Diabetic nephropathy (DN), a common microvascular complication of type 2 diabetes mellitus (T2DM), is an important factor causing chronic kidney disease. However, the relationship between miR‐29a and DN remains unknown. Therefore, a cross‐sectional study was conducted to identify a potential molecular biomarker for DN prevention and management by detecting the serum miR‐29a levels.The serum miR‐29a levels were measured in 360 subjects  using quantitative reverse transcription PCR (qRT‐PCR), and other conventional indicators were measured and analysed. A binary logistic regression was used to evaluate the DN risk factors; a receiver operating characteristic (ROC) curve was applied to analyse the diagnostic efficacy of miR‐29a for DN, and a Spearman's rank correlation analysis was used to evaluate the correlation between serum miR‐29a and cystatin C.p < 0.05). Serum miR‐29a and cystatin C are independent predictors of the occurrence of DN. Compared with a single indicator, the combination of serum miR‐29a and cystatin C has better DN diagnostic performance. In addition, the serum miR‐29a levels were positively correlated with cystatin C in the patients with DN .The serum miR‐29 levels in the T2DM patients were higher than those in the healthy subjects and significantly increased with the progression of DN  ROC curve of serum miR‐29a and cystatin C for patients with DN. Subjects with T2DM were diagnosed according to the American Diabetes Association criteria as follows: fasting blood glucose (FBG) ≥ 7.0 mmol/L, 2‐hour glucose ≥ 11.1 mmol/L and/or glycated haemoglobin A1c (HbA1c) ≥ 6.5%.n = 64), (2) microalbuminuria group  and (3) clinical albuminuria group . Consistent with the American Diabetes Association guidelines,In total, 360 participants, including 180 T2DM patients and 180 healthy individuals, were recruited in this research. According to the urinary albumin‐to‐creatinine ratio (UACR), the T2DM patients were divided into the following three groups2.22 anticoagulated venous blood (2 ml) was used for the testing of HbA1c, and anticoagulant‐free venous blood  was used for the detection of serum biochemical indicators, such as fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TGs), urea (Urea), creatinine (Crea) and cystatin C. In addition, the remaining serum specimens were stored in a refrigerator at −80℃ for subsequent research . Random spot urine specimens  were collected for the detection of urinary albumin and Crea, and then, the UACR results were calculated.The subjects fasted for 10–12 h, and blood samples were collected on the following morning. EDTA KCG = [(140‐age) × weight (kg)]/SCr × 72 × [0.85 if female] and adjusted for a body surface area of 1.73 m2.The HbA1c levels were measured using commercial reagents on an HLC‐723G8 HbA1c analyser (Tosoh Corporation). The levels of FBG, TC, TGs, Urea, Crea and cystatin C were measured using commercial reagents on an AU5800 biochemical analyser (Beckman Coulter Corporation). The estimated glomerular filtration rate (eGFR) was calculated with the Cockcroft‐Gault equation as follows: eGFR2.3According to the protocol reported by Luo et al.2, 14.77 μl of DEPC water, 0.4 μl of 10 mM dNTPs and 0.33 μl of TaqMan probe (Applied Biosystems). The reaction conditions for qRT‐PCR were as follows: 95°C for 5 min, followed by 40 cycles (95°C for 15 s and 60°C for 1 min). All samples were equipped with three reaction wells, including a blank control (the sample was replaced with EDPC water). Since conventional reference genes (U6 and 5S rRNA) are unstable in serum samples, they are not suitable as internal references in this experiment. However, since miR2911 (5′‐GGCCGGGGGACGGGCUGGGA‐3′) does not have a mammalian homologue and the measurement of its expression has high repeatability and reproducibility, it was added to each sample during the RNA extraction at a concentration of 10 nmol/L.−ΔCq), where ΔCq was calculated by subtracting the Cq value of miR2911 from the Cq value of miR‐29a. Notably, miR2911 (10 nmol/L) was not subjected to serial dilution and standard curve preparation and was only used as an internal reference to represent the relative expression of miR‐29a (nmol/L). Therefore, the concentration of miR‐29a in this study is not an absolute concentration but a relative concentration obtained from the internal reference (miR2911).According to the protocol provided by the reagent manufacturer, qRT‐PCR was performed on a TL988 Real‐Time PCT System  using TaqMan probes (Applied Biosystems). Briefly, the total volume of the qRT‐PCR was 20 μl, which consisted of 1 μl of cDNA, 2 μl of 10 × PCR buffer, 0.3 μl of Taq polymerase (TaKaRa), 1.2 μl of 25 mM MgCl2.4t test was conducted for the comparisons between two groups, a one‐way analysis of variance was conducted for the comparisons of multiple groups, and the LSD test was conducted for the comparisons across multiple groups. To analyse the nonnormally distributed variables, a Mann–Whitney U test was used for the comparisons between two groups, the Kruskal‐Wallis H test was used for the comparisons among multiple groups, and Dunn's post hoc test was used for the pairwise comparisons across multiple groups. To analyse the categorical variables, a chi‐square test was used for the comparisons between two groups. A binary logistic regression analysis was used to assess the independent risk factors of DN, and a receiver operating characteristic (ROC) curve was generated to evaluate the ability of the candidate biomarkers to predict DN. The method of combining multiple variables for a ROC curve analysis is briefly described as follows: the patients (DN patients and controls) were used as the dependent variable, the laboratory test indices  were used as the independent variables, a logistic regression equation was constructed, a prediction probability was generated as a new independent variable, and then, this independent variable was further analysed using ROC curves. The correlation of the nonparametric data was evaluated by a Spearman's rank correlation analysis. Two‐tailed p‐values less than 0.05 were considered statistically significant.The statistical analyses were conducted with SPSS version 19 (IBM Corp.). The Kolmogorov‐Smirnov test was utilized to analyse the normality of the data. The normal variables are expressed as the means and standard deviations, while the nonnormally distributed variables are presented as medians and interquartile ranges (IQRs). To analyse the normally distributed variables, an independent‐samples 33.1p > 0.05). The levels of systolic blood pressure (SBP), diastolic blood pressure (DBP), FBG, HbA1c, TC, TGs, UACR, cystatin C and miR‐29a in the T2DM patients were significantly higher than those in the control subjects (p < 0.05), while eGFR in the T2DM patients was significantly lower than that in the control subjects (p < 0.05).In total, 180 patients with T2DM and 180 healthy controls were included in the present study. The conventional and laboratory indicators of the participants are listed in Table 3.2p > 0.05). The levels of the disease course, miR‐29a, cystatin C and eGFR showed significant differences among the subgroups of T2DM patients. In addition, compared with the NA group, the levels of the disease course, miR‐29a and cystatin C in the DN patients (MA and CP groups) were significantly higher, and the levels of miR‐29a and cystatin C significantly increased with the progression of DN. The detailed information is listed in Table According to the concentrations of UACR, the T2DM patients were divided into the following groups: NA group, MA group and CP group. There were no significant differences in age, sex, BMI, smoking status, blood pressure (SBP and DBP), FBG, HbA1c, TC or TGs among the T2DM subgroups (3.3p = 0.005) and 19.740 , respectively.To ensure the accuracy of the binary logistic regression, we conducted a multicollinearity test of all independent variables using SPSS version 19 (IBM Corp.) and finally determined that age, sex, BMI, smoking status, course of disease, SBP, FBG, TGs, cystatin C and miR‐29a were defined as independent variables in this study, while the group allocation  was defined as a dependent variable. Subsequently, a binary logistic regression analysis was performed to predict the risk factors for the occurrence of DN. The odds ratios (ORs) of serum miR‐29a and cystatin C for DN were 1.060 .Referring to the diagnostic criteria for DN, UACR ≥ 30 mg/g was defined as DN.4Studies have increasingly proven that the expression of circulating miRNAs is dysregulated in various diseases, and miRNAs have been considered promising novel biomarkers for the diagnosis and monitoring of almost all diseases, including DN.In this study, we found that the basic indicators of blood pressure and serum lipids in the T2DM patients were significantly increased compared with those in the healthy subjects. This finding is consistent with those in previous reports, further confirming that changes in blood pressure and blood lipids are involved in the progression of diabetes in some way.Based on the levels of UACR, the T2DM patients were divided into three groups . Our study refers to the diagnostic guidelines for DN, and the latter two groups of subjects were defined as patients with DN.There are several limitations in our study that need to be mentioned. First, this study was a single‐centre study, and the characteristics of the subjects were not sufficiently diverse, thereby restricting the generalizability of our findings. Second, because this study was a cross‐sectional study, follow‐up of the subjects was not completed; thus, the relationship between miR‐29a and the prognosis of DN was not clarified. Third, although the concentrations of serum miR‐29a in the occurrence and progression of DN were investigated systematically in this study, the molecular mechanism of miR‐29a in the development of DN is still unclear. In our future research, we need to carry out a multicentre case‐control study and establish an animal model of DN to clarify the pathological mechanism of the involvement of miR‐29a in DN and increase its clinical value.5In conclusion, the expression of serum miR‐29a was significantly associated with the occurrence and progression of DN and is expected to become a potential biomarker for the diagnosis of DN. The underlying mechanism by which serum miR‐29a correlates with DN needs to be explored in depth in basic research.All authors declare that they have no conflicts of interest.QL and FMY conceived and designed the experiments. QL, MLW and TDX performed the experiments. MLW and WL analysed the data. QL and FMY wrote the first draft of the manuscript. All authors accept responsibility for the entire content of this submitted manuscript and approve its submission.


