Clinical experts from the Europe and North America had very similar experiences with the clinical use of the test. Types of patients being tested and the types of actions based on the test result were similar. More variation was seen in terms of when to test. Some areas emphasized by the participants warrant further discussion.
Which patients to test
All postoperative cardiac surgery patients
The Society of Thoracic Surgeons’ Adult Cardiac Surgery Database contains more than 6.5 million cardiac surgery procedure records and currently has approximately 3800 participating physicians . After cardiovascular surgery, between 5 and 10% of patients develop kidney failure, defined by a threefold increase in serum creatinine from baseline or increase to a creatinine > 4 mg/dL (which would be equivalent to KDIGO criteria stage 3 AKI by creatinine ). Rates of AKI by full KDIGO criteria are much higher, approaching 2 in 3 patients . Specific considerations for cardiac surgery patients include the common practice of reducing circulating fluid volume on cardiopulmonary bypass (hemoconcentration) often resulting in postoperative oliguria. Current medical literature has demonstrated that post-cardiac surgery patients, identified as high risk by biomarker testing, and randomized to a KDIGO treatment had up to a 34% reduction in stage 2/3 AKI compared with those patients randomized to standard of care . Similar results were reported for non-cardiac major surgery. 
Patients with shock or hemodynamic instability regardless of the cause
Patients with shock, including hypovolemic, distributive/septic, and cardiogenic, as well as patients with acute decompensated heart failure, are at high risk for AKI.
Patients with sepsis
Sepsis is the most common cause of AKI in the ICU . Patients with sepsis, particularly those with septic shock also have more severe AKI—in a recent study, 44% of septic shock patients developed stage 2–3 AKI .
Unplanned admission to the ICU
Patients admitted to the ICU from the ward or emergency department are often at high-risk for AKI, especially if they are hemodynamically unstable or septic. The initial studies validating [TIMP-2]•[IGFBP7] enrolled patients with cardiovascular or respiratory failure going to the ICU . For practical purposes, this includes most unplanned admissions and some planned postoperative admissions (e.g., cardiac surgery). Patients assessed for possible ICU admission by a rapid response team are also at high risk, and [TIMP-2]•[IGFBP7] testing is currently being used by some institutions to help evaluate and triage these patients.
When to test
For cardiac surgery patients, most measured [TIMP-2]•[IGFBP7] within 4 h post-surgery. Performing the test at a few different postoperative timepoints is helpful to identify the most appropriate testing time for a particular program given inherent differences in care across institutions. Studies have reported a variety of results in this regard. In several studies [14,15,16], [TIMP-2]•[IGFBP7] detected elevations at 4 h; in another study, elevations were not detected until the day after surgery . A recent study , with the most granular time-course published to date, shows bimodal elevations of [TIMP-2]•[IGFBP7] with the first peak occurring intraoperatively and the second 6 h after ICU admission in patients who developed stages 2/3 AKI. The authors postulate that the first peak indicates kidney stress caused during the surgery, while the second peak may indicate kidney stress caused during early postoperative care. Measurement at both times resulted in the best predictive ability, as would be expected for two independent episodes of stress.
For patients in shock, [TIMP-2]•[IGFBP7] testing is ordered as early as possible during patient evaluation. Interestingly, there is emerging evidence in septic shock that the post-resuscitation test results may be most predictive . However, it also has been noted that when test results improve (levels decrease) with resuscitation, outcomes are better. There is therefore the hypothesis that [TIMP-2]•[IGFBP7] testing might ultimately be proven useful as a tool to monitor resuscitation efficacy. Establishing clinical utility for this indication will require studies that compare a biomarker-guided approach to a standard approach. Such studies are currently lacking.
What actions to take and how to integrate the technology into practice
Management of potential nephrotoxic medications was the top priority in patients with positive test results. The clinical panel participants agreed that all nonessential nephrotoxic medications should be avoided. The combination of vancomycin and piperacillin-tazobactam, in particular, has been noted to significantly increase risk for AKI . If vancomycin (or an aminoglycoside) is used, it should be dosed strictly by levels, and its duration of use should be as limited as possible. If a pharmacist is not already part of the critical care team, consultation may be appropriate. Likewise, NSAIDs and ACE inhibitors/ARBs should be avoided in the early postoperative period.
