|Year : 2021 | Volume
| Issue : 5 | Page : 1330-1339
|Platelet indices as an assessment tool of septic acute kidney injury
Mahmoud Emara1, Sabry Shoeib1, Abeer Reda2, Mohamed Helwa3, Zeineb Kassemy4, Mohamed Abdelhafez1
1 Department of Internal Medicine, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Department of Internal Medicine, Shebeen Alkom Teaching Hospital, Menoufia, Egypt
3 Department of Clinical Pathology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
4 Department of Community Medicine, Faculty of Medicine, Menoufia University, Menoufia, Egypt
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|Date of Web Publication||4-May-2022|
| Abstract|| |
Platelet (PLT), one of blood cells, plays a major role in physiological and pathological processes such as coagulation, thrombosis, inflammation, and keeping the integrity of vascular endothelium. There are a group of parameters that are used to measure the total amount of PLTs, PLTs morphology, and proliferation. PLT indices are associated with the severity of illness and patients’ prognosis. It was reported that mean platelet volume (MPV) was raising synchronously with interleukin (IL)-6 and C-reactive protein in sepsis, and was correlated to the severity of the disease. We aimed to study PLT indices and its changes in sepsis and septic acute kidney injury (AKI) patients to assess the disease and its severity. The present study is a cross-sectional study, had been carried out at Menoufia University hospitals from August 2017 to August 2019. The various platelet indices [MPV, platelet distribution width (PDW) and plateletcrit (PCT)] are considered as outcome variables were compared among controls, cases with sepsis, and cases with sepsis associated AKI. Group I (31) cases with the clinical diagnosis of septic AKI, Group II (33) cases with the diagnosis of sepsis, and Group III (28) consecutive persons marked as negative in the output of the cell counter were taken as controls. Data were tabulated and statistically analyzed. There were 15 men and 15 women for Group I (septic AKI), 17 males and 16 females for Group II (sepsis) and 15 men and 13 women healthy controls as a control group. According to PLT indices MPV, there was a significant statistical difference (P1 <0.01) between Group I and II of patients as it were12.06 ± 1.23, 11.01 ± 1.20, respectively, and PDW also there was a significant statistical difference (P1 <0.01) as it were16.01 ± 2.33, 13.97 ± 2.14, respectively, and PCT there was no significant difference between the two groups. Furthermore, there was a significant statistical difference between Group I and II of patients according to procalcitonin, TNF-α and IL-10. From these results, we conclude that there were a statistical significant difference between the patient groups of critically ill.
|How to cite this article:|
Emara M, Shoeib S, Reda A, Helwa M, Kassemy Z, Abdelhafez M. Platelet indices as an assessment tool of septic acute kidney injury. Saudi J Kidney Dis Transpl 2021;32:1330-9
|How to cite this URL:|
Emara M, Shoeib S, Reda A, Helwa M, Kassemy Z, Abdelhafez M. Platelet indices as an assessment tool of septic acute kidney injury. Saudi J Kidney Dis Transpl [serial online] 2021 [cited 2022 May 25];32:1330-9. Available from: https://www.sjkdt.org/text.asp?2021/32/5/1330/344752
| Introduction|| |
Platelet (PLT) is an important blood cell which plays a major role in physiological and pathological processes such as coagulation, thrombosis, inflammation, and maintenance the integrity of vascular endothelium. PLT indices are a group of parameters that are used to measure the total amount of PLTs, PLTs morphology, and proliferation.
PLT indices include PLT count, mean platelet volume (MPV), plateletcrit (PCT), and platelet distribution width (PDW). The MPV is the ratio of PCT to PLT count. PDW is the coefficient of PLT volume variation, which is used to describe the varieties of PLTs volume. These indices have been applied not only in the diagnosis of hematological disorders but also, it has been discovered that these indices are related to the severity of some illness and its prognosis.
In addition, Acute Physiology and Chronic Health Evaluation II System also includes thrombocytopenia as an independent risk factor for mortality.
In modern research, it was reported that MPV was rising synchronously with interleukin (IL)-6 and C-reactive protein (CRP) in septic premature infants, and the increment was correlated to the severity of sepsis.