Our goal is to investigate the use of the oxygen reserve index (ORi) to detect hypoxemia and its relation with parameters such as; peripheral oxygen saturation, perfusion index (PI), and pleth variability index (PVI) during one-lung ventilation (OLV).Fifty patients undergoing general anesthesia and OLV for elective thoracic surgeries were enrolled in an observational cohort study in a tertiary care teaching hospital. All patients required OLV after a left-sided double-lumen tube insertion during intubation. The definition of hypoxemia during OLV is a peripheral oxygen saturation (SpO2) value of less than 95%, while the inspired oxygen fraction (FiO2) is higher than 50% on a pulse oximetry device. ORi, pulse oximetry, PI, and PVI values were measured continuously. Sensitivity, specificity, positive and negative predictive values, likelihood ratios, and accuracy were calculated for ORi values equal to zero in different time points during surgery to predict hypoxemia. At Clinicaltrials.gov registry, the Registration ID is NCT05050552.p = 0.044, p = 0.039, p = 0.011, respectively). Time-dependent correlations also showed that; at a time point of DS5, ORi has a significant negative correlation with PI whereas, no correlations with PVI were noted.Hypoxemia was observed in 19 patients (38%). The accuracy for predicting hypoxemia during anesthesia induction at ORi value equals zero at 5 min after intubation in the supine position (DS5) showed a sensitivity of 92.3% (95% CI 84.9–99.6), specificity of 81.1% (95% CI 70.2–91.9), and an accuracy of 84.0% (95% CI 73.8–94.2). For predicting hypoxemia, ORi equals zero show good sensitivity, specificity, and statistical accuracy values for time points of DS5 until OLV30 where the sensitivity of 43.8%, specificity of 64%, and an accuracy of 56.1% were recorded. ORi and SpO2 correlation was found at DS5, 5 min after lateral position with two-lung ventilation (DL5) and at 10 min after OLV (OLV10)  up to 30 min after the start of OLV, ORi provides valuable information in predicting hypoxemia defined as SpO2 less than 95% on pulse oximeter at FiO2 higher than 50%. There is an ongoing investigation to provide advanced monitoring techniques during thoracic surgeries that require one-lung ventilation (OLV). For patients with a possible diagnosis of lung tumor, the surgical team performs either a video-assisted thoracoscopy (VATS) or thoracotomy surgical procedures. The anesthesiologists perform OLV in a lateral decubitus position after a double-lumen tube (DLT) insertion during tracheal intubation. There is usually a request from the surgeon for a collapsed lung where they perform the operative procedure in a surgical field. The lower, dependent lung is ventilated, whereas the upper, non-dependent lung collapses when opening the chest. There is perfusion in this lung, causing a transpulmonary shunt without ventilation. The transpulmonary shunt in the non-dependent lung is the main reason for hypoxemia during OLV. This hypoxemia in the upper deflated lung causes a physiological mechanism called hypoxic pulmonary vasoconstriction (HPV) which is responsible for diverting blood flow from the non-ventilated lung to the ventilated lung. Therefore, HPV causes a decrease in ventilation-perfusion mismatch and improves arterial oxygenation –4. There2) value of less than 95% while the inspired oxygen fraction (FiO2) is 50% or higher on a pulse oximetry device [2 values are between 95 and 90% meanwhile, arterial partial pressure of oxygen (PaO2) values from arterial blood gas analysis show values of 75–60 mmHg. Severe hypoxemia refers to a SpO2 value of less than 90% and corresponds to PaO2 values of less than 60 mmHg [2 using a non-invasive monitoring device called pulse oximetry. This device measures the level of PaO2 in the range of 0 to 100 mmHg where FiO2 value is equal to 21%. However, a pulse oximetry device cannot consistently detect desaturation when FiO2 is greater than 50% [The definition of hypoxemia during OLV is a peripheral oxygen saturation , and perfusion pleth variability (PVI). The multiwave pulse co-oximetry device can provide a calculated ORi for pulse oximetry values greater than 98%. If we could give an example, it would be an incidence where a falling PaO2 value approaches 100 mmHg, and a SpO2 value is higher than 98%. The multiwave oximeter device measures an ORi value that decreases and approaches a value of 0.24 [2 value of 100 mmHg and reaches a plateau of 1.00 at a PaO2 value of 200 mmHg.The Oxygen Reserve Index (ORi) is a multiwavelength pulse oximeter, and it provides continuous analysis of PaO200 mmHg . This de of 0.24 –10. ORi PI is an indicator of the relative strength of the pulsatile signal from a pulse oximetry device. A higher PI value shows that the pulsatile movement increases, and peripheral circulation at the sensor site improves accordingly. The PVI is a relative variability in the pleth waveform and provides a value between 0 and 100 in a noninvasive measurement from a pulse oximetry device. PVI is an automatic measurement of the dynamic change in PI that occurs during a complete respiratory cycle , 12.The main objective of this study is to investigate the effects of ORi parameter on hemodynamical parameters (heart rate and blood pressure) and oximeter-related parameters such as; peripheral oxygen saturation, PI, and PVI during elective thoracic surgeries requiring OLV and general anesthesia.1%), the ratio of FEV1/FVC%  were done in some patients with a possible diagnosis of severe lung disease because of the global pandemia in 2020 and 2021. Patients with FEV1 between 30 and 80% and FEV1/FVC ratio of < 70% were considered as having a moderate level of chronic obstructive pulmonary disease as per literature. These patients were included whereas, severely restricted patients were excluded [The investigators performed a prospective observational cohort study in 14 months on patients requiring elective thoracic surgery for open lung resection via a thoracotomy or VATS at the Trakya University School of Medicine Hospital, Edirne, Turkey. The investigators conducted the study between 2020 and 2021. After the Hospital Ethics Committee (TÜTF-BAEK 2020/108), the investigators recruited patients for this clinical study. Out of a total of 59 patients, 50 patients with a diagnosis of lung tumor underwent either VATS or open thoracotomy. The surgical procedures during these operations include; either lobectomy, pneumonectomy, lung biopsy, or wedge resection. The Human Research Ethics Committee of Trakya University Medical Faculty, Edirne, Turkey approved this clinical study protocol. The investigators collected written informed consent from patients or their relatives for this clinical study during preoperative visits. The study is registered in the Clinicaltrials.gov registry, and our Registration ID is NCT05050552. The pulmonary function tests, including the percentage of expected, forced expired volume during the first second  risk groups of 1 to 3, surgical procedures of either open lung resection with thoracotomy or VATS, general anesthesia including sevoflurane inhalational anesthesia during maintanence, the use of DLT and OLV. Exclusion criteria include; refusal to participate in a study, history of severe asthma, preoperative renal insufficiency (creatinine > 114 umol/L); preoperative liver dysfunction ; previous history of coronary or vascular disease or heart failure with an ejection fraction less than 40%, lung function study showing an FEVopathies , 13.2. The anesthesiologists provided general anesthesia using intravenous doses of propofol , 2 to 3 mg/kg, rocuronium  at a dose of 0.6 mg/kg, and fentanyl  at a dose of 2 to 3 mcg/kg. The anesthesiologist placed a 20 Gauge radial artery catheter on all patients and connected it to a disposable pressure transducer to provide continuous monitoring following the induction of anesthesia. During tracheal intubation, a left Robertshaw DLT was used. The anesthesiologist used a flexible broncoscopy for correct positioning of DLT in supine and lateral decubitus positioning. For anesthetic maintenance, anesthesiologists used inhalational anesthetic of sevoflurane  at an end-tidal concentration of 1 to 2% and intravenous fentanyl boluses at a dose of 0.5 to 1 microgram/kg every hour. The hemodynamical stability was maintained during the surgical procedures where keeping HR between 60 and 100 beats/minute and keeping MAP between 60 and 80 mmHg. During surgery, intravenous rocuronium was used every hourly at a dose of 0.05 mg/kg. All patients received an intravenous infusion of lactated Ringer’s solution at a dose of 10 ml/kg/hr.The investigators did not administer drugs for premedication to prevent hypoxemia-related events. After admitting a patient to the operating theatre, anesthesiologists applied electrocardiogram, noninvasive blood pressure and pulse oximetry monitoring devices, and measured these parameters continuously. The monitored parameters include; heart rate (HR), mean arterial pressure (MAP), systolic blood pressure (SBP), diastolic blood pressure (DBP), and SpO2, PaO2, ORi, PI, and PVI values were recorded at thirteen different time points during anesthesia induction and maintenance of the surgery. Radical-7 Pulse CO-Oximeter is used to measure oximeter parameters of ORi, PI, and PVI . During the collection of these parameters, the investigators measured peripheral oxygen saturation using a Pulse CO-Oximetry probe. For other oximeter-related parameters, the Rainbow R1 25-L probe was used, a product of the same company [Hemodynamical and oximeter-related data of HR, MAP, SBP, DBP, SpO company , 9. Base company , 14.2 of 0.5 with an Aestiva 3000 ventilator  [After general anesthesia induction and intubation, the anesthesiologists provided mechanical ventilation, and two lung ventilation in the supine position required the settings of a tidal volume of 8–10 mL/kg, inspiration to expiration ratio of 1:2, and respiratory rate of 10–12/min, without positive end-expiratory pressure (PEEP). During operation, the surgical team provided a lateral decubitus position before incision and the anesthesiologist initiated OLV after positioning. The dependent lung was ventilated with a tidal volume of 6–8 mL/kg, I: E ratio of 1:2, respiratory rate of 12–14/min with an unchanged FiO U.S.A.) . During 2 value of less than 95% while the FiO2 is 50% or greater on a pulse oximetry device [2, using bag-mask ventilation of 100% for a while, implementing an alveolar recruitment maneuver, or using continuous positive airway pressure to the collapsed lung during a desaturation of SpO2 value less than 95% [Hypoxemia during OLV is a SpOy device , 5, 9. Tthan 95% , 13. A f2 values in our study group of patients. The data collectors were usual residents in anesthesiology. The residents performed a blood gas analysis at DL5 time point