Assessment of ovarian reserve based on hormonal parameters,ovarian volume,and antral follicle count in women with familial Mediterranean fever

Objective

To evaluate ovarian reserve in women with familial Mediterranean fever (FMF).

Study design

Thirty women with FMF (20–29 years) and thirty healthy controls (20–29 years) were admitted to this study. Basal serum levels of follicle-stimulating hormone (FSH), oestradiol (E2), luteinizing hormone (LH) and inhibin B were measured on cycle day 3. All participants underwent transvaginal ultrasonographic examination on the third day of their menstrual cycle for the determination of ovarian volume (OV) and total antral follicle count (AFC).

Results

Women with FMF had significantly higher concentrations of FSH, LH and E2 than healthy controls. Total AFC was significantly lower in women with FMF than in healthy controls. OV was also lower in the FMF group but there was no statistically significant difference in OV between the groups. Age was negatively associated with FSH and LH. Inhibin B was found to be negatively correlated with LH and OV.

Conclusions

In this preliminary study, the first in FMF patients, we found that ovarian reserve was reduced in women with FMF compared with healthy controls. FMF may affect the ovarian reserve but the mechanism of this effect is unclear.     

血小板相关参数对胶质瘤患者预后的影响

目的 探讨术前血小板相关参数对胶质瘤患者肿瘤复发的预测作用。方法 分析联勤保障部队第九〇九医院2015—2017年收治的93例胶质瘤患者临床病理资料,根据随访期间肿瘤是否复发分为无复发组（n=52）和复发组（n=41）,分析血小板相关参数与胶质瘤分级的相关性,采用ROC曲线分析血小板计数（PLT）、血小板体积分布宽度（PDW）、血小板压积(PCT)、平均血小板体积（MPV）、平均血小板体积/血小板计数（MPV/PLT）对肿瘤复发的预测作用,多因素Cox分析肿瘤复发的影响因素,采用Kaplan-Meier曲线分析这些因素对肿瘤复发的影响。结果 胶质瘤Ⅲ、Ⅳ级患者PLT、PCT、高于胶质瘤Ⅰ、Ⅱ级患者（t=-2.388、-2.335,均P<0.05）;胶质瘤Ⅲ、Ⅳ级患者中MPV、MPV/PLT低于胶质瘤Ⅰ、Ⅱ级患者（均P<0.05）;无复发组患者PLT和PCT低于复发组（均P<0.05）;无复发组患者MPV和MPV/PLT高于复发组（均P<0.05）;PLT的ROC曲线下面积（UAC）为0.630（95%CI=0.517~0.743,P=0.032）,阈值为216×10⁹/L;MPV的UAC为0.633（95%CI=0.518~0.747,P=0.029）,阈值为8.65 fL;MPV/PLT的UAC为0.731（95%CI=0.626~0.835,P<0.001）,阈值为0.040;多因素分析结果发现,肿瘤分级（Ⅲ、Ⅳ）、MPV≤8.65 fL、MPV/PLT≤0.040是术后肿瘤复发的危险因素（95%CI分别为1.778~3.530、1.730~4.450、1.811~6.067,均P<0.05）;肿瘤分级（Ⅲ、Ⅳ）预测术后肿瘤复发曲线下面积为0.679（95%CI=0.569~0.789,P=0.003）。Kaplan-Meier曲线分析显示,MPV≤8.65 fL患者术后3年复发率高于MPV>8.65 fL患者（Long Rank=10.990,P=0.001）;MPV/PLT≤0.040患者术后3年复发率高于MPV/PLT>0.040患者（Long Rank=6.289,P=0.012）。结论 胶质瘤患者术前MPV和MPV/PLT与术后肿瘤复发有关,可以用于肿瘤预后预测,具有一定临床意义。 [国际神经病学神经外科学杂志, 2023, 50(4): 29-33]     

Small antral follicle count (2–5 mm) and ovarian volume for prediction of pregnancy in in vitro fertilization cycles

Aims.?To assess the value of antral follicle count (AFC) and other parameters as predictors of pregnancy in in vitro fertilization (IVF).

Methods.?In a cohort study, unselected consecutive women in IVF treatment were evaluated. Pretreatment parameters included AFC (subpopulations of small (2–5?mm) and large (5–10?mm) AFC), ovarian volume, and ovarian stroma Doppler indices.

Results.?The study included 115 women of whom 38 (33%) were pregnant. Total AFC was significantly higher in the pregnant than in the non-pregnant group (13.7?±?5.8 vs. 11.3?±?5.3, p?=?0.034). On receiver operator characteristic (ROC) curve analysis, the pretreatment variables that were significantly associated with pregnancy were small AFC (2–5?mm), total AFC, and ovarian volume/AFC ratio. Women with a positive score (total AFC >15; small AFC (2–5?mm) >10; ovarian volume in mm³/AFC, <1400), had a significantly higher number of retrieved oocytes and a higher pregnancy rate than women with a negative score (12.1?±?5.1 vs. 8.7?±?5.0, p?=?0.027 and 58.3% vs. 30.1%, p?=?0.049, respectively). On multivariate logistic regression analysis, total AFC was the only significant and independent predictor of pregnancy (p?=?0.034).

