Predicting postoperative nausea and vomiting after cesarean section ： a nomogram model combined with gastric ultrasound

doi:10.21203/rs.3.rs-3584621/v1

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Predicting postoperative nausea and vomiting after cesarean section ： a nomogram model combined with gastric ultrasound

https://doi.org/10.21203/rs.3.rs-3584621/v1

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We aimed to explore the independent risk factors for postoperative nausea and vomiting (PONV) after caesarean section and to establish and validate a nomogram prediction model combined with gastric ultrasound. Clinical data from 116 patients were randomly divided into training (n = 87) and validation groups (n = 29). Univariate and multivariate logistic regression were used to analyse the risk factors for PONV after the caesarean section. Independent risk factors related to PONV were identified, and a nomogram model was established. Receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) were employed to assess the predictive efficacy, accuracy, and clinical practicability of the model and internally verified. Twenty-four patients experienced PONV in the training group. Motion sickness history, a systolic blood pressure fall > 20%, and gastric volume were identified as independent PONV risk factors, which were used to construct a nomogram model. The area under the ROC curve values for predicting the training and validation groups were 0.813 and 0.738, respectively. DCA confirmed the clinical practicability and application. The nomogram model provides an intuitive and visual tool for rapid PONV risk assessment before a caesarean section, facilitating accurate, individualised perioperative management strategies and promoting rapid recovery.

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Health sciences/Medical research

Health sciences/Risk factors

Postoperative nausea and vomiting (PONV) is a common adverse reaction following a caesarean section. Griffith et al. reported that the incidence of PONV varies from 21–79% [1]. Numerous studies have demonstrated that PONV after a caesarean section not only increases the risk of postoperative bleeding and wound rupture but also affects the postpartum recovery of pregnant and breastfeeding women. Additionally, it can elevate the risk of postpartum depression [2–4]. Therefore, caesarean section guidelines also prioritise the prevention of PONV as a key aspect of ensuring rapid postoperative recovery [5]. Current PONV prevention strategies mainly include the prophylactic use of antiemetic drugs, multimodal analgesia, and the perioperative administration of dexmedetomidine [2]. However, most current interventions carry potential risks for pregnant women and may impact newborns either through placental transplantation or during breastfeeding [6]. Therefore, it becomes crucial to perform individualised PONV risk assessments in pregnant women before a caesarean section. The Apfel score is presently employed to assess patient susceptibility to PONV based on risk factors such as female sex, non-smoking status, opioid use, previous history of PONV, and motion sickness [7]. However, as all caesarean section recipients are non-smoking women who typically receive postoperative opioids by default, the Apfel score may have limitations in predicting PONV occurrence in this population [8]. Furthermore, in addition to common anaesthetic and surgical factors and the physiological changes occurring in pregnant women, such as increased gastric pressure due to the upward displacement of the uterus during pregnancy [9], Hong et al. showed that the increase in gastric volume in pregnant women compared to non-pregnant women is a significant factor contributing to the elevated risk of PONV [10]. Gastric ultrasound, a non-invasive method for evaluating gastric contents, has been extensively studied in the field of anaesthesiology [11]. Chen et al. found that the gastric content and volume in pregnant women can be calculated according to the cross-sectional area (CSA) of the gastric antrum [12]. Therefore, the objective of this study was to combine gastric ultrasound assessments of pregnant women with a comprehensive collection of PONV-related risk factors for caesarean sections. This would enable us to establish a caesarean section-specific PONV prediction model, offering valuable insights for clinical prevention and intervention.

2.1 Baseline characteristics

A total of 116 adult patients who underwent a caesarean section met the inclusion criteria, with 87 in the training group, among whom 24 (27.59%) experienced PONV. The validation group comprised 29 patients, with 8 (27.59%) developing PONV (Table 1). The difference between the two groups was not statistically significant (P > 0.05).

