Universally, the volume of data has increased, with the collection rate doubling every 40 months, since the 1980s. “Big data” is a term that was introduced in the 1990s to include data sets too large to be used with common software. Medicine is a major field predicted to increase the use of big data in 2025. Big data in medicine may be used by commercial, academic, government, and public sectors. It includes biologic, biometric, and electronic health data. Examples of biologic data include biobanks; biometric data may have individual wellness data from devices; electronic health data include the medical record; and other data demographics and images. Big data has also contributed to the changes in the research methodology. Changes in the clinical research paradigm has been fueled by large-scale biological data harvesting (biobanks), which is developed, analyzed, and managed by cheaper computing technology (big data), supported by greater flexibility in study design (real-world data) and the relationships between industry, government regulators, and academics. Cultural changes along with easy access to information via the Internet facilitate ease of participation by more people. Current needs demand quick answers which may be supplied by big data, biobanks, and changes in flexibility in study design. Big data can reveal health patterns, and promises to provide solutions that have previously been out of society’s grasp; however, the murkiness of international laws, questions of data ownership, public ignorance, and privacy and security concerns are slowing down the progress that could otherwise be achieved by the use of big data. The goal of this descriptive review is to create awareness of the ramifications for big data and to encourage readers that this trend is positive and will likely lead to better clinical solutions, but, caution must be exercised to reduce harm.

The use of synthetic cannabinoids (SCBs) is associated with many severe adverse effects that are not observed with marijuana use. We report a unique case of a patient who developed rhabdomyolysis and acute kidney injury (AKI) requiring dialysis after use of SCBs combined with quetiapine. Causes for the different adverse effects profile between SCBs and marijuana are not defined yet. Cases reported in literature with SCBs use have been associated with reversible AKI characterized by acute tubular necrosis and interstitial nephritis. Recent studies have showed the involvement of cytochromes P450s (CYPs) in biotransformation of SCBs. The use of quetiapine which is a substrate of the CYP3A4 and is excreted (73%) as urine metabolites may worsen the side effect profiles of both quetiapine and K2. SCBs use should be included in the differential diagnosis of AKI and serum Creatinine Phosphokinase (CPK) level should be monitored. Further research is needed to identify the mechanism of SCBs nephrotoxicity.

There are no guidelines for transitioning patients from chronic kidney disease stage 5 to hemodialysis. We conducted this study to determine if there are uniform patterns in how nephrologists transition patients to dialysis. We designed an electronic survey with 39 questions and sent it to a database of practicing nephrologists at the National Kidney Foundation. Factors that were important for transitioning a patient to hemodialysis were evaluated, including medication changes on dialysis initiation, dry weight and dialysis prescription. 160 US Nephrologists replied to the survey; 18% (29/160) of the responses were completed via social media sites. Prior to dialysis, 74% (118/160), prescribed furosemide and 67% (107/160) used furosemide with metolazone. Once dialysis started, only 46% (74/160) of the responders continued patients on diuretics daily. Hypertension medications prescribed in dialysis were calcium channel blockers 69% (112/160), beta blockers 36% (58/160), angiotensin converting enzyme inhibitor 32% (53/160), angiotensin receptor blocker 29% (46/160) and diuretics 25% (42/160). Once dialysis started, 68% (109/160) routinely changed medications. Most, 67% (107/160) ordered patients to avoid anti-hypertensive medications on dialysis days to allow for ultrafiltration. Dry weight was determined in the first week by 29% (46/160) and in the first month by 53% (85/160). Most, 59% (94/160) felt that multiple causes lead to hypertension. Most nephrologists would prescribe small dialyzers and a shorter period of time for the first dialysis session. The transition period to chronic hemodialysis has variations in practice patterns and may benefit from further studies to optimize clinical practice.

Acute kidney injury due to urinary tract obstruction invariably suggests lower urinary tract obstruction or bilateral ureteric obstruction since obstruction of a single kidney while the contralateral kidney is normal and not obstructed would not cause a perceptible rise in creatinine. Assuming a total body volume of 42 L, 70 kg male that generates approximately 1400 mg of creatinine daily (20 mg/kg/day) who has complete urinary tract obstruction would experience a 3.33 mg/dL per day increase in serum creatinine. Thus, for an individual who had prior normal renal function and who presents with a creatinine of 30 mg/dL, one could surmise that the obstructive pathology had lasted at least 10 days. However, the rise in serum creatinine is a poor marker of renal injury and subsequent prognosis. Urinary tract obstruction leading to AKI can be due to a variety of causes, and its management is tailored to the underlying etiology. This case series describes the varied clinical course of four patients at our center who experienced AKI from atypical causes of obstructive uropathy. Current and future diagnostic modalities and caveats in the treatment of this disease entity are also discussed.

69 year old woman with hypertension, sleep apnea and who had a recent knee replacement, was brought in to the emergency room (ER) for syncope. She had her physiotherapy session earlier in the day and became symptomatic with dizziness and shortness of breath and passed out. In the ER she had a systolic blood pressure (SBP) of 90mmHg and an oxygen saturation (O2 sat) of 80% on room air. She was given fluid bolus with improvement of SBP to 110mmHg. O2 sat improved to 99% with 10L of oxygen. Treatment was started with full dose of Enoxaparin subcutaneously. A 12-lead electrocardiogram (EKG) showed sinus tachycardia (ST) at 117 beats per minute (BPM), right bundle branch block (RBBB) and S1Q3T3 pattern. A bedside echocardiogram showed right ventricular (RV) distension. A CT-angiogram showed bilateral main stem pulmonary emboli (PE) with signs of RV strain. Patient was admitted and remained hemodynamically stable. A repeat EKG done the following day showed ST at 110 BPM with resolution of RBBB. An echocardiogram done now showed normal RV size and function. Patent was eventually discharged home on full dose apixaban. Q3S1T3 Figure 1 - ST, RBBB, S1Q3T3 pattern Figure 2 - ST Discussion: The patient presented with new RBBB (Figure 1) due to RV strain from acute PE as shown by the CT-angiogram and bedside echocardiogram. The EKG also showed S1Q3T3 pattern. With the resolution of the RV strain the following day, as noted on the subsequent echocardiogram, the 12 lead EKG showed the resolution of the RBBB and the QRS complex became narrow (Figure 2). RBBB is thought to be caused by acute RV overload and dilatation, accompanied by subendocardial ischemia in the right bundle. The S1Q3T3 pattern is historically considered as a “classic” EKG pattern associated with acute PE, even though it is neither sensitive nor specific for acute PE. Conclusion: The RBBB along with the S1Q3T3 pattern and its resolution with improvement of RV hemodynamics, is the first reported case in the literature. Download figure