Acute kidney injury (AKI), chronic renal failure, and tubular abnormalities represent the kidney disease spectrum of malignancy. Prompt diagnosis and treatment may prevent or reverse these complications. The pathogenesis of AKI in cancer is multifactorial. AKI affects outcomes in cancer, oncological therapy withdrawal, increased hospitalization rate, and hospital stay. Renal function derangement can be recovered with early detection and targeted therapy of cancers. Identifying patients at higher risk of renal damage and implementing preventive measures without sacrificing the benefits of oncological therapy improve survival. Multidisciplinary approaches, such as relieving obstruction, hydration, etc., are required to minimize the kidney injury rate. Different keywords, texts, and phrases were used to search Google, EMBASE, PubMed, Scopus, and Google Scholar for related original and review articles that serve the article’s aim well. In this nonsystematic article, we aimed to review the published data on cancer-associated kidney complications, their pathogenesis, management, prevention, and the latest updates. Kidney involvement in cancer occurs due to tumor therapy, direct kidney invasion by tumor, or tumor complications. Early diagnosis and therapy improve the survival rate. Pathogenesis of cancer-related kidney involvement is different and complicated. Clinicians’ awareness of all the potential causes of cancer-related complications is essential, and a kidney biopsy should be conducted to confirm the kidney pathologies. Chronic kidney disease is a known complication in malignancy and therapies. Hence, avoiding nephrotoxic drugs, dose standardization, and early cancer detection are mandatory measures to prevent renal involvement. Acute kidney injury (AKI) is a frequent complication of cancers that can affect up to 50% of the patients during their course of cancer. It significantly influences the overall prognosis, duration of hospitalization, and consequent healthcare costs. Various factors, including patient type, malignancy type, or therapy, may cause AKI. The patient-related risk factors for AKI are the same as those in the general population. Tumor-related risk factors include compression, blockage, direct kidney infiltration from the tumor, paraprotein precipitation, aggregation, and crystallization in renal tubules. Treatment-related risk factors are the most prevalent in clinical practice. They may manifest as tumor lysis syndrome (TLS), venous-occlusive disease (VOD), or thrombotic microangiopathy (TMA), increasing AKI risk.,3 However, it is unknown whether this increased risk occurs more in the early or late stages of chronic kidney disease (CKD). Depending primarily on the type of cancer and the patient’s age, the effects of CKD may vary. The relationship between cancer and CKD seems to be bidirectional: cancer may induce CKD directly or indirectly via the side effects of medications, and CKD is a known risk for cancer.End-stage renal disease (ESRD) increases malignancy risk in native and transplanted kidneys. In moderate to severe CKD, the risk of cutaneous and urogenital cancer was observed to be exceptionally high; however, this can partially be due to bias. Yang et al emphasized that CKD is present in almost 32.4% of newly diagnosed cancer patients. It is especially critical to evaluate the degree of this link for the identification of cancer in patients with CKD, which affects not only their short-term results but also their treatment choices for the underlying disease. Studies have revealed that cancer patients with CKD have an increased mortality risk compared with those without CKD. Another study concluded that CKD patients had a high mortality rate due to liver, urinary tract, and kidney cancers. However, a previous study reported an inverse relationship between eGFR and the death rate from liver cancer. They related this inverse relationship to poor response to therapy or increased cancer incidence. Furthermore, following non-dialyzed-CKD patients for the 20-year, nearly a quarter had developed malignancies. Moreover, elderly males with low eGFR have a higher malignancy risk. Although the reasons for renal failure in cancer are usually multifactorial, the classification of prerenal, renal, and postrenal causes remains clinically relevant.There is conflicting evidence regarding the relationship between cancer risk and the estimated glomerular filtration rate (eGFR). A Scandinavian study investigated the possible association between renal function and cancer incidence. Between 1997 and 2001, 58% of ESRD cases caused by cancer were due to myeloma; however, myeloma accounts for only up to 1% of all cancers. A recent Eastern Europe study reported that of the 24 different cancers studied, breast (22%), lung (10%), and colon (10%) cancers were more common in CKD patients compared to the normal population. After the first and the second year of follow-up, the prevalence of CKD (stage 3–5) was (12% and 13%), respectively. Patients with pancreatic cancer (19.6%), renal cancer (50%), and urinary tract cancer (34%) were more likely to have CKD, whereas those with brain tumors (3%) and colon cancer (5.3%) were less likely to have CKD. An eGFR of ≤6 mL/min/1.73 m2 was present in 0.7% of the CKD patients who needed renal replacement therapy (RRT). Finally, a multidisciplinary strategy is required to limit the prevalence of cancer-associated kidney complications.Renal impairment affects approximately 20% of myeloma patients. About 50% of myeloma patients have kidney dysfunction at presentation, and almost 5% may require dialysis, significantly affecting the outcome.In this nonsystematic clinical-oriented review, we aim to update the renal complications, pathogenesis, epidemiology, prevention, and related treatments of cancer-associated kidney diseases from a nephrology perspective. PubMed, EMBASE, Google, Scopus, and Google Scholar were searched for original and review articles using different phrases and texts, such as acute renal injury in malignancy, hyperuricemia in cancer, CKD in malignancies, kidney involvement in cancer, RRT in cancer patients, etc.The Medical Research Centre in Doha did not have to give ethical approval because it was just a review of articles that had already been published. or oncological . By RIFLE criteria, AKI is defined as a sudden (1–7 days) and sustained (>24 hours) impairment of renal function. The RIFLE criteria define renal failure as having 4 stages. Furthermore, the RIFLE criteria provide a graded definition of AKI, which the staging criteria imply. Arbitrarily, AKI is divided according to the underlying cause into prerenal, renal, and postrenal types. In cancer patients, the same classification is followed and accepted by almost all the experts. Table AKI has been defined differently according to the systems used. Nephrological  or medical,a sudden –7 days a The prospect of higher mortality in a cancer patient who develops AKI, in addition to preexisting chronic renal conditions, is of grave concern and alarming to the patients. A bidirectional pattern describing the association between renal injury and cancer has been described. Indeed, AKI may affect pharmacokinetics, including the bioavailability of several anticancer medications and their safety profiles. Physicians unaware of these facts can result in suboptimal therapies or increased drug-induced renal toxicity risk. Furthermore, an overcautious approach may lead some physicians to omit certain highly effective anticancer medications that may cause AKI. Identifying, understanding, and managing every risk factor is vital in preventing AKI. Presently, there are no viable therapy schemes for AKI in malignancy; therefore, preventive measures should be highly prioritized.The annual AKI incidence is estimated at 13.3 million worldwide. Indeed, oncology patients, especially the elderly, have a higher chance of developing AKI during the first year after a cancer diagnosis. This combination negatively impacts patients’ survival. Cheng et al reported that AKI affected 7.5% of cancer patients. Approximately 1.6% of AKI cases were from the community, and 5.9% had AKI in hospitals. Studying 37,267 incident cases of cancer, the incidence of AKI was 258/1000 person-years, which decreased to 43/1000 person-years a year after a cancer diagnosis, and the 5-year risk was decreased further to 27%. The same study reported the highest 1-year risk (44%) in patients with renal cancer, 33% with hepatic cancer, and multiple myeloma (MM) (31.8%). Moreover, they reported that overall, and for most exact cancer sites, risks were high in patients with metastases at malignancy diagnosis. At 1 and 5 years, 4.5% and 7.6% of patients, respectively, had more severe AKI. Notably, the 28-day death rate of cancer patients on dialysis is projected to be 66% to 88%. AKI is very common in the inpatient setting; oncology, critical care, heart surgery, and transplantation units have extraordinarily high rates of AKI, exceeding 50%. Furthermore, recent research examined 163,071 patients undergoing systemic chemotherapy or targeted medicines for their disease and found that 6.6% had developed AKI. The AKI rate was 27/1000 persons/year with a total incidence of 9.3%. Myeloma [26%], bladder cancer (19%), and leukemia (15.4%) had the most significant 5-year AKI incidences. AKI occurs more with advanced cancer stages, CKD, and diabetes. The co-prescription of a diuretic and an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker was associated with increased AKI rate in individuals aged 66 years and had systematic antitumor therapy. Another recent Chinese study found that 14% to 20% of cancer patients had AKI.According to research, AKI is more likely to occur in cancer than in non-cancer patients.AKI mechanism(s) in cancer is multiple in origin, as will be discussed later. The possible mechanism(s) are summarized in Figure  A prospective multicenter study was conducted in 2013 to determine the primary risk variables for AKI. The study revealed that age, hypotension, sepsis, hypovolemia, preexisting CKD, concomitant vascular disease (including atherosclerosis), and congestive heart failure were potentially associated with AKI development. Additionally, vomiting and diarrhea due to some malignancies and chemotherapy increase dehydration rate and AKI. Prevention of AKI includes general strategies such as maintaining a good volume status, achieving hemodynamic stability, optimizing cardiac function, and treating anemia.Patient-related risk factors for AKI in cancer are similar to the other population; however, cancer patients have tumors, and their therapies as additional significant risk factors.,26 According to published studies, several types of carcinomas, and rarely leukemia and lymphoma, are related to membranous nephropathy. However, this relationship has been disputed, and registry data is only sometimes supportive.,28 In 107 patients with biopsy-proven membranous nephropathy, 8.4% had underlying malignancy, and in prior publications, the incidence ranged from 5.8% to 10.6%.,31 Because of this substantial connection, some experts recommend tumor screening in older individuals with membranous nephropathy.,29 The exact mechanism by which cancer causes glomerular damage remains unknown. However, it may include tumor antigens being deposited in the subepithelial region, the creation of in situ immune complexes, and subsequent complement activation. This conception has some indirect support since treating the underlying tumor may result in clearing the nephrotic manifestations.,34Although glomerular disease in malignancy is generally uncommon, paraneoplastic glomerular involvement was reported. There are additional cases of