Mortality and evolution between community and hospital-acquired COVID-AKI.

BACKGROUND: Acute kidney injury (AKI) is associated with poor outcomes in COVID patients. Differences between hospital-acquired (HA-AKI) and community-acquired AKI (CA-AKI) are not well established.
METHODS: Prospective, observational cohort study. We included 877 patients hospitalized with COVID diagnosis at two third-level hospitals in Mexico. Primary outcome was all-cause mortality at 28 days compared between COVID patients with CA-AKI and HA-AKI. Secondary outcomes included the need for KRT, and risk factors associated with the development of CA-AKI and HA-AKI.
RESULTS: A total of 377 patients (33.7%) developed AKI. CA-AKI occurred in 202 patients (59.9%) and HA-AKI occurred in 135 (40.1%). Patients with CA-AKI had more significant comorbidities, including diabetes (52.4% vs 38.5%), hypertension (58.4% vs 39.2%), CKD (30.1% vs 14.8%), and COPD (5.9% vs 1.4%), than those with HA-AKI. Patients' survival without AKI was 87.1%, with CA-AKI it was 75.4%, and with HA-AKI it was 69.6%, log-rank test p < 0.001. Only age > 60 years (OR 1.12, 95% CI 1.06-1.18, p <0.001), COVID severity (OR 1.09, 95% CI 1.03-1.16, p = 0.002), the need in mechanical lung ventilation (OR 1.67, 95% CI 1.56-1.78, p <0.001), and HA-AKI stage 3 (OR 1.16, 95% CI 1.05-1.29, p = 0.003) had a significant increase in mortality. The presence of CKD (OR 1.48, 95% CI 1.391.56, p < 0.001), serum lymphocytes < 1000 μL (OR 1.03, 95% CI 1.00-1.07, p = 0.03), the need in mechanical lung ventilation (OR 1.06, 95% CI 1.02-1.11, p = 0.003), and CA-AKI stage 3 (OR 1.37, 95% CI 1.29-1.46, p < 0.001) were the only variables associated with a KRT start.
CONCLUSIONS: We found that COVID patients who are complicated by CA-AKI have more comorbidities and worse biochemical parameters at the time of hospitalization than HA-AKI patients, but despite these differences, their probability of dying is similar.

Introduction

COVID-19 has been a unique challenge to the field of nephrology. Acute kidney injury (AKI) presents in 4.5% of cases [1] and up to 78% of patients in the intensive care unit [2]. AKI is associated with poor outcomes [3], and it has been reported that AKI has the highest risk of mortality in hospitalized patients [4]. Mexico has been one of the most adversely affected countries in the world by the pandemic [5]. Up to 37% of COVID-19 patients present to the hospital with AKI, that is, they acquire it in the community (CA-AKI) [6], an event that can be explained by the fact that COVID patients develop such symptoms as fever, cough, anorexia, diarrhea, and fatigue several days before going to the hospital [7], and delaying care and management can negatively impact its clinical evolution. It has been reported that the development of in-hospital (HA) AKI confers a greater risk of mortality than in patients with community-acquired (CA) AKI [8-10], but little is known regarding the outcomes of AKI according to the site of acquisition in COVID patients.

The primary aim of this article is to describe the incidence, risk factors and mortality between CA-AKI and HA-AKI in two reference centers for patients with COVID-19 in Mexico and to develop a simple score that predicts which COVID-AKI patients have a higher risk of dying during hospitalization. Our hypothesis is that CA-AKI carries the same risk of dying as HA-AKI due to the conditions involved in the care of those affected by this pandemic in our country.

Materials and methods

Study design and cohort

This was a prospective observational study conducted at the Civil Hospital of Guadalajara Fray Antonio Alcalde, Guadalajara, and the Medical Center 20 de November in Mexico City between April 2020 and February 2021. All adult patients (age ≥ 18 years) who tested positive by polymerase chain reaction of a nasopharyngeal sample for COVID-19 and were hospitalized were eligible. All hospitalized patients had COVID classified as moderate and severe. For patients who had multiple qualifying hospital admissions, we included only the first hospitalization. Patients who were transferred between hospitals within the health system were treated as 1 hospital encounter. Patients were excluded if they were transferred to hospitals out of the health system for which we were unable to obtain data, if they had chronic kidney disease (CKD) grade 5 on dialysis, or if there was a lack of data. Patients who had preexisting CKD G1-G5 not on dialysis and who did not have creatinine measurements during the previous 3 months were also excluded from the analysis. This study was approved by the Institutional Review Board of both hospitals (Hospital Civil de Guadalajara HCG/CEI-0473/20 and Centro Medico Nacional 20 de Noviembre 09–240.2020) was conducted in adherence to the Declaration of Helsinki. Written informed consent was obtained from all of the subjects at hospitalization. The protocol followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [11].

Data collection, definitions, and measurements

Clinical characteristics, demographic information, and laboratory data were collected prospectively using automated retrieval from the institutional electronic medical record system. COVID severity was categorized as follows: moderate illness, individuals who showed evidence of lower respiratory disease during clinical assessment or imaging and who had saturation of oxygen (SpO2) ≥94% on room air at sea level; and severe illness, individuals who had SpO2 <94% on room air at sea level, a ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) <300 mm Hg, respiratory frequency >30 breaths/min, or lung infiltrates >50% [12]. AKI was diagnosed by the serum creatinine (Scr) KDIGO criteria [13], and patients were stratified according to the highest AKI stage attained during their hospital stay.

We identified community-acquired AKI when the patient met any of the following criteria: (a) an increased Scr level at admission and a trend of decreasing Scr levels during the hospital stay; (b) an increased Scr level at admission and an Scr level that continued to increase or remained at a high level during the hospital stay, with preadmission Scr values establishing the existence of AKI; or (c) normal kidney function upon admission with Scr levels that began to increase and AKI that could be defined within 2 days after hospitalization combined with causal factors that were determined (by the nephrologists among the investigators) to be present prior to admission based on review of their medical records. If otherwise, AKI was classified as hospital-acquired [14].