Conclusion.?Pretreatment small AFC and ovarian volume may identify women with a higher probability to achieve pregnancy in IVF.     

Anti-Müllerian hormone and antral follicle count for prediction of ovarian stimulation response in polycystic ovary syndrome

Abstract

Objective: To evaluate the ability of a combination of multiple ovarian reserve markers to predict ovarian stimulation response in polycystic ovary syndrome (PCOS).

Methods: On cycle Day 3 of 75 infertile patients with PCOS, serum follicle stimulating hormone (FSH), luteinizing hormone (LH), and anti-Müllerian hormone (AMH) were measured, and antral follicle count (AFC) and ovarian volume (OV) were evaluated by transvaginal sonography (TVS). All patients underwent the same mild ovarian stimulation protocol using clomiphene citrate and highly purified FSH. Ovulation was monitored by TVS and confirmed by midluteal serum progesterone level.

Results: AMH, AFC, and “ovulation index” [OI, serum AMH (ng/ml)?×?bilateral AFC] were significantly lower in the ovulatory group (n?=?57, 76%) compared with the anovulatory group, whereas LH, FSH, LH/FSH ratio, and OV were not significantly different. Using receiver-operating characteristic curve analysis, the OI at a cutoff value of “85” had a sensitivity of 73.7% and a specificity of 72.2% in the prediction of ovulation, with an area under the curve of 0.733. Patients with OI?<?85 had significantly higher ovulation rate (p?<?0.001).

Conclusion: The OI, combining both AMH and AFC, is a potentially useful predictor of the outcome of ovarian stimulation in PCOS.     

血液营养指标预测老年粗隆间骨折术后1 年的死亡率

目的 回顾性分析血液营养指标对预测老年粗隆间骨折患者术后1 年死亡率的价值。方法 选取 2012 年1 月-2016 年1 月99 例年龄>65 岁,采用髓内钉手术治疗的粗隆间骨折患者。分析患者的性别、年龄、 入院血清白蛋白、总蛋白、球蛋白、前白蛋白、淋巴细胞计数（TLC）、血红蛋白、血清钾及钙等因素。手术后 随访1 年,随访患者生存情况。结果 99 例患者,术后随访1 年内死亡35 例。性别比较无差异（P >0.05）; 男女患者血液参数和淋巴细胞计数比较,差异无统计学意义（P >0.05）;男女的年龄、白蛋白含量及血红蛋白含 量比较,差异有统计学意义（P <0.05）。多因素线性回归分析显示,年龄和血红蛋白含量是预测术后1 年死亡 率的影响因素。结论 营养指标对粗隆间骨折患者的术后1 年死亡率有预测价值,年龄、血红蛋白及白蛋白对 死亡率有影响。     

Sysmex XS 800i 血细胞分析仪血小板计数性能评价

目的 评价Sysmex XS-800i 血细胞分析仪血小板(PLT)计数性能。 方法 遵照行业指南验证Sysmex XS-800i血细胞分析仪PLT计数的精密度、线性、携带污染率和正确度; 以显微镜计数法为参考方法对仪器低值PLT检测一致性、小红细胞(RBC)和大PLT的干扰性和仪器报警有效性进行评价。 结果 精密度、线性、携带污染率、正确度均符合行业标准。对于11×10⁹～55×10⁹ L^-1范围内的低值PLT,Sysmex XS-800i检测相关性(r=0.923 9)优于ADVIA 2120i(r=0.908 0); 平均红细胞体积(MCV)<70 fL或MCV<75 fL且PLT直方图异常时、平均血小板体积(MPV)>x^-+2s即MPV>12 fL时,仪器检测PLT结果均有显著性差别(P<0.05)。特异性较高的报警为“RBC大小不一”和“小RBC”,分别为89.47%和83.87%; 阳性预测值较高的报警为“RBC大小不一”(92.00%)。 结论 Sysmex XS-800i血细胞分析仪的PLT计数性能符合行业标准要求; 对低值PLT计数准确性良好,但抗小RBC、大PLT干扰能力较差。日常使用应结合仪器各相关报警的有效性,建立合适的人工镜检复检规则。     

Value of the use of absolute lymphocyte as surrogate for CD4 count in resource poor situations

Background:

The initiation of antiretroviral (ARV) drugs and monitoring of human immunodeficiency virus (HIV) treatment in developing nations such as sub-Sahara Africa is based on the clinical stage and level of CD4 count. Clinical stages can easily be determined using the World Health Organisation (WHO) criteria, this is not so with CD4 count where the right equipment and expertise are not easily available. This lead to various studies being carried out in search of surrogates for CD4 count with use of total lymphocyte count (TLC) being suggested by some studies.

Objective:

In situation where determination of CD4 cell count is not available or feasible, lymphocyte count is believed to be one alternative method for immunological classification of Acquired Immunodeficiency Syndrome (AIDS). Such assumption may not be true of every population. The objective is, therefore, to examine the correlation between the absolute lymphocyte count and the CD4+ lymphocyte count in HIV positive patients.

