产妇产后72 h乳汁分泌缺乏影响因素分析及列线图模型构建

吴梅, 王思思

吴梅, 王思思. 产妇产后72 h乳汁分泌缺乏影响因素分析及列线图模型构建[J]. 实用临床医药杂志, 2024, 28(4): 61-65, 69. DOI: 10.7619/jcmp.20233011
引用本文: 吴梅, 王思思. 产妇产后72 h乳汁分泌缺乏影响因素分析及列线图模型构建[J]. 实用临床医药杂志, 2024, 28(4): 61-65, 69. DOI: 10.7619/jcmp.20233011
WU Mei, WANG Sisi. Influencing factors of lactational insufficiency at 72 hours postpartum and construction of nomogram model[J]. Journal of Clinical Medicine in Practice, 2024, 28(4): 61-65, 69. DOI: 10.7619/jcmp.20233011
Citation: WU Mei, WANG Sisi. Influencing factors of lactational insufficiency at 72 hours postpartum and construction of nomogram model[J]. Journal of Clinical Medicine in Practice, 2024, 28(4): 61-65, 69. DOI: 10.7619/jcmp.20233011

产妇产后72 h乳汁分泌缺乏影响因素分析及列线图模型构建

基金项目: 

江苏省卫生健康委2021年度医学科研立项项目 M2021101

详细信息
    通讯作者:

    王思思, E-mail: 657884990@qq.com

  • 中图分类号: R714;R473.71;R319

Influencing factors of lactational insufficiency at 72 hours postpartum and construction of nomogram model

  • 摘要:
    目的 

    探讨产妇产后72 h乳汁分泌缺乏的影响因素并构建列线图模型。

    方法 

    选取住院分娩的345例产妇作为研究对象, 按照7∶3的比例分为建模组242例和验证组103例,并根据产后72 h乳汁分泌情况将建模组产妇分为乳汁分泌缺乏组69例和乳汁分泌正常组173例。收集产妇的临床资料,采用多因素Logistic回归模型分析产妇产后72 h乳汁分泌缺乏的影响因素; 采用R3.6.3软件构建预测产妇产后72 h乳汁分泌缺乏的列线图模型; 分别绘制受试者工作特征(ROC)曲线和校准曲线,评估列线图模型预测产妇产后72 h乳汁分泌缺乏的区分度和一致性。

    结果 

    建模组产妇年龄、孕次、分娩方式、乳头类型等与验证组比较,差异无统计学意义(P>0.05)。乳汁分泌缺乏组初产、剖宫产、分娩至开奶时间>1 h、婴儿24 h吮吸乳房次数≤6次、未进行乳房按摩产妇占比高于乳汁分泌正常组,差异有统计学意义(P<0.05); 多因素Logistic回归模型分析结果显示,产次、分娩方式、分娩至开奶时间、婴儿24 h吮吸乳房次数均为产妇产后72 h乳汁分泌缺乏的影响因素(OR=3.488、2.381、2.442、2.223, P<0.05)。ROC曲线显示,该列线图模型在建模组、验证组中预测产妇产后72 h乳汁分泌缺乏的曲线下面积分别为0.844(95%CI: 0.792~0.897)、0.863(95%CI: 0.791~0.935), 校准曲线斜率均接近1,且Hosmer-Lemeshow拟合优度检验结果显示该模型拟合良好(χ2=7.002、4.560, P=0.429、0.714)。

    结论 

    产次、分娩方式、分娩至开奶时间、婴儿24 h吮吸乳房次数为产妇产后72 h乳汁分泌缺乏的影响因素,据此构建的列线图预测模型具有较好的区分度和一致性。

    Abstract:
    Objective 

    To investigate the influencing factors of lactational insufficiency in 72 hours postpartum and to construct a nomogram model.

    Methods 

    A total of 345 puerperae who were hospitalized for delivery were selected as research subjects. According to a ratio of 7 to 3, they were divided into modeling group (242 cases) and validation group (103 cases). Based on the lactation situation at 72 hours postpartum, the modeling group was further divided into lactational insufficiency group (69 cases) and normal lactation group (173 cases). The clinical data of the puerperae were collected. Multivariate Logistic regression model was used to analyze the influencing factors of lactational insufficiency at 72 hours postpartum. R 3.6.3 software was used to construct a nomogram model for predicting lactational insufficiency at 72 hours postpartum. The receiver operating characteristic (ROC) curve and calibration curve were plotted to evaluate the discrimination and consistency of the nomogram model in predicting lactational insufficiency at 72 hours postpartum.

    Results 

    There were no significant differences in age, parity, delivery mode, nipple type, and other factors between the modeling group and the validation group (P>0.05). The proportions of primipara, cesarean section, time from delivery to milk expression >1 hour, the number of breastfeeding ≤6 times in 24 hours, and absence of breast massage in the lactational insufficiency group were higher than those in the normal lactation group (P < 0.05). Multivariate Logistic regression model analysis showed that parity, delivery mode, time from delivery to milk expression, and the number of breastfeeding in 24 hours were influencing factors of lactational insufficiency at 72 hours postpartum (OR=3.488, 2.381, 2.442, 2.223, P < 0.05). The ROC curve showed that the area under the curve of the nomogram model in the modeling group and the validation group was 0.844 (95%CI, 0.792 to 0.897) and 0.863 (95%CI, 0.791 to 0.935), respectively. The slope of calibration curve was close to 1, and the Hosmer-Lemeshow goodness-of-fit test showed that the model fitted well (χ2=7.002, 4.560, P=0.429, 0.714).