The baseline Scr level was defined as the lowest Scr value that was available in the last 3 months prior to admission and throughout the hospital stay. For patients who had no reliable Scr record before admission and no evidence of baseline CKD, a back-estimation of the baseline Scr level was performed based on the 4-variable MDRD (Modification of Diet in Renal Disease) Study equation with the assumption of an estimated glomerular filtration rate of 75 mL/min/1.73 m2 following the recommendations of the 2012 KDIGO AKI clinical practice guideline [14, 15]. The estimated glomerular filtration rate was calculated using the Chronic Kidney Disease Epidemiology Collaboration creatinine equation [16].

We collected data on patient demographics, baseline history of comorbid conditions, and home medications. Comorbid conditions were determined from provider-entered past medical history and admission medication reconciliation. In addition to baseline clinical data, we collected information from the time of hospital admission, such as hemoglobin, platelets, leukocytes, glucose, urea, creatinine, sodium, potassium, chloride, phosphate, calcium, arterial pH, PCO2, PO2, bicarbonate and lactate levels. We also recorded the need for invasive mechanical ventilation, length of stay, and the need for KRT. Indications for KRT were fluid overload resistant to diuretics, severe hyperkalemia, severe metabolic acidosis, and uremic manifestations, including encephalopathy, pericarditis, and convulsions [17, 18].

Outcomes

The primary outcome was 28 days survival compared between hospitalized COVID patients with CA-AKI and HA-AKI. Secondary outcomes included the need for KRT, risk factors associated with the development of CA-AKI and HA-AKI, and the creation of a predictive mortality score for hospitalized COVID-AKI patients.

Statistical analysis

Continuous variables are summarized as the mean ± SD unless otherwise specified. Categorical variables are summarized as numbers with percentages. We compared baseline patient characteristics between patients with or without AKI and with CA-AKI or HA-AKI using Fisher exact tests for categorical variables and nonparametric Wilcoxon signed-rank tests for continuous variables. Survival after hospital admission was estimated using Kaplan–Meier plots and compared using the log-rank test. To identify risk factors associated with mortality, KRT, CA-AKI, and HA-AKI, we constructed a logistic regression model adjusted for age, sex, COVID severity, diabetes, hypertension, CKD, stroke, COPD, BMI, ferritin, leukocytes, lymphocytes, mechanical ventilation, KRT, AKI stage, and AKI acquisition. Only the independent variables found to have P < 0.05 based on univariate analysis were included in the multivariate analysis. P < 0.05 was considered significant. A predictive mortality score was developed, which we called SARS-AKI. Variables that were statistically significant in the multivariate logistic regression method were included in the SARS-AKI score. To quantify the goodness of fit of our prediction model, we used the area under the receiver operating characteristic (ROC) curve and calibration. The statistical analyses were performed using R (version 3.6.3; R Foundation for Statistical Computing, Vienna, Austria).

Results

From April 1, 2020, to February 1, 2021, 1251 patients were admitted to the Civil Hospital of Guadalajara Fray Antonio Alcalde, Guadalajara, and the Medical Center 20 de Noviembre in Mexico City with a diagnosis of COVID-19 present on admission or made during hospitalization. Of these, 877 were used as the analysis cohort (Fig 1). The baseline characteristics of the study cohort by AKI and no AKI are provided in Table 1. A total of 377 patients (33.7%) developed AKI. Patients with AKI were significantly older, predominantly male, had more comorbidities, increased markers of inflammatory response, more severe COVID-19, an increased need for mechanical ventilation, and increased mortality.

Fig 1

Flowchart of study population.

Table 1

Baseline characteristics of the study cohort by AKI and no AKI.

Variable	Total (N = 877)	No AKI (N = 540)	AKI (N = 337)	p value
Age [years], mean (SD)	55.9 (15.7)	54.5 (15.6)	58.2 (15.6)	<0.001*
Male [N (%)]	548 (62.5)	321 (59.4)	227 (67.3)	0.02*
Body Mass Index [kg/m2], mean (SD)	28.1 (6.3)	28.3 (6.2)	27.7 (6.5)	0.06
Comorbidities [N (%)]
Diabetes	311 (35.4)	153 (28.3)	158 (46.8)	<0.001*
Hypertension	332 (37.8)	161 (29.8)	171 (50.7)	<0.001*
CKD	97 (11)	16 (2.9)	81 (24)	<0.001*
Stroke	37 (4.2)	15 (2.7)	22 (6.5)	0.01*
COPD	27 (3.0)	13 (2.4)	14 (4.1)	0.14
Admission biochemical data, mean (SD)
Serum Ferritin [ng/m]	1144 (2068)	940 (2350)	1484 (2962)	<0.001*
Serum Leukocytes [109/L]	4.2 (5.2)	4.1 (4.7)	4.4 (6.0)	0.98
Serum Lymphocytes [μL]	1130 (1297)	1190 (784)	1037 (1824)	<0.001*
Serum Hemoglobin [g/dL]	13.7 (2.3)	14.1 (2.1)	13.2 (2.6)	<0.001*
Serum Platelets [109/L]	245 (156)	249 (100)	240 (216)	0.56
Serum Sodium [mEq/L]	136 (7.4)	136.3 (8.1)	135.5 (6.2)	0.26
Serum Potassium [mEq/L]	4.1 (0.8)	4 (0.7)	4.4 (0.9)	<0.001*
Arterial pH	7.41 (0.1)	7.43 (0.1)	7.40 (0.1)	0.76
Serum bicarbonate [mEq/L]	21.6 (4.6)	22.2 (4.5)	20.8 (4.6)	0.001*
Serum Creatinine [mg/dL]	1.7 (3.3)	0.8 (0.4)	2.9 (5.0)	<0.001*
COVID severity [N (%)]				<0.001*
Mild	511 (58.2)	370 (68.5)	141 (41.8)
Severe	366 (41.8)	170 (31.5)	196 (58.2)
Need in mechanical lung ventilation [N (%)]	219 (24.9)	73 (13.5)	146 (43.3)	<0.001*
Length of stay, days, mean (SD)	9.9 (6.7)	9.0 (6.2)	11.4 (7.2)	<0.001*
Disposition [N (%)]				<0.001*
Discharged	597 (68.1)	429 (79.4)	168 (49.8)
Expired	280 (31.9)	111 (20.6)	169 (50.2)

AKI, acute kidney injury; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; KRT, kidney replacement therapy.