Materials and Methods:

One hundred and sixty-five consecutive HIV positive patients were recruited for the study before the commencement of ARV drugs over a period of 13 months. The haemotological parameters such as the CD4 count was done by flow cytometry using Partec cyflow counter machine made in Germany, with strict adherence to the manufacturer''s standard operating procedure. TLC were also determined using Sysmex haematology blood analyser, following the manufacturer''s standard operating procedure. Patients were then grouped into CD4 and Total lymphocyte (TLC) categories. These were then compared to determine if there is any correlation as shown in previous studies. Statistical analysis of data was done using Statistical Package for Social Sciences (SPSS) and statistical significance of data was based on P value of less than 0.05. There was significant positive correlation (P value 0.000) between TLC and CD4 count.

Results:

Majority of the patients with TLC less than 1000/mm^[3] had CD4 count <200 cells/μl. Using TLC <1000/mm^[3] threshold, there was high sensitivity of 81.8% but low specificity and positive predictive value of 47.5% and 19.4%, respectively, for CD4 count <200 cells/μl. Further assessment using TLC of <1,200/mm^[3] for the currently accepted CD4 count cut-off of <350 cells/μl for initiation of antiretroviral drugs, the sensitivity, specificity, positive predictive value were found to be 76.5%, 26.7%, 21.3%, respectively.

Conclusions:

Considering the low specificity and positive predictive value, it was concluded that the use of TLC of as a surrogate for CD4 count is unreliable. However, where there is no alternative, it could be used with caution bearing in mind its limitations.     

Is total lymphocyte count a predictor for CD4 cell count in initiation antiretroviral therapy in HIV-infected patients?

Background:

Since laboratory assessments of HIV-infected patients by flow cytometric methods are expensive and unavailable in resource-limited countries, total lymphocyte count by haematology cell counter is supposed to be a suitable surrogate marker to initiate and monitor course of the disease in these patients. The aim of this study was to evaluate the utility of total lymphocyte count as a surrogate marker for CD4 count in HIV-infected patients.

Patients and Methods:

In a prospective study 560 HIV-positive individuals evaluated for total and CD4 lymphocyte count. For correlation between CD4 count and total lymphocyte count, haemoglobin and haematocrit we defined cut-off values as 200 cell/μl, 1200 cell/μl, 12 gr/dl and 30%, respectively, and compared CD4 count with each parameter separately. Positive predictive value, negative predictive value, sensitivity and specificity of varying total lymphocyte count cutoffs were computed for CD4 count ≤ 200 cell/μl and ≤ 350 cell/μl.

Results:

Strong degree of correlation was noted between CD4 and total lymphocyte count (r: 0.610, P < 0.001). Mean and standard deviation of total lymphocyte count, haemoglobin and haematocrit in relation to CD4 count were calculated which indicated significant correlation between these variables. Kappa coefficient for agreement was also calculated which showed fair correlation between CD4 200 cell/μl and total lymphocyte count 1200 cell/μl (0.35).

Conclusion:

This study reveals that despite low sensitivity and specificity of total lymphocyte count as a surrogate marker for CD4, total lymphocyte count is of great importance and benefit in resource-limited settings.     

Rate of decline in CD4 count in HIV patients not on antiretroviral therapy

Background

The progressive decline in the CD4 count in HIV patients leads to a more general decline in immune functioning. The study has been carried out to determine the decline in CD4 count in HIV patients.

Methods

The study was conducted in a medical college hospital at Maharashtra. The information on baseline CD4 count was gathered from positive patient records registered in the central disease registry. The baseline CD4 count was the first count of CD4 obtained when the patient is diagnosed as HIV positive and further two subsequent readings. The time from baseline (t1) till the last CD4 count (t2) was divided into the different quartiles and the median decline in CD4 count in each quartile was determined. As the time between the two CD4 count measurements was not uniform the rate of change in CD4 was measured with respect to time as [X (t2) − X (t1)/(t2 − t1)]. Correlation was assessed using correlation coefficient.

Results

As the CD4 counts were following skewed distribution, the normality was achieved by cuberoot transformation. The overall rate of decline in CD4 count was estimated to be 35 cells/μL per year with 95% confidence interval (CI) as (17.01, 85.04). The correlation coefficient between decline in CD4 and the initial CD4 count in the four time quartiles was (r = −0.51; p = 0.001, r = −0.79; p = 0.000, r = −0.48; p = 0.015 and r = −0.80; p = 0.000) respectively. The median decline in the CD4 count in 0–6 months was 3 cells/μL, in (6–11) months was approximately 26 cells/μL, in (11–21.5) months was 30 cells/μL and in more than 21.5 months the median decline was 52 cells/μL.

Conclusions

There was a progressive decline in the CD4 count following HIV infection. An understanding of the influence of decline in CD4 count in HIV patients not on ART is important for clinical management of HIV disease.