Table 1

Participant characteristics
	Cohort
Variable	Training (n = 87)	Validation (n = 29)	P Value
Age [mean ± s], y	30.26 ± 4.23	31.10 ± 3.52	0.338
Gestational age [mean ± s], weeks	38.07 ± 1.13	38.52 ± 1.40	0.127
BMI [mean ± s], kg/m²	26.95 ± 2.96	25.92 ± 4.11	0.220
History of smoking, %			0.681
Yes	6 (6.90%)	2 (6.90%)
No	81 (93.1%)	27 (93.10%)
Hyperemesis Gravidarum, %			0.574
Yes	13 (14.94%)	4 (13.80%)
No	74 (85.05%)	25 (86.21%)
History of motion sickness, %			0.409
Yes	22 (25.29%)	6(20.69%)
No	65 (74.71%)	23 (79.31%)
History of PONV, %			0.091
Yes	17 (19.54%)	2(6.90%)
No	70 (80.46%)	27 (93.10%)
History of migraine, %			0.217
Yes	20 (22.99%)	4 (13.80%)
No	67 (77.01%)	25 (86.20%)
Gastric volume [mean ± s], ml	304.18 ± 43.55	292.14 ± 17.36	0.150
Operation time, %			0.062
≤ 60 min	58 (66.67%)	14(48.28%)
> 60 min	29 (33.33%)	15 (51.72%)
Anaesthesia time, %			0.362
≤ 90min	64 (73.56%)	23 (79.31%)
> 90min	23 (26.44%)	6 (20.69%)
Intraoperative dexamethasone, %			0.152
Yes	17 (19.54%)	9(31.03%)
No	70 (80.46%)	20(68.97%)
Intraoperative morphine, %			0.083
Yes	25 (28.74%)	4(13.79%)
No	62 (71.26%)	25 (86.21%)
Systolic blood pressure fall > 20%, %			0.400
Yes	16 (18.39%)	3 (10.34%)
No	71 (81.61%)	26 (89.66%)
Postoperative nausea and vomiting, %			0.601
Yes	24 (27.59%)	8(27.59%)
No	63 (72.41%)	21 (72.41%)

2.2 Analysis of PONV risk factors

The results of the univariate analysis showed that a history of motion sickness, gastric volume, and a systolic blood pressure fall > 20% were risk factors for PONV (P < 0.05, Table 2). These three variables were subsequently included in the logistic multivariate regression model, revealing that a history of motion sickness, gastric volume, and a systolic blood pressure fall > 20% were independent risk factors for PONV (P < 0.05; Table 3).

Table 2

Univariate logistic regression analysis in the training cohort
Variable	Β	OR (95%CI)	P Value
Age, y Gestational age, weeks	-0.011 0.153	0.989(0.884–1.106) 1.165 (0.765–1.774)	0.849 0.476
BMI, kg/m²	0.031	1.031 (0.880–1.208)	0705
History of smoking, yes or no	-0.293	1.341(0.229–7.845)	0.745
Hyperemesis Gravidarum, yes or no	0.981	2.667(0.793–8.968)	0.113
History of motion sickness, yes or no	1.110	3.036 (1.087–8.475)	0.034
History of PONV, yes or no	0.780	0.458 (0.151–1.390)	0.168
History of migraine, yes or no	0.532	1.702 (0.505–5.732)	0.391
Gastric volume, ml	0.014	1.014 (1.003–1.025)	0.012
Operation time＞60 min, yes or no	0.749	2.115(0.801–5.588)	0.131
Anaesthesia time＞90 min, yes or no	0.742	2.100(0.759–5.810)	0.153
Intraoperative dexamethasone, yes or no	-0.78	2.182 (0.719–6.620)	0.168
Intraoperative morphine, yes or no	0.916	0.400(0.121–1.321)	0.133
Systolic blood pressure fall > 20%, yes or no	1.915	6.786 (2.109–21.838)	0.001
PONV, postoperative nausea and vomiting; BMI, body mass index

Table 3

Multivariate logistic regression analysis in the training cohort
Variable	β	OR (95%CI)	P Value
History of motion sickness, yes or no	1.628	5.091 (1.474–17.581)	0.010
Gastric volume, ml	0.018	1.018 (1.005–1.032)	0.009
Systolic blood pressure fall > 20%, yes or no	2.061	9.515 (2.410-37.563)	0.001

2.3 Establishment and evaluation of the PONV nomogram

Based on the logistic analysis results, data from the three aforementioned predictors were input into the R 4.2.2 software to construct a nomogram model for predicting PONV following a caesarean section (Fig. 2). The constructed model underwent internal verification using the bootstrap method.