Among the patients with AKI, we observed that CA-AKI occurred in 202 patients (59.9%) and HA-AKI occurred in 135 (40.1%). Patients with CA-AKI had more significant comorbidities, including diabetes (52.4% vs 38.5%), hypertension (58.4% vs 39.2%), CKD (30.1% vs 14.8%), and COPD (5.9% vs 1.4%), than those with HA-AKI. CA-AKI also presented with less significant lymphocytes, hemoglobin, and bicarbonate levels, a greater increase in serum potassium, and a greater need for KRT. No significant difference was observed in AKI stages, the need for mechanical ventilation, or mortality (Table 2).

Table 2

Baseline characteristics by AKI acquisition.

Variable	AKI acquisition		p-value
	CA-AKI (N = 202)	HA-AKI (N = 135)
Age [years], mean (SD)	58.1 (15.7)	58.4 (15.4)	0.74
Male [N (%)]	132 (65.3)	95 (70.3)	0.33
Body Mass Index [kg/m2], mean (SD)	27.7 (7.6)	27.5 (4.5)	0.23
Comorbidities [N (%)]
Diabetes	106 (52.4)	52 (38.5)	0.01*
Hypertension	118 (58.4)	53 (39.2)	<0.001*
CKD	61 (30.1)	20 (14.8)	0.001*
Stroke	13 (6.4)	9 (6.6)	0.64
COPD	12 (5.9)	2 (1.4)	0.04*
Admission biochemical data, mean (SD)
Serum Ferritin [ng/m]	1325 (1259)	1725 (4424)	0.47
Serum Leukocytes [109/L]	4.0 (6.3)	5.0 (5.5)	0.09
Serum Lymphocytes [μL]	1032 (2139)	1044 (1122)	0.04*
Serum Hemoglobin [g/dL]	12.8 (2.9)	13.8 (1.8)	0.003*
Serum Platelets [109/L]	231 (101)	255 (328)	0.70
Serum Sodium [mEq/L]	135 (6.6)	136.3 (5.3)	0.46
Serum Potassium [mEq/L]	4.6 (1.0)	4.1 (0.6)	<0.001*
Arterial pH	7.37 (0.1)	7.41 (0.1)	0.07
Serum bicarbonate [mEq/L]	19.9 (4.5)	21.9 (4.5)	0.01*
Serum Creatinine [mg/dL]	3.8 (5.9)	1.3 (1.7)	<0.001*
COVID severity [N (%)]			0.43
Mild	88 (43.5)	53 (39.2)
Severe	114 (56.5)	82 (60.8)
AKI
KDIGO-1	64 (31.6)	41 (30.3)	0.87
KDIGO-2	49 (24.2)	33 (24.4)	0.88
KDIGO-3	89 (44.1)	61 (45.1)	0.76
KRT	60 (29.7)	27 (20.0)	0.04*
Need in mechanical lung ventilation [N (%)]	80 (39.6)	66 (48.8)	0.09
Length of stay, days, mean (SD)	11.0 (7.4)	12.0 (7.4)	0.20
Disposition [N (%)]			0.06
Discharged	109 (53.9)	59 (43.7)
Expired	93 (46.1)	76 (56.3)

AKI, acute kidney injury; CA-AKI, community-acquired AKI; HA-AKI, hospital-acquired AKI; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; KRT, kidney replacement therapy.

The overall 28-day survival among hospitalized COVID patients was 68.0% (IC 95% 0.65–0.71) (S1 Fig). The 28-day survival comparing CA-AKI, HA-AKI, and mechanical ventilation is presented in Fig 2. Patients’ survival without AKI was 87.1% (IC 95% 0.84–0.90), with CA-AKI it was 75.4% (IC 95% 0.68–0.83), with HA-AKI it was 69.6% (IC 95% 0.59–0.81), and with mechanical ventilation it was 30.1% (IC 95% 0.21–0.42). Patient survival with CA-AKI and mechanical ventilation was 21.2% (IC 95% 0.13–0.32), while with HA-AKI and mechanical ventilation it was 16.7% (IC 95% 0.09–0.28), log-rank test p < 0.001. When comparing the 28-day survival between AKI stages and mechanical ventilation, patients’ survival with AKI stages 2–3 was 68.5% (IC 95% 0.60–0.77), and with mechanical ventilation plus AKI stages 2–3 it was 17.2% (IC 95% 0.11–0.25) (S2 Fig).

Fig 2

Kaplan–Meier survival statistics comparing community-acquired AKI, hospital-acquired AKI, and mechanical ventilation.

Numbers of patients at risk at each time point shown below the graph.

The mortality percentage according to AKI stage, CA-AKI, and HA-AKI is presented in Fig 3. Patients with stage 3 AKI and CA-AKI had a mortality of 48.9%, while patients with stage 3 AKI and HA-AKI had a mortality of 52.6%, p = 0.12.

Fig 3

Mortality percent according to AKI stage, CA-AKI, and HA-AKI.

In an attempt to identify variables associated with mortality at the 28-day follow-up, univariate and multivariate analyses were performed. Only age > 60 years (OR 1.12, 95% CI 1.06–1.18, p <0.001), COVID severity (OR 1.09, 95% CI 1.03–1.16, p = 0.002), the need for mechanical ventilation (OR 1.67, 95% CI 1.56–1.78, p <0.001), and HA-AKI stage 3 (OR 1.16, 95% CI 1.05–1.29, p = 0.003) had a significant increase in mortality (Table 3). The presence of CKD (OR 1.48, 95% CI 1.391.56, p < 0.001), serum lymphocytes < 1000 μL (OR 1.03, 95% CI 1.00–1.07, p = 0.03), the need for mechanical ventilation (OR 1.06, 95% CI 1.02–1.11, p = 0.003), and CA-AKI stage 3 (OR 1.37, 95% CI 1.29–1.46, p < 0.001) were the only variables associated with a KRT start in the multivariable analysis (Table 3).

Table 3

Factors associated with mortality at 28-days of follow up and the requirement of kidney replacement therapy in hospitalized COVID patients, in the univariable and multivariable logistic regression model.