A second category of high-priority actions involved fluid management. Participants noted that patients with a positive test result are at risk for fluid overload but also might be volume depleted. There was strong consensus therefore that a “goal-directed” approach to fluid/diuretic management was essential. Two examples of such an approach were published, one in 2017 in cardiac surgery patients  and one in 2018 in non-cardiac surgery patients . In the first study, biomarker-positive patients were randomized to receive a care bundle that included a hemodynamic management algorithm based on mean arterial pressure and stroke volume variation. AKI was significantly reduced with the intervention compared to controls (55.1 vs. 71.7%; ARR 16.6% (95% CI 5.5–27.9%); p = 0.004). Rates of moderate to severe AKI were also significantly reduced by the intervention compared to controls (41/138 (29.7%) vs 62/138 (44.9%); p = 0.009; OR, 0.518 (95% CI, 0.316–0.851); ARR, 15.2% (95% CI, 4.0–26.5%)). The intervention resulted in significantly improved hemodynamics (p < 0.05) as well as less hyperglycemia (p < 0.001) and use of ACEi/ARBs (p < 0.001) compared to controls. The total administered volume was not different between the two groups, but the distribution of fluid was different, with patients in the intervention group receiving significantly less volume during the last 3 h of the intervention period (p = 0.024). However, there were no differences in rates of renal replacement therapy between intervention and control either within 72 h (7.2% vs. 5.1%, p = 0.45), during hospitalization (10.1% vs. 6.5%, p = 0.28), or at 30 days (3.1% vs. 2.3%. p = 0.72). Neither were there differences in mortality or persistent renal dysfunction at 30, 60, or 90 days.
In the second study , a similar care bundle including early optimization of fluid status and maintenance of perfusion pressure, was applied to non-cardiac major surgery patients after testing positive for the biomarker. Overall AKI rates were not statistically different between groups (19/60 (31.7%) in the intervention group vs. 29/61 (47.5%) in the standard care group, p = 0.076). However, rates of moderate and severe AKI, a secondary endpoint, were reduced with the intervention (4/60 (6.7%) vs. 12/61 (19.7%), p = 0.04), as were lengths of ICU stay (median difference 1 day, p = 0.035) and hospital stay (median difference 5 days, p = 0.04). There were no significant differences regarding renal replacement therapy, in-hospital mortality, or major kidney events at hospital discharge. Interestingly, 48-h cumulative balance was not statistically different (2567 ml (1617–3706) vs. 3207 ml (2015–4486), p = 0.085) but favored lower volumes in the intervention group. This last finding brings to attention the fact that “optimization” of fluid status for AKI patients does not mean “give fluid” and frequently results in less fluid.
As with any new technology, there are potential barriers to adoption. The value proposition for new technology involves both potential benefits as well as costs. Although a cost-effectiveness analysis for the test is beyond the scope of this report, it is notable that AKI is extremely expensive—estimates put the cost at more than 19,000 USD  to as much as 39,000 USD per case . By comparison, the test itself retails for approximately 100 USD per determination. However, the test will not be useful in all patients, and protocols should define appropriate lines of communication to ensure that the [TIMP-2]•[IGFBP7] test is ordered for the appropriate patients. Given that [TIMP-2]•[IGFBP7] provides an early warning of kidney stress, the test results are most valuable when reported promptly. Therefore, the [TIMP-2]•[IGFBP7] should be ordered as a “stat” (i.e., as soon as possible) test so that results are available as quickly as possible. Most participants reported a 1-h turn around by their clinical lab. By instituting an AKI biomarker protocol, hospitals have the opportunity to develop and test metrics that can enhance quality improvement initiatives.
As part of [TIMP-2]•[IGFBP7] test protocol integration, the inclusion of information technology and the electronic health record (EHR)/electronic medical record (EMR) system is imperative to ensure that test reporting is online, and the test is used consistently. The test may become a part of cardiopulmonary bypass protocols and can be added as an EHR order. It is helpful to provide sample protocols and data to demonstrate what is needed. If [TIMP-2]•[IGFBP7] testing is effectively integrated into these systems, it also may be beneficial to expand testing into other hospital systems and networks. For example, [TIMP-2]•[IGFBP7] testing could work well in other ICUs, for all patients admitted with shock, the emergency department, and/or trauma unit, as well as operating rooms.
Despite its brief history, dozens of studies have evaluated the diagnostic value of [TIMP-2]•[IGFBP7] for AKI, in various settings (e.g., cardiac surgery, ICU, emergency department/trauma), different patient populations (e.g., KDIGO criteria, elderly, high-risk surgeries), and measurement criteria (e.g., thresholds, sampling times). Detailed discussion of these studies is beyond the scope of this report, but several systematic reviews are available [23,24,25,26,27]. Overall, [TIMP-2]•[IGFBP7] is accurate in identifying patients at risk for AKI. However, to our knowledge, only two studies, thus far, have attempted to evaluate whether use of the test alters the clinical course of AKI [7, 11]. Thus, future research is warranted to better understand how treatment protocols based on [TIMP-2]•[IGFBP7] results can improve outcomes.