The area under the receiver operating characteristic (ROC) curve (AUC) values for the nomogram models in the training and validation groups were 0.813 (95% CI = 0.709–0.918) and 0.738 (95% CI = 0.594–0.942), respectively, indicating excellent prediction performance (Fig. 3). The calibration curve illustrated consistency between predicted and actual probabilities in both the training and validation sets (Fig. 4). Decision curve analysis revealed that when the threshold probability of the prediction model was > 7%, predicting PONV following a caesarean section using the nomogram led to the formulation of individualised prevention and treatment plans for PONV, offering greater clinical benefits compared to uniform interventions for all patients or no targeted interventions (Fig. 5).

2.4 PONV risk based on nomogram score

The Hosmer–Lemeshow goodness-of-fit test coefficient for the nomogram model was 0.076. When applied to distinguish the occurrence of PONV, the sensitivity, specificity, positive predictive value, and negative predictive value in the training group were 0.792, 0.841, 0.655, and 0.914, respectively. In the validation group, these values were 0.875, 0.667, 0.500, and 0.933, respectively (Table 4).

Table 4

Using the nomogram to evaluate the accuracy of postoperative nausea and vomiting
	Value (95% CI) Training Cohort	Validation cohort
AUC	0.813(0.709–0.918)	0.738 (0.594–0.942)
Hosmer–Lemeshow goodness-of-fit test Brier score	0.076 0.147 0.188
Cut-off probability	0.333	0.099
Youden index	0.633	0.541
Sensitivity	0.792	0.875
Specificity	0.841	0.667
Positive predictive value	0.655	0.500
Negative predictive value	0.914	0.933
Positive likelihood ratio	4.988	2.623
Positive likelihood ratio	0.248	0.188
AUC: area under curve

PONV is a common adverse reaction following surgery, including caesarean sections [1]. PONV not only increases the risk of other postoperative complications but also often causes discomfort to patients with nausea and vomiting, leading to reduced patient satisfaction and extended discharge time, imposing a substantial burden on patients [2].

In non-obstetric surgery, patient susceptibility to PONV is evaluated using the Apfel simplified risk score [7]. In the Apfel score, patient and anaesthesia factors contribute most to the risk of vomiting. For instance, the ORs for postoperative opioid use in women were reported as 4.78 and 2.44, respectively [7]. However, in patients undergoing spinal anaesthesia, these two factors generally exist by default, potentially limiting their predictive value for caesarean sections. In contrast, some maternal physiological and caesarean section-related factors may be associated with PONV risk; however, their predictive performance has not been integrated into the risk score prediction model. In addition, when evaluating the efficacy of the Apfel score, it was found that the AUC ROC of obstetric patients was 0.59, while that of non-obstetric patients was 0.753, further indicating the limited predictive performance of the Apfel score in the obstetric population [7].

To establish a specific risk prediction model for caesarean section, this study collected information on potential perioperative risk factors such as patients’ basic conditions, surgical factors, anaesthesia factors, and gastric ultrasound. In this study, a total of 32 patients developed PONV, accounting for 27.59% of the total sample size. Analysis of the collected data revealed that a history of motion sickness, gastric volume, and systolic blood pressure fall > 20% were independent risk factors for nausea and vomiting after caesarean section. Based on these three factors, a predictive model for nausea and vomiting after the caesarean section was established using R software and visualised as a nomogram. The model underwent verification and evaluation using the area under the ROC curve, calibration curve, and decision curve analysis. The model demonstrates good predictive performance and clinical application value.