membranoproliferative glomerulonephritis that progress quickly in conjunction with cancer. Pankhurst et al conducted retrospective case-control research comparing patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis with age- and gender-matched control to examine the relationship between ANCA vasculitis and cancer. One-third of the patients were diagnosed with malignancy when renal involvement was detected. Although cyclophosphamide treatment has been linked to bladder cancer , this research supports an earlier small series that demonstrated a direct connection between ANCA vasculitis and cancer, irrespective of the drug used to treat the vasculitis.,37With a frequency of 0.4% among 1700 studied individuals, the link between minimal-change disease and Hodgkin’s disease was observed, although rare. AKI, proteinuria, or hematuria may sometimes accompany lymphomatous invasion of renal tissues. However, this diagnosis is often accidental. Most patients have trivial kidney function disarrangement; however, AKI occurs mainly due to infection, aminoglycoside, diuretics, hypercalcemia, TLS, and chemotherapy rather than lymphoma kidney invasion. Kidney involvement was suspected before the kidney biopsy, mainly based on radiographic evidence of enlarged kidneys in 80% of B-cell lymphoma. Most patients show bilateral enlargement on renal imaging. AKI coupled with lymphomatous infiltration may respond effectively to treatment focused on the underlying malignancy. Recently published data reported that AKI occurred in 29% of B-cell lymphoproliferative disorders.Solid and hematological malignancies may affect the renal parenchyma; however, its clinical consequences are often unnoticeable. The most prevalent malignancies, besides multiple myeloma, are lymphomas and leukemias that affect the kidney, causing AKI. In these situations, AKI is often quickly reversible with prompt treatment. When red blood cell casts, hematuria, or proteinuria are discovered, cancer-related glomerulonephritis, such as membranoproliferative glomerulonephritis or amyloidosis, should be considered. In these situations, a kidney biopsy is essential for determining the diagnosis prognostication and guiding the best course of therapy. Malignancy-related glomerulonephritis may be the first sign of cancer and is relatively rare; therefore, it should be suspected, and age-appropriate cancer screening must be effectively conducted. Significantly, lymphomatous kidney invasion causes AKI, which improves with anticancer treatment. Rarely extrarenal solid metastatic tumors can lead to AKI. There are a few examples of AKI caused by solid tumor infiltration; when they do, there is often extensive parenchymal invasion by the tumor. The most common solid tumors that spread to the kidney are bronchogenic carcinomas, followed by stomach and breast carcinomas.Tumor cells that compress tubules and disturb renal microcirculation are likely to be the etiology of AKI. In these circumstances, urine protein electrophoresis may contain a significant amount of lysozyme.The cellular damage and AKI result from the filtration of lysozyme at the glomerulus and its uptake by proximal tubular cells. Patients with acute promyelocytic, monocytic, or chronic myelomonocytic leukemia, in which malignant cells create excessive levels of lysozyme, are more likely to develop lysozymuria, a rare condition. AKI caused by light chain cast nephropathy is regarded as a myeloma-defining event according to the 2014 International Myeloma Working Group criteria. Rarely, additional hematological malignancies such as Waldenstrom macroglobulinemia, chronic lymphocytic leukemia, or lymphoma may be linked to light chain cast nephropathy.Patients with MM are more susceptible to AKI. The etiology of AKI in these individuals is complex and varies. AKI is quite typical and may make the course of myeloma more severe in 20% to 50% of patients. The carbohydrate moieties on Tamm-Horsfall proteins engage non-covalently with shared binding sites on the kappa and lambda light chains. Reduced tubular flow rates and increased urine electrolyte concentrations (such as those associated with diuretics) encourage these interactions and the development of obstructive casts.,49 Additionally, there is a clear connection between serum FLC concentration and the risk of cast nephropathy. Diffuse interstitial inflammation is observed upon histological analysis; the leakage of light chains may have brought this inflammation into the renal interstitium. Due to this interstitium infiltration, different pro-inflammatory pathways are activated, and continued inflammation may lead to irreversible kidney damage, emphasizing the need for prompt and aggressive therapy. However, new research projects are needed to explore inflammatory and proinflammatory factors’ role in AKI in malignancy.The thick ascending limb of the loop of Henle is where Tamm-Horsfall protein (uromodulin) binds to free light chain (FLCs), freely filtered by the glomerulus, to form insoluble casts that impede the tubular lumen and cause local inflammation. To differentiate cast nephropathy, where proteinuria is mostly unbound albumin FLCs, from paraprotein-related glomerular disorders, such as albuminuria and serum FLCs, serum protein, and urine protein electrophoresis are used. According to a Mayo Clinic study, the median amount of urinary albumin excretion in individuals with light-chain cast nephropathy was 7%, and urinary albumin excretion was <25% of total urinary protein excretion. Kidney biopsy is advisable when urine albumin excretion is high, especially if blood FLC levels are <50 mg/dL.Serum FLC measurements, including quantitative measurements of kappa and lambda FLCs and serum and urine protein electrophoresis, are the main components of cast nephropathy diagnosis.,55 These regimens were linked to dramatically increased survival high and renal function improvement rates.,56 Importantly, within a median duration of r 1.34 months, bortezomib works swiftly to enhance GFR. Adding alkylating medication (bendamustine) to a prednisone and bortezomib regimen increased kidney response rates to more than 80%, with most of the response happening within 6 weeks.,58During the last 10 years, cast nephropathy treatment has advanced significantly. It now focuses on providing appropriate hydration to increase tubular flow and treats preexisting volume depletion (“flushing out the tubular casts”), as the chemotherapy quickly lowers FLC levels. Proteasome inhibitors such as bortezomib are combined with other medications such as thalidomide, corticosteroids, vincristine, and Adriamycin. Two recent experiments have been reported, and most recently, the use of high flux dialyzers with better capacity for light chain removal has been examined. There was no advantage of high flux dialysis over standard dialysis in a European study of FLC elimination by prolonged hemodialysis. However, in Patients With MM and Renal Failure Due to Myeloma Cast Nephropathy study that included patients with renal biopsy-proven cast nephropathy revealed that high-flux dialysis was advantageous. In this experiment, high-flux dialysis increased dialysis dependency to 56.5% compared with conventional dialysis . Due to the inconsistent results of the two studies, it is still being determined whether high-cutoff hemodialysis is beneficial or not. Therefore, new research is required to elucidate the issue further.There is still interest in using RRT to quickly remove FLCs when more decisive chemotherapy is used because a rapid drop in the blood concentration of FLCs is essential for restoring kidney function. A continuous debate is ongoing over therapeutic plasma exchange (TPE) and high-cutoff hemodialysis . Randomized controlled studies on plasmapheresis have been limited and inconclusive in 97 participants. Urinary system obstruction by lithiasis occurs in patients with malignancy due to stone formation or clots. Ureter obstruction occurs because of stones or compression. Urinary bladder outlet obstruction and tumors have been reported to cause obstructive uropathy. Penile and vaginal tumors rarely lead to obstructive uropathy. The absence of hydronephrosis does not exclude obstructive uropathy because pelvic-ureteric dilatation may not develop if a retroperitoneal tumor or fibrosis significantly encases the kidney pelvises and ureters. Retroperitoneal fibrosis (a cancer complication) rarely occurs and is often idiopathic. However, it occurs mainly as a radiotherapy complication for malignant pelvic organ cancers and lymphoma patients.More often than the general population, AKI’s postrenal causes should always be considered in cancer patients. Urogenital system obstruction is prevalent more with uterine, prostate, and cervical tumors.Beyond TLS, no specific preventive measures should be implemented in cases of tumor-specific AKI. Preventing AKI in cancer includes adequate hydration, prophylactic antibiotics, and hematopoietic growth factors in patients with neutropenia/febrile neutropenia. Furthermore, avoiding the repeated and frequent use of potentially nephrotoxic drugs and contrast agents is essential to prevent AKI. The pathological traits of TMA include endothelial edema, microvascular blockage, and intrarenal or systemic microvascular thrombi. It is typically associated with renal failure, neurological problems, and gastrointestinal complaints.,36According to previous prospective research, almost 6% of patients with metastatic cancer developed microangiopathic hemolytic anemia.2. Cisplatin, 5-fluorouracil, and bleomycin have been linked less commonly to TMA. Treating cancers such as pancreatic, bladder, and advanced non-small-cell lung malignancies with the nucleoside analog gemcitabine is common. The cumulative incidence was 0.31%, greater than the estimated 0.01%. TMA syndromes and hypertension (HTN) are linked, and HTN severity in TMA correlates with poor outcomes. Glomerular ischemia caused by the microvascular capillary blockage in the glomeruli and other kidney tissues is the most likely mechanism through which TMA causes HTN. Patients who take gemcitabine have a risk of developing new or worsening HTN. Hence, regular weekly follow-up at the start of treatment is required, enabling the early detection of TMA and AKI linked to gemcitabine.It is well-documented that cancer affects the kidneys and causes AKI, CKD, and other kidney dysfunctions. TMA syndrome is highly correlated with the use of anticancer medications. One common causative drug is mitomycin C, with a 2% to 10% risk that has risen considerably with a collective dose of 40 mg/m According to the consensus definition, the characteristics of biological TLS include the rapid release of intracellular contents with a subsequent 25% change in the level above average for any two or more serum values of uric acid, potassium, phosphate, and calcium within 3 days before or 7 days after the start of chemotherapy.,74 Additionally, a significant amount of purine released from DNA catabolism is transformed into xanthine and uric acid, increasing the risk of intrarenal and extrarenal obstructive uropathy. Acute renal damage is detrimental to complete remission and survival rates in this situation.,76 Uric acid, xanthine, and calcium phosphate crystal precipitation in renal tubules are one of the main mechanisms of TLS-induced AKI. Additional mechanisms may also contribute to acute tubular necrosis, including the increase in pro-inflammatory cytokines production, affecting renal microcirculation, and increasing renal parenchyma tumor infiltration. According to the consensus definition, other clinical TLS signs, including cardiac arrhythmia and seizures, are also features. TLS may sometimes resemble sepsis and present with