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Inicio Endocrinología, Diabetes y Nutrición (English ed.) Validation of CIPA nutritional screening through prognostic clinical variables i...
Journal Information
Vol. 67. Issue 5.
Pages 304-309 (May 2020)
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2141
Vol. 67. Issue 5.
Pages 304-309 (May 2020)
Original article
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Validation of CIPA nutritional screening through prognostic clinical variables in hospitalized surgical patients
Validación del cribado nutricional CIPA mediante variables clínicas pronósticas en pacientes quirúrgicos hospitalizados
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2141
Alejandra Mora Mendozaa,b,
Corresponding author
almomend@gmail.com

Corresponding author.
, José Pablo Suárez Llanosa, Alba Sánchez Moralesb, Cristina Lorenzo Gonzáleza, Yolanda Zambrano Huertaa, Ignacio Llorente Gómez de Seguraa,b
a Servicio de Endocrinología y Nutrición, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
b Universidad de La Laguna, Facultad de Medicina, Santa Cruz de Tenerife, Spain
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Table 1. Baseline characteristics of the study sample.
Abstract
Introduction

CIPA (Control of Food Intake, Protein, and Anthropometry) nutritional screening is positive when one of the following conditions is met: Control of Food Intake for 48−72h <50%; Albumin <3g/dL, Body Mass Index <18.5kg/m2 or Arm Circumference ≤22.5cm. Following its validation in non-surgical inpatients, the same process was performed with surgical inpatients.

Objectives

Validity of the CIPA screening tool in surgical inpatients by comparison with Subjective Global Assessment (SGA) and analysis of clinical outcomes

Material and methods

A prospective study of hospitalized surgical patients, evaluating the prevalence or risk of malnutrition through CIPA and SGA. Analysis of hospital malnutrition according to CIPA screening and association with the clinical outcomes of median length of stay, mortality and early readmission. Concordance between both screening methods by Kappa Index (κ), sensitivity (S) and specificity (SP).

Results

A total of 226 patients were analysed. The prevalence of malnutrition or risk of malnutrition was identified by CIPA in 35.40% and by SGA in 30.08%. CIPA is capable of detecting patients at a greater risk of mortality during hospitalization (5% vs 0%, p=0.006), unlike the SGA (2.94% vs 1.27%, p=0.385). CIPA also detected patients with higher median length of stay (21 days, IQR 14–34 days vs 14.5 days, IQR 9–27 days, p=0.002) and rate of early readmissions (25.3% vs 8.2%, p<0.001). S and SP of CIPA vs SGA was 70.59% and 79.75% respectively; Kappa index was 0.479 (p<0.001).

Conclusions

Using CIPA nutritional screening, the prevalence and risk of malnutrition in surgical patients is high, and they present poorer clinical outcomes, making CIPA valid and effective in this type of patients.

Keywords:
Malnutrition
Hospitalization
Nutrition assessment
Prevalence
Prognosis
Surgery
Resumen
Introducción

El cribado nutricional CIPA (Control de Ingestas, Proteínas, Antropometría) es positivo cumpliendo al menos una de las siguientes condiciones: Control de Ingestas en 48−72h <50%; Albúmina <3g/dl, Índice de Masa Corporal <18,5kg/m2 o Circunferencia del Brazo ≤22,5cm. Tras su validación en pacientes hospitalizados con patologías no quirúrgicas, se realiza el mismo proceso en pacientes quirúrgicos.

Objetivos

validación del cribado CIPA en pacientes hospitalizados quirúrgicos mediante comparación con Valoración Global Subjetiva (VGS) y analizando el pronóstico clínico de los pacientes.

Material y métodos

estudio prospectivo de pacientes quirúrgicos hospitalizados, valorando la prevalencia o riesgo de desnutrición a través de CIPA y Valoración Global Subjetiva (VGS). Análisis de desnutrición hospitalaria a través de la asociación con las variables clínicas pronósticas estancia mediana, mortalidad y reingreso precoz. Concordancia entre ambos métodos de cribado mediante índice Kappa (κ), sensibilidad (S) y especificidad (E).