    Conclusion 

    Parity, delivery mode, time from delivery to milk expression, and the number of breastfeeding in 24 hours are influencing factors of lactational insufficiency at 72 hours postpartum. The nomogram prediction model constructed based on these factors has good discrimination and consistency.

  • 图  1   预测产妇产后72 h乳汁分泌缺乏的列线图模型

    图  2   列线图模型在建模组中的预测效能

    A: ROC曲线; B: 校准曲线。

    图  3   列线图模型在验证组中的预测效能

    A: ROC曲线; B: 校准曲线。

    表  1   建模组与验证组基线资料比较(x±s)[n(%)]

    指标 分类 建模组(n=242) 验证组(n=103) t/χ2 P
    年龄/岁 28.01±5.51 27.45±5.42 0.868 0.386
    孕前体质量指数/(kg/m2) 22.51±3.24 22.13±3.26 0.995 0.320
    孕次 1次 145(59.92) 57(55.34) 0.624 0.430
    ≥2次 97(40.08) 46(44.66)
    产次 初产 140(57.85) 51(49.51) 2.032 0.154
    经产 102(42.15) 52(50.49)
    分娩方式 阴道分娩 164(67.77) 63(61.17) 1.400 0.237
    剖宫产 78(32.23) 40(38.83)
    分娩至开奶时间 ≤1 h 159(65.70) 74(71.84) 1.243 0.265
    >1 h 83(34.30) 29(28.16)
    婴儿24 h吮吸乳房次数 ≤6次 74(30.58) 37(35.92) 0.945 0.331
    >6次 168(69.42) 66(64.08)
    乳头类型 突出 182(75.21) 71(68.93) 1.455 0.228
    凹陷/扁平 60(24.79) 32(31.07)
    乳房按摩 128(52.89) 48(46.60) 1.144 0.285
    114(47.11) 55(53.40)
    乳房胀痛程度 无/轻度 137(56.61) 63(61.17) 0.687 0.709
    中度 71(29.34) 28(27.18)
    重度 34(14.05) 12(11.65)
    下载: 导出CSV

    表  2   乳汁分泌正常组和乳汁分泌缺乏组基线资料比较(x±s)[n(%)]

    指标 分类 乳汁分泌正常组(n=173) 乳汁分泌缺乏组(n=69) t/χ2 P
    年龄/岁 28.36±5.62 27.14±5.25 1.553 0.122
    孕前体质量指数/(kg/m2) 22.27±3.18 23.10±3.39 1.799 0.073
    孕次 1次 98(56.65) 47(68.12) 2.701 0.100
    ≥2次 75(43.35) 22(31.88)
    产次 初产 88(50.87) 52(75.36) 12.138 <0.001
    经产 85(49.13) 17(24.64)
    分娩方式 阴道分娩 127(73.41) 37(53.62) 8.842 0.003
    剖宫产 46(26.59) 32(46.38)
    分娩至开奶时间 ≤1 h 125(72.25) 34(49.28) 11.558 0.001
    >1 h 48(27.75) 35(50.72)
    婴儿24 h吮吸乳房次数 ≤6次 41(23.70) 33(47.83) 13.526 <0.001
    >6次 132(76.30) 36(52.17)
    乳头类型 突出 134(77.46) 48(69.57) 1.647 0.199
    凹陷/扁平 39(22.54) 21(30.43)
    乳房按摩 100(57.80) 28(40.58) 5.873 0.015
    73(42.20) 41(59.42)
    乳房胀痛程度 无/轻度 99(57.22) 38(55.07) 1.965 0.374
    中度 53(30.64) 18(26.09)
    重度 21(12.14) 13(18.84)
    下载: 导出CSV

    表  3   产妇产后72 h乳汁分泌缺乏的多因素Logistic回归分析

    变量 β SE Wald χ2 P OR 95%CI
    产次 1.249 0.352 12.564 <0.001 3.488 1.748~6.958
    分娩方式 0.867 0.348 6.207 0.013 2.381 1.203~4.711
    分娩至开奶时间 0.893 0.338 6.972 0.008 2.442 1.259~4.737
    婴儿24 h吮吸乳房次数 0.799 0.333 5.756 0.016 2.223 1.157~4.269
    乳房按摩 0.385 0.327 1.384 0.239 1.469 0.774~2.789
    常量 -2.840 0.401 50.091 <0.001 0.058
    下载: 导出CSV
  • [1]

    LOCKYER F, MCCANN S, MOORE S E. Breast milk micronutrients and infant neurodevelopmental outcomes: a systematic review[J]. Nutrients, 2021, 13(11): 3848. doi: 10.3390/nu13113848

    [2]

    SHENDE P, KHANOLKAR B. Human breast milk-based nutritherapy: a blueprint for pediatric healthcare[J]. J Food Drug Anal, 2021, 29(2): 203-213.