Among the included indicators, a history of motion sickness has been widely confirmed to possess a high predictive value for PONV. Apfel and Koivaranta included it in their studies, constructing PONV prediction models that have found widespread use in clinical practice [7, 13]. The results highlighted that a history of motion sickness stands as an independent risk factor for PONV during caesarean section, with the incidence of PONV being 5.08 times higher in patients with this history than in those without [14]. Lee et al. further demonstrated the efficacy of prophylactic dexamethasone administration in reducing the incidence of PONV in patients with a history of motion sickness [15]. Horn et al. found that after spinal anaesthesia, hypotension caused by vasodilation, whether postural hypotension or hypotension caused by other factors, can stimulate the receptors of the central nervous system to release emetic neurochemical transmitters, resulting in nausea and vomiting. This is consistent with the results of the present study, illustrating that intraoperative hypotension is an independent risk factor for PONV during caesarean section [16]. The use of gastric ultrasound has become increasingly prevalent in obstetric anaesthesia in recent years [17, 18]. Hong et al. observed that pregnant women had larger gastric volumes than non-pregnant women, while Cozza et al. found that increased gastric volume corresponds to a higher incidence of PONV. Hamed et al. showed that preoperative metoclopramide administration could effectively reduce the incidence of PONV by decreasing gastric volume, further substantiating these findings [10, 19, 20]. The results of this study also suggest that increased stomach volume is an independent risk factor for PONV in caesarean sections.

The nomogram prediction model constructed in this study effectively foresees the risk of PONV in caesarean sections. Internal verification shows that the model exhibits good discrimination, consistency, and clinical utility. In the era of individualised precision medicine, which is gaining increasing attention, the ability to promptly identify caesarean section patients at risk of PONV and implement targeted preventive measures, such as preoperative antiemetic drugs administration, intraoperative management of blood pressure stability, adjustment of opioid dosage, auxiliary support, and other treatment measures, is invaluable. These measures can significantly enhance postoperative recovery speed and patient satisfaction.

However, this study has some limitations. First, this was conducted at a single centre with a relatively small sample size, potentially introducing selection bias. As such, further verification using larger, multicentre datasets is warranted to validate the study's results. Second, the scope of relevant factors considered in this study was limited, potentially overlooking certain risk factors associated with PONV. Follow-up studies can further expand patient data based on this study, identifying screen indicators with stronger correlations to PONV to establish a more precise prediction model. In this study, a nomogram model for predicting PONV was constructed by combining three independent risk factors identified through multivariate regression analysis. This model serves to optimise the preoperative evaluation system for caesarean sections, formulate individualised perioperative management strategies, accelerate recovery, and improve prognosis.

4.1 Patients

This prospective observational cohort study was approved by the Research Ethics Committee of the Second Affiliated Hospital of Fujian Medical University (2022 Ethics Review No.285). This study was conducted from August 2022 to February 2023, and the data of 116 adult patients who underwent caesarean sections were continuously collected. All participants gave written informed consent to take part in the study. The studies were performed in accordance with relevant guidelines/regulations, and conducted following the Helsinki Declaration and good clinical practice.

The inclusion criteria were as follows: (1) adult women who underwent caesarean section delivery under spinal anaesthesia; (2) American Society of Anesthesiologists (ASA) classification: I-III; and (3) single pregnancy ≥ 36 weeks. The exclusion criteria were as follows: (1) height < 152 cm or height > 180 cm; (2) patients who received antiemetic medication within 24 hours before caesarean section; (3) patients requiring emergency caesarean section; (4) pregnant women with severe hypertension during pregnancy (systolic blood pressure > 160 mmHg, diastolic blood pressure > 110 mmHg), heart disease, and diabetes; (5) patients treated with monoamine oxidase inhibitors or tricyclic antidepressants; and (6) morbid obesity (body mass index > 45 kg/m²).

4.2 Preoperative ultrasound assessment of gastric volume

Prior to surgery, ultrasonography was performed in the preparation room using a Mindray M6 ultrasonic diagnostic instrument equipped with a 3C5S convex array probe set to a frequency of 2–5 MHz. The pregnant woman was asked to assume the right position and the head of the bed was elevated to 45°. The probe was placed in the subxiphoid region, utilising the abdominal aorta and left lobe of the liver as localisation markers to obtain the sagittal plane of the scan [21]. The gastric antrum was explored through a sagittal section (Fig. 1), and the maximum anteroposterior diameter (AP) and craniocaudal diameter (CC) of the antrum were measured three consecutive times [21–23]. The average of each diameter was used to calculate the area of the gastric antrum area (CSA), CSA (cm²) = (AP * CC * π)/4 [24]. The gastric volume was calculated by measuring the CSA of the antrum: gastric volume (mL) = 270.76 + 13.68 * CSA − 1.20 * gestational age [12].