Acute kidney injury (AKI) is a very common clinical problem in the intensive care unit (ICU), where mortality rates approach 25% and rise to 50%–60% when the patient is indicated to going on renal replacement therapy. These statistics have not significantly improved over the past years. Clinical situation of combined sepsis and AKI soar the hospital mortality rate as high as 70%.
The pathogenesis of septic AKI in humans should not be exclusively viewed in the context of distributive shock-associated ischemia, but rather also within the context of a dysregulated and ill-defined inflammatory response to septic stimuli. So trials and therapies aimed at targeted treatment based on where patients lie along the immunologic spectrum.
We aimed to study PLT indices and its changes in septic AKI patients to assess the disease and its progression.
| Methods|| |
This is a cross-sectional study, had been carried out at Menoufia University hospitals in the period from August 2017 to August 2019. The various PLT indices (MPV, PDW, PCT) considered as outcome variables were compared among 92 adult subjects divided into controls, cases with sepsis and cases with the diagnosis of sepsis-associated AKI, which were considered as explanatory variables. Group I consisted of 31 cases with clinical diagnosis of sepsis-associated AKI, Group II consisted of 33 cases with the diagnosis of sepsis and Group III with 28 consecutive apparently healthy volunteers marked as controls.
Patients with a past history of the renal disorder (chronic renal disorder or who underwent dialysis), patients with the hematological disorder (active hemorrhage, anemia, hyper-splenia, lymphoma or leukemia, immunologic or rheumatic disorder, and bone marrow diseases; patients who had infused with blood or PLTs before their admission; patients who had used some drugs as anti-inflammatory, anti-PLT drugs (clopidogrel…) before their admission; patients who had received radiotherapy or chemotherapy) were excluded from the study.
The data includes admission and history of the presenting illness, the severity of illness scores, physiological measurements, and physical examination.
All persons in this study underwent these laboratory values;
- Routine investigations (e.g., urine analysis, liver enzymes, bilirubin… )
- Complete blood picture including all PLT indices (MPV, PDW, and PCT) taken within the first 4 days of admission
- Blood urea nitrogen and serum creatinine
- Serum level of
- Tumor necrosis factor a (TNF-α) in the blood to as a proinflammatory
- IL-10 in the blood as anti-inflammatory.
Cytokine level measurements
Serum levels of IL-10 were measured using a commercially available enzyme-linked immuno-adsorbent assay ELISA kit (Diaclone Research, Besancon, France) and TNF-α level was measured by ELISA kits was purchased from R and D Systems (Minneapolis, Minn) according to the manufacturer’s instruction with detection limit up to 3 pg/mL and 6.23 pg/mL for human IL-10 and TNF–α, respectively.
All cytokine measurements were performed on frozen samples for a few weeks with kits that were purchased simultaneously.' The following definitions were used to assess the patients:
- The KDIGO criteria including both changes in serum creatinine and hourly urine output to define and stage AKI
- Organ dysfunctions, sepsis, and severe sepsis (defined according to the American College of Chest Physicians/Society of Critical Care Medicine criteria
- Organ failure (OF) as a daily organ-specific Sequential OF Assessment score >2,
- Patients who had organ dysfunction and/or hypoperfusion abnormalities were defined as severe sepsis.
Finally this study approved by the Ethics Committee of Menoufia University Hospitals and conducted in accordance with the Declaration of Helsinki.
| Statistical Analysis|| |
Data were collected, tabulated, statistically analyzed using an IBM personal computer with IBM SPSS Statistics version 22.0 (IBM Inc., Armonk, NY, USA). Quantitative data were presented in the form of mean, standard deviation,and range. Qualitative data were presented in the form of numbers and percentages and analyzed by applying Chi-square (χ2) and Fisher’s exact tests. Independent sample t and analysis of variance tests were used for comparison between means of normally distributed quantitative variables. Mann–Whitney and Kruskal–Wallis tests were used for not normally distributed quantitative variables. Spearman correlation was used to assess the strength and direction of correlation among nonparametric variables. P <0.05 was considered statistically significant.
| Results|| |
Sepsis-associated AKI patients were 15 men and 15 women (Group I), patients with sepsis were 17 males and 16 females (Group II), and there were 15 men and 13 women healthy subjects as a control group [Table 1].