acute respiratory failure, hemodynamic instability, and systemic inflammatory response syndrome. Abdel-Nabey et al reported that in 153 TLS patients admitted into intensive care, AKI was reported in 82% of the patients.Hematological malignancies or, less commonly, solid tumors may cause a potentially fatal condition known as TLS. It happens due to the tumor cells being massively destroyed at the start of cancer chemotherapy, but it may also occur spontaneously in one-third of cases. Furthermore, the urate-oxidase enzyme levels may indirectly indicate the liability for high tumor cell lysis and chemosensitivity. It was reported that delayed hyperuricemia treatment might have long-term effects. Identifying high-risk TLS patients as soon as possible to prevent TLS and TLS-induced AKI is crucial. The cornerstone of TLS care is hydration and hypouricemic medications . Recombinant urate oxidase (rasburicase) degrades uric acid to ten times soluble metabolites. Despite rasburicase’s widespread use, Darmon et al reported that TLS occurred in >60% of HR-TLS patients, and half also had AKI. Additionally, only a limited number of patients were included, and most of those studies did not involve intensive care unit admitted patients. Therefore, more data is needed on the overall care and result of TLS among adults, particularly with rasburicase use.A recombinant urate oxidase enzyme (rasburicase) administration is linked to increased remission rates for underlying cancers.The exact incidence of TLS is unknown. Factors such as tumor load, tumors with a high proliferation rate, tumors with increased sensitivity to chemotherapy, and previous renal illness or impairment may all raise the occurrence of TLS. Race and gender are not essential reported factors in the propensity to develop TLS. According to the documented National Inpatient Sample database, non-Hodgkin lymphoma (30%), solid tumors (20%), acute myeloid leukemia (19%), and acute lymphocytic leukemia (13%) are the most frequent malignancies linked to TLS. TLS causes around 21% of the total in-hospital mortality.Severe tumor cell lysis contributes to the pathophysiology of AKI due to significant quantities of calcium, phosphate, and uric acid release. The kidney ordinarily excretes these substances; preexisting renal impairment worsens TLS’s metabolic disturbances. AKI may result from the buildup of uric acid-calcium phosphate crystals in the renal tubules, which may sometimes worsen by concurrent intravascular volume depletion. The kidney is the main organ for uric acid, calcium, potassium, and phosphate clearance. Patients with volume depletion or renal impairment are more likely to develop acute kidney damage in TLS status. The AKI has a complex etiology and is often oliguric in TLS. The primary cause of AKI, however, is uric acid nephropathy. Patients at high or intermediate risk and those with established TLS should undergo comprehensive medical treatment in a hospital and sometimes an intensive care unit. Patients with refractory AKI in TLS mostly need RRT. VOD is regarded as a conditioning-related hazard most often linked to cyclophosphamide, busulfan, and total-body irradiation regimens. Older patients, female gender, advanced malignancy, prior abdominal radiation, amphotericin B, vancomycin, or acyclovir medication are additional factors for developing VOD.Despite initial renal problems in the early post-transplantation stages, hepatorenal syndrome (HRS) is the most prevalent cause of severe AKI after a hematopoietic stem cell transplant (HSCT). Depending on the diagnostic criteria used, the incidence of VOD might vary from 5 to 70% in various publications. Symptom-onset timing helps establish the diagnosis; VOD often manifests during the first 30 days after HSCT. Sodium retention is the primary feature in the early stages of HRS, followed by weight gain, edema, and ascites that follow right upper quadrant pain and jaundice. AKI affects around 50% of VOD patients; however, almost all patients have some degree of renal insufficiency. Although diuresis or analgesia for right upper quadrant pain may be necessary for mild illness, nephrotoxic analgesics are not advisable. In HSCT, the mortality rate for severe VOD is very high.Jaundice, tender liver enlargement, and weight gain are all clinical signs of VOD. Acute hepatic graft-versus-host disease (GVHD), sepsis, drug-induced cholestasis, calcineurin inhibitor toxicity, gall bladder disease, and use of total parenteral nutrition are a few disorders that might resemble VOD, making the differential diagnosis list long and differentiate difficultly. Several factors are implicated in endothelial damage, such as conditioning regimens, cytokines, endogenous microbial products, drugs used during the transplant , and the engraftment process itself. The increased risk of VOD linked to greater plasma levels of cytotoxic medicines such as busulfan and cyclophosphamide demonstrates that conditioning regimens play a significant role in the etiology of VOD. The cytochrome P450 complex metabolizes chemotherapy, creating toxic compounds that are eventually transformed into nontoxic ones by the glutathione enzymatic system and then can be excreted. Decreased detoxifying capacity owing to an immature enzymatic system should, at least in part, explain the greater frequency of VOD in children. Moreover, endothelial cell detachment is possibly connected to nitric oxide deficiency, resulting from postconditioning damage. Blood flow blockage is increased by the growth of perisinusoidal cells and subendothelial fibroblasts in the liver. VOD is currently categorized as a transplant-related endothelial dysfunction due to the significant involvement of endothelial damage in its pathophysiology, along with posttransplant microangiopathy, idiopathic pneumonia, diffuse alveolar hemorrhage, and engraftment syndrome.The pathogenesis of VOD is complex. It is primarily due to injury of the blood vessels’ endothelium, mainly in the liver sinusoids, leading to endothelial cell detachment with downstream embolization and obstruction. Although the typical incidence of VOD is 13.7%, newer therapy regimens have dramatically reduced the disease percentage. Damage to sinusoidal endothelial cells and hepatic cells brought on by cytoreductive regimens causes a hepatic sinusoidal blockage. Hepatic VOD resembles HRS and is marked by jaundice, oliguria, and ascites. In these circumstances, hypervolemia is often resistant to diuretics, and spontaneous recovery is uncommon. AKI negatively impacts survival, with a higher death rate in patients needing RRT in 80% of these patients. Prostaglandin-E, pentoxifylline, and low-dose heparin are used for preventing and treating VOD.Numerous insults may cause the development of HSCT-associated AKI, some of which are unique to this clinical situation and others more widespread, such as sepsis. Hepatic VOD during HSCT, an independent risk factor for AKI, may result from liver damage sustained during the procedure (particularly during the induction phase). which supports the theory that the renal damage in HRS is hemodynamic rather than structural. The coagulation cascade may be a site of intervention in this condition since the endothelial injury has been postulated to play a significant role in the onset of VOD. Defibrotide is a single-stranded polydeoxyribonucleotide. It has been proven for use in renal or pulmonary dysfunction following HSCT. Defibrotide (an antithrombotic and fibrinolytic drug) seems advantageous if started early and may enhance GFR. It has shown promising effects in recent controlled studies after unsatisfactory findings from earlier investigations of antithrombotic and thrombolytic drugs. Defibrotide contains fibrinolytic, antithrombotic, and anti-ischemic characteristics in addition to binding to vascular endothelium. Prospective studies are being conducted to verify its effectiveness in preventing and treating VOC.Although hepatic microangiopathy is the hallmark of VOD histologically, this change is not seen in the kidney histology at autopsy,,103 Whether an allogeneic or autologous transplant is carried out and high-dose or low-intensity chemotherapeutic precondition regimens are used, the incidence of HSCT-associated AKI varies from 15% to 73%. A greater risk of AKI is linked to allogeneic HSCT and myeloablative regimens. RRT was required in only 5% of patients; the number surpassed 30% in high-risk individuals. AKI is linked to a higher mortality rate, occurring before engraftment and early in the post-HSCT course. Since post-HSCT-AKI often affects people with severe immunosuppression and may be accompanied by additional conditions such as GVHD, sepsis, and other serious illnesses, which may be a challenge to treat. The relationship between the incidence of AKI post-HSCT and the ultimate onset of CKD has been documented in the literature. Hingorani reported that CKD might develop between 6 months and ten years following HSCT, with a cumulative incidence of 7% to 48%. AKI, acute and chronic GVHD, older age at HSCT, a decline in baseline GFR, HTN, use of calcineurin inhibitors, and exposure to whole-body irradiation are risk factors for developing CKD following HSCT.HSCT is a critical and potentially curative therapy for cancer patients, particularly those with hematological malignancies. The conditional use of chemotherapy, radiation exposure, sepsis, VOD, TMA, GVHD, or nephrotoxic drugs may cause AKI, making HSCT more challenging. Endothelial edema, destruction, and fibrin thrombi inside capillary loops and arterioles are the hallmarks of the lesion.,64 The conditioning programs for HSCT can potentially result in renal endothelial damage and TMA. Due to direct endothelial cell damage calcineurin inhibitors use, GVHD may exacerbate TMA. Treatment options include stopping or lowering the dosage of calcineurin inhibitors, TPE, and defibrotide. TPE response rates have been found to range between 27% and 80%, including 64% for TPE with cyclosporine cessation. Further evidence is required to support the use of rituximab for TMA post-HSCT.,109Patients with HSCT-associated TMA may ultimately get CKD or AKI. Cytokine-mediated renal inflammation and cyclosporine use can cause AKI. Other causes of AKI in patients with GVHD include viral reactivation , vomiting, and diarrhea, which may be severe, inducing prerenal AKI. Prednisone, antithymocyte globulin, sirolimus, and mycophenolate mofetil are all used in graft versus host disease therapy and supportive measures.Another important risk factor for the development of AKI in HSCT patients is acute GVHD.,106 The tubules, interstitium, vasculature, and glomeruli may all sustain damage from conventional chemotherapeutic drugs, resulting in different types of AKI. Acute tubular injury (ATI), acute interstitial necrosis (AIN), and other glomerular and vascular injuries are the leading causes of anticancer-induced AKI. The pathogenesis of AKI or kidney involvement differs from one drug to another.Generally, 3 chemotherapy medication types are used to treat cancer: traditional, targeted, and immunotherapies.,112,113 Drug-induced endothelial damage with the release of von Willibrand factor and plasminogen activator inhibitor, as well as exposure of the endothelial surface to fibrin and platelets, all aid the damage process inside the renal microvasculature. Even if drug withdrawal is necessary, treatment using various methods has proved unsuccessful. Some case studies have reported Eculizumab and rituximab, and TPE is often ineffective but still can be tried.TMA’s microvascular process complicates gemcitabine, mitomycin C, and cisplatin treatment. In most of these situations, severe proteinuria is linked to the gradual emergence of renal