4.3 Intraoperative management

The patient was placed in the supine position before the operation, and the patient 's blood pressure was measured every 5 minutes for three consecutive times without interference. The baseline systolic blood pressure of the patient was determined by calculating the average of the three systolic blood pressures.

Spinal anaesthesia was followed by puncture in the L2/L3 space, and 15 mg 0.75% ropivacaine hydrochloride was injected into the subarachnoid space. The spinal needle was pulled out, and a 3–4 cm catheter was inserted into the head through an epidural puncture needle. Subsequently, the patient was immediately adjusted to the supine position, with appropriate left tilt and adjustment of the anaesthesia plane to the T6-T8 range. If the mother complained of pain for more than 1 min after successful delivery of the foetus, 2 mg of morphine was injected into the epidural space. Intravenous infusion of 8 µg norepinephrine was given immediately after spinal anaesthesia to maintain systolic blood pressure changes within 20% of the baseline. A systolic blood pressure fall of greater than 20% of the baseline or less than 90 mmHg was judged to be hypotension. Therefore, an additional 5 µg of norepinephrine was required, with the blood pressure monitored every 2 minutes, and medication was repeated according to the situation until the systolic blood pressure was maintained in the expected range. If the heart rate was under 50 beats/min, 0.5 mg atropine was administered, and an additional dose was given according to the situation. A rapid fluid infusion immediately after spinal anaesthesia was performed, with the aim of administering 500 ml of colloidal solution before delivery and subsequently maintaining the infusion rate. A caesarean section was performed in the lower uterine segment. After delivery, 10 U of ordinary oxytocin was injected into the uterus, and 100 µg (1 ml) of carbetocin was slowly intravenously injected within 1 min. Intraoperative maternal nausea or vomiting, the use of 10 mg dexamethasone treatment. Postoperative analgesia was performed using a postoperative analgesia pump (20 mg dezocine + 0.9% normal saline to 100 ml) and a patient-controlled intravenous analgesia mode.

4.4 Data collection

The primary outcome measure was the incidence of PONV within 24 h after surgery, as determined during follow-up on the second day after surgery. Postoperative vomiting data were collected through follow-up with patients, patients ' families, and nurses. Postoperative nausea data were collected using the visual analogue scale (VAS ) [25]. A VAS score of 0–1 was considered as no nausea, and a score above 1 was considered indicative of nausea. Data on the potential risk factors for PONV were obtained from patients before surgery, the electronic medical record system of our hospital, and data recorded during surgery. Gestational age, age, hyperemesis gravidarum, PONV history, motion sickness history, smoking history, migraine history, body mass index, gastric volume, operation time, anaesthesia time, intraoperative dexamethasone, intraoperative morphine, and systolic blood pressure fall > 20% were recorded.

4.5 Statistical analysis

SPSS 26.0.0.0 and R 4.2.2, were used for statistical analysis. A total of 116 patients were divided into the training and validation groups in a 3:1 ratio using a random number table. Categorical variables are expressed as an example (%), and measurement data are expressed as the mean ± standard deviation (xˉ ± s).

Categorical variables were compared using the χ² test, and measurement data were compared using an independent two-tailed t test. In all analyses, statistical significance was set at P < 0.05. The significance of each variable in the training group in the univariate analysis was included in the multivariate logistic regression analysis model to identify the independent risk factors associated with the occurrence of PONV. The "rms" package of R, version 4.2.2, was used to construct a nomogram prediction model. The bootstrap method was used to verify the nomogram internally, and the predictive performance of the nomogram was measured using the concordance index (C index) and calibrated with 1,000 bootstrap samples to decrease the overfit bias. The ROC curve was analysed to calculate the optimal cut-off value, which was determined by maximising the Youden index (sensitivity + specificity − 1). The accuracy of the optimal cut-off value was evaluated by sensitivity, specificity, predictive value, and likelihood ratio, and calibration and decision curves (decision curve analysis curves) were drawn to further supplement the accuracy, predictive efficacy, and clinical practicability of the evaluation model.