	Univariable analysis, OR (95% CI)	p	Multivariable analysis, OR (95% CI)	p
Mortality
Age > 60 [years]	1.20 (1.13–1.27)	<0.001	1.12 (1.06–1.18)	<0.001
COVID severity
Mild	Reference	-	Reference	-
Severe	1.41 (1.33–1.49)	<0.001	1.09 (1.03–1.16)	0.002
Need in mechanical lung ventilation	1.82 (1.72–1.93)	<0.001	1.67 (1.56–1.78)	<0.001
AKI acquisition and KDIGO stage
CA-AKI and stage 2–3	Reference	-	Reference	-
HA-AKI and stage 2	1.38 (1.18–1.63)	<0.001	1.11 (0.97–1.27)	0.10
HA-AKI and stage 3	1.43 (1.27–1.61)	<0.001	1.16 (1.05–1.29)	0.003
Kidney replacement therapy
CKD	1.69 (1.59–1.78)	<0.001	1.48 (1.391.56)	<0.001
Serum Lymphocytes < 1000 [μL]	1.10 (1.06–1.15)	<0.001	1.03 (1.00–1.07)	0.03
Need in mechanical lung ventilation	1.12 (1.07–1.18)	<0.001	1.06 (1.02–1.11)	0.003
AKI acquisition and KDIGO stage
HA-AKI and stage 2–3	Reference	-	Reference	-
CA-AKI and stage 2	0.99 (0.90–1.08)	0.90
CA-AKI and stage 3	1.66 (1.56–1.76)	<0.001	1.37 (1.29–1.46)	<0.001

AKI, acute kidney injury; CA-AKI, community-acquired AKI; HA-AKI, hospital-acquired AKI; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; KRT, kidney replacement therapy.

On the other hand, it was observed that having severe COVID (OR 1.08, 95% CI 1.02–1.14, p = 0.005), diabetes (OR 1.08, 95% CI 1.02–1.15, p = 0.005), hypertension (OR 1.07, 95% CI 1.00–1.14, p = 0.02), CKD (OR 1.47, 95% CI 1.35–1.60, p < 0.001), COPD (1.25, 95% CI 1.07–1.45, p = 0.003), and serum leucocytes > 12 109/L (OR 1.10, 95% CI 1.04–1.17, p < 0.001) were associated with the development of CA-AKI, while only the presence of severe COVID (OR 1.13, 95% CI 1.06–1.20, p < 0.001), and serum ferritin > 500 [ng/m] (OR 1.07, 95% CI 1.01–1.14, p = 0.01) were significant factors for the development of HA-AKI (Table 4).

Table 4

Factors associated with CA-AKI and HA-AKI in hospitalized COVID patients, in the univariable and multivariable logistic regression model.

	Univariable analysis, OR (95% CI)	p	Multivariable analysis, OR (95% CI)	p
Community-acquired AKI
Grade COVID
Mild	Reference	-	Reference	-
Severe	1.15 (1.08–1.21)	<0.001	1.08 (1.02–1.14)	0.005
Diabetes	1.18 (1.12–1.25)	<0.001	1.08 (1.02–1.15)	0.005
Hypertension	1.22 (1.15–1.29)	<0.001	1.07 (1.00–1.14	0.02
CKD	1.56 (1.43–1.70)	<0.001	1.47 (1.35–1.60)	<0.001
COPD	1.24 (1.06–1.46)	0.007	1.25 (1.07–1.45)	0.003
Serum Leukocytes > 12 [109/L]	1.14 (1.07–1.21)	<0.001	1.10 (1.04–1.17)	<0.001
Hospital-acquired AKI
COVID severity
Mild	Reference	-	Reference	-
Severe	1.12 (1.07–1.18)	<0.001	1.13 (1.06–1.20)	<0.001
Serum Ferritin > 500[ng/m]	1.10 (1.04–1.16)	<0.001	1.07 (1.01–1.14)	0.01

AKI, acute kidney injury; CA-AKI, community-acquired AKI; HA-AKI, hospital-acquired AKI; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease.

We developed the predictive SARS-AKI score as a tool for predicting mortality at 28 days in COVID patients. We included age > 60 years, severe COVID, the need for mechanical ventilation, AKI stage, and AKI acquisition (Fig 4). A cutoff value ≥ 3 points had an AUC of 0.82 (95% CI 1.15–1.18), p < 0.001, with a specificity of 0.87, sensitivity of 0.66, PPV of 0.71, and an NPV of 0.84.

Fig 4

COVID-AKI score as a tool for predicting death in COVID AKI patients and the ROC curve of the logistic regression model for predicting all-cause mortality.

Discussion

In this multicenter prospective cohort, we found that COVID patients who are complicated by CA-AKI have more comorbidities and worse biochemical parameters at the time of hospitalization than HA-AKI patients, but despite these differences, their probability of dying is similar. In addition, when these patients needed MV, the prognosis in both groups worsened markedly, and we were able to develop a predictive score for death among patients with AKI COVID.

Notably, the mortality of patients with COVID and AKI was not different between the HA-AKI and CA-AKI subgroups. Even when comparing the CA-AKI and HA-AKI KDIGO stages, there were no differences in mortality between them, results that could be contrasted with previous studies. In our cohort, the mortality of patients with AKI at 28 days was 68%, higher than that reported by the STOP-COVID Investigators group, where they described that 54.9% of AKI COVID patients in the ICU died within 28 days of ICU admission [19], and more likely to the 60.1% mortality rate reported in a Sau Paulo cohort [20]. These results can be explained by the conditions, hospital infrastructure and health system of our country compared to the US and Brazil.

Studying the distinction in mortality between CA-AKI and HA-AKI is relevant in the context of COVID because AKI due to other causes has historically shown epidemiological, clinical and prognostic differences between these two groups [8-10]. It is possible that the natural trajectory of COVID-19 with fever, nausea, vomiting, fatigue, anorexia, self-medication, fear of imminent hospitalization and lack of hospital beds for their care has resulted in patients in our cohort arriving late to the hospital, and this time lost by delaying its management also helps explain these unfavorable results [21].

In our cohort, CA-AKI patients more frequently had hypertension, CKD and COPD than HA-AKI patients, antecedents that have been linked to a worse clinical evolution in patients with COVID [22, 23], including the development of AKI [4].

