Objective To establish a clinical nursing pathway for elderly parturients. Methods The clinical nursing pathway draft for elderly parturients were designed though the method of case analysis and literature review. Delphi method was used by 10 experts engaged in clinical medical or nursing with 2 rounds. Results The recovery rates of the two Delphi method were 100%, the experts who put forward the proposal on the 2 rounds of expert conclusion were 60.00% (6/10) and 20.00% (2/10) respectively. The expert's familiarity with the correspondence is 0.90, the coefficient of judgment is 0.80 and the coefficient of authority is 0.85.The mean value and standard deviation of the 2 rounds of correspondence were 3.60～5.05 (standard deviation 0.34～0.94) and 3.91～4.13 (standard deviation 0.26～0.60)respectively. The coordination coefficients of the 2 rounds of experts consultation were 0.441 and 0.592 (all P＜0.001). The clinical nursing pathway for elderly parturients with pregnancy management were three stages: confirmed pregnancy to 13+6weeks, 14 weeks to 27+6days pregnant and 28 weeks pregnant to childbirth, including a total of 74 projects for 4 modules such as medical history collection, physical examination, clinical laboratory and other examination and nursing measures. Conclusions The practicable clinical nursing pathway for elderly parturients was constructed because its high degree of familiarity,authority,coordination and concentration. The statistical analysis results are reliable,it is beneficial to standardize the pregnancy management for elderly parturients and improve the quality of clinical nursing.

Metabolic characteristics of 39 human brain tumor tissues, including 15 astrocytomas, 13 fibroblastic meningiomas and 11 transitional meningiomas from 39 individual patients, have been studied using high resolution magic-angle spinning (HRMAS) 1H NMR spectroscopy in conjunction with principal component analysis (PCA). With rich metabolite information, 1H NMR spectra showed that the tumor-tissuc metabonome was dominated by lipids, lactate, myo-inositol, ereatine, choline metabolites such as choline, phosphocholine and glycerophosphocholine, amino acids such as alanine, glutamate, glutamine, taurine, N-acetyl-aspartate and glutathione. PCA of the tumor NMR spectra clearly showed metabonomic differences between low-grade astrocytomas and meningiomas whereas such differences were more moderate between fibroblastic and transitional meningiomas. Compared with meningiomas, the low-grade astrocytomas had higher levels of glycerophosphocholine, phosphocholine, myo-inositol and creatine but lower levels of alanine, glutamate, glutamine, glutathione and taurine. The N-acetyl-aspartate level was low but detectable in low-grade astrocytomas whereas it was not detectable in meningiomas. It is concluded that tissue metabonomics technology consisting of HRMAS 1H NMR spectroscopy and multivariate data analysis (MVDA) offers a useful tool (1) for distinguishing different types of brain tumors, (2) for providing the metabolic information for human brain tumors, which are potentially useful for understanding biochemistry of tumor progression.