Acknowledgments: Not applicable.

Author Contributions: Conceptualization, Y.L. and H.Z.; methodology, Y.H.; software, H.Z.; validation, Y.L. and H.Z.; formal analysis, Y.L.; investigation, H.H.; resources, Y.L.; data curation, Y.L.; writing—original draft preparation, Y.L.; writing—review and editing, W.L.; visualization, Y.L.; supervision, W.L. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement: The datasets used and analysed during the current study available from the corresponding author (Weifeng Liu) on reasonable request.

Funding: This research received no external funding

Institutional Review Board Statement: This prospective observational cohort study was approved by the Research Ethics Committee of the Second Affiliated Hospital of Fujian Medical University (2022 Ethics Review No.285).

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Conflicts of Interest: The authors declare no competing interests.

Griffiths, J. D. et al. Interventions for preventing nausea and vomiting in women undergoing regional anaesthesia for caesarean section. Cochrane Database Syst. Rev. 5, Cd007579; 10.1002/14651858.CD007579.pub3 (2021).
Gan, T. J. et al. Fourth Consensus Guidelines for the Management of Postoperative Nausea and Vomiting. Anesth. Analg. 131, 411–448; 10.1213/ane.0000000000004833 (2020).
Wittels, B., Scott, D. T. & Sinatra, R. S. Exogenous opioids in human breast milk and acute neonatal neurobehavior: a preliminary study. Anesthesiology 73, 864–869; 10.1097/00000542-199011000-00012 (1990).
Eisenach, J. C., Grice, S. C. & Dewan, D. M. Patient-controlled analgesia following cesarean section: a comparison with epidural and intramuscular narcotics. Anesthesiology 68, 444–448; 10.1097/00000542-198803000-00023 (1988).
Macones, G. A. et al. Guidelines for postoperative care in cesarean delivery: Enhanced Recovery After Surgery (ERAS) Society recommendations (part 3). Am. J. Obstet. Gynecol. 221, 247.e1-.e9; 10.1016/j.ajog.2019.04.012 (2019).
Valentine, A. R., Carvalho, B., Lazo, T. A. & Riley, E. T. Scheduled acetaminophen with as-needed opioids compared to as-needed acetaminophen plus opioids for post-cesarean pain management. Int. J. Obstet. Anesth. 24, 210–216; 10.1016/j.ijoa.2015.03.006 (2015).
Apfel, C. C., Läärä, E., Koivuranta, M., Greim, C. A. & Roewer, N. A simplified risk score for predicting postoperative nausea and vomiting: conclusions from cross-validations between two centers. Anesthesiology 91, 693–700; 10.1097/00000542-199909000-00022 (1999).
Tan, H. S., Cooter, M., George, R. B. & Habib, A. S. A risk score for postoperative nausea and/or vomiting in women undergoing cesarean delivery with intrathecal morphine. Int. J. Obstet. Anesth. 44, 126–130; 10.1016/j.ijoa.2020.08.008 (2020).
Hundley, V., Downe, S. & Buckley, S. J. The initiation of labour at term gestation: Physiology and practice implications. Best Pract. Res. Clin. Obstet. Gynaecol. 67, 4–18; 10.1016/j.bpobgyn.2020.02.006 (2020).
Hong, J. Y., Park, J. W. & Oh, J. I. Comparison of preoperative gastric contents and serum gastrin concentrations in pregnant and nonpregnant women. J. Clin. Anesth. 17, 451–455; 10.1016/j.jclinane.2004.10.010 (2005).
Bouvet, L. et al. Reliability of gastric suctioning compared with ultrasound assessment of residual gastric volume: a prospective multicentre cohort study. Anaesthesia 75, 323–330; 10.1111/anae.14915 (2020).
Chen, X., Chen, F., Zhao, Q., Zhang, L. & Liu, Z. Ultrasonographic measurement of antral area for estimating gastric fluid volume in pregnant women. J. Clin. Anesth. 53, 70–73; 10.1016/j.jclinane.2018.06.040 (2019).
