Study design
In order to reveal the association between CVP and new-onset AKI in sepsis patients, we conducted a case control study by retrieving electronic health record (EHR) from Medical Information Mart for Intensive Care III(MIMIC-III) database. Sepsis patients who had new-onset AKI within the first 48h or 7d after their ICU admission were categorized as the SAKI group, with the remaining patients making up the non-SAKI group.
We discovered significant differences of the baseline demographic and clinical characters between SAKI patients and non-SAKI patients in our preliminary dataset, thus 1:1 propensity score matching (PSM) was applied to balance out these baseline difference that may confound the CVP-SAKI relation (Figure 1).
Data source
Data used for this study was retrieved from the MIMIC-III (Medical Information Mart for Intensive Care III) Clinical Database, which is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who admitted to critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012[11]. The current version of the MIMIC-III Clinical Database is 1.4 version which contains data from 53,423 distinct hospital admissions for adult patients admitted to ICUs during the study period, the data covers 38,597 distinct adult patients and 49,785 hospital admissions, the median age of adult patients is 65.8 years, 55.9% patients are male, and in-hospital mortality is 11.5%. All data are extracted from the MIMIC-III database using custom PostgreSQL which is s a powerful, open source, object-relational database system and can be downloaded from internet freely. Since the Institutional Review Board of the Beth Israel Deaconess Medical Center (BIDMC) and Massachusetts Institute of Technology have approved the use of the MIMMICII database by any investigator who fulfills data user requirements, IRB approval from our institution and Informed consent were exempted.
This study was reported according to The Reporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement[12].
Patient inclusion and exclusion
Inclusion criteria was patients: (1) adult patient with sepsis(aged 18 years or above); (2)admitted to MICU or SICU; and (3) with the data of CVP measured in 24h,and the data of new-onset AKI recorded within the first 48h or 7d. In this study, the diagnosis of sepsis was in accordance with Angus criteria[13] to retrospectively identify patients using billing codes. To identify cases with severe sepsis, we selected all cases from MIMIC-III database with ICD-9-CM codes for both a bacterial or fungal infections process and a diagnosis of acute organ dysfunction. The code of Angus criteria for searching the database and other related concepts could be captured at the MIMIC Code Repository[14] which is available online and is open[15].
Patients aged over 89 were excluded because date of birth for patients aged over 89 were shifted to obscure their true age for the reason of deidentification in MIMIC-III database[11].
Demographical and laboratory variables
The following baseline variables were extracted from the MIMICIII database for the at the time of ICU admission: age at the time of hospital admission, gender, sequential organ failure assessment(SOFA), Simplified Acute Physiology Score II (SAPSII), The Logistic Organ Dysfunction system (LODS), Acute Physiology Score III(APS III), use of vasopressors and renal replacement therapy (RRT).
Information regarding the baseline comorbidities were also extracted. We collected at the baseline the history of congestive heart failure, cardiac arrhythmias, valvular disease, pulmonary circulation disease, peripheral vascular disease, hypertension, chronic pulmonary disease, diabetes, hypothyroidism, renal failure, liver disease, solid tumor, metastatic cancer, coagulopathy, deficiency anemias. All comorbidities were identified according to the method defined by Elixhauser which’s coding algorithms was developed by Quan et. al[16].(A detailed coding of the Elixhauser comorbidities used for querying MIMIC-III database is also available online)
Variables that represent early admission hemodynamic stability, such as CVP, MAP, DAP were collected within the first 24 hours after the ICU admission as the lowest, mean, highest values. If a variable was measured more than once in the first 24h, the value associated with the greatest severity of illness was used. For example, the lowest value of mean BP reported in the first 24 h were used in the study. Daily fluid balance (input-output) of the first 3 days were also included for analysis. Usage of nephrotoxic antibiotics such as vancomycin, aminoglycosides which was a confounding factor of AKI was also analyzed.
Laboratory variables during the first 24 hours of admissions were collected for analysis, including white blood cell count, hematocrit, platelet count, sodium, potassium, bicarbonate, chloride, blood urea nitrogen, lactate, creatinine, pH, anion gap, bilirubin, albumin and creatinine kinase. For patients with multiple measurements, the lowest value of hematocrit, platelet count, bicarbonate, pH, albumin, and highest value of WBC, potassium, chloride, sodium, potassium, BUN, lactate, creatinine, anion gap, bilirubin, and creatinine kinase.
Definition of other clinical variables
CVP-variation: we used coefficient of variation to describe the variability of CVP which calculated as the standard deviation of the CVP divided by the mean of the CVP. Accumulative fluid balance was defined as total net fluid balance after ICU admission.
Primary outcome
The primary outcome was new-onset AKI (SAKI) within the first 48 hour or 7 days after their ICU admission. New-onset AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria where AKI was defined as any of the following:Increase in creatinine by 0.3 mg/dl within 48 hours; or Increase in creatinine to 1.5 times baseline, which was known or presumed to have occurred within the prior 7 days; or urine volume 0.5 ml/kg/h for 6 hours[17]. In this study, baseline creatinine was defined as first measurement in 6 hours before or 24 hours after ICU admit. For urine output, the highest UO in 0-48 hours was used, and for creatinine, creatinine value from days 0-2 or 0-7 is used.
Statistical analysis
Continuous variables were compared using independent t-test. Categorical variables were compared using chi-squared, if the expected value in the cell was less than 5, Fisher’s exact test will be used.
Repeated measures such as the fluid accumulation between the SAKI and non-SAKI for the first 3 days were compared using Two-way repeated measure ANOVA. In consider that the fluid accumulation was measured repeatedly and may confound the effect of CVP on SAKI risk, we chose to use generalized estimate equation (GEE) to evaluate the potential factors and their effect on the SAKI risk. All statistical analysis was completed by using SPSS 24.0