|Table 1: Distribution of the studied groups regarding their characteristics.|
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Clinical and laboratory findings are defined in [Table 2], from that the mean for temperature, heart rate and respiratory rate in Group I were 38.36 ± 1.02, 103.03 ± 9.35 and 26.06 ± 5.08 respectively. The mean for temperature, heart rate and respiratory rate in Group II were 38.39 ± 1.01, 102.09 ± 9.92, and 26.06 ± 4.67, respectively, with no statistical difference between the two groups of patients.
|Table 2: Clinical and laboratory findings in the studied patients at presentation.|
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[Table 3] shows the hemogram and PLT indices for the two groups of patients and also for the control group. This study had found a significant statistical difference between Group I and III and also Group II and III according to hemoglobin level, white blood cells, and platelets and also PLT indices (MPV, PDW and PCT). There was a significant difference between Group I and II of patients according to PLT indices as MPV was 12.06 ± 1.23, PDW was 16.01 ± 2.33 and PCT was 0.19 ± 0.11 in Group I and MPV were11.01 ± 1.20, PDW 13.97 ± 2.14 and PCT was 0.22 ± 0.09 in Group II of patients.
|Table 3: Distribution of the studied groups regarding their peripheral blood picture.|
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Serum levels of CRP and inflammatory cytokines TNF-α and IL-10 were described in [Table 4] for the two groups of patients and also for the control group. This study had found a significant statistical difference between Group I and III and also Group II and III according serum CRP level, however, there was a significant statistical difference between Group I and II of patients according to TNF-α and IL-10 as TNF-α was 43.88 ± 12.31 pg/mL), (and IL-10 was 93.82 ± 32.76 (pg/mL) in Group I. In group II TNF-α was 22.78 ± 14.76 (pg/mL), and IL-10 was 132.24 ± 63.77 (pg/mL).
|Table 4: Distribution of the studied groups regarding their inflammatory markers.|
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[Figure 1] shows the area under the curve for PLT indices and CRP between septic AKI Group I and controls (III). [Figure 2] shows the area under the curve for inflammatory markers and CRP between septic AKI Group I and controls III.
|Figure 1: Receiver operating characteristic curve for platelets indices and C-reactive protein between septic acute kidney injury group and controls.|
ROC curve: Receiver operating characteristic curve, CRP: C-reactive protein, MPV: mean platelet volume, PDW: Platelet distribution width, PCT: Platelet crit.
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|Figure 2: Roc curve for inflammatory markers between septic acute kidney injury group and controls.|
ROC curve: Receiver operating characteristic curve, CRP: C-reactive protein, INF gamma: Interferon gamma, IL-10: Interleukin-10.
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The correlation between MPV and other variables are in [Table 5], which were significantly negative with serum urea and creatinine in-between the two groups of patients (group I and II). There were no other correlations with other inflammatory markers, procalcitonin, or coagulation tests (PT and PTT).
|Table 5: Correlation between mean platelet volume (MPV) and other variables.|
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[Table 6] shows the correlation between PLT diameter width (PDW) and other variables, which were significantly positive with serum urea, creatinine, bilirubin, and CRP in-between the two groups of patients (Group I and II). There were negative correlations with serum levels of TNF-α.
|Table 6: Correlation between platelet distribution width (PDW) and other variables.|
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| Discussion|| |
MPV is available worldwide; suitable enough to be used as one of the prognostic markers in critically ill patients.
In the current study, the PLT indices were affected by disease progression as it were more perturbed in the septic AKI patients than the two other groups and this finding is consistent with the study done by Sampoorna, also in agree with Gao et al who had studied 124 patients with sepsis, and found that MPV and PDW were increasing, while PLT and PCT were decreasing with time.
In another two studies done by Tajarernmuang et al and Akarsu et al, they found the rise in MPV and to a lesser extent an increase in PDW, giving a worse prognosis in patients with sepsis and non-survivors. The discrepancies in MPV found in the previous studies may be due to different laboratory methods used. Studies have shown that the normal range of MPV should be established and calibrated within each specific laboratory.