failure over an extended period. ATI is the most frequent lesion associated with AKI with conventional chemotherapy, and many medications may produce ATI.,117 Ifosfamide, pemetrexed, zoledronate, and others damage the tubular epithelium cells by direct intoxication, inducing apoptosis, causing oxidative stress, and mitochondria injury.Pamidronate and zoledronate have been used less often to treat glomerular damage, especially podocyte injury with the histological subtypes of focal segmental glomerulosclerosis or minimal change disease.,117 AKI is facilitated by intratubular crystal precipitation in conjunction with obstructive and inflammatory interstitial damage. While urinary alkalinization and intravenous fluids are used for prophylaxis and therapy, severe toxicity may need hemodialysis and glucarbidase. Methotrexate clearance is primarily by the kidneys. Toxic amounts of methotrexate may build up in the presence of AKI, resulting in severe bone marrow toxicity. Therefore, AKI brought on by methotrexate is a medical emergency. Physicians should actively evaluate GFR in such cases and consider using hemodialysis or glucarbidase early on if methotrexate levels increase. Lastly, chemotherapy drugs, such as carboplatin, ifosfamide, and adriamycin, may result in AKI from interstitial nephritis.Crystalline-induced AKI has been linked to methotrexate. The oncogenesis signaling cascades promote tumor development by explicitly targeting the gene mutations that characterize individual tumors. Unfortunately, medications that block this cascade are associated with AKI, proteinuria, and HTN, despite their effectiveness in treating cancer. This often occurs because the mechanisms involved in angiogenesis may serve similar changes in the kidney. Anti-angiogenesis medications that target vascular endothelial growth factors, such as bevacizumab, axitinitib, sorafenib, and sunitinib, predominantly induce AKI. At the same time, focal segmental glomerulosclerosis and AIN have also been seen with severe HTN. Vemurafenib and dabrafenib, serine/threonine kinase BRAF  inhibitors, have been associated with dose-related AKI. Although there is little histological information available, it is likely that the suppression of the mitogen-activated protein kinase pathway causes acute tubular necrosis damage. Most of the time, stopping a drug is linked to the reversal of AKI. Anaplastic lymphoma kinase inhibitor crizotinib, which induces AKI via tubulointerstitial damage, is only partly curable by stopping the treatment. Since this is a developing field, doctors should be aware of medication toxicity in patients with unexplained AKI and consider doing a kidney biopsy to guide them for further actions. This is a growing research field, and other studies are required.The Ras-Raf-MEK-ERK signal transduction cascade is perhaps the most significant pathway in human cancer. Although the cytokines IL-6 and -13 may also be involved, natural interferon binding to podocyte receptors and modification of normal cellular proliferation may enhance podocyte damage. High-grade proteinuria from focal segmental glomerulosclerosis or minimal change nephropathy is a common clinical symptom of interferon-associated AKI. Drug stoppage (with or without steroids) may reverse AKI and proteinuria with little-to-no change in the illness progression, but it works less well in segmental glomerulosclerosis.The well-known causes of AKI include older drugs like interferon and high-dose interleukin (IL)-2. As a result, the T-cell destruction of tumor cells is activated and increased. Unfortunately, AIN and a range of glomerular lesions are caused by a loss of tolerance to drugs that tend to trigger an immune response. In general, drug withdrawal combined with steroids helps to correct AKI, particularly if this action is initiated early, although a significant proportion of patients develop CKD. However, it is crucial to understand that AKI, in the presence of immune checkpoint inhibitors, may be linked to tubular or glomerular damage, necessitating a kidney biopsy to confirm it. Host cells are extracted and modified to express receptors that identify and bind tumor antigens to create chimeric antigen receptor T-cells. Cancer cells are specifically targeted and eliminated by T lymphocytes. However, this approach encourages cytokine release syndrome and macrophage activation, which may cause a capillary leak and prerenal AKI. To lessen the tumor load, steroids and prior chemotherapy are used to prevent and treat AKI. An IL-6 receptor blocker and steroid may diminish side effects due to severe cytokine release syndrome.Ipilimumab, nivolumab, and pembrolizumab are immune checkpoint inhibitors that improve tumor killing by inhibiting dendritic cells and tumor antigen ligands from attaching to CTLA-4 and PD-1 receptors, respectively. Over 99% of uric acid is ionized at physiological pH. However, the uric acid may crystallize at the tubular level in the presence of an acidic pH and a high concentration, causing the blockage and leading to acute obstructive uropathy. Clinical symptoms include hematuria, flank discomfort, HTN, hyperazotemia, acidosis, edema, oliguria, anuria, lethargy, and sleepiness. In the absence of conclusive evidence, in patients with hyperuricemia (uric acid > 8 mg/dL), elevated lactate dehydrogenase , despite adequate volume resuscitation without evidence of post-obstructive cause, acute oliguric or anuric kidney failure should be sought as potential reasons.Hyperuricemia usually develops due to the fast degradation of intracellular nucleic acids released after the lysis of cancer cells during 48 to 72 hours following starting anticancer therapy.All hematological cancer patients receiving chemotherapy are advised to receive TLS prophylaxis. Additionally, prophylaxis is recommended for all high- and moderate-risk patients, including those with significant tumor loads, decreased GFR, and extremely chemosensitive malignancies. The precise prophylaxis plan should be customized to the patient’s clinical situation. It should include lowering uric acid levels, maintaining appropriate hydration and tubular urine flow rate, and managing abnormal electrolyte levels, especially hypercalcemia. Hydration improves renal blood flow, maintains GFR, and lowers extracellular uric acid concentrations to prevent urate nephropathy. Intravenous fluid administration (≥3 L/d) and xanthine oxidase inhibitors in high-risk patients before chemotherapy are two methods for preventing and treating renal damage due to hyperuricemia, especially in TLS.Allopurinol, an isomer of hypoxanthine, prevents the production of uric acid by blocking the enzyme xanthine oxidase. Allopurinol will raise plasma levels of the uric acid precursors hypoxanthine and xanthine. These metabolites in alkaline urine may crystallize and deposit in the kidneys and cause xanthine nephropathy. Fever, rash, eosinophilia, systemic hypersensitivity responses, Stevens-Johnson syndrome, hepatitis, AIN, and bone marrow suppression are known side effects of allopurinol. Allopurinol should be started 2 to 3 days before the definitive treatment and continued for 10 to 14 days. It is crucial to understand that xanthine oxidase inhibitors can only prevent new uric acid elevations because they cannot reduce the existing high uric acid level. A non-purine analog xanthine oxidase inhibitor called febuxostat is helpful for people who cannot take allopurinol. In a recent study, febuxostat was shown to be better than allopurinol in decreasing uric acid levels. However, the clinical outcome was similar. Since the discovery of rasburicase, hemodialysis for treating TLS is probably no longer necessary. Hemodialysis is still a successful treatment option for electrolyte and acid-base problems, mainly when oliguric AKI is present. Continuous renal replacement treatments prevent “rebound” metabolic abnormalities, although higher clearance values (at least 30–40 mL/kg/h) should be sought if a continuous renal replacement is used.Recombinant urate oxidase (rasburicase) may treat hyperuricemia in individuals with both underlying renal impairment, AKI or CKD, and hyperuricemia at diagnosis. Rasburicase catalyzes the conversion of soluble allantoin that is quickly eliminated by the kidney. The medication causes a drop-in blood uric acid levels due to its rapid onset of action (within 4 hours). In leukemia, lymphoma, and solid tumor malignancies undergoing anticancer therapy likely to cause tumor lysis and rise of plasma uric acid, rasburicase is suggested as a single agent for high uric acid treatment with hydration. Rasburicase is not advised for use in individuals with glucose-6-phosphate dehydrogenase deficiency because it produces toxic hydrogen peroxide while converting uric acid to allantoin. Since 1975, a nonrecombinant urate oxidase formulation has been used in Europe; however, there has been a 5% rate of allergic responses.,134 Rasburicase, a recombinant uricase preparation, has been approved by the Food and Drug Administration to treat pediatric patients at risk for TLS. The recombinant rasburicase has fewer allergic responses and is both efficient and well-tolerated. In patients at risk for tumor lysis, Goldman et al demonstrated a decreased area under the curve for uric acid over 96 hours with 128 ± 70 mg/dL in the Rasburicase group versus 329 ± 129 mg/dL in the allopurinol group (P = .001). Hemodialysis for the AKI was required for 1 patient in the allopurinol group but for none in the rasburicase group. Other research reported that 3-day rasburicase therapy reduced plasma uric acid levels in 49 hyperuricemia adult patients from a median of 11.9 to 0.7 mg/dL. One hundred adult patients with aggressive non-Hodgkin lymphoma who received a preventive regimen of 0.2 mg/kg intravenous Rasburicase starting the day before chemotherapy and intravenous hydration were studied. Within 4 hours, the serum uric acid levels for all the patients were controlled, and throughout the observation period, none of the patients had hyperuricemia, and none of them required hemodialysis or had a rise in serum creatinine. It has been reported that urate oxidase is filtered through the glomeruli and may degrade the precipitated uric acid crystals and alleviate the intratubular blockage. Further research is required to understand Rasburicase’s function in treating already occurred uric acid nephropathy.The enzyme uricase or urate oxidase, which catalyzes the conversion of uric acid to the more water-soluble allantoin, is a novel strategy for preventing and treating uric acid nephropathy.2/dL, leading to metastatic calcifications. Particularly at the renal level, it is possible to detect clinical disorders ranging from acute obstructive uropathy to nephron calcinosis and lithiasis using a computed tomography scan. A prevalent cause of hypercalcemia related-AKI occurs in 20% to 30% of all malignancies, including commonly MM and squamous cell carcinomas.Hyperphosphatemia and hypercalcemia cause calcium-phosphate crystals to precipitate into the renal tubule. The danger of calcium phosphate deposition in the kidney and other organs increases when the calcium-phosphorus product is >70 mg Additionally, volume loss may happen due to various processes affecting renal function. A prime mechanism is a deficiency in urine concentrating capacity, which results in polyuria and polydipsia. The downregulation of aquaporin 2 (AQP2) water channels in the collecting tubules and tubulointerstitial damage brought on by calcium buildup in the medulla are suggested to be the causes. Research has revealed a substantial decrease in AQP2 expression in the collecting ducts of hypercalcemic rats as compared to controls confirmed the dysregulation of