only. The reason for the abscence of this routine arterial blood gas analysis during thoracic surgeries was a recent colloborative decision of our hospital and anesthesiology department to decrease medical costs. In addition, although arterial blood gases analysis is crucial to document the exact measurement of oxygenation via PaO2 values, it is impractical to obtain real-time values during an episode of hypoxemia [The anesthesiologists provided oxygen titration depending mainly on the SpOypoxemia , 9.2 . The anesthesiologist was responsible for keeping SpO2 values greater than 94. For this purpose, necessary adjustments in FiO2 values and mechanical ventilation parameters as well as necessary maneuvers were performed to provide better oxygenation. The incidence of thromboembolic complications, arrhythmias, pneumonia, the duration of hospital and intensive care unit stay were recorded [After induction, patients were routinely ventilated with 50% FiOrecorded , 13–18. recorded .Surgical resection was performed through a posterolateral thoracotomy. A suspicious tumor was located, and if possible all necessary frozen section samples were obtained for pathological evaluation. At the end of the operation, the suspicious mass was removed from its location. The necessary suturing, aspiration, and irrigation of fluids and blood were performed , 15, 18.Trakya University Faculty of Medicine University Ethical Committee agreed and approved the study in February 2020. All patients approved the fully informed written consent to participate in the study. The participants had confidentially during the study process and were able to withdraw from the research process at any time. The investigators discussed any expected benefits or potential harm for the research in detail.2 value of < 95%) episode after OLV [p-value of less than 0.05. For calculation of sample size, a hypoxemia rate of 30% after OLV, and a 10% precision at 95% confidence intervals, an alpha error of 0.05, and a power of 80%, the number of patients for the study was calculated as 28 patients [The investigators used an SPSS 15.0  program to analyze the data of our clinical study. Data were presented as mean ± SD and numbers (percentages), as indicated. Normality was tested with the Kolmogorov-Smirnov test. Some parameters are reported as median . Sensibility, specificity, positive and negative predicted values, likelihood ratios, and their respective confidence intervals were obtained from a two-by-two contingency table for the validity of ORi equals to zero during different moments before and after OLV was achieved to predict the first hypoxemia . There were 28 males and 22 females. The data presented in Table Table The accuracy for predicting hypoxemia during anesthesia induction at ORi equals zero at 5 min after placing the patient in a ORiDL5 showed a sensitivity of 69.2%, specificity of 83.3%, and an accuracy of 76.0%. The 95% confidence interval (CI) values are presented in Table 2 values of less than 95% at or higher than FiO2 value of 50% during the surgical procedure. At the time point of DS5, ORi equals to 0 value was observed in 12 of the 19 patients (63.16%) who presented with hypoxemia. At other time points this hypoxemia was observed as follows; DL5; 11 patients (22%), OLV1; 8 patients (16%), OLV2; 9 patients (18%), OLV5 12 patients (24%) and OLV10 15 patients (30%).Overall, from a total of 50 patients in the study group, 19 patients (38%) developed hypoxemia defined as SpO2 values in a continuous graph at thirteen different time points during the anesthesia induction and maintenance of the surgery. This correlation showed that; a strong correlation between ORi and SpO2 was found at time points of DS5 , DL5 , and, at OLV10 . Therefore, Fig. 2 values and ORi equals to zero values for predicting hypoxemia during anesthesia induction and maintanence.In Fig. Later, we evaluated the representative trends of the ORi and PI values and the ORi and PVI values at different time points during anesthesia induction and maintenance of thoracic surgeries. These are represented in Figs. 2 values, a correlation between these parameters were not found in the statistical analysis (p > 0.05). In our study, we demonstrated a time-dependent correlation between PVI and MAP at the time point of OLV90, indicating that PVI showed a relation to MAP at a late stage of the thoracic surgical procedure.For hemodynamical and oximeter parameters including; HR, MAP, SBP, DBP, SpOr = − 0.332, p = 0.019), whereas; no correlations with PVI were noted.In our study, we investigated the ORi and PVI values at different time points during anesthesia induction and maintenance of thoracic surgery and our findings show that fluid deficit or fluid overload causes changes in PI and PVI values. This is observed in our representative trend graphs in Figs. r = − 0.284, p = 0.046). In other time points, correlations were not demonstrated (p > 0.05).Table 2, PI, and PVI. These correlation analysis provide data that ORi has significant correlations with SpO2, PI and PVI at some specific time points and these include; at time point of DS5; , DL5 , and OLV10; ORi has a significant correlation with SpO2 , at time point of DLS5; ORi has a significant negative correlation with PI , whereas; 3- no correlations with PVI was noted.Table The main findings of this study are provided below:2 values of less than 95% while the FiO2 is 50% or higher on a pulse oximetry device at 5 min after intubation in the supine position  [The main conclusion is that ORi is sensitive and specific in predicting hypoxemia defined as SpOf 84.0%) , 17–21.There are other time points where there is statistically good report of sensitivity, specificity and accuracy for time points at ORiDL5, and during OLV until OLV30 where sensitivity of 43.8%, specificity of 64%, and an accuracy of 56.1% are recorded. These findings correlated to the previous reports that HPV increases and intrapulmonary shunting decreases after the start of OLV within 30 to 60 min , 14.2 values, to perform necessary mechanical ventilation adjustments, to perform aspiration or other anesthetic management techniques to prevent hypoxemia [In our study group of patients, a total of 19 patients (38%) developed hypoxemia at various recorded time points during the surgical procedure. ORi provides information for impending hypoxemia that a change in ORi value can be detected 5 to 6 min earlier than pulse oximetry value. Therefore, ORi can provide a valuable time to the anesthesiologist to provide an increase in FiOypoxemia , 17–21.During OLV, hypoxemia can develop not only by the intrapulmonary shunt in the non-ventilated lung but also by the ventilation-perfusion mismatch in the ventilated lung or hemodynamic instability , 5. In o2 was found at time points of DS5, DL5 and, at OLV10. The relationship between SpO2 values and ORi equals to zero values for predicting hypoxemia during anesthesia induction and maintenance is supported by these statistical findings. There are previous studies that support these correlations [2 values were set at 50% and may have been rised up to 70% after anesthesia management throughout the surgical procedures. In addition to temporary rises in FiO2 throughout surgery, mechanical ventilation and anesthetic maneuvers were performed by the anesthesiologists. Because of these interventions, in our opinion, we were not able to show a continuous a correlation between ORi and SpO2 values at all measured time points. When ORi which is an oximeter-related parameter is used along with the pulse oximeter monitoring, ORi values may present and record early signs of the downward trend of PaO2 in comparison to a pulse oximetry value. In a previous study, at 1 min after start of OLV the measurements show that; hypoxemia was 27.5% where SpO2 value was less than 90% whereas; a negative predictive value was reported as 12.9% in those patients who did not achieve an ORi value of 0 at 1 min after the lung collapsed. It has been reported that median time until desaturation was approximately 5.5 to 6 min. Therefore, FiO2 values should be kept between 50 to 60% to avoid hyperoxemia and its related adverse effects such as atelectasis [A significant correlation between ORi and SpOelations , 17–21. lectasis , 20, 21.2 values are kept at a value of 50 to 70% in our patients whereas other studies investigated the use of ORi for hyperoxemia as well [2 values of 240 mmHg or lower  in comparison to ORi values and PaO2 values of higher than 240 mmHg  [2 values on each time point because of hospital policies to decrease medical costs. In our study, at the measurement time of arterial blood gas analysis at DL5, we found that 4 patients had a PaO2 value above 240 mmHg and ORi values showed statistically significant negative correlation . In another study, 15 patients undergoing elective thoracic surgery using OLV were evaluated for correlation between PaO2 and ORi parameters throughout the surgical procedure and showed that ORi has a significant correlation with PaO2  [2 values show positive correlation with ORi values [Our findings show similarity with a recent study by Alday and his colleagues  however, as well , 20, 21. > 0.05) . In our < 0.001) . There ai values , 20, 21.2 value on the pulse oximetry device. This relationship causes no change in pulse oximeter values until PaO2 falls below 80 mmHg. Afterward, there is a sudden drop in pulse oximetry value; however, the PaO2 is unacceptable for more than 3 to 5 min. Therefore, there is a need to investigate a larger scale of several wavelengths to detect quantitative measurement of methemoglobin, carboxyhemoglobin, and total hemoglobin, and a newly presented device achieved this. Masimo Rainbow Signal Extraction Technology introduced the device [2 value remains 100%, whereas, there is a decrease in the value of ORi [2.During pulse oximetry monitoring, there is a sigmoidal relationship between arterial oxygenation in blood gas value and peripheral oxygenation reported as SpOe device –16, 19. e device , 20, 21.e of ORi , 20, 21.Increased intrathoracic pressure with respiration leads to more immediate reductions in peripheral perfusion in patients with a fluid deficit. In this case, a decrease in the PI value of the patient is observed. As a result of these changes with respiration, the highest and lowest PI ratio corresponds to the PVI. High PVI values are observed in patients with a high fluid deficit or those who do not respond to fluid application changes with changes in the PI , 23, 24.r = − 0.332, p = 0.019), whereas; no correlations with PVI were noted. This finding is thought to result from anesthesia drugs that are use during anesthesia induction and especially the use of opioid medications [Our study provides valuable data for the investigation of correlations between ORi and PI, and PVI. OLV with DLT has significant