PDW is an indicator of the heterogeneity in PLT size. A high value of PDW suggests a large range of PLT size due to swelling, destruction, and immaturity. Moreover, it indirectly measures PLT size and the PLT activation.
In a study that included 13,701 healthy adults in the United States, among the PLT indices, only PDW was found to be an independent predictor of all-cause and cardiovascular mortality.
In this study, PDW was more elevated inpatient groups being more in the septic AKI group. This finding is similar to that found by Akarsu et al.
Zhang et al had found that PDW values were valuable for predicting mortality in patients hospitalized in ICU.
The PCT is nonlinearly correlated to the PLT count and has a similar clinical outcome. In the current study, PCT was significantly decreased in patients groups (sepsis group and group of septic associated AKI) and this is in parallel with the findings by Gao et al.
Thrombocytopenia found in the current study was significant in sepsis and gave a prognostic indicator for critically ill, a finding that has already been described previously by Mavrommatis et al, and Irmak et al. And this in consistence with a study by Oraket al who found PLT number was related to severity and mortality. Furthermore, Gao et al have reported that the PLT count decreased and the PDW amounts increased in patients with sepsis.
In one study, thrombocytopenia was found in the first three to four days of septic patients. Several studies have suggested PLT activation exacerbates renal injury., A study in rats by Li et al, showed that in renal ischemia-reperfusion injury, P-selectin was widely expressed in renal tissue. Furthermore, inhibition of P-selectin could increases inflammation and cell necrosis.
In the present study, MPV value at the septic AKI was higher than the group of sepsis only and this is in agreement with many studies like Han et al, and also the study by Venkata et al who found MPV was significantly higher in patients underwent continuous renal replacement therapy (CRRT) initial treatment, however, the value of PLT count was just the opposite. It is reported that thrombocytopenia is common in critically ill patients, and is associated with an increase in the incidence of AKI as well prolonged ICU stay. Therefore, PLT count and their indices can be used as a direct indicator of organ dysfunction.
Procalcitonin is recognized as a suitable marker for the diagnosis of sepsis or severe sepsis. However, some other non-infective conditions, such as trauma, burn, pancreatitis, surgery, and renal dysfunction, can also increase serum procalcitonin levels. In this study, procalcitonin was elevated above the cut-off value (procalcitonin >0.3 ng/mL) in both patients’ groups the sepsis and the septic AKI, and there was a significant difference than the control group, however, there was no statistical difference between patients with sepsis only and the septic AKI group but it was higher in the septic AKI patients. And this meets the findings by Chun et al.
Data from the literature have confirmed that bacterial toxins and other inflammatory mediators can induce procalcitonin. Procalcitonin acts as a chemoattractant in the inflammatory area, attracting more immune cells. Procalcitonin is initially produced in adherent monocytes that later contribute to the marked increase in circulating procalcitonin by recruiting parenchymal cells when they are in direct contact with activated monocytes.
One study found elevated serum procalcitonin level has been shown to affect impaired renal function, but there is a lack of evidence as to whether procalcitonin can be used as a predictive marker for AKI. Other studies showed that procalcitonin could destroy mesangial cells through increased synthesis of IL-6, and TNF-α, inducing apoptosis. This result reflects the consideration for procalcitonin as a toxic mediator of AKI. In some studies., Additionally, it is suggested that an indirect pathway induced through cell-mediated host responses caused by inflammatory cytokines (e.g., IL-1β, IL-6, and TNF-α) plays a pivotal role in AKI.
In this study, the level of TNF-α which reflect endothelial injury significantly increased in septic patients compared with the control group. And it is more elevated in the septic AKI group giving a statistically significant difference.
According to IL-10 this study showed significant increases of its serum level in the septic patients compared with those of the controls throughout the acute phase. However, there was a significant difference between patients with sepsis and those with septic AKI but it was lower in the septic AKI group.
Results from the current study were consistent with this and in agreement with Xiao et al who reported that both pro-inflammatory and anti-inflammatory actions correlate with the progression of sepsis in a mutual relationship. This suggests that the cytokine network composed of the pro-inflammatory cytokines could facilitate the progression of sepsis based on the coagulation disorder and this disturbance leads to a serious outcome. However, the anti-inflammatory cytokines might act as a negative feedback mechanism against the inflammatory response.