AQP2; however, the molecular mechanism is unclear. Additionally, calcium reabsorption is decreased by activating the calcium-detecting receptors found on the basolateral membrane of the thick ascending limb of the Henle loop. The sodium-potassium-chloride cotransporter in the luminal membrane of the thick ascending limb of the loop of Henle is inhibited due to calcium-sensing receptor activation, which decreases sodium chloride reabsorption and increases urine calcium excretion. Additionally, it is believed that the production of prostaglandin E2 by hypercalcemia decreases sodium chloride reabsorption in the loop of Henle. AKI brought on by hypercalcemia is often curable by reducing blood calcium levels and volume expansion with a saline solution. Rarely, severe hypercalcemia may lead to AKI by intratubular calcium-phosphate deposition, mainly if the calcium-phosphate concentration product is ≥70 mg2/dL. It should be noted that nephrocalcinosis-associated AKI may not get better with therapy for hypercalcemia; instead, patients may end up with substantial CKD, depending on how long the hypercalcemia has lasted. This emphasizes the need for a rapid decrease in serum calcium levels to prevent CKD.Direct renal vasoconstriction is thought to mediate the reversible reduction of GFR in severe hypercalcemia. This was shown in research comparing the GFR and renal blood flow in rats with hypercalcemia with rats with normocalcemia. Low-dose pamidronate  infused over 4 hours effectively decreases serum calcium over several days and has a longer-lasting effect of preventing recurrent hypercalcemia in addition to aggressive intravenous fluids with normal saline, even without diuretics, unless hypervolemia is present. In rare cases, severe hypercalcemia in AKI may need dialysis. RANKL stands for receptor activator of nuclear factor kappa-beta ligand. It is also known as osteoprotegerin ligand, osteoclast differentiation factor, or tumor-necrosis-factor-related activation-induced cytokine. The primary function of RANK is to preserve bone physiologic remodeling. Denosumab, a humanized monoclonal antibody against RANK ligand, does not need dosage adjustment for GFR and can effectively reduce high serum calcium.Hypotension, dry mucous membranes, flat neck veins, weakness, disorientation, nausea, and polyuria are symptoms of hypercalcemia. Intravascular volume resuscitation, improving GFR, increasing calcium excretion, and hypercalcemia-lowering agents are all needed to reduce the risk of AKI due to hypercalcemia. Reported data showed that cancer cells might have up to 4 times more organic and inorganic phosphorus than nonmalignant cells. Additionally, acute renal insufficiency may significantly exacerbate this imbalance, especially when it is linked to uric acid precipitation or other side effects chemotherapy brings.Hyperphosphatemia might happen within 24 to 48 hours following the initiation of chemotherapy. Nausea, vomiting, diarrhea, lethargy, and seizures are usual presenting symptoms. AKI, CKD, acidosis, or excessive iatrogenic potassium administration during the induction phase of chemotherapy are a few concomitant conditions that may exacerbate this hyperkalemia.Cardiac arrhythmias are a dangerous complication of high serum potassium levels. Cellular lysis causes a significant release of potassium into the extracellular space. It might happen 6 to 72 hours after the start of chemotherapy.,20 However, depending on the severity of AKI and underlying comorbidities, investigations in higher-risk, critically sick populations have shown that 8% to 60% of patients needed RRT. Within a year after AKI, 5% of patients in a large Danish cohort with cancer and AKI needed RRT. Early detection and good hydration are crucial methods to prevent AKI in cancer.AKI is a frequent complication in cancer patients linked to decreased treatment dosage intensity, worse remission rates, higher mortality, hospitalization duration, and higher healthcare cost. The patients with AKI and cancer have in-hospital mortality of 12%, whereas this figure is only 0.9% for the AKI patients without cancer. In two other recent studies, AKI was reported in 11% and 20% of cancer patients over a year of follow-up, with hematological cancer patients at greater risk. The overall prevalence of CKD in allogeneic HSCT survivors constitutes a future public health issue due to the increased number of allogeneic transplants. A low-grade renal TMA is assumed to be the primary cause of most CKD patients after HSCT. These patients usually have persistently increased plasma creatinine, HTN, and anemia. Proteinuria and hematuria are recognized features. There are no characteristic renal imaging features; however, a kidney ultrasound is usually advisable. Kidney biopsy results are unlikely to alter the prognosis of CKD significantly, and the biopsy carries increased bleeding risks in patients with thrombocytopenia and coagulopathy. Renal histological findings include mesangial layer damage, basement membrane duplication, glomerular endothelial cell enlargement, and tubular damage with interstitial fibrosis. Various glomerular diseases following HSCT have been reported but are relatively uncommon. Kidney biopsy may be indicated and needed in some cancer cases, although there is much doubt about the benefit of the result. This topic needs further studies to assess the role of kidney biopsy benefits in malignancy-associated CKD.CKD is a significant long-term side effect of HSCT, especially allogeneic HSCT (which develops in 15–20% of survivors). Renal shielding during whole-body irradiation is moderately protective. Radiotherapy dose and concomitant cytotoxic treatment are considered significant in kidney damage. It has been thought that sirolimus may be linked to a greater incidence of TMA when combined with calcineurin inhibitor medication; however, this is often reversible. An angiotensin convertase enzyme genotype in HSCT-associated renal failure genes may affect renal damage; however, the findings were only marginally significant. Further studies to analyze the patient’s pre- and post-HSCT history carefully the underlying causes and prevention methods of CKD. It is crucial to analyze the patient’s pre- and post-HSCT history carefully. The following should be considered: kind of HSCT, type of conditioning treatment plan , and level of nephrotoxin exposure .The onset of renal failure often occurs several months after HSCT, which is characteristic of radiation-induced kidney injury. Compared to mucosal cells, kidney cells have a far slower rate of turnover, which causes radiation damage to manifest much later. Angiotensin-converting enzyme inhibitor or angiotensin receptor blockers, a low-potassium diet, diuretics, and low-dose sodium polystyrene, may be used. A small percentage of people may develop ESRD, and generally, these patients may do worse on hemodialysis than those with ESRD due to other causes. However, later reports showed successful kidney transplantation after bone marrow transplantation. Suitability for a kidney transplant must be determined case-by-case basis; it is important to note this because of the allograft’s immunologic tolerance. It is well-documented in nonrenal solid organ transplantation and autoimmune illness that prolonged use of these calcineurin inhibitors after HSCT most certainly causes CKD. Fortunately, most HSCT recipients stop taking calcineurin inhibitors after 4-12 months. In many HSCT patients, the impact of this medication class on CKD is likely to be minimal.For CKD patients, general therapy, including HTN management, should follow the recommendations. Patients with various kinds of CKD may frequently have anemia and hyperkalemia, necessitating more intensive treatment. Low platelet and neutropenia increase the risk of bleeding and infection, challenging vascular access. Hydration is the key to preventing and treating AKI in malignancy-induced nephropathy. Prevention of TLS, high serum uric acid, phosphate, and calcium is essential to diminish the risk of AKI. Early diagnosis of malignant diseases that directly affect the kidneys is necessary; however, the best method is a renal biopsy, but unfortunately is not usually possible due to bleeding risks or insufficient resources. Physicians should be aware of contrast-induced, direct radio, and chemotherapy-induced nephropathy. Adjusted doses of radiation and chemotherapy are essential to prevent CKD progression and AKI on top of CKD. Dialysis modalities are sometimes indicated. PET has been advocated in some cases of TMA, although there is conflicting data about its effectiveness.A cancer patient with AKI should be assessed as any other patient with a hospital-acquired AKI. Further exposure to nephrotoxic medications should be avoided wherever possible. In the case of severe AKI after HSCT, no randomized controlled studies have compared continuous treatments with intermittent hemodialysis. Whatever the treatment method, it should be recognized that patients who have significant liver and renal failure have exceedingly poor prognoses. Continuous therapies have at least 2 potential benefits; there is some evidence that they are associated with increased intrarenal pressure in cardiac transplanted patients.AKI occurs uncommonly in cancer patients due to cancer or therapy. There are significant improvements in treating cancer patients, which have been shown to extend their lifespan. Rapid detection of kidney injury and proper management is essential to maintain the improvements in outcomes linked to chemotherapy and cancers.AKI in cancer has multiple causes. Clinicians should be aware of all the potential causes of AKI, and when in doubt and the cause cannot be established, a kidney biopsy should be considered if there are no contraindications.CKD is a known complication in cancer patients due to different causes, including medications; therefore, avoiding nephrotoxic agents and standardizing the doses of drugs is essential to minimize the risk of CKD.Finally, given that AKI has the potential to impair outcomes considerably and invariably restrict the range of cancer medications’ accessibility, all attention should be paid to preventing AKI in the first place whenever feasible, as holding or avoiding anticancer therapy affects patient improvement and survival.We thank the Qatar National Library and Internal Medicine Residency Program of Hamad Medical Corporation for their scientific support.Conceptualization: Elmukhtar Habas, Raza Akbar, Amnna Rayani.Methodology: Elmukhtar Habas, Kalifa Farfar, Nada Arrayes.Project administration: Elmukhtar Habas, Aisha Aladab.Software: Hafidh Ghazouani.Supervision: Elmukhtar Habas, Amnna Rayani.Validation: Elmukhtar Habas.Visualization: Aml Habas, Gamal Alfitori, Eshrak Habas, Yaqeen Magassabi.Writing – original draft: Elmukhtar Habas, Raza Akbar, Kalifa Farfar, Nada Arrayes, Aml Habas, Amnna Rayani, Gamal Alfitori, Eshrak Habas, Hafidh Ghazouani, Aisha Aladab.Writing – review & editing: Elmukhtar Habas, Raza Akbar, Amnna Rayani, Abdel-Naser Elzouki.