Resultados

Se analizan 226 pacientes. CIPA identifica una prevalencia de desnutrición o riesgo de padecerla del 35,40%, y VGS 30,08%. CIPA es capaz de detectar al paciente con mayor mortalidad hospitalaria (5% vs 0%, p=0,006), a diferencia de la VGS (2,94% vs 1,27%, p=0,385). CIPA también detectó aquellos con mayor estancia mediana (21 días, RIC 14-34 días vs 14,5 días, RIC 9-27 días, p=0,002) y reingresos precoces (25,3% vs 8,2%, p<0,001). S y E de CIPA vs VGS: 70,59% y 79,75% respectivamente; κ=0,479 (p<0,001).

Conclusiones

Mediante el cribado nutricional CIPA la prevalencia de desnutrición o riesgo de padecerla en pacientes quirúrgicos es elevada, y estos cursan con peor evolución clínica, siendo válido y efectivo en este tipo de pacientes.

Palabras clave:
Desnutrición
Hospitalización
Evaluación nutricional
Prevalencia
Pronóstico
Cirugía
Full Text
Introduction

The high prevalence of malnutrition in hospitals has become a public health problem, with a strong impact regardless of the country or health system involved.1,2 An estimated 20 million people are affected in Europe, with an annual cost of 120,000 million euros.3 When subjected to surgical procedures, such patients are in a greater state of stress derived from surgery and its associated catabolic response. In addition, they may experience other metabolic and physiological changes, with altered gastrointestinal function, symptoms such as nausea, vomiting or postoperative pain, paralytic ileus, perioperative fasting periods, and immobilization. Impaired patient nutritional status has a clear prognostic impact upon complications, recovery and postoperative mortality,4–6 and is associated with direct increments in healthcare costs. Nutritional support is indicated for both the prevention and treatment of catabolism-malnutrition, and there is evidence that improved nutritional status contributes to the prevention of postoperative complications and helps functional recovery.4

Despite the evidence, malnutrition in hospitals is often unrecognized and therefore untreated.2,7 In recent years, enhanced awareness among healthcare professionals has led to the widespread use of nutritional screening for the early detection of patients at risk. There is no consensus as to which is the best method in clinical practice, though the Subjective Global Assessment (SGA) score is advised as a comparison tool for the validation of new screenings.8

The Spanish national CIPA (Control of Food Intake, Protein and Anthropometry [Control de Ingestas, Proteínas, Antropometría]) is a nutritional screening tool designed at Hospital Universitario Nuestra Señora de la Candelaria (HUNSC)(Santa Cruz de Tenerife, Spain), with the premise of utilizing the resources available in daily clinical practice.6,8 The screening score is positive when any of the following conditions are met: control of 48−72h intake below 50%; serum albumin <3g/dl; a body mass index (BMI) <18.5kg/m2 or alternatively arm circumference (AC) ≤22.5cm in those cases where patient body weight or height cannot be measured. In the case of negative screening scores, the tests are repeated every 10 days until hospital discharge, while the positive cases are treated, based on a therapeutic protocol associated with diet and oral nutritional supplements (ONS) according to the criterion of the professionals in charge. Screening based on the CIPA has been validated in patients with medical disorders,9 and the tool has been subjected to optimization processes in order to perfect its use in hospital practice.10 Its cost-effectiveness has also recently been demonstrated in surgical patients.11,12 The present study was designed to complete validation of the tool in surgical patients, with a view to allowing for its global application in hospitals with heterogeneous activities.

Material and methods

A prospective longitudinal study was conducted on the prevalence of malnutrition in patients admitted to surgical wards of the HUNSC between July 2016 and December 2018. The study included patients of legal age of either gender with both emergency and scheduled admissions of over 72h, and with nutritional screening performed and validated through electronic (digital) support. The study was approved by the Ethics Committee of the HUNSC, and patient data collection and inclusion complied with the hospital protocol for access to cases histories and the signing of informed consent by patients.