The body mass index (BMI) in our cohort was 28.1 (overweight), we found no association between BMI and the development of COVID AKI or its complications, in contrast to previous meta-analysis where 9 cohorts were included and two of them considered BMI> 24, and reported that obesity increases the severity of COVID [24], this lack of association could be explained by the fact that most of the evidence has reported obesity, not overweight, as a risk factor for complications from COVID. The comorbidities that we found in patients with CA-AKI are very similar to those described in the Mexican cohort by Martínez-Rueda et al. [25], where it was found that patients with COVID CA-AKI have older age and a greater number of comorbidities compared to patients with HA-AKI; results that validate ours findings since they are patients from the same region.

Which could explain why these patients, with a susceptible kidney, quickly develop AKI in the face of COVID. Pelayo et al. highlighted that patients with CA-AKI have fewer complications during hospitalization than those with HA-AKI, such as the need for vasopressors, MV and death (23% vs 52%) [26]. These data differ from our cohort, since in our study, there was no difference in the need for MV between CA-AKI and HA-AKI. It is striking that in the subgroup with CA-AKI, more patients were intubated (39.6%), and it is likely that this complication explains that in our cohort, twice as many patients (46%) died compared to only 23% in the Pelayo et al. study [26]. We also described the impact that the combination of AKI and VM has on mortality. We found a poor prognosis in this scenario with a mortality rate of only 17.2%.

The adverse renal effects of mechanical ventilation have been studied [27, 28]. The risk of developing AKI in mechanically ventilated patients has been demonstrated in various entities: in cardiovascular disease [29]; gastrointestinal disease [30]; even in past pandemics like H1N1 [31]. Where the exposed to varying levels of continuous positive airway pressure causes a reduction in cardiac output by impeding venous return, circulatory stress, and neurohumoral mediators released that alter renal blood flow from cortex to medulla which leads to sodium reabsorption and a reduction in the glomerular filtration rate [32]. More recently, mechanical ventilation induced lung injury (VILI) has been proposed as another mechanism of AKI via inflammatory crosstalk from the lung to kidney. Although mechanical ventilation has a major role in life support, evidence suggests that certain ventilator settings may induce lung injury in some cases or may worsen lung injury once established [33]. Our study provides data on epidemiological aspects as well as the etiology and outcomes of COVID-AKI and adds to the literature the important differences between CA-AKI and HA-AKI.

We identified risk factors for the development of CA-AKI, is likely to be multifactorial, with cardiovascular comorbidity and predisposing factors as important contributors [27] including comorbidities such as diabetes, hypertension, CKD and COPD, and debilitating chronic diseases that have been universally associated with a worse evolution of COVID 19. In addition, we also identified that the severity of COVID and markers linked to inflammation, which is consistent with the pathophysiological mechanisms described in its pathology, where high inflammatory activity plays a preponderant role in kidney injury [34], evident in high levels of leukocytes (> 12 109/L) and ferritin (> 500 ng/mL), similar to ferritin levels (798 ng/mL) previously described by the Northwell COVID-19 Research Consortium [22] and similar leukocytes than the Brazilian cohort [20] cohort.

Patients with CA-AKI needed KRT more frequently than patients with HA-AKI (29.7% vs 20.0%), with exactly the same frequency as that reported in the EPILAT-IRA study, where KRT was performed in 29% of cases. Relevant data in this context were obtained because, as in our population, this is a Latin-American study with a high prevalence of CA AKI 63% [35]. We identified that having CKD increased the need for KRT by almost 50%, a result that is not surprising since CKD is considered the greatest risk factor for AKI and its complications [36]. Additionally, receiving MV increased the risk of KRT; again, a widely described event, the kidney and lung are closely related, and having MV increases the risk of AKI 3-fold. High levels of inflammation triggered by lung damage could affect kidney function [37].

The high frequency of KRT in the CA-AKI group can be justified by the presence of more comorbidities (hypertension, CKD and COPD) and markers of inflammation such as lymphopenia, anemia and electrolyte disturbance related to AKI-specific complications such as hyperkalemia, hypobicarbonatemia, and azotemia, all of which may have been triggers for the initiation of KRT.

The ADQI group recommends identifying COVID patients who are at high risk of developing AKI and its complications [2]. To our knowledge, a predictive death score has never been described in patients with AKI COVID. In this study, we developed a risk score derived from patient demographics, COVID severity and acute risk factors and demonstrated that it can reliably predict mortality in AKI COVID patients, with an AUC of 0.82 with the optimal cutoff for mortality was estimated to be ≥ 3 points (Fig 4). Implementation of this risk model in clinical practice may help target high-risk patients for surveillance and enable clinicians to evaluate novel diagnostic, preventive and therapeutic modalities to mitigate mortality in AKI COVID.

Our study has limitations that must be interpreted together with its results, although its retrospective design may have failed to capture relevant variables, such as the treatment offered. The incidence of AKI might be underestimated due to the real-world nature of data collection. As expected, there was uncertainty regarding the time of onset of AKI before admission among those with CA-AKI. Mortality was only considered during the 28 days of hospitalization and a longer follow-up would have been appropriate since many patients have prolonged hospital stays.

Finally, the possibility of residual confounding exists for our observational study.

Our study has the strength of a relatively large sample size and detailed information on various variables obtained from two of the largest tertiary hospitals in Mexico. We divided the analysis between patients with HA-AKI and CA-AKI, a topic little explored until now.

In conclusion, in this multicenter prospective cohort, we found that patients with COVID who are complicated with CA-AKI have more comorbidities, and despite this, they have the same evolution when compared with HA AKI. We also developed a death predictive score for patients with AKI COVID.

Overall, 28-days survival in hospitalized COVID patients.

(DOCX)

Click here for additional data file.

Kaplan–Meier survival statistics comparing AKI stages and mechanical ventilation.

(DOCX)

Click here for additional data file.

(XLSX)

Click here for additional data file.

