wave variability represents the amplitude change in R waves on ECG calculated as (highest QRS amplitude – shortest QRS amplitude in one respiratory cycle)/mean QRS amplitude in same cycle × 100 and expressed as percentage. After 6 of hours of fluid resuscitation as per standard guidelines, hemodynamic status and volume status of the patient was assessed. Patients were classified as ‘volume responders’ or ‘non-responders’ depending on hemodynamic stabilization using parameters like systolic blood pressure (SBP) and MAP. Hemodynamic stabilization is characterized by MAP exceeding 65 mmHg beyond 1 hour with no change in the rate of catecholamine infusion or fluid vascular loading. Re-assessment of all variables including estimation of SCr, CI, BE, R wave variability, MAP and RI, was done at 24 hours and 72 hours after admission. The primary outcome was persistent AKI after 72 h. The secondary outcome was initiation of dialysis and death within 15 days of admission. AKI that resolves in 3 days of inclusion with conventional standard treatment in the ICU is called transient AKI. The recovery from AKI is characterized by SCr decreasing by 50% or absence of diuretics indicating normalization of urine output or both. Persistent AKI is characterized by persistently higher SCr or oliguria. 6 , 12 Statistical analysis The expression of percentages was done using categorical variables with means and standard deviations being expressed by continuous variables. Binary logistic regression was used to predict the AKI recovery using multiple variables as stated above, unadjusted and adjusted with noradrenaline and volume response and other variables. Based on the odds ratios (OR), a predictive equation was derived, and efficiency testing was performed with the use of a receiver operating characteristic curve (ROC) analysis. This curve’s coordinates, that yielded best sensitivity and specificity, were taken as a cut-off to develop a model (PASS score) for predicting recovery from AKI. In order to test the efficacy of the equation, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were considered. Additionally, the calculation of Kappa scores was done for the PASS score. Decision tree analysis was used for preparing the flow chart. All statistical analyses were performed using SPSS v.20 software. Our data showed no statistically significant difference in S creatinine, RI and R wave amplitude variation at admission between the genders. Hence gender specific subanalysis was not carried out. Results A total of 63 subjects admitted to ICU with AKI were included as study participants. The following parameters were studied at admission and repeated at 6 hours: MAP, SCr, BE, PVI, CI, R wave variability, and RI. Table 1 shows the patients’ baseline characteristics; patients were managed with standard protocols for fluid resuscitation and other specific treatments. Overall, 32 patients showed volume response with respect to hemodynamic parameters and 31 patients were non-responders to fluid resuscitations. A total of 34 subjects recovered from AKI. 11 Non-responders and 4 volume responders were dialysed. 34 patients (53.9%) needed vasopressors to maintain MAP above 65 mmHg of which 22 were in Non responders and 12 were volume responders. Table 1. Baseline characteristics of the patients. Age (Years) 55.98±14.27 Sex ratio Males (M): 40 Females (F): 23 MAP ADMISSION (mmHg) 63.57±4.88 RI atADMISSION 0.80±0.08 R wave Avariability at ADMISSION 15.09±2.05 CAVAL INDEX ON ADMISSION 54.53±12.54 BE ON ADMISSION (- mEq) 14.62±4.45 SCr ON ADMISSION 2.47±0.66 PVI ON ADMISSION 18.46±4.289 Gender (Male:Females) Males 40; Females 23 Co-morbidities: HTN: 34 (53.9%), DM: 21(33.4%) Ventilated: 11 patients were ventilated (17.5%) of which 7 were Non responders and 4 were volume responders. Multiple logistic regression analysis showed that response to fluid (seen as change in MAP at 6 hours); MAP, BE and PVI at admission and requirement of noradrenaline did not correlate with recovery of AKI ( Table 2 ). RI, RVI and SCr at admission correlated well with recovery from AKI, which was statistically significant. Cut-offs for these parameters were derived from the ROC curve analysis. Hence, these three parameters were evaluated further to develop the model for predicting recovery from AKI. Multiple logistic regression showed that creatinine 14.45 and RI < 0.8 at the time of admission were correlated with recovery from AKI with adjusted ORs of 5.447, 4.032 and 6.208 respectively ( Table 3 ). Based on this, the following formula was constructed in which SCr, RVI and RI were allotted points: • SCr 2.36 was allotted 0 points; • R wave variability > 14.45 was allotted 1 point and values < 14.45 were allotted 0 points • RI 0.8 was allotted 0 points. Table 2. Logistic regression analysis for prediction of non-recovery from AKI. Acronyms: S.Cr - Serum creatinine, BE - Base excess in Arterial blood gas analysis, PVI - Plethysmographic variability index, MAP - Mean arterial blood pressure, RI - renal resistive index, CI - confidence interval. Unadjusted Adjusted for nor adrenalin and volume response Adjusted for all other variables OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value MAP difference at 6 hours 0.883 (0.738, 1.058) 0.177 0.878 (0.725,1.063) 0.181 0.681 (0.409,1.13232734) 0.14 MAP at admission 1.001 (0.904, 1.109) 0.982 1.055 (0.94,1.185) 0.36 0.849 (0.629,1.147) 0.286 RI at admission 184159.441 (78.714, 430858802.455) 0.002 63532.03 (19.266, 209500675.204) 0.007 19780.188 (1.413, 276815193.317) 0.042 R wave variability at admission 0.564 (0.39, 0.817) 0.002 0.562 (0.361,0.873) 0.01 0.476 (0.261,0.868) 0.015 Caval Index At admission 0.971 (0.932, 1.012) 0.16 0.994 (0.932,1.06) 0.851 1.027 (0.938,1.125) 0.564 BE at admission 0.906 (0.806, 1.019) 0.101 0.98 (0.844,1.137) 0.786 0.948 (0.765,1.175) 0.626 SCr at admission 3.908 (1.459, 10.471) 0.007 3.428 (1.198,9.807) 0.022 4.248 (1.145,15.763) 0.031 PVI at admission 0.879 (0.759, 1.017) 0.084 0.9 (0.762,1.064) 0.217 1.024 (0.806,1.3) 0.847 Table 3. Multivariate analysis showing p-value, adjusted odds ratio and 95% confidence interval (CI) for odds for variables. P Adjusted odds ratio 95% CI for odds ratio Lower Upper Creatinine > 2.36 0.010 5.447 1.494 19.859 R wave variability > 14.45 0.038 4.032 1.083 15.011 Resistive Index < 0.8 0.005 6.208 1.750 22.021 Persistent AKI Scoring System (PASS) formula ( Table 4 ) Table 4. Persistent AKI score-: points to be alloted for variables. Parameter Cut-off Points Creatinine 2.36 0 R wave variability at admission >14.45 4.0 <14.45 0 Resistive index on admission 0.8 0 SCr points × 5.4 + R wave