Limitations of this study are: first, the relatively small number of patients included and the use of data from a single institution. Further study is necessary to clarify the role of cytokine networks in the pathogenesis of sepsis and its reflection on routine labs like PLT indices. Second, due to the one spot cross-sectional observational design with its inherent biases, the control of confounding factors may be insufficient, although data were collected from medical files with a high level of accuracy. It’s well known that there were many factors affecting platelets indices, such as pharmacological agents, smoking, occult hematologic diseases, malignancy, or inflammation. However, it was difficult to obtain all the factors. These could have an impact on our results. Third, some patients did not have preadmission blood routine and blood biochemical indices. This was common in clinical practice, especially in developing countries. This may result in less accurate baseline data. Finally, we believe that these findings will have implications for the management of patients with sepsis and its progression.
From these results, PLT indices were significantly affected in the septic AKI group of patients more than the non-AKI groups.
Conflict of interest: None declared.
| References|| |
Golebiewska EM, Poole AW. Platelet secretion: From haemostasis to wound healing and beyond. Blood Rev 2015;29:153-62.
Guclu E, Durmaz Y, Karabay O. Effect of severe sepsis on platelet count and their indices. Afr Health Sci2013;13:333-8.
Zhang S, Cui YL, Diao MY, Chen DC, Lin ZF. Use of platelet indices for determining illness severity and predicting prognosis in critically ill patients. Chin Med J (Engl) 2015;128:2012-8.
Sezgi C, Taylan M, Kaya H, et al. Alterations in platelet count and mean platelet volume as predictors of patient outcome in the respiratory intensive care unit. Clin Respir J 2015;9:403-8.
Zhang Z, Xu X, Ni H, Deng H. Platelet indices are novel predictors of hospital mortality in intensive care unit patients. J Crit Care 2014; 29:885.e1-6.
Catal F, Tayman C, Tonbul A, et al. Mean platelet volume (MPV) may simply predict the severity of sepsis in preterm infants. Clin Lab 2014;60:1193-200.
Morrell ED, Kellum JA, Pastor-Soler NM, Hallows KR. Septic acute kidney injury: Molecular mechanisms and the importance of stratification and targeting therapy. Crit Care 2014;18:501.
Bagshaw SM, Uchino S, Bellomo R, et al. Septic acute kidney injury in critically ill patients: Clinical characteristics and outcomes. Clin J Am Soc Nephrol 2007;2:431-9.
Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int 2012;2:1-138.
Bone RC, Balk RA, Cerra FB, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM consensus conference committee. American college of chest physicians/society of critical care medicine. Chest 1992;101:1644-55.
Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/ failure. On behalf of the working group on sepsis-related problems of the European Society of Intensive Care Medicine. Intensive Care Med 1996;22:707-10.
Brun-Buisson C, Meshaka P, Pinton P, Vallet B; EPISEPSIS Study Group. EPISEPSIS: A reappraisal of the epidemiology and outcome of severe sepsis in French intensive care units. Intensive Care Med 2004;30:580-8.
Dellinger RP, Levy MM, Carlet JM, et al. Surviving sepsis campaign: International guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med 2008;36:296-327.
Tajarernmuang P, Phrommintikul A, Limsukon A, Pothirat C, Chittawatanarat K. The role of mean platelet volume as a predictor of mortality in critically ill patients: A systematic review and meta-analysis. Crit Care Res Pract 2016;2016:4370834.
Sampoorna G. A comparative study of platelet indices, in cases of fever, sepsis leading to multiorgan dysfunction and control group, at a tertiary care hospital using an automated hematology analyzer sysmex Xn_1000. IOSR J Dent Med Sci (IOSR-JDMS) 2017;16:27-33.
Gao Y, Li Y, Yu X, et al. The impact of various platelet indices as prognostic markers of septic shock. PLoS One 2014;9:e103761.
Akarsu S, Taskin E, Kilic M, et al. The effects of different infectious organisms on platelet counts and platelet indices in neonates with sepsis: Is there an organism-specific response? J Trop Pediatr 2005;51:388-91.