cardiopulmonary physiological changes, as has been discussed elsewhere , 17, 19.ications , 10, 12.2 values higher than 50% during anesthesia is related to hyperoxemia, and this high oxygenation decreases cardiac output by reducing heart rate and causing systemic vasoconstriction. Furthermore, hyperoxemia is a potent vasoconstrictor stimulus to the coronary circulation, functioning at the level of the microvascular resistance vessels [The use of FiO vessels , 21. Tsu vessels . This te vessels . There a vessels , 24. HigIn our study, we demonstrated a time-dependent correlation between PVI and MAP at the time point of OLV90, indicating that PVI showed a relation to MAP at a late stage of the surgical procedure. Recently, it is pointed out in a meta-analysis that PVI is a reliable marker in evaluating a response to fluid management .2 values were higher during right-sided OLV than left-sided OLV. Although it could be predicted that ORi would decrease before the decrease in SpO2 during left-sided OLV, the actual extent of this application of either right-sided or left-sided OLV needs to be further evaluated [2 values between 100 and 240 mmHg, ORi decreases, but SpO2 does not [2 values secondary to hospital protocol to decrease medical costs, we were not able to evaluate these findings.Malpositioning of DLT may cause hypoxemia and, in our study protocol, we included these patients and therefore, this is a limitation of our study , 13, 25.valuated , 20, 21.2 less than 95% on pulse oximeter at FiO2 higher than 50%. These findings correlated to the previous reports that HPV increases and intrapulmonary shunting decreases after the start of OLV within 30 to 60 min. ORi provides information for impending hypoxemia that a change in ORi value can be detected 5 to 6 min earlier than pulse oximetry value. Therefore, ORi can provide a valuable time to the anesthesiologist to provide an increase in FiO2 values, to perform necessary mechanical ventilation adjustments, to perform aspiration or other anesthetic management techniques to prevent hypoxemia. Fluid responses and anesthesia induction medications has influence over changes in PI and PVI oximeter values. The use of ORi for hyperoxemia during OLV and thoracic surgeries may be useful however, it is not practical as the PaO2 values of these patients usually range between 60 mmHg and 200 mmHg and patients are not under risk of hyperoxemia related problems when compared to a higher possible risk of hypoxemia.During use of OLV for thoracic surgeries, from 5 min after intubation (DS5) up to 30 min after start of OLV, ORi provides valuable information in predicting hypoxemia defined as SpO


Hypertension (HT) is associated with adverse outcomes in kidney transplant (KTX) recipients. Blunting of physiological decrease in nighttime compared to daytime blood pressure (non-dipping status) is frequent in this setting. However, weather non-dipping is independently associated with renal function decline in KTX patients is unknown.We retrospectively screened KTX outpatients attending for a routine ambulatory blood pressure monitoring (ABPM) (T1) at a single tertiary hospital. Patients had two successive follow-up visits, 1 (T2) and 2 (T3) years later respectively. Routine clinical and laboratory data were collected at each visit. Mixed linear regression models were used with estimated glomerular filtration rate (eGFR) as the dependent variable.2 respectively. 61 patients (50.4%) had sustained HT and 81 (65.8%) were non-dippers. In multivariate analysis, systolic dipping status was positively associated with eGFR (p = 0.009) and compared to non-dippers, dippers had a 10.4 mL/min/1.73m2 higher eGFR. HT was negatively associated with eGFR (p = 0.003).A total of 123 patients were included with a mean follow-up of 2.12 ± 0.45 years after ABPM. Mean age and eGFR at T1 were 56.0 ± 15.1 and 54.9 ± 20.0 mL/min/1.73mWe confirm a high prevalence of non-dippers in KTX recipients. We suggest that preserved systolic dipping is associated with improved renal function in this setting independently of potential confounders, including HT and proteinuria. Whether modification of dipping status by chronotherapy would preserve renal function remains to be tested in clinical trials.The online version contains supplementary material available at 10.1186/s12882-021-02523-7. Ambulatory blood pressure monitoring (ABPM) allows serial blood pressure (BP) measurements over a 24-h period. Compared to office BP measurement (OBPM), ABPM is a stronger predictor of target organ damage (TOD), cardiovascular (CV) events as well as all-cause and CV mortality in hypertensive patients , 2. The HT is a frequent disorder in kidney transplant (KTX) recipients and is regarded as a major risk factor for CV disease, chronic allograft nephropathy and graft loss –11. As iBased on current state of knowledge, we conducted a longitudinal cohort study in order to i) characterize circadian BP patterns measured by ABPM in KTX patients, ii) compare OBPM and ABPM readings in this population and iii) describe the evolution of eGFR over time and its relationship with dipping status independently of potential confounders.We retrospectively screened adult KTX patients between 2003 and 2016 at a single tertiary hospital. During this time period, 401 adults had a renal transplant. Of those, 140 (34.9%) had ABPM performed as part of their routine follow-up. Inclusion criteria were i) ABPM available after KTX, ii) a minimum of 2-year follow-up after ABPM and iii) age ≥ 18. Exclusion criteria were i) unwilling to participate, ii) multi-organ graft, iii) haemodialysis or peritoneal dialysis and iv) pregnancy. At our institution, post-transplant ABPM are not routinely ordered but are instead requested by the attending physician based on individual clinical appreciation.Variables were longitudinally collected at four distinct visits: T0 corresponded to discharge after transplant, T1 corresponded to ABPM while T2 and T3 corresponded to subsequent follow-up visits, 1 and 2 years after ABPM respectively. The time interval between T0 and T1 was not predefined. The time interval between T1 and T2 as well as T2 and T3 was 1 year. Thus, all included patients had a 2-year follow-up.All patients underwent a 24 h ABPM using a DIASYS INTEGRA II monitor at T1. Cuff size was chosen based on arm circumference. BP was recorded every 15 min from 7 am to 10 pm and every 30 min from 10 pm to 7 am. Daytime and night-time periods were defined by patient themselves according to their own daily schedule. Measures validity intervals were as follows: Systolic BP (SBP) > 50 mmHg and diastolic BP (DBP) > 30 mmHg and < 150 mmHg [Demographic characteristics, medical history, current medication, OBPM and laboratory data were collected at T0, T1, T2 and T3. Serum creatinine was analysed by standard clinical laboratory method. Proteinuria was estimated on a single urinary specimen. OBPM was measured by oscillometric sphygmomanometer in the seated position after a resting period of ≥ 5 min according to European guidelines .Renal ultrasound (US) was performed by experimented radiologists as part of routine follow-up in a subset of patients. Renal resistive index (RRI) were measured in three segmental arteries .HT related definition were based on latest European guidelines . Thus, HContinuous variables are expressed as mean ± standard deviation (SD) or median (interquartile range) according to distribution and categorical variables as number and relative frequencies (%). Normality of distribution was assessed graphically. No outliers were predefined. Variables were compared between groups (dipping vs non-dipping status as well as low eGFR vs high eGFR) using Student’s T test and Chi2 for continuous and categorical variables respectively.p-value for likelihood ratio test (LRT) comparing models with and without interaction term was < 0.1First, multivariate linear regressions were used with eGFR at T1 as the dependent variable and systolic dipping status as the main independent variable. The following covariates were a priori selected as potential confounders, based on prior scientific knowledge: gender, age, body mass index (BMI), smoking, HT, diabetes, graft vintage (corresponding to the timespan between T0 and T1), proteinuria, donor type (deceased vs living), past rejection, use of calcineurin inhibitors, use of steroid and use of renin angiotensin aldosterone blocker. Then, in longitudinal analysis, we considered repeated measures over time  and implemented multi-level mixed effect analysis to account for inter-dependence of data. The same above specified covariates were used in longitudinal models. Patient identification was considered as the grouping variable while random effects were applied to time variable and intercept. Interaction between ABPM parameter and time was considered in every model. Modification effect was considered significant if Sensitivity analyses were conducted considering i) HT defined by ABPM values instead of related medication, ii) diastolic and mean dipping status instead of systolic dipping status and iii) systolic dip as continuous variable instead of systolic dipping status as a binary variable.For every model, linearity of relationship, normality of residuals and homoscedasticity of residuals were assessed graphically. Collinearity was assessed using the variance inflation factors method. Log-normal variables were log-transformed when used in regression models if necessary.p-values. A two-sided p-value < 0.05 was considered significant. Statistical analyses were conducted using STATA version 15  [Data were considered to be missing completely at random and therefore patients with any missing value were excluded from the multivariate analyses. For every model, results are presented as β coefficients and associated 95% confidence intervals (95% CI) as well as 845 USA) .p = 0.20 and 63.0 vs 59.1%, p = 0.45 respectively.Between 2003 and 2016, 401 adults had a renal transplant. Of those, 140 (34.9%) had ABPM performed as part of their routine follow-up. We excluded 17 patients: Eight for undocumented follow-up, one for unavailable night-time ABPM, one for insufficient ABPM quality and four because of missing values on ABPM. Finally, three patients were excluded as they required haemodialysis. Thus 123 (87.8%) patients without missing values on ABPM were included in the present analysis. Compared to renal transplant patients who had an ABPM performed, those who did not have an ABPM performed had similar mean age and proportion of men: 52.8 ± 15.0 vs 50.7 ± 15.4, Among included patients, 21 (17.3%) had no HT on OBPM or ABPM, 13 (10.7%) had white-coat HT, 26 (21.4%) had masked HT and 61 (50.4%) had sustained HT. Non-dipping status was present in 81 (65.8%) of patients.p < 0.05 for all). Patients tended to be younger and to have longer graft vintage in