variability points × 4.0 + RI points × 6.2 A total score > 7.8 predicted recovery from AKI. Sensitivity, specificity, predictive value, diagnostic accuracy and Kappa value (agreement with actual outcome) for SCr, RI at admission and RVI and for PASS score are shown in Table 5 . A PASS Score > 7.8 had a sensitivity of 79.4% and 72.4% specificity for recovery from AKI. The PPV was 81.8% and NPV was 76.7%. The test and the gold standard agreed on 50 out of 63 having a diagnostic accuracy of 79.34%. The Kappa value of 0.586 indicated good agreement, with a p-value of 7.8, obtained by analysis of the ROC curve, had an ROC curve area of 0.85 (95% confidence interval of 0.755 to 0.943; p < 0.001) ( Figure 1 ). Table 5. Sensitivity, specificity, predictive value, diagnostic accuracy and Kappa value forserum creatinine (SCr), Resistive Index (RI) at admission and R wave at admission, and of PASS study score. Parameter RI at admission < 0.8 SCr at admission 14.45 PASS > 7.8 Sensitivity 79.30% 72.40% 73.50% 79.40% Specificity 58.80% 70.60% 58.60% 79.30% Positive predictive value 62.20% 67.70% 67.60% 81.80% Negative predictive value 76.90% 75.00% 65.40% 76.70% Diagnostic accuracy 68.25% 71.43% 66.67% 79.37% Kappa statistics 0.374 0.428 0.324 0.586 p-value 0.004 0.001 0.012 <0.001 Figure 1. ROC curve for PASS score. Discussion The Renal Angina Index, that detects minor variations in SCr along with other clinical variables, was proposed by some studies for identifying critically ill patients who are more likely to experience persistent AKI. 12 , 13 Few studies have tried to predict the severity of renal angina and utilized plasma and/or urinary biomarkers like cystatin C, L-FABP, NGAL, IL-18, KIM-1, among others, which are time consuming and expensive to measure. 7 , 8 In the Indian setting, some of the tools for measuring these biomarkers are not routinely available, limiting their widespread use. We have tried to utilize easily available data at the time of admission to develop a system that can solve this issue in developing countries. Some of these previous studies have used parameters at admission and after 24 hours for understanding whether AKI will be persistent. This method only helped to prognosticate patients after 24 h of admission. 9 As these test results are available after a lag time, they do not help clinicians in deciding at the time of admission whether patients will benefit from aggressive resuscitation. Thus, a robust system is needed, not only to assess but also to intervene at the earliest to reverse the damage. Our study concluded that SCr, RI and RVI at admission are statistically significant (p < 0.05) to predict AKI reversibility, which we have further analyzed to develop the PASS (Persistent AKI Scoring System) formula to predict the course of AKI. PASS is a combined scoring system that includes SCr levels, RI and RVI at admission. A total score greater than 7.8 predicted recovery from AKI. We also developed a flow chart for prediction of recovery from AKI which is shown in Figure 2 . We found that the use of the PASS score and flow chart in adult ICU patients to be an effective tool to decide which patients have high risk of persistent AKI, and identify those who have potential for recovery from persistent AKI and will benefit from aggressive therapy, thus helping better prognostication. Figure 2. Flow chart for assessing renal anginal recovery i.e. recovery from AKI. Studies in the literature have also shown that RI is an important predictor of AKI and can even be used as a preoperative screening tool to predict AKI after surgeries. 14 Renal doppler and RI measurement can be done as a bedside tool to assess the renal circulation and are also a useful marker of sepsis 14 ; they can also help to differentiate persistent AKI from transient AKI in critically ill ICU patients. 15 RI is a non-invasive Doppler-measured parameter, corresponding to intra-renal arterial resistance and central hemodynamic parameters. Estimating increased RI on the first day of admission can help predict AKI in septic shock, and the literature has shown that these patients usually require mechanical ventilation. While some studies have shown higher RI values in AKI stages 2 and 3, this is not the case for patients in AKI stage 1. 14 , 15 A RI value beyond 0.795 predicts possibility of persistent AKI with good sensitivity and specificity. 16 Intravascular blood volume is dependent on the hemodynamic status of the patient and correlates with IVC diameter, in addition to morphological variations within the ECG like amplitude of waves. This phenomenon called “Brody effect”, related to the relationship of left ventricular volume on QRS-wave amplitude, can be identified by an increased amplitude of the QRS-wave due to increased ventricular preload. Thus, R wave variability is a reliable indicator for intravascular volume status variations. 17 Choudhary et al, in a large observation study using deep learning cluster analysis, have identified three distinct clusters in sepsis-induced AKI. The cluster with favourable outcome, in addition to having lesser severity of sepsis and also lesser multi organ involvement, had relatively lesser creatinine and lesser number of patients with creatinine criteria for AKI. Our study also confirmed that lower creatinine is associated with favourable outcome in sepsis induced AKI. Patients with sepsis-induced AKI had better come if they had only oliguric criteria as per Choudhary et al study. Our study also showed that patients with lower resistive index had favourable outcome indicating that patients without structural changes in kidney (as evidence by lower resistive index) had favourable outcome compared to those who had higher resistive index. 18 Our study is limited by being a single-centre study with a relatively smaller sample size. Wider application of our conclusions and predictive tool would require validation in larger multi-center studies. Conclusion Acute kidney injury is very common in patients admitted to critical care. Invasive monitoring help us judge and guide resuscitation, but in rural areas facilities for these are not available. This study is to help these healthcare workers to use bed side non invasive parameters and blood reports at admission to assess and prognosticate kidney injury. Early identification of recoverable AKI patients will help in aggressive approach or early referral to tertiary center. Ethical considerations Ethical approval was obtained from the Institutional Ethics Committee, Medical College, Mangaluru (Reg. No. ECR/541//nst/KA/2014/RR-17; Approval number IEC KMC MLR 08-19/327). Data availability Underlying data Zenodo: PASS - A SCORING SYSTEM TO EVALUATE PERSISTENT ACUTE KIDNEY INJURY IN CRITICALLY ILL ADULT ICU PATIENTS, https://doi.org/10.5281/zenodo.7879938 . 