Variables specific to the CIPA screening procedure (control of food intake, albumin, weight, height and the BMI or alternatively AC) and SGA were recorded in 226 patients, together with epidemiological data (age, gender, admission date, hospital discharge date, type of admission, surgery) and prognostic variables (median stay, mortality and early readmission). Albumin was determined during hospital admission on the occasion of the first blood sampling of the patients on their arrival at the hospital ward. The prevalence of hospital malnutrition or risk of malnutrition was assessed, based on CIPA versus SGA upon hospital admission, with evaluation of the agreement between both tools (kappa coefficient). The sensitivity (Se) and specificity (Sp) of CIPA with respect to SGA was analyzed, taking the latter as the gold standard for validation purposes. We examined the relationship between the CIPA and SGA screening outcomes and the prognostic parameters: early readmission (in the first 31 days after hospital discharge), mortality (both in hospital and in the first 3 months after discharge), and median stay (given its high dispersion and non-normal distribution). After checking normal data distribution with the Kolmogorov-Smirnov test, a bivariate analysis was performed based on the Student t-test or Mann-Whitney U test in the case of nonparametric contrasting. The chi-squared test was used to compare categorical variables. Results for quantitative variables were reported as the mean±standard deviation (SD) or as the median and interquartile range (IQR), while qualitative variables were reported as frequencies and percentages. A significance level of 5% was used in all hypothesis tests. The SPSS version 24.0 statistical package was used throughout.

Results

Table 1 shows the basal characteristics of the 226 patients included in the study. With regard to gender distribution, females slightly predominated, with no relation to CIPA screening positivity (33.7% of the males had a positive result versus 36.6% of the females). The prevalence of malnutrition risk according to the CIPA was 35.4% (95% confidence interval [95%CI]: 29.12–41.68), versus 30% according to the SGA score (95%CI: 24.06–36.11).

Table 1.

Baseline characteristics of the study sample.

Parameter  Mean  SD 
Age (years)  66.74  16.24 
Weight (kg)  73.49  16.68 
BMI (kg/m227.30  6.71 
Albumin (g/dl)  3.46  0.57 
 
No. subjects  226  100 
Gender
Males  92  40.7 
Females  134  59.3 
Type of admission
Urgent  182  82.4 
Scheduled  39  17.6 
Surgical treatment
Yes  193  87.3 
No  28  12.7 
Department and disease
General surgery  73  32.30 
Tumor  23  31.51 
Biliary disease  16  21.92 
Diverticulitis  12.33 
Others  25  34.24 
Traumatology  96  42.9 
Hip fracture  50  51.55 
Other fractures  27  27.83 
Other conditions  20  20.61 
Neurosurgery-ENT  16  7.1 
Tumor  56.25 
Others  43.75 
Vascular surgery  33  14.7 
Limb ischemia  14  42.42 
Diabetic foot  13  39.40 
Others  18.18 
Plastic surgery- Maxillofacial surgery  3.1 

With regard to the prognostic clinical variables, the CIPA was able to detect patients with increased mortality risk during hospital admission (5% vs. 0%, p=0.006), in contrast to SGA (2.9% vs. 1.3%; p=0.385). In relation to deaths occurring in the first months after hospital discharge, the CIPA was able to detect mortality (8.7% vs. 0.7%; p=0.002) as effectively as SGA (8.8% vs. 1.3%; p=0.005) (Figs. 1 and 2).

Figure 1.

In-hospital mortality according to the findings of the CIPA and SGA.

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Figure 2.

Mortality in the first three months after hospital discharge according to the findings of the CIPA and SGA.

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Patients with positive CIPA screening remained in hospital for longer, with a median stay of 21 days (IQR 14–34 days) versus 14.5 days in CIPA negative cases (IQR 9–27 days) (p=0.002). Similar results were obtained using SGA, with a median stay of 23 days (IQR 14.25–37.25) versus 15 days (IQR 9–25) (p<0.001) (Fig. 3). The CIPA tool was also able to detect patients at greater risk of early readmission (25.3% vs. 8.2% in the case of a negative CIPA) (p<0.001). Likewise, SGA found the risk of readmission to be 23.5% versus 10.1% in those with a negative screening test (p=0.008) (Fig. 4).