the dipping group without reaching statistical significance. Other considered characteristics were similar between groups.Patient’s characteristics according to systolic dipping status at the time of ABPM T1) are described in Table  are descp < 0.001 for both). Pearson correlation coefficients between systolic dippers and diastolic dippers as well as between systolic dippers and mean dippers were 62.7 and 82.9% respectively. Compared to the non-dipping group, dippers had higher diurnal MAP (p = 0.047) and lower nocturnal SBP, DBP and MAP . Prevalence of HT was similar between groups.ABPM readings according to systolic dipping status at T1 are described in Table 2 in 126 patients without missing values on eGFR. Patient’s characteristics according to median eGFR value at T1 are described in supplementary table p = 0.029), had less frequently HT (p = 0.010) and had less frequently deceased donor (p = 0.024). Other characteristics were similar between groups.Median value of eGFR at T1 was 52.6 mL/min/1.73mp = 0.013) and compared to non-dippers, dippers had a 9.4 mL/min/1.73m2 higher eGFR. In multivariate analysis, dipping status was positively associated with eGFR (p = 0.019) and compared to non-dippers, dippers had a 10.1 mL/min/1.73m2 higher eGFR (Table p = 0.018 and 0.002 respectively). Other covariates were not associated with eGFR.Proteinuria required log-transformation in regression analyses. In univariate analysis, dipping status was positively associated with eGFR at T1 p = 0.01 and compp = 0.012) and compared to non-dippers, dippers had a 9.1 mL/min/1.732 higher eGFR. An interaction between time and dipping status was present (p = 0.085 for LRT): eGFR slope was -0.3 mL/min/1.73m2/year in non-dippers (p = 0.59) and -2.4 mL/min/1.73m2/year in dippers (p = 0.010). eGFR evolution over time between dippers and non-dippers is illustrated in Fig. p = 0.009) and compared to non-dippers, dippers had a 10.48 mL/min/1.73m2 higher eGFR (Table p = 0.17 for LRT) and eGFR slopes were thus not different between dippers and non-dippers. HT was negatively associated with eGFR (p = 0.003). Other covariates were not associated with eGFR.Mean follow-up after ABPM was 2.12 ± 0.45 years. In univariate analysis, dipping status was positively associated with eGFR (p = 0.005). HT based on ABPM definition was negatively associated with eGFR (p = 0.019).HT defined by ABPM values instead of related medication was substituted in the final multivariate model. Dipping status remained positively associated with eGFR (p = 0.029 and p = 0.010 respectively).Diastolic and mean dipping status instead of systolic dipping status were substituted in the final multivariate model. Mean and diastolic dipping statuses were positively associated with eGFR (p = 0.06).Systolic dip as continuous variable instead of systolic dipping as a binary variable was substituted in the final multivariate model. Systolic dip was not associated with eGFR  and renal function is intricate, reverse causality should be considered. While the longitudinal design, statistical methodology and pathophysiologic considerations could indicate a causal effect of circadian BP patterns on renal function, a reverse impact of eGFR on dipping status is possible. Second, as in most similar studies, a single ABPM measurement was conducted. Longitudinal evaluation could thus be hampered by the intrinsic moderate reproducibility of dipping categorization. We believe however that our findings were discussed in the light of this phenomenon. Third, the rather limited sample size prevented us to further investigate specific sub-group of patients and to detect potential association with smaller effect size. However, achieved statistical power was by definition sufficient to investigate our primary objective as attested by the highly significant and robust associations presented. Fourth, as a fraction only of screened KTX patients had ABPM performed, selection bias cannot be excluded. Excluded patients were however similar to those included. Finally, the number of donor characteristics considered in our study was limited, as ethics regulation does not allow documentation of such data in medical records at our institution.In conclusion, we confirm that non-dipping status is highly prevalent in KTX patients while not necessarily associated with the presence of HT. Moreover, we suggest that systolic dipping status could be a major determinant of renal function in KTX patients. This relationship was independent of major potential confounders, including HT and proteinuria. The only other determinant of renal function was the presence of HT itself, in agreement with prior knowledge in non-KTX patients. Post-transplant ABPM should be offered to all KTX recipients as a screening tool, even in those with controlled OBPM. Whether modification of dipping status by chronotherapy would preserve renal function cannot be inferred from our results and remains to be tested in clinical trials.Additional file 1: Supplementary table 1. Patients characteristics according to median eGFR value at T1.


In order to explore the clinical nursing effect of blood glucose level in elderly type 2 diabetic patients, this paper combines the deep neural network model and factor analysis from the perspective of multifactor analysis to construct a multifactor analysis model for the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients. Moreover, this paper analyzes the effects through experimental methods, collects cases through hospitals, and formulates research methods and related standards based on nursing research needs. In addition, this paper uses statistical methods to perform data processing, uses factor analysis to screen critical factors, and uses deep neural networks to process nursing data. The statistical results of the experimental research show that the deep neural network model combined with factor analysis can play a certain role in the clinical nursing effect. Thus, the blood glucose level analysis in elderly type 2 diabetic patients can provide a reference direction for the clinical care of blood glucose levels in elderly type 2 diabetic patients. The physiology of elderly type 2 diabetes patients is quite special. With the increase of age, the incidence rate gradually increases. Meanwhile, the patient has the following characteristics: 1) The patient's condition is hidden and often serious, and the early symptoms of the patient are not typical, which is easily missed and misdiagnosed  The pati. HbA1c iThis article analyzes the impact of health education on the level of blood glucose control in elderly type 2 diabetic patients.The bone tissue morphology of diabetic animal models provides evidence for the study of bone mineralization and bone transformation rate. Through the morphological examination of diabetic rats, the literature  found thOne of the reasons for the increase of bone fragility in diabetic patients is the increase in the concentration of advanced glycation end products (AGE) of bone collagen, which leads to changes in the physical and chemical properties of the collagen matrix. The effect of AGE on osteoblasts has been studied in depth. Integrins play a role in adhering cells and collagen as a receptor for osteoblasts on the surface of type I collagen. The literature  synthesiMany people with type 2 diabetes are overweight or obese. This increase in weight compared to people of the same age adds mechanical stress to the bones, which is equivalent to continuous weight-bearing training for the bones, and repeated mechanical stress stimulation will inevitably lead to an increase in bone density . Adipocyγ (PPARγ), which is an important factor in adipocyte differentiation. It can promote the differentiation of stromal stem cells in bone marrow to adipocytes but not osteoblasts and inhibit the differentiation and function of osteoblasts. Furthermore, obesity can aggravate oxidative stress and release inflammatory factors such as tumor necrosis factor-alpha and interleukin 1-beta.In addition, obesity is associated with type 2 diabetes. In the past, obesity was considered to be a bone protective factor, but recent studies have found that obesity can cause more bone damage . MoreoveκB ligand) by osteoblasts. The latter is the most important factor that promotes osteoclasts' differentiation, maturation, and functional activity. Therefore, obesity affects the bone remodeling process through different mechanisms, and the role of bone damage may be dominant  represents data-related statistics, and EPelmod[·] represents model-related statistics.Among them, In fact, the partition function of BM is difficult to calculate, and the accurate calculation of the maximum likelihood function is very difficult to handle. The computational complexity of BM's data-related statistics is exponential with the number of hidden layer units. At the same time, the calculation complexity of BM's model data-related statistics and the sum of the number of visible layer and hidden layer units are also exponential.v={vi}i=1D and hidden layer units h={hi}i=1J, then the energy function of RBM can be expressed asAs shown in θ={W, c, b} is the network weight in the RBM model. When any of the visible layer and the hidden layer in the RBM is in a fixed state, the conditional probability distribution of the other layer can be calculated:Here, Like BM, RBM maximizes the likelihood function training to obtain the parameters of the model. However, since RBM restricts the intralayer connections of BM, the accurate calculation of the RBM maximization likelihood function is much simpler than that of the BM model. In this way, the calculation of RBM data-related statistics can be obtained through variational inference. The lower bound of the log-likelihood function of RBM can be expressed asQμ(h|v) is an approximate posterior of the actual posterior Pθ, and L is the lower bound of the log-likelihood function. In order to eliminate the phenomenon of explanation and elimination, the uniform field approximation method is used to approximate the actual posterior Pθ.Here, L is expressed asThen, θ is fixed and the partial derivative of L on μj is set to zero, we can getTherefore, when weight In this way, the hidden layer output obtained by variational inference is consistent with the result obtained by conditional probability sampling.W as an example, the gradient of weight W can be expressed asAt present, the training of RBM networks often encounters overfitting problems. Commonly used solutions include weight attenuation, dropout, DropConnect, and weight uncertainty. The weight decay method is to add regularization during the training of the weight learning in small batches. Taking the calculation of the gradient of weight W′ represents the gradient learned from the previous mini-batch block.Here, momentum represents the weight attenuation