19 This project contains the following underlying data: - PASS SCORE- AKI masterchart.xlsx Extended data Zenodo: PASS - A SCORING SYSTEM TO EVALUATE PERSISTENT ACUTE KIDNEY INJURY IN CRITICALLY ILL ADULT ICU PATIENTS, https://doi.org/10.5281/zenodo.7879938 . 19 This project contains the following extended data: - CHARTS AND TABLES (PASS SCORE-AKI).docx Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Acknowledgements This study was presented as an Abstract at the 21 st Annual Congress of Indian Society of Critical Care Medicine CRITICARE 2021, held online from 24-28 th February 2021. The abstract was published in the Indian Journal of Critical Care Medicine, 2021 Feb; 25(Suppl 1): S1–S114. 4. Pass—A Novel Study to Predict Recovery from AKI in Critically Ill Adult ICU Patients (Conference Abstract ID: 55) DOI: 10.5005/jp-journals-10071-23711.4 . References 1. Case J, Khan S, Khalid R, et al. : Epidemiology of acute kidney injury in the intensive care unit. Crit. Care Res. Prac. 2013; 2013 : 479730. Epub 2013 Mar 21. PubMed Abstract | Publisher Full Text | Free Full Text 2. Basile DP, Anderson MD, Sutton TA: Pathophysiology of acute kidney injury. Compr. Physiol. 2012 Apr; 2 (2): 1303–1353. PubMed Abstract | Publisher Full Text | Free Full Text 3. Uchino S, Kellum JA, Bellomo R, et al. : Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA. 2005 Aug 17; 294 (7): 813–818. PubMed Abstract | Publisher Full Text 4. Lopes JA, Jorge S: The RIFLE and AKIN classifications for acute kidney injury: a critical and comprehensive review. Clin. Kidney J. 2013 Feb; 6 (1): 8–14. PubMed Abstract | Publisher Full Text | Free Full Text 5. Bellomo R, Ronco C, Kellum JA, et al. : Acute renal failure - definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit. Care. 2004 Aug; 8 (4): R204–R212. Epub 2004 May 24. PubMed Abstract | Publisher Full Text | Free Full Text 6. Bhatraju PK, Zelnick LR, Katz R, et al. : A Prediction Model for Severe AKI in Critically Ill Adults That Incorporates Clinical and Biomarker Data. Clin. J. Am. Soc. Nephrol. 2019 Apr 5; 14 (4): 506–514. PubMed Abstract | Publisher Full Text | Free Full Text 7. Tsigou E, Psallida V, Demponeras C, et al. : Role of New Biomarkers: Functional and Structural Damage. Crit. Care Res. Prac. 2013; 2013 : 13. Article ID 361078. Publisher Full Text 8. Teo SH, Endre ZH: Biomarkers in acute kidney injury (AKI). Best Pract. Res. Clin. Anaesthesiol. 2017 Sep; 31 (3): 331–344. PubMed Abstract | Publisher Full Text 9. Matsuura R, Iwagami M, Moriya H, et al. : A Simple Scoring Method for Predicting the Low Risk of Persistent Acute Kidney Injury in Critically Ill Adult Patients. Sci. Rep. 2020 Mar 31; 10 (1): 5726. PubMed Abstract | Publisher Full Text | Free Full Text 10. Rhodes A, Evans LE, Alhazzani W, et al. : Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016. Intensive Care Med. 2017 Mar; 43 (3): 304–377. Epub 2017 Jan 18. PubMed Abstract | Publisher Full Text 11. Bone RC, Balk RA, Cerra FB, et al. : Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 1992 Jun; 101 (6): 1644–1655. PubMed Abstract | Publisher Full Text 12. Kellum JA, Sileanu FE, Bihorac A, et al. : Recovery after Acute Kidney Injury. Am. J. Respir. Crit. Care Med. 2017 Mar 15; 195 (6): 784–791. PubMed Abstract | Publisher Full Text | Free Full Text 13. Matsuura R, Srisawat N, Claure-Del Granado R, et al. : Use of the Renal Angina Index in Determining Acute Kidney Injury. Kidney Int Rep. 2018 Feb 3; 3 (3): 677–683. PubMed Abstract | Publisher Full Text | Free Full Text 14. Haitsma Mulier JLG, Rozemeijer S, Röttgering JG, et al. : Renal resistive index as an early predictor and discriminator of acute kidney injury in critically ill patients; A prospective observational cohort study. PLoS One. 2018 Jun 11; 13 (6): e0197967. PubMed Abstract | Publisher Full Text | Free Full Text 15. Bellos I, Pergialiotis V, Kontzoglou K: Renal resistive index as predictor of acute kidney injury after major surgery: A systematic review and meta-analysis. J. Crit. Care. 2019 Apr; 50 : 36–43. PubMed Abstract | Publisher Full Text 16. Dewitte A, Coquin J, Meyssignac B, et al. : Doppler resistive index to reflect regulation of renal vascular tone during sepsis and acute kidney injury. Crit. Care. 2012 Sep 12; 16 (5): R165. PubMed Abstract | Publisher Full Text | Free Full Text 17. Giraud R, Siegenthaler N, Morel DR, et al. : Respiratory change in ECG-wave amplitude is a reliable parameter to estimate intravascular volume status. J. Clin. Monit. Comput. 2013 Apr; 27 (2): 107–111. Epub 2012 Nov 2. PubMed Abstract | Publisher Full Text 18. Chaudhary K, Vaid A, Duffy Á, et al. : Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury. Clin. J. Am. Soc. Nephrol. 2020; 15 (11): 1557–1565. PubMed Abstract | Publisher Full Text | Free Full Text 19. Prabhu D, Prabhu SD, Mahabala C, et al. : PASS - A SCORING SYSTEM TO EVALUATE PERSISTENT ACUTE KIDNEY INJURY IN CRITICALLY ILL ADULT ICU PATIENTS. [Data set]. f1000. Zenodo. 2023. Publisher Full Text Comments on this article Comments (0) Version 3 VERSION 3 PUBLISHED 28 Jul 2023 ADD YOUR COMMENT Comment Author details Author details 1 Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India 2 Department Of Radiodiagnosis, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India 3 Department of Medicine, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India 4 Department of Nephrology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 575001, India Dattatray Prabhu Roles: Conceptualization, Data Curation, Investigation, Methodology, Project Administration, Writing – Review & Editing Sonali Dattatray Prabhu Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Chakrapani Mahabala Roles: Conceptualization, Formal Analysis, Methodology, Project Administration, Supervision, Visualization, Writing – Review & Editing Mayoor V Prabhu Roles: Data Curation, Investigation, Methodology, Resources, Supervision, Visualization Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (3) version 3 Revised Published: 16 Sep 2024, 12:902 https://doi.org/10.12688/f1000research.134459.3 version 2 Revised Published: 12 Feb 2024, 12:902 https://doi.org/10.12688/f1000research.134459.2 version 1 Published: 28 Jul 2023, 12:902 https://doi.org/10.12688/f1000research.134459.1 Copyright © 2024 Prabhu D et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Prabhu D, Prabhu SD, Mahabala C and Prabhu MV. PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.12688/f1000research.134459.3 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 3 VERSION 3 PUBLISHED 16 Sep 2024 Revised Views 0 Cite How to cite this report: Chaudhry D. Reviewer Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.171311.r353011 ) The direct URL for this report is: https://f1000research.com/articles/12-902/v3#referee-response-353011 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 14 Jan 2025 Dhruva Chaudhry , Pt BD Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana, India Approved VIEWS 0 https://doi.org/10.5256/f1000research.171311.r353011 Prabhu et al have tried to make an objective predictive model for resource limited countries or institutions. The article is well written ,however few corrections are required especially in Result section of Abstract. 