Serum concentrations of adropin and afamin were determined using ELISA. Clinical variables  were correlated to adropin and afamin concentrations. Results: Afamin concentration was found to be higher in group IV, followed by groups III and II when compared to the control group, i.e.,  mg/L (p < 0.001), and adropin concentration was found to be lower in group IV as compared to groups III, II, and I (200.342 ± 8.37 vs. 284.682 ± 9.89 vs. 413.208 ± 12.32 vs. 706.542 ± 11.32) pg/mL (p < 0.001), respectively. Pearson correlation analysis showed that afamin was positively correlated with traditional cardiovascular risk biomarkers, while adropin showed a negative correlation. Conclusions: Adropin and afamin may potentially serve as futuristic predictors for the deterioration of renal function and may be involved in the pathological mechanisms of CKD and its associated complications such as CKD-MBD and high lipid levels.Aim: The study aims to test the hypothesis that concentrations of adropin and afamin differ between patients in various stages of chronic kidney disease when compared with healthy controls. The study also investigates the association of the biomarkers (adropin and afamin) with CKD-MBD and traditional cardiovascular risk parameters in CKD patients. Methodology: The cross-sectional study includes the subjects divided into four groups comprising the control group , CKD stages 1–2 patients ( Cardiovascular risk and its related complications are higher in patients with chronic kidney disease (CKD), which further causes mortality in CKD patients. The American Heart Association and National Kidney Foundation identify chronic kidney illness as a risk equivalent to coronary heart disease, an independent risk factor for cardiovascular disease . PatientAs cardiovascular complication is one of the predisposing factors for mortality in CKD, it is of utmost importance to evaluate the cardiac health in CKD at the earliest stages. Although traditional biomarkers of cardiac health, such as lipid profile, are the important predictors of progression to cardiac dysfunction, these estimations are not enough for the early prediction and monitoring of the disease development ,9. MoreoIt has also been hypothesized in the literature that adropin expressions in plasma regulate the endothelial function and the function of nitric oxide synthase. Impaired endothelial dysfunction contributes to the development of cardiovascular dysfunction ,13. AdroOn the contrary, afamin is the human plasma Vitamin E-binding glycoprotein of the albumin gene family primarily expressed in the liver, brain, kidneys, testes, and ovaries. There is not much information on the physiological roles of afamin. Lines of evidence state that afamin could have a role in neuroprotection, fertility, Vitamin E bioavailability, and bone metabolism. Afamin is strongly associated with the development of metabolic syndrome in animal studies (transgenic mice). Elevated levels of afamin in mice are positively correlated with the increase in body weight, total cholesterol, TG, and glucose levels that induce the state of hyperlipidemia . MoreoveMoreover, compared with healthy controls, adropin and afamin have not been studied together in CKD patients. The current study aimed to test the hypothesis of whether expressions of adropin and afamin change between patients in various stages of CKD with change in the renal parameters and CKD-MBD parameters to assess the renal function and cardiovascular health.n = 50). For comparison, 50 healthy individuals as a control group were included. The study protocol was approved by the Institutional Human Ethical Committee (IHEC) of Chitkara University, Punjab, and the study was conducted according to the principles of the Declaration of Helsinki and the Code of Good Clinical Practice (GCP).In this cross-sectional study, 150 CKD patients and 50 healthy subjects were recruited according to the inclusion/exclusion criteria, and written informed consent was obtained from all the study participants. CKD patients of either stage (1–5) were screened per the National Kidney Foundation CKD classification criteria by the physician based on the Glomerular filtration rate (GFR). Patients were included in the study from the tertiary care hospital in North India. Patients were excluded from the study if they had any history of stroke, malignancy, congenital heart disease, diabetes mellitus, or patients receiving estrogen or steroidal therapy. CKD patients (20–50 years) were then divided into four groups, Group II (CKD stage 1–2 patients), Group III (CKD stage 3–4 patients), and Group IV , consisting of 50 patients in each group , determination of systolic blood pressure (SBP), diastolic blood pressure (DBP), and the assessment of serum renal biomarkers (urea and creatinine), CKD-MBD biomarkers , lipid biomarkers  of the recruited subjects were conducted during their routine clinical visits. Serum concentrations of adropin and afamin were analyzed using an enzyme-linked immunosorbent assay  according to the manufacturer’s protocol. Blood samples for the adropin and afamin estimation were taken on the same day when other clinical variables were measured. p ≤ 0.05 was considered as statistically significant. To find the association of serum levels of adropin and afamin with the CKD variables, CKD-MBD variables , and cardiovascular risk biomarkers , Pearson correlation analysis was carried out as the data passed the normality test conducted with the Shapiro–Wilk test. In addition, the relationship between serum adropin, afamin, and all other biochemical variables was determined using multilinear regression analysis.One-way analysis of variance (ANOVA) was used to compare the significant changes between all the groups in terms of clinical variables and biochemical parameters, followed by the Tukey’s post hoc test. All the data were expressed as Mean ± Standard Error Mean (SEM). The results were analyzed using Graph Pad Prism version 9. The current study was designed and aimed to assess the serum detection of the proteins (adropin and afamin) and MBD biomarkers  in the study, including the CKD patients with CKD stages 1–2, CKD stages 3–4, and CKD stage 5. Traditional risk biomarkers  were also investigated in the study population. The demographic and biochemical profile of the included population is shown in The association of serum adropin with various clinical variables, including renal parameters, lipid parameters, CKD-MBD parameters , and protein—namely afamin—were carried out using the Pearson correlation analysis in group IV, group III, and in group II as presented in Similarly, the association of serum afamin with various clinical variables in CKD patients was also carried out using the Pearson correlation analysis as results are shown in p = 0.04, 0.0002, and 0.02) were significantly correlated with afamin depicting the role of afamin in renal dysfunctioning. Adropin and calcium were also significantly correlated with afamin in group IV patients followed by Vitamin D in group II, LDL in group III, and total cholesterol in group II patients. Similarly, in multiple linear regression analysis presented in p = 0.0005 and 0.0001) were significantly correlated with adropin, followed by afamin in group IV; calcium in groups II, III, and IV; LDL and TG in group IV; and Vitamin D in groups II and III.Furthermore, multiple linear regression analysis presented in CKD-MBD results from mineral and metabolic abnormalities and is the major pathophysiological link for cardiovascular disease in CKD and ESRD patients ,18,19,20Vitamin D is an important parameter that should also be monitored to check the calcium levels in the blood, as Vitamin D deficiency is associated with mineral and bone disorders leading to vascular calcification in CKD patients. Vitamin D has a protective effect on vascular calcification in CKD via various mechanisms such as reduction in cholesterol and foam cell inhibition and cholesterol efflux in the macrophages and modulating vascular regeneration, modulation of the calciprotein particles, and matrix vesicles . Our stuAdropin and afamin, the newly discovered peptides, correlate with inflammation and its associated conditions, such as hyperlipidemia and metabolic syndrome ,26,27.In the present study, patients undergoing hemodialysis in group IV had significantly lower levels of serum adropin, followed by group III (CKD 3 and 4) and group II (CKD 1 and 2) patients as compared to group I . In the present study, the normal concentration of adropin was found to be (706.542 ± 11.32) pg/mL in the healthy group, which was found to be lower than the findings in CKD patients such as 413.208 ± 12.32 in CKD stage 1 and 2 patients, 284.682 ± 9.89 in CKD stage 3 and 4 patients, and 200.342 ± 8.37 in CKD stage 5 patients. Lower levels of adropin were also supported by the previous findings in metabolic syndrome patients [In the current study, lower levels of serum adropin were inversely correlated with cardiovascular health biomarkers such as total cholesterol, TG, LDL, SBP, DBP, phosphorous, and calcium. At the same time, no correlation was observed with HDL in group IV. The positive association of adropin with Vitamin D was statistically significant. In group III and group II, all the parameters were negatively correlated, and Vitamin D was positively correlated, which was in line with previous findings of K. Ganesh et al., which stated that increased adiposity and hyperlipidemia are found to be correlated with decreased levels of adropin in adropin knockout mice . AdditioA research study suggested a relationship between decreased adropin concentrations and increased obesity ,30. SeruIn the current study, serum afamin concentrations were increased in ESRD patients, followed by CKD III and IV as well as CKD I and II patients compared to the control group. The serum levels of afamin were lower in the healthy group compared to CKD patients. The strongest positive and significant association of adropin and negative association of afamin with renal parameters in the current study suggest that adropin and afamin may possibly play a role in the CKD/ESRD pathophysiology. Additionally, increased serum afamin levels positively correlated with LDL, cholesterol, TG, creatinine, urea, blood pressure, and calcium phosphorous and negatively correlated with Vitamin D in group IV. However, the correlation of afamin with phosphorous in group III and association with blood pressure and calcium in group II showed a weak association with non-significant results. These results are in line with the previous findings in metabolic syndrome patients. In the study, increased afamin levels were linked with metabolic syndrome markers such as high blood glucose, dyslipidemia, obesity, high blood pressure, type 2 diabetes mellitus, and pre-eclampsia ,33. A stIn addition, various preclinical and clinical studies supported the protective role of adropin in cardiovascular risk. Adropin regulates metabolic homeostasis in cardiac cells through GPR19-MAPK-PDK4 pathway ,35. A stCKD patients with mineral bone abnormalities seek more attention in managing mineral metabolism and traditional risk factors to prevent harmful effects on the vascular part and to diagnose renal health with the effective use of novel biomarkers.The current study also has some limitations. The study does not include the ESRD patients on peritoneal dialysis compared to the hemodialysis patients. Moreover, the lack of vascular calcification assessment via Doppler ultrasound is also the limiting factor, as vascular calcification is the major pathological link leading to cardiovascular events in CKD. Vascular calcification can predict cardiovascular health in CKD patients. More studies on different disease populations need to be conducted to understand the mechanisms or pathways by which adropin maintains cardiac cell homeostasis. The nutritional status of the patients and use of several medications by CKD patients that might lead to any side effects or interactions have not been taken into account and could affect our results. Therefore, to identify a causal relationship between these biomarkers, genetic and multicenter studies on large cohort of patients are necessary to further specify and validate the findings of the current study and to confirm the prediction accuracy of adropin and afamin in the CKD population, along with other clinical factors and diagnostic techniques. There