coefficient, and Δr={0,1}j. If the value of rj is equal to 1, the corresponding hidden layer output remains unchanged; otherwise it is 0. The probability that the value of rj is equal to 1 is p. At this time, the energy function of DRBM can be expressed asIn Dropout RBM (DRBM), the output of the hidden layer is related to a set of binary variables When any of the visible and hidden layers in DRBM is in a fixed state, the conditional probability distribution of the other layer can be calculated:M ∈ RD×J. If the value of Mij is equal to 1, the corresponding connection weight Wij remains unchanged; otherwise it is 0. Moreover, the probability that the value of Mij is equal to 1 is p. At this time, the energy function of DcRBM can be expressed asIn DropConnect RBM (DcRBM), the weights connecting visible and hidden units are related to a set of binary matrices When any of the visible and hidden layers in DcRBM is in a fixed state, the conditional probability distribution of the other layer can be calculated:This article uses deep neural network model combined with factor analysis to analyze the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients.p > 0.05), and they were comparable. The Medical Ethics Committee approved the study.In the experiment, 114 elderly patients with type 2 diabetes and cataract surgery from January 2019 to December 2020 were selected and divided into two groups by the random number table, 57 cases in each group. Among them, there were 28 females and 27 males in the study group: ages of 61–78 (69.13 ± 4.21) years with 21 cases of left eye disease and 21 cases of right eye disease. In the control group, there were 26 females and 29 males: ages of 63–76 (68.89 ± 4.27) years with 20 cases of left eye disease and 22 cases of right eye disease. There was no statistically significant difference between the two groups of general information  type 1 diabetes, (2) acute and chronic infectious diseases, (3) drug exocrine pancreatic diseases, (4) endocrine diseases such as hypercortisolism, (5) patients with severe mental and/or neurological diseases, (6) patients with chronic liver and kidney diseases, (7) patients treated with glucocorticoids, (8) patients with anemia and hematological diseases, (9) patients with a history of drug or alcohol dependence, (10) patients with autoimmune diseases, and (11) patients who use drugs that affect the immune response.Before the experiment, it is essential to inquire for medical history and record basic information, including age, course of DM, altitude of habitual habitation, complications and severity of DM, prevalence of cardiovascular and respiratory illnesses, and cerebrovascular diseases. All participants' height (BH), weight, waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI) were taken after they awoke on an empty stomach (fasting for more than 8 hours).In the experiment, 10 ml of cubital venous blood was collected and submitted for examination. A part was used to measure glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), and postprandial blood glucose (PBG). The other part was used to determine biochemical indicators . After the collected data were comprehensive, statistical analysis will be performed. The grading standard of DM complications and severity refers to the grading standard of scientific research methods of metabolic syndrome commonly used in the endocrine system. Furthermore, the experiment was graded based on the existence of metabolic syndrome in each system component, with each syndrome receiving one point. Cardiovascular illnesses like premature atrial flutter, ventricular flutter, pericardial effusion, aortic valve calcification, tricuspid valve regurgitation, aortic valve calcification and regurgitation, and pulmonary valve regurgitation were all mentioned.Respiratory diseases such as chronic bronchitis, emphysema, pulmonary hypertension, lung inflammation, pleural effusion, interstitial pulmonary fibrosis, pulmonary heart disease, and respiratory failure were also scored according to the number of diseases. In addition, cerebrovascular diseases such as cerebral infarction, cerebral ischemia, senile brain, and other diseases were scored by the number of diseases. According to the above method, the prevalence of cardiovascular and respiratory diseases and cerebrovascular diseases was converted into scores and quantified as observation indicators. The scores of different system diseases were accumulated in sequence and analyzed statistically.x ± S). Moreover, the significance test between the groups uses one-way analysis of variance, the pairwise comparison uses the LSD test method, and the regression analysis is performed simultaneously. Finally, the count data uses the χ2 test, and the test level is α = 0.05.In the statistical method, the experiment uses SPSS 19.0 statistical software to analyze the data, and the measurement data results are expressed as mean ± standard deviation (This article analyzes the influencing factors through experimental research, including age, course of DM, complications of DM, cardiopulmonary disease, cerebrovascular disease, permanent low altitude, and other factors. Moreover, this paper uses factor analysis to obtain the above-mentioned main factors, analyzes these influencing factors through the deep neural network model of this paper, and develops targeted nursing methods. In addition, this paper uses the sample data of this paper as input and uses deep neural network to process the data and get the corresponding results.First, this paper analyzes the correlation between age and the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients, and the results are shown in This article analyzes the correlation between the course of DM and the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients, and the results are shown in This article analyzes the correlation between the DM complications and the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients, and the results are shown in This article analyzes the correlation between cardiopulmonary diseases and the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients, and the results are shown in This article analyzes the correlation between the resident at low altitude and the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients, and the results are shown in The pancreatic islet function of the elderly gradually declines with age. As the age continues to increase, INS resistance will gradually increase with the increase of age. Moreover, the body's resistance to the outside world will be low for older people, and infection will occur easily. The condition is easily disturbed by psychological reasons. Moreover, patients often have different systemic diseases and need to cross medication, so hypoglycemic drugs are limited. As a result, patients' blood sugar increases with age and becomes more and more difficult to control. In addition, the cognition level of the elderly gradually decreases with age. The main manifestations are poor ability to accept new things, inability to strictly follow the doctor's instructions for diet and exercise treatment, and inability to use oral medication or insulin on time, and some patients even use the wrong medication, which will affect the patient's blood sugar control.When the patient has pulmonary heart disease, it will cause insulin resistance in the body itself. If the patient is in a more serious condition, the pancreatic islet B cells will be severely damaged, and the body will secrete more hormones that raise blood sugar than usual. Moreover, the liver's glucose metabolism is lower than normal. All of the above factors make it difficult to control blood sugar. In patients with coronary heart disease, because they cannot eat foods high in sodium or fat, they will gradually change their diet and eat some foods with high starch and high sugar content.Moreover, the patient's heart burden is very heavy and they canno't do too much activity, making it difficult to control blood sugar after a meal. Drugs used to treat cardiovascular diseases may also affect glucose metabolism, so blood sugar and HbA1c levels increase. Patients with the cerebrovascular disease will have reduced self-care ability, irregular diet and medication, and restricted exercise after meals, which will cause poor blood sugar control.With the prolongation of the course of DM, blood sugar will become more and more difficult to control. At this time, B-cell function gradually declines, insulin concentration in the body decreases with the course of the disease, and blood sugar is more difficult to control, which is consistent with this result.Diabetes itself does not cause serious physical harm to patients. However, long-term hyperglycemia may cause various concurrent diseases, and diabetes can cause great pressure on major body organs such as the heart and brain blood vessels, liver, and kidneys and may be fatal in critical conditions. Patients with diabetic retinopathy have lower self-care ability than normal people, and oral medication and insulin are restricted. The INS of patients with DM nephropathy will slowly accumulate in the human body and cannot be excreted normally. Patients with peripheral neuropathy will have numbness and pain in their limbs, and the patient's mood will be poor, sleep will be affected, and blood sugar will also change accordingly. In addition, patients with acute complications of DM have insufficient secretion of INS, which has a more pronounced impact on HbA1c levels.Under high altitude stimulation, various metabolic rates in the human body will increase, disturbing the source and the way of glucose and leading to increased blood sugar.Elderly type 2 diabetic patients have poor overall blood glucose control, and most patients have high blood glucose levels. In nursing, it is necessary to formulate targeted nursing strategies from age, DM course, complications of DM, cardiopulmonary disease, cerebrovascular disease, permanent low altitude, and other factors. At the same time, it is necessary to strengthen the publicity and education of patients' health and safety knowledge, enhance the awareness of patients, and enable patients to truly realize the role and significance of continuous diet care in diabetic patients. At the same time, it is necessary to pay attention to the psychological counseling of patients so that patients can actively obey nursing work and implement continuous diet care. In addition, it is necessary to provide patients with a scientific diet plan from a health point of view and prohibit patients from eating foods that are not conducive to the recovery of patients and ensure that the food is easy to digest and absorb. Finally, it is necessary to effectively stabilize the patient's blood sugar level and stabilize the patient's condition under diet care and medication intervention.