Farias MG, Schunck EG, DalBó S, deCastro SM. Definition of reference ranges for the platelet distribution width (PDW): A local need. Clin Chem Lab Med 2010;48:255-7.
Qayyum R, Vaidya D. Platelet distribution width is an independent predictor of all-cause and cardiovascular mortality among healthy US adults. Circulation 2011;124:A1678.
Mavrommatis AC, Theodoridis T, Orfanidou A, Roussos C, Christopoulou-Kokkinou V, Zakynthinos S. Coagulation system and platelets are fully activated in uncomplicated sepsis. Crit Care Med 2000;28:451-7.
Irmak K, Sen I, Cöl R, et al. The evaluation of coagulation profiles in calves with suspected septic shock. Vet Res Commun 2006;30:497-503.
Orak M, Karakoç Y, Ustundag M, Yildirim Y, Celen MK, Güloglu C. An investigation of the effects of the mean platelet volume, platelet distribution width, platelet/lymphocyte ratio, and platelet counts on mortality in patents with sepsis who applied to the emergency department. Niger J Clin Pract 2018;21:667-71.
] [Full text]
Aydemir H, Piskin N, Akduman D, Kokturk F, Aktas E. Platelet and mean platelet volume kinetics in adult patients with sepsis. Platelets 2015;26:331-5.
Schwarzenberger C, Sradnick J, Lerea KM, et al. Platelets are relevant mediators of renal injury induced by primary endothelial lesions. Am J Physiol Renal Physiol 2015;308:F1238-46.
Jansen MP, Emal D, Teske GJ, Dessing MC, Florquin S, Roelofs JJ. Release of extracellular DNA influences renal ischemia reperfusion injury by platelet activation and formation of neutrophil extracellular traps. Kidney Int 2017; 91:352-64.
Li JH, Wang F, Wang NS, Jian GH, Xue Q. Effects of magnolin on expression of P-selectin in rats with renal ischemic reperfusion injury. Chin J Integr Tradit West Nephrol 2008;9:586-8.
Han JS, Park KS, Lee MJ, et al. Mean platelet volume is a prognostic factor in patients with acute kidney injury requiring continuous renal replacement therapy. J Crit Care2014;29:1016-21.
Venkata C, Kashyap R, Farmer JC, Afessa B. Thrombocytopenia in adult patients with sepsis: Incidence, risk factors, and its association with clinical outcome. J Intensive Care 2013;1:9.
Meisner M, Adina H, Schmidt J. Correlation of procalcitonin and C-reactive protein to inflammation, complications, and outcome during the intensive care unit course of multiple-trauma patients. Crit Care 2006;10: R1.
Chun K, Chung W, Kim AJ, et al. Association between acute kidney injury and serum procalcitonin levels and their diagnostic usefulness in critically ill patients. Sci Rep 2019;9:4777.
Chang CF, Lu TM, Yang WC, Lin SJ, Lin SJ, Lin CC, Chung MY. Gene polymorphisms of interleukin-10 and tumor necrosis factor-a are associated with contrast-induced nephropathy. Am J Nephrol 2013;37:110-7.
Ramesh G, Reeves WB. TNF-αlpha mediates chemokine and cytokine expression and renal injury in cisplatin nephrotoxicity. J Clin Invest 2002;110:835-42.
Steinbach G, Bölke E, Grਖnert A, Störck M, Orth K. Procalcitonin in patients with acute and chronic renal insufficiency. Wien Klin Wochenschr 2004;116:849-53.
El-Sayed D, Grotts J, Golgert WA, Sugar AM. Sensitivity and specificity of procalcitonin in predicting bacterial infections in patients with renal impairment. Open Forum Infect Dis 2014;1:ofu068.
Xiao W, Mindrinos MN, Seok J, et al. A genomic storm in critically injured humans. J Exp Med 2011;208:2581-90.
Matsumoto H, Ogura H, Shimizu K, et al. The clinical importance of a cytokine network in the acute phase of sepsis. Sci Rep 2018;8: 13995.
Department of Internal Medicine, Shebeen Alkom Teaching Hospital, Menoufia
Source of Support: None, Conflict of Interest: None
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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