Koivuranta, M., Läärä, E., Snåre, L. & Alahuhta, S. A survey of postoperative nausea and vomiting. Anaesthesia 52, 443–449; 10.1111/j.1365-2044.1997.117-az0113.x (1997).
Figueredo, E. & Canosa, L. Prophylactic ondansetron for post-operative emesis: meta-analysis of its effectiveness in patients with and without a previous history of motion sickness. Eur. J. Anaesthesiol. 16, 556–564; 10.1046/j.1365-2346.1999.00541.x (1999).
Lee, Y., Lai, H. Y., Lin, P. C., Huang, S. J. & Lin, Y. S. Dexamethasone prevents postoperative nausea and vomiting more effectively in women with motion sickness. Can. J. Anaesth. 50, 232–237; 10.1007/bf03017790 (2003).
Horn, C. C., Wallisch, W. J., Homanics, G. E. & Williams, J. P. Pathophysiological and neurochemical mechanisms of postoperative nausea and vomiting. Eur. J. Pharmacol. 722, 55–66; 10.1016/j.ejphar.2013.10.037 (2014).
Haskins, S. C., Kruisselbrink, R., Boublik, J., Wu, C. L. & Perlas, A. Gastric ultrasound for the regional anesthesiologist and pain specialist. Reg. Anesth. Pain Med. 43, 689–698; 10.1097/aap.0000000000000846 (2018).
Fiszer, E., Aptekman, B., Baar, Y. & Weiniger, C. F. The effect of high-dose versus low-dose epidural fentanyl on gastric emptying in nonfasted parturients: A double-blinded randomised controlled trial. Eur. J. Anaesthesiol. 39, 50–57; 10.1097/eja.0000000000001514 (2022).
Cozza, V. et al. Prediction of postoperative nausea and vomiting by point-of-care gastric ultrasound: can we improve complications and length of stay in emergency surgery? A cohort study. BMC Anesthesiol. 21, 211; 10.1186/s12871-021-01428-0 (2021).
Hamed, E., Hamza, W. S., Farghaly, T. A. & Hamed, R. Ultrasonographic assessment of metoclopramide effect on gastric volume in parturients females undergoing Caesarean section: a randomized double blind study. Minerva Anestesiol. 89, 529–535; 10.23736/s0375-9393.22.16913-0 (2023).
Bouvet, L. et al. Could a single standardized ultrasonographic measurement of antral area be of interest for assessing gastric contents? A preliminary report. Eur. J. Anaesthesiol. 26, 1015–1019; 10.1097/EJA.0b013e32833161fd (2009).
Bouvet, L. et al. Clinical assessment of the ultrasonographic measurement of antral area for estimating preoperative gastric content and volume. Anesthesiology 114, 1086–1092; 10.1097/ALN.0b013e31820dee48 (2011).
Benini, L. et al. Simultaneous measurement of gastric emptying of a solid meal by ultrasound and by scintigraphy. Am. J. Gastroenterol. 94, 2861–2865; 10.1111/j.1572-0241.1999.01429.x (1999).
Van de Putte, P. & Perlas, A. Ultrasound assessment of gastric content and volume. Br. J. Anaesth. 113, 12–22; 10.1093/bja/aeu151 (2014).
Li, F., Zhu, L., Geng, Y. & Wang, G. Effect of hip replacement surgery on clinical efficacy, VAS score and Harris hip score in patients with femoral head necrosis. Am. J. Transl. Res. 13, 3851–3855 (2021).

No competing interests reported.

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Predicting postoperative nausea and vomiting after cesarean section ： a nomogram model combined with gastric ultrasound

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Abstract

Figures

1. Introduction

2. Results

2.1 Baseline characteristics

2.2 Analysis of PONV risk factors

2.3 Establishment and evaluation of the PONV nomogram

2.4 PONV risk based on nomogram score

3. Discussion

4. Methods

4.1 Patients

4.2 Preoperative ultrasound assessment of gastric volume

4.3 Intraoperative management

4.4 Data collection

4.5 Statistical analysis

Declarations

References

Additional Declarations

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