11 Jun 2021

PONE-D-21-11844

Mortality and evolution between Community and Hospital-acquired COVID-AKI

PLOS ONE

Dear Dr. Chávez-Iñiguez,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

As the Academic Editor, I have sent your manuscript for revision to several persons. Currently one expert in the field has already provided the peer-review with a very detailed and useful comments, suggesting Major Revision. Other experts invited so far have declined the invitation to review the manuscript (it is rather widespread situation, related to different factors).

I would like to save your time, and provide the possibility to perform the revision of the manuscript based on the feedback from one expert in the field, and make it stronger. Once you submit the revised manuscript, I will send it to the expert who provided the feedback, and also involve another reviewer. If you have any objections for this approach, please let me know. If you agree, please proceed this way and submit the revised manuscript along with the point-by-point responses to the reviewer.

Please submit your revised manuscript by Jul 26 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Boris Bikbov

Academic Editor

PLOS ONE

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

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Reviewer #1: Yes

**********

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Reviewer #1: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is an interesting retrospective study highlighting the differences between HA AKI and CA AKI in COVID patients. The findings are in contrast to that of literature where HA AKI due to usual causes have been found to have worse outcome due to the number of comorbidities. Interestingly, the difference of > 10% in mortality between CA AKI and HA AKI did not show significance. The authors have 28-day mortality as the primary outcome. Does the table 1 show 28-day outcome as some patients may still be in-patient as we know COVID patients have longer length of stay. Do the authors have in-hospital mortality as FU after discharge may result in loss of follow up. Loss of 18.3% of study population due to loss of creatinine is surprising. Do decide about baseline creatinine, the authors have gone back a year but to get a baseline for patients who had pre-existing CKD G1-G5 not on dialysis, only previous 3 months creatinine was necessary, otherwise they were also excluded from the analysis

The other observation is that patients with first admission were included. This creates a survival bias as patient may have died in subsequent admission

The authors have used variable end-points. On some occasions, the authors report survival and on other occasion, mortality. The literature reports mortality for AKI. For example: The multivariable regression is using mortality as dependent variable which survival is quoted for HA & CA AKI

Was AKI not defined by KDIGO classification? This is not stated in methods

**********

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Reviewer #1: Yes: Nitin V Kolhe

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25 Jun 2021

Response to Reviewers'

We appreciate the time and the review process, without a doubt the comments of the editors are all relevant and pertinent, they contribute to making our manuscript stronger. We have done our best to satisfy each of them.

Reviewer #1:

1.-The findings contrast with that of literature where HA AKI due to usual causes have been found to have worse outcome due to the number of comorbidities.

R= We are glad that the editor has noted this point, from our perspective it is also a valuable argument in our manuscript, and we give a detailed explanation of why this result happened in page 21, 22.

2.-Interestingly, the difference of > 10% in mortality between CA AKI and HA AKI did not show significance.

R= We believe that the limited number of the event could have explained the lack of statistical significance (p = 0.06), although the trend is notable.

3.- The authors have 28-day mortality as the primary outcome. Does the table 1 show 28-day outcome as some patients may still be in-patient as we know COVID patients have longer length of stay. Do the authors have in-hospital mortality as FU after discharge may result in loss of follow up.

R= We understand the point, without a doubt the long-term follow-up would be relevant, but we only took into account the first 28 days of the stay in the hospital, unfortunately we could not follow the patients once they were discharged from the hospital, we faced the reality where COVID patients hardly come for follow-up.

If the reviewer agree, we could add the following sentence to the limitations (page 24):

Mortality was only considered during the 28 days of hospitalization and a longer follow-up would have been appropriate since many patients have prolonged hospital stays.

4.- Loss of 18.3% of study population due to loss of creatinine is surprising.

R= We excluded 230 (18.3%) patients from the analysis, mainly because despite being hospitalized, they did not have serum creatinine measurement, we know the importance of this variable, but in our hospitals the systematic request of serum creatinine is not performed unless the treating physicians request it.

It is probable that the overload of work and the saturation of the clinical laboratories during pandemic has contributed as well.

5.-Do decide about baseline creatinine, the authors have gone back a year but to get a baseline for patients who had pre-existing CKD G1-G5 not on dialysis, only previous 3 months creatinine was necessary, otherwise they were also excluded from the analysis

R= We agree with the reviewer's comment, we only need 3 months was necessary, we will change the text of the manuscript as follows:

The baseline Scr level was defined as the lowest Scr value that was available in the last 3 months prior to admission and throughout the hospital stay (page 7)

6.- The other observation is that patients with first admission were included. This creates a survival bias as patient may have died in subsequent admission

R= We understand the concern of the reviewer.

We decided to consider only the first hospital admission since the nature of our study was mainly to compare HA-AKI vs CA-AKI. The event of CA-AKI would not be interpreted properly if the patient who had been discharged was hospitalized again, we think that this previous hospitalization strongly contributes to her readmission, making the conditions of CA-AKI completely different. Finally we believe that readmissions were <10%.

7.- The authors have used variable end-points. On some occasions, the authors report survival and on other occasion, mortality. The literature reports mortality for AKI. For example: The multivariable regression is using mortality as dependent variable which survival is quoted for HA & CA AKI

R=We appreciate the observation, we fully agree. We will change all the words surival for mortality when apropiate, you will find it on pages: 7, 8, 9, 11, 13, 14

8.- Was AKI not defined by KDIGO classification? This is not stated in methods

R= In methods section (page 6) you will find the phrase where we describe the definition of AKI by KDIGO.

AKI was diagnosed by the serum creatinine (Scr) KDIGO criteria (13)

Submitted filename: response to reviewer 25_6_21.docx

Click here for additional data file.

14 Jul 2021

PONE-D-21-11844R1

Mortality and evolution between Community and Hospital-acquired COVID-AKI

PLOS ONE

Dear Dr. Chávez-Iñiguez,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 28 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Boris Bikbov

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have revised the document, but there remains inherent inconsistencies with the data.

Authors have 230 patients who did not have baseline within 3 months and were excluded. Did these patients have baseline creatinine in last 12 months? For other patients, baseline creatinine within a year was considered and there is no clear explanation offered by the authors.

The manuscript still has conflicting use of mortality and survival Eg: page 14

The study is retrospective observational study and consent was taken at the time of hospitalization. The conclusion states that this is prospective study

There are too many unnecessary tables. On page 14, please ensure confidence interval is correctly reported.