is a pressing need to further establish the physiological and pathological connection of adropin and afamin with renal and cardiovascular health in CKD population.The findings from the present study suggest that a decrease in adropin and rise in afamin may potentially serve as futuristic predictors for the deterioration of renal function and may be involved in the pathological mechanisms of CKD and its associated complications such as CKD-MBD and high lipid levels. High lipid levels, blood pressure, and CKD-MBD biomarkers such as phosphorous, calcium, and Vitamin D could play an important role in predicting cardiovascular health in CKD. So, measuring the afamin and adropin concentrations along with CKD-MBD parameters may play an important role in the management of renal and cardiovascular health. Adropin and afamin may have a significant independent potential role as novel biomarkers to predict the futuristic development of renal dysfunction and cardiovascular complications, which may further have the potential to act as a therapeutic target in future. However, further genetic and multicenter studies on large sample sizes are necessary to specify further and validate the current study’s findings.Adropin and afamin mediate metabolic homeostasis in various tissues and cells, including brain tissue, cardiomyocytes, vascular endothelial cells, fibroblasts, etc. According to several studies, adropin regulates various physiological processes such as energy metabolism, insulin sensitivity, and cardiovascular function. The molecular, biochemical, and structural aspects of adropin and afamin biology, physiology, mechanism of action still need to be investigated. More research is required to understand the signaling processes by which adropin and afamin function, particularly in various disease populations. Identifying these mechanisms in the vasculature and their subsequent signaling processes will make it easier to use adropin and afamin biology therapeutically to treat cardiometabolic and renal illnesses. Moreover, clinical research (diagnostic tools/biomarkers and therapeutic target) is continuously evolving. Therefore, the current study provides the future perspective of adropin and afamin potential to assess renal dysfunction.


Intensive care medicine is complex and resource-demanding. A critical and common challenge lies in inferring the underlying physiological state of a patient from partially observed data. Specifically for the cardiovascular system, clinicians use observables such as heart rate, arterial and venous blood pressures, as well as findings from the physical examination and ancillary tests to formulate a mental model and estimate hidden variables such as cardiac output, vascular resistance, filling pressures and volumes, and autonomic tone. Then, they use this mental model to derive the causes for instability and choose appropriate interventions. Not only this is a very hard problem due to the nature of the signals, but it also requires expertise and a clinician’s ongoing presence at the bedside. Clinical decision support tools based on mechanistic dynamical models offer an appealing solution due to their inherent explainability, corollaries to the clinical mental process, and predictive power. With a translational motivation in mind, we developed iCVS: a simple, with high explanatory power, dynamical mechanistic model to infer hidden cardiovascular states. Full model estimation requires no prior assumptions on physiological parameters except age and weight, and the only inputs are arterial and venous pressure waveforms. iCVS also considers autonomic and non-autonomic modulations. To gain more information without increasing model complexity, both slow and fast timescales of the blood pressure traces are exploited, while the main inference and dynamic evolution are at the longer, clinically relevant, timescale of minutes. iCVS is designed to allow bedside deployment at pediatric and adult intensive care units and for retrospective investigation of cardiovascular mechanisms underlying instability. In this paper, we describe iCVS and inference system in detail, and using a dataset of critically-ill children, we provide initial indications to its ability to identify bleeding, distributive states, and cardiac dysfunction, in isolation and in combination. A common challenge clinicians face across different disciplines is estimating the hidden physiological state of a patient based on partially observed data. Here we describe iCVS (inferring Cardio-Vascular States): a dynamical mechanistic model of the cardiovascular system. We developed iCVS with a translational goal in mind, showing high explanatory power, its inference relies only on routinely available signals, and enables the identification of various clinically important shock states. We demonstrate the use of the model on a dataset that was collected in a pediatric intensive care unit. Intensive care medicine is complex, resource demanding and expensive. High-stakes decisions need to be made rapidly based on the evolving clinical state of the patient and the interpretation by clinicians of continuous physiological and ancillary data. The patient’s cardiovascular state may fluctuate over minutes with rapid transitions due to external perturbations, internal failures of the physiological sub-components, or their control. Moreover, these patients are very diverse in their physiological and disease processes. Inferring the underlying hidden physiological state of a patient from observed data is a critical problem that is encountered by clinicians across different disciplines daily. While the modality of the available data and the frequency of sampling may vary between different clinical scenarios, in almost all cases clinicians must rely on partial observations that are a peripheral reflection of the internal, hidden states that are of importance. Specifically, clinicians use observable measurements of heart rate, arterial and venous blood pressures as well as findings from the physical examination  to estimate internal variables that are not readily observable at the bedside such as cardiac output, systemic vascular resistance, filling pressures and volumes, autonomic tone, and more. As the physiological signals are often noisy and ambiguous, creating these mental models is a notoriously hard task that requires clinical expertise. Moreover, since the patient’s state fluctuates frequently, repeat assessments by clinicians are required. The clinicians then use this mental model of the patient’s cardiovascular internal state to derive the causes of instability such as shock type , and choose appropriate treatments and interventions.The large amount of data available from ICUs motivated researchers from computational disciplines to develop mathematical tools which aim to support decision-making in this area. An appealing approach to the analysis of continuous physiological times series relies on mechanistic modeling, grounded in a biophysical understanding of systems. Mechanistic modeling of the cardiovascular system often requires an understanding of the cardiac cycle as a pump coupled to the arterial and venous conductance systems with associated autonomic nervous control. This understanding is derived from years of experiments analyzing human and animal cardiovascular physiology. Such models are usually based on sets of ordinary differential equations (ODEs). In a sense, they simulate the thought process of the critical-care physician at the bedside trying to estimate the underlying pathophysiology of the patient to tailor care. However, due to the complexity of even the simplest models and the number of unobserved variables and unknown parameters, such mechanistic models were mostly published in the context of well-curated “toy” datasets and in-silico simulations physiology of critical illness. We derive a simple model (iCVS), which retains a high explanatory power of the cardio-vascular system including cardio-vascular control, which can capture different clinical scenarios such as bleeding or evolving hypovolemia, cardiogenic shock and distributive shock, in isolation or in combinations. iCVS takes into account the autonomic control of the cardiovascular system, which couples the dynamics of its different components, mathematically imposing coupling constraints on inferred parameters. This reduces the effective dimensionality of the parameter space over which we look for a solution to an inverse problem, allowing us to infer a larger set of unobserved parameters compared to previous models. The estimated parameters enable us to capture individual patients’ traits.iCVS is designed to allow deployment at the bedside in the pediatric and adult intensive care unit: no prior assumptions regarding the physiological parameters of the patients are required except age and weight, and the only inputs which are required for the estimation process are arterial and venous blood pressures waveforms, which are commonly measured in the ICU. In order to gain more information about the cardiovascular state, without increasing model complexity, we introduce a novel approach that exploits both slow and fast timescales of the blood pressure trace. From the pulse contour shape of the blood pressure waveform, we extract quantities related to the peripheral resistance, stroke volume, and pulse pressure, while the main mathematical model and its inference run using the mean, smoothed, arterial and venous pressures at the longer, clinically-relevant, time scale of minutes. Thus, the main model and its inference focus on processes that evolve over minutes, and are of interest to clinicians, and further allow for a much simpler model than those that capture all the intricacies of each cardiac cycle . All thiIn what follows, we describe the iCVS model and inference system in detail and demonstrate its use and power for real-time estimation using a dataset of 10 patients admitted to a pediatric intensive care unit. While our estimation process entails inferring the full iCVS model including 15 hidden parameters, we focus our demonstration on the identification of three clinical shock states, representing a dire, hard clinical challenge, and a testable task. Shock, due to any cause is a state in which the cardiovascular system fails to deliver an adequate supply of oxygen to the tissues. There are several prototypical physiological shock states, each requiring specific interventions, without which there is a high risk for mortality or morbidity. Identifying shock and its causes is a notoriously hard task due to the nature of the observed physiological signals (demonstrated below), requiring continuous vigilance and clinical expertise. Specifically, using iCVS, we map certain hidden parameter ranges to identify (i) ongoing bleeding, (ii) distributive shock, and (iii) cardiogenic shock due to reduced cardiac contractility.The goal of this work is to derive a new model of the cardiovascular system which can be deployed at the patient’s bedside, requires only routinely acquired measurements as input, and provides an inference of the hidden, internal physiological state of the patient in real-time. The model should be flexible enough to capture the different types of shock and account for the inter-subject variability which characterizes the patients in the pediatric and adult critical care unit. The full details of the model and its development are provided in the Materials and Methods section.Pa and Pv are the mean arterial and venous pressures respectively, Hr is the heart rate, R is the systemic vascular resistance and Pp is the pulse pressure. In addition, Ca and Cv are the arterial and venous compliances respectively, ΔVv0 is the difference between