An increase in intraocular pressure during chronic hemodialysis is linked to ocular complications, such as glaucoma. The behavior of intraocular pressure during hemodiafiltration is unknown. Changes in intraocular pressure with a sodium dialysate concentration fixed at 138 mmol/L and an individualized concentration were studied in 13 patients with end-stage renal disease treated with hemodiafiltration. Up to 31% patients presented an episode of intraocular hypertension without differences between sodium profiles. A large variability in intraocular pressure within patients and a high prevalence of transient intraocular hypertension were found.Ocular complications are common among end-stage renal disease patients and some complications had been linked to increments of intraocular pressure (IOP) during hemodialysis. The changes of IOP during hemodiafiltration (HDF) have been scarcely investigated and the potential influence of the sodium dialysate concentration is unknown. The aim of this study was to compare the IOP changes during HDF with sodium dialysate concentration, either fixed or individualized. Thirteen end-stage renal disease patients participated in the study; they were treated with HDF using a dialysate sodium profile fixed at 138 mmol and another session with an individualized sodium profile. The intraocular pressure was measured before and after each session and every 30 min during HDF. Both groups had a similar HDF prescription, blood pressure, and biochemical parameters. At the end of hemodiafiltration, sodium concentration decreased only in the fixed sodium profile group. The number of patients with at least an episode of intraocular hypertension during HDF ranged from 5 (19%) to 8 (31%) without significant differences between right and left eye nor between dialysate sodium concentration. During HDF, there is a large variability of IOP; transient events of intraocular hypertension are highly prevalent in this sample, and they are not related to the sodium dialysate concentration. End-stage renal disease is a major public health problem in industrialized and developing countries, it is highly prevalent and requires expensive therapies to maintain patients’ long-term survival ,2. ThereIn healthy individuals, an increase in salt consumption is associated to a discrete decrease on IOP . MoreoveThere are several case reports of important IOP increments, glaucoma and retro-ocular pain during hemodialysis ,15,16,17In a previous study, it was shown that the IOP during HD and hemodiafiltration (HDF) has a similar behavior . HoweverThis exploratory study included 13 adult patients with end-stage renal disease, under treatment with HDF three times per week for at least 3 months. Patients were recruited consecutively (non-random sampling). Inclusion criteria were male or female adult patients. Exclusion criteria were previous symptoms of retro-ocular pain, previously diagnosed glaucoma, newly diagnosed glaucoma  or use of ocular hypotensive drugs. Elimination criteria were patients that showed hemodynamic instability during hemodialysis .All patients underwent ophthalmological bio-microscopy and fundoscopy by an ophthalmologist. IOP was measured in both eyes under topical anesthesia with tetracaine 0.5% eyedrops in both eyes. All procedures performed in studies involving human participants were in accordance with the ethical standards of the Research and Ethics Committee of the Instituto Nacional de Cardiología Ignacio Chávez (protocol number 14-891) and with the 1964 Helsinki declaration and its later amendments. Informed consent was obtained from all the participants.3− = 35, Na+ = 138, K+ = 2; (mEq/L) Ca2+ = 3.5, Mg2+ = 1, and polysulfone membranes were used . Two dialysate solutions were used, each with a different sodium’s concentration. Each patient received one HDF session with a profile of dialysate sodium concentration fixed at 138 mmol/L (standard sodium concentration in our center) and another HDF session with individualized sodium. The personalized profile started the HDF session with a dialysate sodium concentration was set to the same value of the venous sodium concentration and gradually moved towards the standard concentration during HDF (one mEq/L every 36 min). Every session lasted 3 h with fixed ultrafiltration profile and HDF were similar in both sessions . Ultrapure dialysate (mmol/L): HCOsessions . All pat+ + K+) + ([glucose]/18) + ([blood urea nitrogen]/2.8).Before the dialysis started, a venous blood sample was obtained in order to measure biochemical parameters . The following dialysis parameters were recorded at 30, 60, 90, 120, 150, and 180 min during HDF and 30 min after the end of the session: systolic and diastolic blood pressure, heart rate, temperature, and oxygen saturation level. At the end of the session, a blood sample was obtained from the venous access to obtain the same parameters as in the first blood sample and the following dialysis parameters were recorded: total filtration volume (mL), ultrafiltration rate (mL/h), blood flow rate (mL/min), arterial pressure (mmHg), venous pressure (mmHg) and final body weight (Kg). The osmolality was estimated with the following formulae: osmolality = 2 × . Baseline IOP was measured before the beginning of dialysis. During dialysis, intraocular pressure was evaluated in millimeters of mercury (mmHg) at the following times: 30, 60, 90, 120, 150, 180 min, and after the end of the session. Intraocular hypertension episode was defined as an intraocular pressure ≥22 mmHg measured during hemodialysis.t test (two group comparisons) or analysis of variance for repeated samples with post-hoc analysis using the Bonferroni method (3 or more groups). The variables without a normal distribution are reported as median (percentile 25–percentile 75) and were compared with the U Mann–Whitney test. The absolute value and percentage were used to report qualitative variables and were compared with Chi-squared test or Exact Fisher’s test. The statistical analysis was performed with SPSS version 15.0 (IBM). Considering that there are no previous reports on the effect of the sodium dialysate profile tested in this study, we could not perform an a priori sample size estimation. However, we estimated an achieved statistical power of 0.56 with the results of the present exploratory study , urate nephropathy (n = 3), IgA nephropathy (n = 2), kidney-transplant rejection (n = 4), focal segmental glomerulosclerosis (n = 1), or collapsing glomerulopathy (n = 1). The hemoglobin measured by routinely laboratory measurements in both groups before HDF sessions was 9.7± 3.1 g/dL and after HDF sessions was 12 ± 3.2 g/dL (p < 0.01). The vascular access was arteriovenous fistula (n = 7) or central venous catheter (n = 6).The study included 13 patients (eight men and five women), with mean age 42 ± 7 years old, median HD vintage was 191 (80–436) weeks. End-stage renal disease etiology was systemic lupus erythematosus  and the severity of these changes (IOP change ≥6 mmHg) to increase towards the end of the HDF in both groups. Despite a significantly lower osmolality in the fixed sodium profile at the end of the HDF compared with the beginning of it, there was no difference compared with the individualized sodium profile and the IOP values. Although the results did show a significant difference of sodium after dialysis (137.7 ± 1.3 vs. 138.9 ± 2.5 mEq/L), this difference might be too small to cause any difference of IOP. Probably the variation in IOP relies with much more importance in the production of aqueous humor rather than the outflow from the eye.A previous study found that increased blood glucose levels decrease IOP in hemodialysis . HoweverIOP is given by the flow rate of the aqueous humor that drains in the trabecular meshwork into the Schlemm canal, the input rate of aqueous flow and the episcleral venous pressure. The modification in any of these variables will modify IOP. Whether the output of aqueous flow rate decreases or the input flow rate or the episcleral venous pressure increases, the IOP will also increase . AlthougDuring HDF, the body fluid volume, plasma osmolarity, and electrolyte concentration is corrected . It has The transient increase of IOP during HDF may be subject to a therapeutic intervention as part of the management of patients during the HDF session. However, the changes are rather heterogenous in hemodialysis ,37, for The measuring of IOP is a technical challenge, although applanation tonometry is the most accurate method, it requires the patient to sit and mount a slit lamp inside the hemodialysis center. Furthermore, changes in the position of the patient are routinely made as part of hypotension management, which is a difficulty for the application of applanation tonometry . TonopenAn important advantage in this study is that the same individuals received both sodium profiles with similar HDF prescriptions; therefore, there was a better control of variability among individuals. Another advantage is the frequency of intra-dialysis IOP measurements, which is likely to allow the identification of transient IOP changes. The limitations in this study include the small number of participants  and the measurement of the data from only one HDF session per group. The limited number of volunteers in this study compromises the external validity of our findings, which should be corroborated with further clinical research. On the grounds that there is a great variability in IOP during hemodiafiltration, IOP measurement should be taken into consideration in patients with risk factors of developing glaucoma. It is known that there is a diurnal variation of IOP intraocular pressure, the mean range of fluctuation is 5 mmHg . TherefoThere is a large variability of IOP during HDF. Transient events of intraocular hypertension are highly prevalent during this HDF pilot study and they are not related to sodium concentration nor osmolarity. The results of this exploratory study highlight the need for more pertinent diagnostic and treatment strategies to prevent further visual field damage in dialysis patients.