Kaplan Meier curve has time on x-axis, which does not make sense and should have days. Even with days, Kaplan Meier curve is inappropriate for short duration of follow-up of 28 days and does not add any information on long–term outcome

Reviewer #2: Dear authors,

The manuscript makes a different contribution to the understanding and management of patients with AKI-Covid. I highlight the data on the mortality score for AKI-Covid. However, the manuscript needs adjustments:

Abstract

-Use the KDIGO standardized nomenclature for renal replacement therapy-RRT (throughout the text) instead of KRT.

-Conclusions: add data on mechanical ventilation and LRA.

Introduction

-Subsidize with more references. Sugestions:

https://pubmed.ncbi.nlm.nih.gov/32416769

https://pubmed.ncbi.nlm.nih.gov/34033655

Methods

- I would like to see the ethics committee protocol number.

Results

-Format the tables. They are presented in frame format.

-I suggest unifying the results of tables 3 and 4; 5 and 6.

-Present the score data only with figure 4. Leave table 7 in the supplementary material.

- Figure 1 is incomplete. Please enter the subdivisions of patients who were elected in the study.

Discussion

-Increase the number of references.

-Better discuss the findings

For example: The Body Mass Index was high and although without statistical relevance in your study, it has been observed that overweight and obesity are risk factors for covid-19.

Att,

Reviewer

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: CASSIANE DEZOTI DA FONSECA

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

1 Aug 2021

Authors response to the reviewers

We appreciate the excellent work of the reviewers, without a doubt their comments and opinions have been of great value to us, they add greater quality to the manuscript. We humbly hope that our responses will satisfy your requests.

Reviewer #1: The authors have revised the document, but there remains inherent inconsistencies with the data.

Authors have 230 patients who did not have baseline within 3 months and were excluded. Did these patients have baseline creatinine in last 12 months? For other patients, baseline creatinine within a year was considered and there is no clear explanation offered by the authors.

R= These 230 patients who were excluded was because lack of data prior to hospitalization, or who for some reason were not taken in hospitalization. We add in figure 1, point 5, the phrase lack of data.

The manuscript still has conflicting use of mortality and survival Eg: page 14

R=We changed the word mortality to survival in page 14.

Survival was used when we reported overall survival, the 28-day survival comparing CA-AKI, HA-AKI, and mechanical ventilation (Fig 2), and the 28-day survival between AKI stages and mechanical ventilation (S2 Fig).

Mortality was used when we reported the percentage of death among those with different types of AKI (Fig 3), and in the multivariable analysis of variables associated with death (Table 3).

The study is retrospective observational study and consent was taken at the time of hospitalization. The conclusion states that this is prospective study.

R=The data were recruited prospectively, from the hospitalization of the patients at the time of admission, informed consent was obtained for the storage of information. In the abstract and methods section, we change the word retrospective to prospective.

There are too many unnecessary tables. On page 14, please ensure confidence interval is correctly reported.

R= Done. We check the confidence intervals, and they are correct.

Kaplan Meier curve has time on x-axis, which does not make sense and should have days. Even with days, Kaplan Meier curve is inappropriate for short duration of follow-up of 28 days and does not add any information on long–term outcome.

R= The Kaplan-Meier procedure is a method of estimating time-to-event models in the presence of censored cases. The Kaplan-Meier model is based on estimating conditional probabilities at each time point when an event occurs and taking the product limit of those probabilities to estimate the survival rate at each point in time.

We understand that the follow-up time is not very long compare to other long-term diseases but due to the severity of the disease that is being analyzed here, the use of a kaplan-meier analysis with a 28-day follow-up is adequate, not to mention that it also offers visual support for greater understanding of the reader.

We also add a new supplemental material file with the figures change in DAYS instead of TIME.

Reviewer #2: Dear authors,

The manuscript makes a different contribution to the understanding and management of patients with AKI-Covid.

I highlight the data on the mortality score for AKI-Covid. However, the manuscript needs adjustments:

Abstract

Use the KDIGO standardized nomenclature for renal replacement therapy-RRT (throughout the text) instead of KRT.

R= In the last KDIGO conference report 2020 it was attended to use “kidney” instead of “renal” or “nephro-“. They suggested to use “Kidney replacement therapy” and to avoid “Renal replacement therapy”.

Kidney International (2020) 97, 1117–1129; https://doi.org/10.1016/ j.kint.2020.02.010

Conclusions: add data on mechanical ventilation and AKI.

Introduction

R= We add 6 more references about the strong association between mechanical ventilation and AKI, you can find them in page 20

Subsidize with more references. Sugestions:

https://pubmed.ncbi.nlm.nih.gov/32416769

https://pubmed.ncbi.nlm.nih.gov/34033655

R= We appreciate the suggestions of these 2 references, we include interesting information about them in the Discussion, in addition, we add 2 additional ones. You can find them with the number in pages 18, 19 and 20

Methods

I would like to see the ethics committee protocol number.

R= we add the committee protocol number in methods page 5.

The Institutional Review Board of both hospitals (Hospital Civil de Guadalajara HCG/CEI-0473/20 and Centro Medico Nacional 20 de Noviembre 09-240.2020)

Results

Format the tables. They are presented in frame format.

R= done, tables are presented in frame format.

I suggest unifying the results of tables 3 and 4; 5 and 6.

R= Done. Thanks for the suggestion, tables 3 and 4 ; 5 and 6 were unifying, in there would be only table 3 and 4. You can find them in pages 15, 16 and 17.

Present the score data only with figure 4. Leave table 7 in the supplementary material.

R= Done.

Figure 1 is incomplete. Please enter the subdivisions of patients who were elected in the study.

R= done, we included elected patients (in the first square)

Discussion

Increase the number of references.

R= We appreciate the suggestions. We found articles that we consider interesting to include in our manuscript, they were essentially added to the Discussion. You can find in page 17-21.

Better discuss the findings

For example: The Body Mass Index was high and although without statistical relevance in your study, it has been observed that overweight and obesity are risk factors for covid-19.

R=We understand the point of discussing the BMI as an interesting point, we appreciate that you have pointed it out. We add reference 25 (a meta-analysis on the relationship between obesity and COVID) and contrast our findings with this variable in the discussion, we believe that it certainly adds value to our manuscript.