Figure 3.

Median stay (in days) according to the findings of the CIPA and SGA.

(0.06MB).
Figure 4.

Early readmission after hospital discharge according to the findings of the CIPA and SGA.

(0.07MB).

Agreement between the two screening tools, based on the kappa coefficient, was 0.479 (95%CI: 0.357−0.601; p=0.001). Taking SGA as the reference method for validation purposes, the CIPA tool yielded sensitivity and specificity values of 70.6% and 79.7%, respectively. With regard to CIPA positivity, 21.2% of the total sample analyzed had pathological albumin levels, 13.3% had decreased food intake, and 11.9% had a BMI and/or AC below normal. Of the patients with hypoalbuminemia, 48.9% corresponded to values recorded during hospital admission and before surgery. In the case of diminished albumin levels after surgery, measurement was made an average of 3.45 days (SD 2.26) after surgery. Considering the type of admission, 15% of all positive screenings corresponded to scheduled patient admissions.

Discussion

Nutritional status in hospitalized patients is directly associated with resolution of the disease and its potential complications. The need for surgery adds a further stress factor requiring all healthcare professionals to assess and detect the malnutrition risk early. The incidence of malnutrition in hospitals has reached 50%, worsening the patient prognosis and increasing healthcare expenditures.1–3,10 Accordingly, current European policies recognize malnutrition as a major health problem, and recommend the development and validation of detection tools that are easy to apply and rapid.3,13,14

The prevalence of malnutrition as shown by the CIPA screening tool was found to be 35.7% in the case of nonsurgical disease,10 this figure being practically identical to that recorded in our own study. Considering the mean age of the patients, the prevalence of malnutrition was similar to that recorded in the Predyces study2 (37% in hospitalized patients over 70 years of age). Taking SGA as reference 8, the CIPA tool yields sensitivity and specificity values that grant it the validity required for screening.7,14 In addition, the items used are simple, and this favors the tool’s applicability. Furthermore, the parameters included are consistent with the criteria recently proposed by the Global Leadership Initiative on Malnutrition (GLIM) working group for the diagnosis of malnutrition.15 These data reflect the capacity of the new screening tool to detect the risk of malnutrition in hospitalized patients regardless of the reason for admission, defining the CIPA as an ideal tool for use in large hospitals that deal with a broad range of disease conditions.

Surgery implies aggression, with increased stress hormone levels and a systemic inflammatory response regardless of the disease for which surgery is indicated or the baseline condition of the patient.16 The metabolic response is characterized by increased catabolism of both glycogen and fatty acids and proteins. Protein catabolism is regarded as a key element in the functional recovery of the patient, given the possible and early loss of muscle tissue that can persist over the long term.4,16,17 Preoperative serum albumin is a good predictor of both postoperative morbidity and nutritional status.4 In our study, hypoalbuminemia was the most common factor in positive CIPA screenings, and preoperative measurement was performed in half of the cases. Recent studies have interpreted postoperative albumin as an indicator of adverse effects and not as a cause of such effects, and the recovery of albumin levels is, moreover, noted in the first 5 days after surgery.17–19 Based on these results and on the physiology of albumin, it may be affirmed that although the relationship between preoperative albumin concentration and patient prognosis is clear, further studies are needed to define the role of hypoalbuminemia after surgery.

After albumin, the control of food intake was the parameter with the strongest association with positive screening, with approximately 13% of the study sample presenting an intake below 50%. This control of intake quantifies the amount of food consumed by the patient in each dish of the four meals dispensed in the hospital (<25%; 25–50%, 50–75%, >75%) during the first 48−72hours of arrival at the hospital ward. It only proved evaluable if the patient presented a diet of over 1000kcal a day, with the inclusion of proteins. At present, with the protocols for the early reintroduction of oral feeding after surgery4,20 and the inclusion of food intake as a criterion for malnutrition by the GLIM group,15 the use of this parameter in hospital malnutrition screening affords quality and increased safety in healthcare.