Introduction: Evidence suggests the high capability of non-invasive assessment of the End-tidal carbondioxide (ETCO2) in predicting changes in arterial carbon dioxide pressure (PCO2) following major surgeries in children. We aimed to compare EtCO2 values measured by capnography with mainstream device and EtCO2 values assessed by arterial blood gas analysis before and after cardiopulmonary bypass pumping in cyanotic children.Methods: This cross-sectional study was performed on 32 children aged less than 12 years with ASA II suffering cyanotic heart diseases and undergoing elective cardiopulmonary bypass pumping. Arterial blood sample was prepared through arterial line before and after pumping and arterial blood gas (ABG)was analyzed. Simultaneously, the value of EtCO2 was measured by capnography with mainstream device.Results: A significant direct relationship was found between the changes in ETCO2 and arterialPCO2  postoperatively. According to significant linear association between postoperative change in ETCO2 and arterial PCO2, we revealed a new linear formula between the two indices: ΔPCO2 = 0.89× ETCO2-0.54. The association between arterial PCO2 and ETCO2 remained significant adjusted for gender, age, and body weight.Conclusion: the value of ETCO2 can reliability estimate postoperative changes in arterial PCO2 in cyanotic children undergoing cardiopulmonary bypass pumping. Capnography as a tool for measuring EtCO2 has become more common in recent years. Continuous measurement of EtCO2 is one of the methods used in the operating room for evaluation of hemodynamic state during general anesthesia and also in intubated patients. But it can even be a non-invasive, fast and reliable method for predicting PaCo2 in non-intubated patients. This measurement makes it possible to estimate arterial PaCo2 without the need for arterial blood sampling. If there is a constant relationship between PaCo2 and EtCO2, this method is reliable and there is no need for frequent arterial blood extraction. Using this method can provide necessary information about the patient’s respiratory status quantitatively with high reliability. Therefore, in any type of monitor, the relationship between measured EtCO2 and arterial blood PaCO2 is an important and significant point. The difference between EtCO2 and PaCO2 represents the pulmonary dead space. Acute increase in dead space, such as in pulmonary embolism, widens this gap. This criterion also indicates the presence of shunting. In some studies, the association between EtCO2 and PaCO2 has been established, but the accuracy of this method is still debated. In a study comparing the relationship between EtCO2 and PaCO2 in the prone and supine positions, it was found that under normal circumstances, EtCO2 is a useful tool for monitoring PaCO2, but its accuracy may decrease when using different surgical techniques and in different positions.The partial pressure of arterial carbon dioxide (PaCo2) is one of the effective and determining factors of blood pH, so its changes can cause many problems for critically ill patients. Because the likelihood of these changes during anesthesia is very high and it is not possible to continuously monitor PaCo2 directly, so during anesthesia, End-tidal CO2 (EtCO2) monitoring is used to estimate PaCo2, which is one of the standard monitoring methods during anesthesia and is often used as a non-invasive method for patients under anesthesia as well as in recovery and intensive care units. In addition, studies have been performed to measure EtCO2 to predict relative PaCo2 or blood bicarbonate levels. Based on the gas sampling method, infrared monitoring of PaCO2 is divided into two mainstream and sidestream methods. Sidestream capnography depends on the amount of gas removed from where the endotracheal tube is attached to the anesthesia machine. If the gas extraction rate is higher than the exhaust gas, the sample is mixed with fresh gas and the measurement accuracy will not be correct. In the Mainstream type, because the capnometer is placed directly on the endotracheal tube, the reaction time is faster and the probability of error is low, but there is a possibility of the endotracheal tube closing due to the weight of the sensor. Sidestream capnographs are highly dependent on the amount of gas that separates from the main breath system and reaches the monitor. In the present study, mainstream devices were used. In the present study, we aimed to compare EtCO2 values measured by capnography with mainstream device and PaCO2 values assessed by arterial blood gas analysis before and after cardiopulmonary bypass pump in cyanotic children. In fact, we attempted to determine the accuracy of measuring EtCO2 by direct capnography and the effect of pumping on its measurement in cardiac cyanotic children.Overall, measuring and monitoring EtCO2 is an important aspect of critical patient care. While EtCO2 monitoring was initially used by physicians to verify the location of endotracheal tubes and mechanical ventilation of patients in the emergency department, today, it is increasingly used for purposes such as monitoring the quality of cardiac resuscitation and assessing the causes of bronchospasm.This cross-sectional study was performed on 32 children aged less than 12 years with ASA II suffering cardiac cyanotic disorders and undergoing elective surgical correction at Pediatric Medical Center in Tehran between January and March 2019. All subjects were operated on by a single team and also had the same anesthesia procedure. In this regard, reluctance of the child’s parents to cooperate in the project, recent colds, airway abnormalities, difficult intubation, high arterial pulmonary pressure, and emergency surgery were considered as the exclusion criteria. The study protocol was ethically approved by the ethical committee at Tehran University of Medical Sciences. The basis for patients’ choice is heart surgery, which requires that an arterial blood sample be taken from the patient during the operation, and from this point of view, there is no moral problem in taking an arterial blood sample.After standard monitoring and induction of anesthesia which were the same in all patients, after initial premedication with fentanyl (2 μg/kg), induction of anesthesia was scheduled with fentanyl (5 μg/kg) plus midazolam (0.05 mg/kg) and cisatracurium (0.15 mg/kg) and achieving sufficient depth of anesthesia, tracheal intubation was performed through the nose and patients were connected to a ventilator. Immediately after intubation, the arterial line was inserted using 20 or 22 gauge arterial catheters from the radial artery of the patient’s right hand. Maintenance of anesthesia was performed with isoflurane (1.5%) and oxygen (100%). The dose of fentanyl was repeated at intervals of one hour. Arterial blood sample was prepared through arterial line before and after cardiopulmonary bypass pumping (CPB) and arterial blood gas (ABG) was analyzed by the GEM Premier 3000 machine. Simultaneously, the value of EtCO2 was measured by capnography with mainstream device. Such measurements were done both before and after CPB. Hemodynamic parameters including systolic and diastolic blood pressure, heart rate and arterial oxygen saturation were also assessed before and after cardiopulmonary bypass.For statistical analysis, results were presented as mean ± standard deviation (SD) for quantitative variables and were summarized by frequency (percentage) for categorical variables. The values of study parameters before and after the procedure were compared using the Paired t test or Wilcoxon test. The agreement between the values of EtCO2 assessed by capnography and PaCO2 measured by arterial blood gas analysis was also examined by the Kappa agreement test. For the statistical analysis, the statistical software SPSS version 23.0 for windows  was used.Overall, 32 children  were included into the study. The age of participants ranged from 6 days to 12 years that 31.2% were neonates, 43.8% were infants, and 25% aged higher than 2 years. The mean weight of the patients was also 7.98 ± 6.22kg. Due to non-parametric distribution of weight in the study subjects, the median of this index was determined as 8.0 kg .The change in both arterial PCO2 and ETCO2 parameters were not significant after cardiopulmonary bypass pumping in cyanotic children remained statistically insignificant and only hemodynamic indices including systolic and diastolic blood pressures as well as arterial oxygen saturation significantly changed that would be related to anesthesia and also procedural-related changes. However, we revealed a direct strong association between the changes in arterial PCO2 and ETCO2 indices after surgery indicating high value of assessing the changes in ETCO2 in predicting postoperative changes in arterial PCO2. The assessment of arterial PCO2 is very important to predicting critical postsurgical outcome especially hemodynamic instability that can be closely linked to patients’ poor outcome. In this regard and aided by the found linear association between PCO2 and ETCO2 parameters, we will be able to easily and noninvasively predict abnormal arterial PCO2 occurs after major surgeries. ETCO2 underestimated venous PCO2 values in neonates and infants under general anesthesia, but they introduced transcutaneous CO2 (tcPCO2) as a valuable parameters to closely approximate venous blood gas values. Wahba et al also showed that the changes in ETCO2 did not accurately indicate the direction and extent of the change in arterial PCO2. However, similar to our results, some studies emphasized the value of ETCO2 in predicting the change in hemodynamic changes following major surgeries particularly cardiac surgeries. As similarly shown by Donati et al, ETCO2 recordings were reliable, and can help in maintaining normocarbia during the short but unstable period associated with rewarming following cardiac surgery. Shibutani et al also revealed that decreases in ETCO2 quantitatively reflected the decreases in CO2 elimination. Burrows also indicated that PETCO2 correlated closely with the arterial PCO2 in the normal and acyanotic groups. Finally, Bissonnette et al showed that single breath ETCO2 measurements from the proximal end of the endotracheal tube accurately estimate the arterial PCO2 in infants and children.Some other similar studies attempted to assess the link between arterial PCO2 and ETCO2 in both children and adults especially following major surgeries, however some believe that ETCO2 might underestimate the value of PCO2 in children under anesthesia. In a recent study by Arvind Chandrakantan et al, Moreover, ETCO2 measurements obtained from the proximal end of the endotracheal tube could not accurately predict arterial PCO2 values in infants and children, however proximal measurements of ETCO2 can accurately estimate arterial PCO2. Thus, measuring ETCO2 obtained from proximal zone of tube can accurately estimate postoperative PCO2 among children undergoing cardiac procedures.As another important finding in the present study was that the value of ETCO2 measured was affected by gender, age or body weight of children. However it was shown that the value of this parameter might be affect by both parameters of patients’ age as well as the site of measuring ETCO2. As the first point, it was shown that ETCO2 monitoring may not be reliable in older ages especially in adults, but it is contrarily valuable in children.Despite significant differences between ETCO2 and arterial CO2 in anesthetized cyanotic children before CPB, these measures become more relevant post CPB and after surgical correction; probably due to enhanced pulmonary blood circulation.There are no acknowledgements to be mentioned in this study.There is no competing interest to be mentioned in this study.This study was approved by the ethical committee of Tehran University of Medical sciences with approval I.D. IR.TUMS.CHMC.REC.1398.043There are no funding or financial interests in this study