1. First line needs to be rewritten ... Continue reading READ ALL Prabhu et al have tried to make an objective predictive model for resource limited countries or institutions. The article is well written ,however few corrections are required especially in Result section of Abstract. 1. First line needs to be rewritten [Volume responders number are from total Cohort & not from patients recovered from AKI]. 2. The formula generated to calculate needs an explanation. 3. As KIDGO is used, one does not find mention of Urine output? reason for exclusion of UO, may please be mentioned. 4. Number in study is small (explanation given), strength seems to be prospective nature. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: critical care, respiratory medicine, public health, infectious diseases, policy etc. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Chaudhry D. Reviewer Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.171311.r353011 ) The direct URL for this report is: https://f1000research.com/articles/12-902/v3#referee-response-353011 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 25 Jan 2025 Dattatray Prabhu , Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, 575001, India 25 Jan 2025 Author Response Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit ... Continue reading Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit the line in the result section and upload. The scoring system was developed based on the findings of multivariate logistic regression analysis. Parameters were selected if they had statistically significant results. The cutoffs for these values were analysed based on the results of the ROC curve analysis. The relative weightage of each of these parameters was identified by the respective regression coefficient or the odds ratio. Ideal cutoff for the outcome of the equation was ascertained by ROC curve analysis. At admission we considered serum creatinine levels and urine output at baseline and for next 6hrs to categorise acute kidney injury at admission using KIDGO criteria. we have not excluded urine output. We have accepted in the literature that our study is limited by being a single-centre study with a relatively smaller sample size. Wider application of our conclusions and predictive tool would require validation in larger multi-center studies. Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit the line in the result section and upload. The scoring system was developed based on the findings of multivariate logistic regression analysis. Parameters were selected if they had statistically significant results. The cutoffs for these values were analysed based on the results of the ROC curve analysis. The relative weightage of each of these parameters was identified by the respective regression coefficient or the odds ratio. Ideal cutoff for the outcome of the equation was ascertained by ROC curve analysis. At admission we considered serum creatinine levels and urine output at baseline and for next 6hrs to categorise acute kidney injury at admission using KIDGO criteria. we have not excluded urine output. We have accepted in the literature that our study is limited by being a single-centre study with a relatively smaller sample size. Wider application of our conclusions and predictive tool would require validation in larger multi-center studies. Competing Interests: none Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 25 Jan 2025 Dattatray Prabhu , Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, 575001, India 25 Jan 2025 Author Response Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit ... Continue reading Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit the line in the result section and upload. The scoring system was developed based on the findings of multivariate logistic regression analysis. Parameters were selected if they had statistically significant results. The cutoffs for these values were analysed based on the results of the ROC curve analysis. The relative weightage of each of these parameters was identified by the respective regression coefficient or the odds ratio. Ideal cutoff for the outcome of the equation was ascertained by ROC curve analysis. At admission we considered serum creatinine levels and urine output at baseline and for next 6hrs to categorise acute kidney injury at admission using KIDGO criteria. we have not excluded urine output. We have accepted in the literature that our study is limited by being a single-centre study with a relatively smaller sample size. Wider application of our conclusions and predictive tool would require validation in larger multi-center studies. Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit the line in the result section and upload. The scoring system was developed based on the findings of multivariate logistic regression analysis. Parameters were selected if they had statistically significant results. The cutoffs for these values were analysed based on the results of the ROC curve analysis. The relative weightage of each of these parameters was identified by the respective regression coefficient or the odds ratio. Ideal cutoff for the outcome of the equation was ascertained by ROC curve analysis. At admission we considered serum creatinine levels and urine output at baseline and for next 6hrs to categorise acute kidney injury at admission using KIDGO criteria. we have not excluded urine output. We have accepted in the literature that our study is limited by being a single-centre study with a relatively smaller sample size. Wider application of our conclusions and predictive tool would require validation in larger multi-center studies. Competing Interests: none Close Report a concern COMMENT ON THIS REPORT Version 2 VERSION 2 PUBLISHED 12 Feb 2024 Revised Views 0 Cite How to cite this report: Agarwal A. Reviewer Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.159669.r308310 ) The direct URL for this report is: https://f1000research.com/articles/12-902/v2#referee-response-308310 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Aug 2024 Anupam Agarwal , The University of Alabama at Birmingham, Birmingham, Alabama, USA Approved VIEWS 0 https://doi.org/10.5256/f1000research.159669.r308310 The authors have provided a new scoring system - PASS - Persistent AKI Scoring System - to identify patients with sepsis-associated AKI who would need early referral to a tertiary care center. Positive aspects of the study include the use ... Continue reading READ ALL The authors have provided a new scoring system - PASS - Persistent AKI Scoring System - to identify patients with sepsis-associated AKI who would need early referral to a tertiary care center. Positive aspects of the study include the use of bedside non-invasive parameters and lab tests at admission to predict outcomes and early identification of patients who may need more aggressive management. Limitations are the small sample size of 63 patients which is duly acknowledged by the authors. Two points the authors should consider: 1. Spell out the abbreviation PASS in the abstract under the results paragraph. 2. Relate their findings in sepsis associated AKI and the use of the PASS scoring system to the work of Chaudhary et al (CJASN 2020, PMID: 33033164) who subphenotyped sepsis-associated AKI into three types based on deep learning and data from the electronic medical record. This could be done in the discussion section of their paper. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Acute kidney injury I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Agarwal A. Reviewer Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.159669.r308310 ) The direct URL for this report is: https://f1000research.com/articles/12-902/v2#referee-response-308310 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 28 Jul 2023 Views 0 Cite How to cite this report: Gómez H. Reviewer Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.147517.r211850 ) The direct URL for this report is: https://f1000research.com/articles/12-902/v1#referee-response-211850 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 24 Oct 2023 Hernando Gómez , University of Pittsburgh, Pittsburgh, Pennsylvania, USA Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.147517.r211850 Title: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients Summary: Prabhu et al. present a prospective study in 63 patients with the objective to predict the course of sepsis induced ... Continue reading READ ALL Title: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients Summary: Prabhu et al. present a prospective study in 63 patients with the objective to predict the course of sepsis induced AKI using easily available parameters and variables. The authors used serum creatinine (SCr), base excess (BE), Plethysmographic Variability Index (PVI), Caval Index, R wave variability index (RVI), mean arterial pressure (MAP) and renal resistivity index (RI) using renal doppler and need for inotropes were assessed on admission, 24 and 72h. They report that 34 patients recovered form AKI. Using multiple logistic regression, they determined thresholds and weights to compound the PASS score, ultimately composed of SCr, RVI and RI, achieving an AUC of 0.85, with sensitivity of 79.4%, specificity 72.4% for a threshold score of > 7.8 to predict recovery. The authors conclude that ‘the PASS score can be used to identify salvageable cases of sepsis-AKI, guiding fluid resuscitation and aiding early referral from rural to tertiary care centers for better management.’ General comments: The manuscript is well written, and is focused on an important topic for the field. However, the enthusiasm is decreased due to significant methodological pitfalls. Specific examples and comments are detailed below. Major comments: The most important limitation of this study is the small sample size and the lack of validation of the PASS score. It is problematic to have less than 10 events per variable (EPV) when running this type of logistic regressions, as this can result in overfitting (type I error, PMID: 8970487). In the absence of a larger sample size and additional validation in an independent data set, it is difficult to consider the internal and external validity of the score. Based on No. 1, it is difficult to accept the conclusion proposed by the authors. Based on the selection criteria, the PASS score may be applicable only to sepsis associated AKI, but not to other forms of AKI? Also, it is unclear what the timing of AKI diagnosis was in relation to sepsis, which is an important component of the definition of SA-AKI (PMID: 36823168) The description of hemodynamic stabilization used a MAP of 60 mmHg instead of a MAP of 65 mmHg as recommended. Can the authors expand on the justification for the selection of this parameter? The definition of volume responsiveness in the literature is not dependent on achieving a goal MAP or SBP, but rather on whether a bolus of fluid will increase cardiac output (or accepted surrogates) by at least 10%. The authors hereby use a different definition of volume responsiveness. The authors may consider modifying the terminology to align better with current definitions of volume responsiveness. How did the authors define persistent AKI? The authors state they used SCr or oliguria to define persistent AKI. However, there is no definition of oliguria. Did the authors use KDIGO criteria? Was any stage AKI considered as persistent AKI if lasting > 72h? How did the authors define transient AKI? How did authors determine the presence of AKI? Was KDIGO staging used to defined AKI, and were both components (SCr and UO) used? Please specify what were the covariates use to adjust the logistic regression model. The description of the cohort is very limited, with only comporbidities shown including HTN and DM. Minor comments Please include measures of dispersion of the data in the form of standard deviation, IQR, etc. Page 7. IVC diameter is not a reflection of intravascular volume. Rather, a specific threshold of static IVC diameter correlates with being above or below a certain CVP. Please revise this comment. There is no conclusion in the manuscript. Please consider adding a conclusion. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? No References 1. Peduzzi P, Concato J, Kemper E, Holford TR, et al.: A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol . 1996; 49 (12): 1373-9 PubMed Abstract | Publisher Full Text 2. Zarbock A, Nadim MK, Pickkers P, Gomez H, et al.: Sepsis-associated acute kidney injury: consensus report of the 28th Acute Disease Quality Initiative workgroup. Nat Rev Nephrol . 2023; 19 (6): 401-417 PubMed Abstract | Publisher Full Text Competing Interests: No competing interests were disclosed. Reviewer Expertise: Sepsis, AKI, metabolic reprogramming, organ dysfucntion I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Gómez H. Reviewer Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.147517.r211850 ) The direct URL for this report is: https://f1000research.com/articles/12-902/v1#referee-response-211850 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 12 Feb 2024 Dattatray Prabhu , Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, 575001, India 12 Feb 2024 Author Response Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its ... Continue reading Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its a small sample size. Certain parameters among others had strong co-relation with AKI recovery. These parameters like R wave variability, Renal Resistive Index and initial S.Cr levels had a strong statistical significance to AKI recovery,so the conclusion was made. This needs a follow up study using larger study population for external validation. Sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI are usually clinical or subclinical at admission. This study includes sepsis related aki patients. During later part of ICU stay if AKI was found to be associated with non-sepsis-related causes such cases were excluded. The term SA-AKI operationally unifies the presence of AKI (according to clinical, biochemical and functional criteria) in the context of sepsis as a specific disease phenotype that is characterized by a specific trajectory and outcome. The target MAP for resuscitation was 65mmhg as per guideline. Correction was made in the manuscript accordingly. This study is mainly looking at non-invasive parameters to assess AKI recovery, hence we did not consider invasive monitors to look at cardiac output. Recovery from AKI was attributed to decreasing creatine and normalizing urine output. KIDGO criteria were used to categorize AKI after admission and recovery 24 hours after admission and beyond. Recovery of renal parameters and/or urine output beyond 72 hours were also considered as AKI recovery. There are studies to show a strong correlation between IVC collapsibility and CVP. In this study, we have not considered CVP as it needs an invasive line and as previously mentioned this study is mainly focused on noninvasive parameters. Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its a small sample size. Certain parameters among others had strong co-relation with AKI recovery. These parameters like R wave variability, Renal Resistive Index and initial S.Cr levels had a strong statistical significance to AKI recovery,so the conclusion was made. This needs a follow up study using larger study population for external validation. Sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI are usually clinical or subclinical at admission. This study includes sepsis related aki patients. During later part of ICU stay if AKI was found to be associated with non-sepsis-related causes such cases were excluded. The term SA-AKI operationally unifies the presence of AKI (according to clinical, biochemical and functional criteria) in the context of sepsis as a specific disease phenotype that is characterized by a specific trajectory and outcome. The target MAP for resuscitation was 65mmhg as per guideline. Correction was made in the manuscript accordingly. This study is mainly looking at non-invasive parameters to assess AKI recovery, hence we did not consider invasive monitors to look at cardiac output. Recovery from AKI was attributed to decreasing creatine and normalizing urine output. KIDGO criteria were used to categorize AKI after admission and recovery 24 hours after admission and beyond. Recovery of renal parameters and/or urine output beyond 72 hours were also considered as AKI recovery. There are studies to show a strong correlation between IVC collapsibility and CVP. In this study, we have not considered CVP as it needs an invasive line and as previously mentioned this study is mainly focused on noninvasive parameters. Competing Interests: We do not have any competing interest. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 12 Feb 2024 Dattatray Prabhu , Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, 575001, India 12 Feb 2024 Author Response Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its ... Continue reading Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its a small sample size. Certain parameters among others had strong co-relation with AKI recovery. These parameters like R wave variability, Renal Resistive Index and initial S.Cr levels had a strong statistical significance to AKI recovery,so the conclusion was made. This needs a follow up study using larger study population for external validation. Sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI are usually clinical or subclinical at admission. This study includes sepsis related aki patients. During later part of ICU stay if AKI was found to be associated with non-sepsis-related causes such cases were excluded. The term SA-AKI operationally unifies the presence of AKI (according to clinical, biochemical and functional criteria) in the context of sepsis as a specific disease phenotype that is characterized by a specific trajectory and outcome. The target MAP for resuscitation was 65mmhg as per guideline. Correction was made in the manuscript accordingly. This study is mainly looking at non-invasive parameters to assess AKI recovery, hence we did not consider invasive monitors to look at cardiac output. Recovery from AKI was attributed to decreasing creatine and normalizing urine output. KIDGO criteria were used to categorize AKI after admission and recovery 24 hours after admission and beyond. Recovery of renal parameters and/or urine output beyond 72 hours were also considered as AKI recovery. There are studies to show a strong correlation between IVC collapsibility and CVP. In this study, we have not considered CVP as it needs an invasive line and as previously mentioned this study is mainly focused on noninvasive parameters. Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its a small sample size. Certain parameters among others had strong co-relation with AKI recovery. These parameters like R wave variability, Renal Resistive Index and initial S.Cr levels had a strong statistical significance to AKI recovery,so the conclusion was made. This needs a follow up study using larger study population for external validation. Sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI are usually clinical or subclinical at admission. This study includes sepsis related aki patients. During later part of ICU stay if AKI was found to be associated with non-sepsis-related causes such cases were excluded. The term SA-AKI operationally unifies the presence of AKI (according to clinical, biochemical and functional criteria) in the context of sepsis as a specific disease phenotype that is characterized by a specific trajectory and outcome. The target MAP for resuscitation was 65mmhg as per guideline. Correction was made in the manuscript accordingly. This study is mainly looking at non-invasive parameters to assess AKI recovery, hence we did not consider invasive monitors to look at cardiac output. Recovery from AKI was attributed to decreasing creatine and normalizing urine output. KIDGO criteria were used to categorize AKI after admission and recovery 24 hours after admission and beyond. Recovery of renal parameters and/or urine output beyond 72 hours were also considered as AKI recovery. There are studies to show a strong correlation between IVC collapsibility and CVP. In this study, we have not considered CVP as it needs an invasive line and as previously mentioned this study is mainly focused on noninvasive parameters. Competing Interests: We do not have any competing interest. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 3 VERSION 3 PUBLISHED 28 Jul 2023 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 3 (revision) 16 Sep 24 read Version 2 (revision) 12 Feb 24 read Version 1 28 Jul 23 read Hernando Gómez , University of Pittsburgh, Pittsburgh, USA Anupam Agarwal , The University of Alabama at Birmingham, Birmingham, USA Dhruva Chaudhry , Pt BD Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana, India Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Chaudhry D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 14 Jan 2025 | for Version 3 Dhruva Chaudhry , Pt BD Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana, India 0 Views copyright © 2025 Chaudhry D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Prabhu et al have tried to make an objective predictive model for resource limited countries or institutions. The article is well written ,however few corrections are required especially in Result section of Abstract. 1. First line needs to be rewritten [Volume responders number are from total Cohort & not from patients recovered from AKI]. 2. The formula generated to calculate needs an explanation. 3. As KIDGO is used, one does not find mention of Urine output? reason for exclusion of UO, may please be mentioned. 4. Number in study is small (explanation given), strength seems to be prospective nature. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise critical care, respiratory medicine, public health, infectious diseases, policy etc. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (1) Author Response 25 Jan 2025 Dattatray Prabhu, Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, 575001, India Respected sir, We thank you for taking the time to review our article. This article provides a simple kidney injury organ-scoring system for resource-limited settings. As suggested we will edit the line in the result section and upload. The scoring system was developed based on the findings of multivariate logistic regression analysis. Parameters were selected if they had statistically significant results. The cutoffs for these values were analysed based on the results of the ROC curve analysis. The relative weightage of each of these parameters was identified by the respective regression coefficient or the odds ratio. Ideal cutoff for the outcome of the equation was ascertained by ROC curve analysis. At admission we considered serum creatinine levels and urine output at baseline and for next 6hrs to categorise acute kidney injury at admission using KIDGO criteria. we have not excluded urine output. We have accepted in the literature that our study is limited by being a single-centre study with a relatively smaller sample size. Wider application of our conclusions and predictive tool would require validation in larger multi-center studies. View more View less Competing Interests none reply Respond Report a concern Chaudhry D. Peer Review Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.171311.r353011) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-902/v3#referee-response-353011 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Agarwal A. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Aug 2024 | for Version 2 Anupam Agarwal , The University of Alabama at Birmingham, Birmingham, Alabama, USA 0 Views copyright © 2024 Agarwal A. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The authors have provided a new scoring system - PASS - Persistent AKI Scoring System - to identify patients with sepsis-associated AKI who would need early referral to a tertiary care center. Positive aspects of the study include the use of bedside non-invasive parameters and lab tests at admission to predict outcomes and early identification of patients who may need more aggressive management. Limitations are the small sample size of 63 patients which is duly acknowledged by the authors. Two points the authors should consider: 1. Spell out the abbreviation PASS in the abstract under the results paragraph. 2. Relate their findings in sepsis associated AKI and the use of the PASS scoring system to the work of Chaudhary et al (CJASN 2020, PMID: 33033164) who subphenotyped sepsis-associated AKI into three types based on deep learning and data from the electronic medical record. This could be done in the discussion section of their paper. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Acute kidney injury I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Agarwal A. Peer Review Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.159669.r308310) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-902/v2#referee-response-308310 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2023 Gómez H. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 24 Oct 2023 | for Version 1 Hernando Gómez , University of Pittsburgh, Pittsburgh, Pennsylvania, USA 0 Views copyright © 2023 Gómez H. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Title: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients Summary: Prabhu et al. present a prospective study in 63 patients with the objective to predict the course of sepsis induced AKI using easily available parameters and variables. The authors used serum creatinine (SCr), base excess (BE), Plethysmographic Variability Index (PVI), Caval Index, R wave variability index (RVI), mean arterial pressure (MAP) and renal resistivity index (RI) using renal doppler and need for inotropes were assessed on admission, 24 and 72h. They report that 34 patients recovered form AKI. Using multiple logistic regression, they determined thresholds and weights to compound the PASS score, ultimately composed of SCr, RVI and RI, achieving an AUC of 0.85, with sensitivity of 79.4%, specificity 72.4% for a threshold score of > 7.8 to predict recovery. The authors conclude that ‘the PASS score can be used to identify salvageable cases of sepsis-AKI, guiding fluid resuscitation and aiding early referral from rural to tertiary care centers for better management.’ General comments: The manuscript is well written, and is focused on an important topic for the field. However, the enthusiasm is decreased due to significant methodological pitfalls. Specific examples and comments are detailed below. Major comments: The most important limitation of this study is the small sample size and the lack of validation of the PASS score. It is problematic to have less than 10 events per variable (EPV) when running this type of logistic regressions, as this can result in overfitting (type I error, PMID: 8970487). In the absence of a larger sample size and additional validation in an independent data set, it is difficult to consider the internal and external validity of the score. Based on No. 1, it is difficult to accept the conclusion proposed by the authors. Based on the selection criteria, the PASS score may be applicable only to sepsis associated AKI, but not to other forms of AKI? Also, it is unclear what the timing of AKI diagnosis was in relation to sepsis, which is an important component of the definition of SA-AKI (PMID: 36823168) The description of hemodynamic stabilization used a MAP of 60 mmHg instead of a MAP of 65 mmHg as recommended. Can the authors expand on the justification for the selection of this parameter? The definition of volume responsiveness in the literature is not dependent on achieving a goal MAP or SBP, but rather on whether a bolus of fluid will increase cardiac output (or accepted surrogates) by at least 10%. The authors hereby use a different definition of volume responsiveness. The authors may consider modifying the terminology to align better with current definitions of volume responsiveness. How did the authors define persistent AKI? The authors state they used SCr or oliguria to define persistent AKI. However, there is no definition of oliguria. Did the authors use KDIGO criteria? Was any stage AKI considered as persistent AKI if lasting > 72h? How did the authors define transient AKI? How did authors determine the presence of AKI? Was KDIGO staging used to defined AKI, and were both components (SCr and UO) used? Please specify what were the covariates use to adjust the logistic regression model. The description of the cohort is very limited, with only comporbidities shown including HTN and DM. Minor comments Please include measures of dispersion of the data in the form of standard deviation, IQR, etc. Page 7. IVC diameter is not a reflection of intravascular volume. Rather, a specific threshold of static IVC diameter correlates with being above or below a certain CVP. Please revise this comment. There is no conclusion in the manuscript. Please consider adding a conclusion. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? No References 1. Peduzzi P, Concato J, Kemper E, Holford TR, et al.: A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol . 1996; 49 (12): 1373-9 PubMed Abstract | Publisher Full Text 2. Zarbock A, Nadim MK, Pickkers P, Gomez H, et al.: Sepsis-associated acute kidney injury: consensus report of the 28th Acute Disease Quality Initiative workgroup. Nat Rev Nephrol . 2023; 19 (6): 401-417 PubMed Abstract | Publisher Full Text Competing Interests No competing interests were disclosed. Reviewer Expertise Sepsis, AKI, metabolic reprogramming, organ dysfucntion I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (1) Author Response 12 Feb 2024 Dattatray Prabhu, Department of Anaesthesiology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, 575001, India Dear Sir, I would like to thank you for taking the time to review this article. This is a pragmatic trial as mentioned in the article , we accept its a small sample size. Certain parameters among others had strong co-relation with AKI recovery. These parameters like R wave variability, Renal Resistive Index and initial S.Cr levels had a strong statistical significance to AKI recovery,so the conclusion was made. This needs a follow up study using larger study population for external validation. Sepsis accounts for 50-70% of cases in our ICU. Sepsis-associated AKI are usually clinical or subclinical at admission. This study includes sepsis related aki patients. During later part of ICU stay if AKI was found to be associated with non-sepsis-related causes such cases were excluded. The term SA-AKI operationally unifies the presence of AKI (according to clinical, biochemical and functional criteria) in the context of sepsis as a specific disease phenotype that is characterized by a specific trajectory and outcome. The target MAP for resuscitation was 65mmhg as per guideline. Correction was made in the manuscript accordingly. This study is mainly looking at non-invasive parameters to assess AKI recovery, hence we did not consider invasive monitors to look at cardiac output. Recovery from AKI was attributed to decreasing creatine and normalizing urine output. KIDGO criteria were used to categorize AKI after admission and recovery 24 hours after admission and beyond. Recovery of renal parameters and/or urine output beyond 72 hours were also considered as AKI recovery. There are studies to show a strong correlation between IVC collapsibility and CVP. In this study, we have not considered CVP as it needs an invasive line and as previously mentioned this study is mainly focused on noninvasive parameters. View more View less Competing Interests We do not have any competing interest. reply Respond Report a concern Gómez H. Peer Review Report For: PASS: A scoring system to evaluate persistent kidney injury in critically ill ICU adult patients [version 3; peer review: 2 approved, 1 not approved] . F1000Research 2024, 12 :902 ( https://doi.org/10.5256/f1000research.147517.r211850) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-902/v1#referee-response-211850 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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