Submitted filename: response to Reviewer 30_7_21.docx

Click here for additional data file.

16 Aug 2021

PONE-D-21-11844R2

Mortality and evolution between Community and Hospital-acquired COVID-AKI

PLOS ONE

Dear Dr. Chávez-Iñiguez,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

There are a few items to correct, mainly considering the terminology. Particularly, this concerns the following:

- Please correct the titles of the tables "Univariable-Multivariable logistic regression..." to better readers' perception, and use the coherent terminology in the title and the column names (Univariate/Multivariate);

- Please exclude subtitles "-Mortality of CA-AKI vs HA-AKI: ", etc from the "Discussion", changing them with a short introductory phrase.

Please submit your revised manuscript by Sep 30 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Boris Bikbov

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Dear authors,

The manuscript is much better presented. My suggestions were successfully carried out. I consider the article suitable for publication.

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Reviewer #2: Yes: cassiane dezoti da fonseca

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17 Aug 2021

Response to reviewers

We deeply appreciate the comments of the reviewers and are pleased that their requests have been successfully fulfilled.

We have made the 2 changes suggested by the editorial committee.

- Please correct the titles of the tables "Univariable-Multivariable logistic regression..." to better readers' perception, and use the coherent terminology in the title and the column names (Univariate/Multivariate)

R= Done, titles of Table 2 and 3 of the words "Univariable-Multivariable" by "Univariate / Multivariate"

-Please exclude subtitles "-Mortality of CA-AKI vs HA-AKI: ", etc from the "Discussion", changing them with a short introductory phrase.

R= Done, we exclude subtitles "-Mortality of CA-AKI vs HA-AKI:", "Risk factors for CA-AKI", "KRT between CA-AKI vs HA-AKI" and "Predictive score of death in patients with COVID-AKI" from the "Discussion". We believe that only by deleting those subtitles and leaving the first sentence of each paragraph as it is in the manuscript, the content is perfectly understood, without adding anything else.

Submitted filename: Response to Reviewers 16_8_21.docx

Click here for additional data file.

20 Aug 2021

PONE-D-21-11844R3

Mortality and evolution between Community and Hospital-acquired COVID-AKI

PLOS ONE

Dear Dr. Chávez-Iñiguez,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Thanks for correcting the minor items mentioned before. The changes you introduced are fine, but since after the acceptance there will be no additional editing, please perform further minor corrections to the tables' title to make it not only technically correct but also more easier to percept by readers who are primary clinicians. For example, the "Table 3. Univariable/Multivariable logistic regression model to determine the variables associated with mortality at 28-days follow up and Kidney replacement therapy in hospitalized COVID patients." could be changed to "Table 3. Factors associated with mortality at 28-days of follow up and the requirement of kidney replacement therapy in hospitalized COVID patients, in the univariable and multivariable logistic regression model." This is just an example, you could change the titles in your own way, but I hope this example demonstrates the idea. Please also change the terminology used in the table ("Grade COVID" -> "COVID severity", "Mechanical ventilator" -> "Need in mechanical lung ventilation") and also in the manuscript text ("ventilator" -> "ventilation", etc). You have prepared a nice manuscript with valuable results, there is only a need to polish a little bit the terminology.

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Academic Editor

PLOS ONE

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

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24 Aug 2021

Response to reviewers

We deeply appreciate the comments of the reviewers and are pleased that their requests have been successfully fulfilled.

We have welcomed comments from the Academic Editor Boris Bikbov about minor edits to the tables and text, which we have corrected according to their instructions. Now the manuscript is easier to read.

"Table 3. Univariable/Multivariable logistic regression model to determine the variables associated with mortality at 28-days follow up and Kidney replacement therapy in hospitalized COVID patients." could be changed to "Table 3. Factors associated with mortality at 28-days of follow up and the requirement of kidney replacement therapy in hospitalized COVID patients, in the univariable and multivariable logistic regression model." This is just an example, you could change the titles in your own way, but I hope this example demonstrates the idea.

R=Done, The changes have been made in table 3 and 4 with the editor's suggestions, now it is as follows:

Table 3. Factors associated with mortality at 28-days of follow up and the requirement of kidney replacement therapy in hospitalized COVID patients, in the univariable and multivariable logistic regression model. (page 16)

Table 4. Factors associated with CA-AKI and HA-AKI in hospitalized COVID patients, in the univariable and multivariable logistic regression model. (page 17)

Please also change the terminology used in the table ("Grade COVID" -> "COVID severity", "Mechanical ventilator" -> "Need in mechanical lung ventilation") and also in the manuscript text ("ventilator" -> "ventilation", etc).

R= Done, we have made the changes suggested by the Editor in tables and the manuscript, of the terms: grade COVID, mechanical ventilator; by the terms: COVID severity, Need in mechanical lung ventilation.

We really hope that this changes satisfy to the Academic Editor.

Submitted filename: Response to Reviewers 21_8_21.docx

Click here for additional data file.

6 Sep 2021

Mortality and evolution between Community and Hospital-acquired COVID-AKI

PONE-D-21-11844R4

Dear Dr. Chávez-Iñiguez,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Boris Bikbov

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

ACADEMIC EDITOR: Please note there are some terminology and formatting incongruences in the tables. For example, the tables' title indicates "... in the univariable and multivariable logistic regression model" that is fine. However, the authors have left the column names as "Univariate (95% CI)" and "Multivariate (95% CI)" - that is not correct and should be "Univariable analysis, OR (95% CI)". In another table the authors compared 2 groups and named the column with p-value as "P value (CA-AKI vs. HA-AKI)", with excessive detail "(CA-AKI vs. HA-AKI)" because that are the groups' names.

The journal office will include the requested edits as part of the final requirements the authors must complete before editorial acceptance. Please correct these formatting incongruencies before the manuscript can be editorially accepted.

Reviewers' comments:

26 Oct 2021

PONE-D-21-11844R4

Mortality and evolution between Community and Hospital-acquired COVID-AKI

Dear Dr. Chávez-Iñiguez:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Boris Bikbov

Academic Editor

PLOS ONE