minimal and maximal unstressed venous volume, Iex is the intravascular volume change, and Stot serves as a general marker for the activation of the autonomic nervous system (see below).Mechanistic models of the cardiovascular system are developed from first principles, tie together changes in blood pressures and volumes, and usually use the latter as the dependent dynamical variables in the set of ODEs . We deriOur proposed model contains fifteen hidden parameters see , and fivSb)—the internal feedback loop that modulates heart rate, contractility, unstressed venous volume, and the systemic vascular resistance (R), meant to keep the mean arterial blood pressure as close to a set-point (Pset) as possible. The baroreflex represents the autonomic component that is dependent on the patient’s current cardiovascular state. (ii) An independent component (S), representing the sum of all autonomic modulation which is independent of the cardiovascular state. While the baroreflex Sb describes the activation of different components in response to a reduction in the arterial blood pressure, and thus manifests as negative correlations between the arterial blood pressure and the heart rate (as well as other variables), the independent autonomic component Sdoes not depend on the arterial blood pressure and thus enables the model to capture different interactions between the blood pressure and heart rate, as well as other cardio-vascular components  The baroreflex , which is negative in case of intravascular fluid or blood loss. A distributive shock state is equivalent to a negative MSVR (non-autonomic vascular resistance modulation). In the next section, we also discuss the cardiogenic shock state which is caused by a reduction in K (heart contractility).The interplay between the fifteen parameters of the model can generate different clinical scenarios. In this work we focus on three different shock states which are described by three hidden parameters. Briefly, shock is a failure of the cardiovascular system to supply adequate blood and oxygen to the body tissues. In order to describe the hypovolemic shock state, we use Iex and MSVR) are presented (resented . The obsresented  are simuresented . The barresented .Iex) is negative (MSVR) remains constant  at a large, tertiary children’s hospital. These children were admitted to the ICU either for routine observation post-operatively (for the control samples) and were stable hemodynamically, or presented with various shock states, for example, due to massive post-operative bleeding, cardiac dysfunction, infections or other causes, see As noted above, iCVS is able to deal with patients of varying weights from neonates (a couple of kilograms) to adult-sized patients, as we demonstrate below. The hemodynamic data for all patients in this ICU are collected as routine practice , 17. TheThe challenge of estimating the causes for cardiovascular instability and shock from real-world data can be appreciated by examining Figs Vvo). This magnitude does not depend on the patient weight or blood volume, has units of MSVR (non-autonomic vascular resistance) which is expected to be negative in a distributive shock state. The cardiac function is described by the Maximal relative contractility: Kmax is the maximal contractility that the ventricle can generate  are not negative, and there are no marked fluctuations in the maximal relative contractility  action plan  and follMSVR, , or by expert clinician assessment preformed pro- and retrospectively. In the current study, the model shows higher accuracy in the evaluation of a hypovolemic shock state than in the evaluation of a distributive shock state see . This maSVR, see –S6 Figs,In addition, we explore model identifiability and estimation process robustness. We did so by simulating several artificial patients with various clinical shock states and examining the model’s ability to correctly recover the preset hidden parameters, demonstrating the model’s ability to capture and track changes in these parameters (shown for three sample patients in the supplementary). We recognize that our model, like many underdetermined mechanistic physiological ones, suffers from an inherent degree of nonidentifaiblity. However, we do believe that both the demonstration with real sample patients and simulated ones indicates that our model is able to capture the salient and clinically important variations in the hidden parameters to be estimated. As noted, this is a proof-of-concept study and we plan a thorough,prospective validation and quantification of the model’s accuracy on a larger clinical set of critically-ill patients.MSVR or While we illustrated the ability of iCVS to identify hidden cardiovascular states that can not be easily identified by simple examination of the physiological recordings, it is obvious that further assessment, ideally prospectively, on a much larger patient cohort is warranted. Generation of a larger dataset, containing a diverse population of patients with various cardiovascular states and their evolution will not only allow model validation and refinement, but also to define cut-off values for shock-state identification. For example, while iCVS can identify ongoing blood loss or maladaptive vasodilatation, ideally we would wish to be able to add an additional layer for a decision support tool that would alert clinicians to the presence of vasoplegic shock or hemorrhagic shock, defined by certain thresholds relating blood pressure to  tissues , or even tissues , 21. In  tissues . The modThe study was approved with waiver of informed consent by the Research Ethics Board at The Hospital for Sick Children, approval number 1000048904.IH is generated by the heart and is given by the product of the heart rate Hr and the stroke volume SV:The goal of this section is to detail iCVS: a mechanistic model of the cardio-vascular system that links measurable variables to clinically relevant physiological parameters that can not be measured directly. We use a lumped parameter model with several compartments: the circulatory system is represented as a closed loop with two compliant vessels  and one pure resistance vessel (the organs) , 23. TheIC flows are modeled as a linear resistor:Pa and Pv are the arterial and venous mean pressures, respectively, and R is the peripheral resistance. The evolution of arterial and venous volumes (Va and Vv respectively) is given by the following differential equations:Iex is the intra-vascular volume change—either loss of volume due to bleeding or extra-vascular capillary leak or conversely intravenous fluid administration.The arteriolar and capillary Eqs α ∈ {a, v} represents either the venous or arterial components, respectively, Cα the compliance, and The pressure in the venous and arterial compartments is derived from the vessel’s volume and compliance as follows:Stot (see below):For the arterial compartment, we assume constant unstressed volume . The venCa , where T = 300 sec. During the estimation procedure, the hidden parameters are estimated by minimizing the time integral over the cost function f(t) within a given interval. For some of the parameters (see θ* below) we assume that the time dependent change is smooth, and consider also the previous estimated value of the parameters.Bi is the upper bound of the parameter θi  on the cardio-vascular dynamics in a simulation of the iCVS model. In response to an increase in S, arterial pressure, venous pressure, vascular resistance, and pulse pressure increase as well. The hidden parameters are fixed and the observables are simulated accordingly (see A. Time dependent intra vascular volume change—zero in this simulation. B. Time course of MSVR—constant in this simulation. C. Time dependent magnitude of the independent autonomic control (S) which does not depend on the cardio-vascular state. D-H The resulting observables: D. Arterial pressure (Pa), E. Venous pressure (Pv), F. Peripheral resistance multiplied by arterial compliance (RC). G. Heart rate (Hr), H. Pulse pressure (Pp). I. Time dependent magnitude of the baro-reflex (Sb) which depends on the arterial blood pressure.S1 Fig demonstrates the effect of ngly see . A. Time(TIFF)Click here for additional data file.S2 FigA-C. Comparison between the measured value  and estimated value . Each point represents the value of a given measurement  in a specific time point. The time points which are presented are a randomly chosen subset that constitute 1% of the whole data-set which is used in D—F. Comparison between observed data and reconstructed values during a segment of 500 seconds. Green—patient number 2, blue—patient number 3 and red—patient number 6 (see D), E) and F). Dashed line—reconstructed value: D), E) and F). G-I. Histograms of the absolute values of the differences between the measured and estimated variables of heart rate (G), peripheral resistance (H) and pulse pressure (I). The dataset is same as presented in panels A-C. The arrows denote the mean differences for each of the patients presented in panels D-F using the same color scheme.er 6 see . ContinuUsing the estimated parameters which are found by the optimization process, we reconstruct the heart rate, peripheral resistance and pulse pressure, and compare the reconstructed values to the observed values. The reconstruction is based on Eqs RC reconstruction, and 0.99 for Pulse pressure reconstruction. MSVR and S are modeled as linear in each interval. (TIFF)Click here for additional data file.S3 FigIex is negative. We used Matlab version 2018b, running on 8 i7–8550U CPU @ 1.8GHz, 16.0GB RAM. The running time for running our optimization routine on a single interval with multiple initialization sets of parameters is 6 to 8 minutes. However, we believe that the running time can be shorter using a more optimal code, a stronger computer and maybe a different programming language. Results for patient number 1 , mean venous pressure (B), heart rate (C.), RC—the peripheral resistance multiplied by the arterial compliance (D) and pulse pressure (E). F-H. Lines represent a smoothed version of the estimated parameters which are obtained in each interval (see F. Relative intra vascular volume change (G. Non autonomic vascular resistance (MSVR). H. Maximal relative contractility Click here for additional data file.S4 FigA-C.—The original parameters of the simulation chosen arbitrarily: relative intravascular volume change: A), MSVR (B), and Kmax (C.). D-I. Each grey line represents a smoothed result of an estimation run obtained for each time interval (see D-F and G-I) represents the results that are obtained with a given set of weights as marked below. D,G Estimated relative intra vascular volume change . F,I estimated maximal relative contractility Click here for additional data file.S5 FigA-C.—The original parameters of the simulation chosen arbitrarily: relative intravascular volume change: A), MSVR (B), and Kmax (C.). D-I. Each grey line represents a smoothed result of an estimation run obtained for each time interval (see D-F and G-I) represents the results that are obtained with a given set of weights as marked below. D,G Estimated relative intra vascular volume change . F,I estimated maximal relative contractility Click here for additional data file.S6 FigA-C.—The original parameters of the simulation chosen arbitrarily: relative intravascular volume change: A), MSVR (B), and Kmax (C.). D-I. Each grey line represents a smoothed result of an estimation run obtained for each time interval (see D-F and G-I) represents the results that are obtained with a given set of weights as marked below. D,G Estimated relative intra vascular volume change . F,I estimated maximal relative contractility Click here for additional data file.