    [3] 朱奕名, 朱金改, 余章斌. 产妇泌乳启动行为的研究进展[J]. 中华围产医学杂志, 2021, 24(7): 525-530.
    [4]

    FARAH E, BARGER M K, KLIMA C, et al. Impaired lactation: review of delayed lactogenesis and insufficient lactation[J]. J Midwifery Womens Health, 2021, 66(5): 631-640. doi: 10.1111/jmwh.13274

    [5]

    OTIM M E, OMAGINO E K, ALMARZOUQI A, et al. Exclusive breast-feeding in the first six months: findings from a cross-sectional survey in Mulago hospital, Uganda[J]. Afr Health Sci, 2022, 22(2): 535-544. doi: 10.4314/ahs.v22i2.62

    [6] 刘性英, 肖桂兰, 唐斌. 手法按摩联合低频脉冲治疗仪对缺乳初产妇乳汁分泌、母乳喂养成功率的影响[J]. 齐鲁护理杂志, 2022, 28(21): 134-137. https://www.cnki.com.cn/Article/CJFDTOTAL-QLHL202221044.htm
    [7]

    TANG X Y, PATTERSON P, MACKENZIE-SHALDERS K, et al. Workplace programmes for supporting breast-feeding: a systematic review and meta-analysis[J]. Public Health Nutr, 2021, 24(6): 1501-1513. doi: 10.1017/S1368980020004012

    [8]

    FAIZ K W. VAS: visual analog scale[J]. Tidsskr Nor Laegeforen, 2014, 134(3): 323. doi: 10.4045/tidsskr.13.1145

    [9]

    RÍOS J, VALERO-JARA V, THOMAS-VALDÉS S. Phytochemicals in breast milk and their benefits for infants[J]. Crit Rev Food Sci Nutr, 2022, 62(25): 6821-6836. doi: 10.1080/10408398.2021.1906627

    [10]

    SEN S. Breast milk and breastfeeding: benefits, barriers, maternal predictors, and opportunities for innovation[J]. Clin Ther, 2022, 44(2): 170-171. doi: 10.1016/j.clinthera.2021.11.004

    [11]

    HOCKAMP N, BURAK C, SIEVERS E, et al. Breast-feeding promotion in hospitals and prospective breast-feeding rates during the first year of life in two national surveys 1997-1998 and 2017-2019 in Germany[J]. Public Health Nutr, 2021, 24(9): 2411-2423. doi: 10.1017/S1368980021001099

    [12] 韩兴思, 郝俊兰, 王俊茹, 等. 产后72 h乳汁分泌量的影响因素分析[J]. 中国性科学, 2021, 30(11): 67-70. https://www.cnki.com.cn/Article/CJFDTOTAL-XKXZ202111023.htm
    [13] 杨桂清, 徐红军. 母婴分离产妇泌乳启动延迟影响因素及干预策略研究进展[J]. 齐鲁护理杂志, 2021, 27(13): 145-148. https://www.cnki.com.cn/Article/CJFDTOTAL-QLHL202113055.htm
    [14]

    ELDER M, MURPHY L, NOTESTINE S, et al. Realigning expectations with reality: a case study on maternal mental health during a difficult breastfeeding journey[J]. J Hum Lact, 2022, 38(1): 190-196. doi: 10.1177/08903344211031142

    [15] 骆琴, 彭树花, 骆佳美. 产妇产后初次泌乳时间及相关因素调查[J]. 华南预防医学, 2021, 47(12): 1506-1509. https://www.cnki.com.cn/Article/CJFDTOTAL-GDWF202112004.htm
    [16] 陈郁葱, 黄欣茵, 李映桃. 泌乳Ⅱ期乳汁分泌影响因素分析[J]. 中国妇幼保健, 2021, 36(12): 2830-2834. https://www.cnki.com.cn/Article/CJFDTOTAL-ZFYB202112047.htm
    [17] 姜艳丽, 高瑞玲, 陈建平, 等. 产妇泌乳Ⅱ期启动延迟发生现况及母婴相关行为因素[J]. 华南预防医学, 2022, 48(9): 1058-1061. https://www.cnki.com.cn/Article/CJFDTOTAL-GDWF202209006.htm
    [18]

    WEN J, YU G L, KONG Y, et al. An exploration of the breastfeeding behaviors of women after cesarean section: a qualitative study[J]. Int J Nurs Sci, 2020, 7(4): 419-426.

    [19]

    LIAN W N, DING J, XIONG T T, et al. Determinants of delayed onset of lactogenesis Ⅱ among women who delivered via Cesarean section at a tertiary hospital in China: a prospective cohort study[J]. Int Breastfeed J, 2022, 17(1): 81. doi: 10.1186/s13006-022-00523-3

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出版历程
  • 收稿日期:  2023-09-20
  • 修回日期:  2023-11-05
  • 网络出版日期:  2024-03-05
  • 刊出日期:  2024-02-27

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