The CIPA screening tool is not limited to detecting the risk of malnutrition, but can also predict those surgical patients with a poor clinical prognosis. In our study, the CIPA identified patients at increased mortality risk during hospital admission, in contrast to SGA. In recent years there has been an increase in the use of risk predictors of in-hospital mortality as an indicator of quality and for assessing the risk-benefit ratio of surgical procedures.21,22 The CIPA also detects mortality in the first months after hospital discharge and the risk of early readmission, this suggesting the ability to assess and treat patients with greater morbidity and its associated complications. The CIPA tool predicts surgical patients presenting a median23 of one additional week of admission, with the associated costs involved. The early introduction of nutritional support helps prevent complications and improves the clinical prognosis.4 The detection capacity of the CIPA screening tool is completed by combining it with a nutritional support protocol, representing an early detection and intervention method with an improvement of the clinical parameters of these patients at risk.

Surgery in itself is regarded as a risk factor for the development of complications, contributing to the proinflammatory state in a way similar to any chronic disease condition.4,16 In addition, many studies show a worsening of nutritional status during admission. In this regard, the detection of malnutrition risk throughout the hospitalization process is of crucial importance.1,2,8 In our study, most patients had an acute condition requiring emergency admission and/or surgery, but it should be noted that 15% of the cases with a positive screening result corresponded to non-emergency admissions. These results suggest the importance of the nutritional screening of all patients admitted to hospital and the need for additional studies and tools to prevent the risk of malnutrition.

The CIPA is currently the reference nutritional screening tool in hospital centers in the Canary Islands.24 Various studies have demonstrated its cost-effectiveness, specifically in patients admitted to General and Digestive Surgery.12,25 The clinical prognostic factors in a group of patients subjected to CIPA screening versus a control group (the diagnosis of malnutrition being established through standard clinical practice, without screening) were also evaluated. Although the patients at risk of malnutrition detected early by means of the CIPA had a higher Charlson index score upon admission and underwent a greater number of cancer surgeries, they exhibited a better prognosis than the controls. The study showed that CIPA screened patients had lower mortality rates, fewer transfers to critical care, and a shorter mean stay (though statistical significance was not reached).26 Although this study was conducted in a single surgical specialty, the CIPA is seen to be a tool for both risk detection and the early intervention and clinical improvement of these patients.

Malnutrition is a serious global health problem with high costs, and requires efforts and attention from both public bodies and healthcare professionals.1,2,24 This study provides further evidence on the CIPA nutritional screening tool as a useful option for detecting the risk of malnutrition in patients, regardless of the disease involved or its management, and has been validated in surgical patients. Thus, CIPA screening can detect patients with a poorer clinical prognosis using nutritional markers in a simple and effective manner.

Authorship

J.P. Suárez and A. Mora designed the study. The field work was supervised by J.P. Suárez and I. Llorente, and was carried out by A. Mora and A. Sánchez. C. Lorenzo and Y. Zambrano actively collaborated in the organization and updating of the data for analysis. A. Sánchez, C. Lorenzo and Y. Zambrano participated in the statistical analysis and interpretation of the results. The initial draft of the article was prepared by A. Mora and P. Suárez. All the authors contributed to the interpretation of the results and subsequent modifications. All the authors provided their critical viewpoint during preparation of the article, along with their review and approval of the final manuscript version.

Conflicts of interest

The authors declare that they have no conflicts of interest or financial ties in relation to the contents of the article.

Acknowledgments

Thanks are due to all the staff members who collaborated in the development of the CIPA screening tool, and particularly to colleagues from the Department of Endocrinology and Nutrition and the Clinical Nutrition and Dietetics Unit of Hospital Universitario Nuestra Señora de la Candelaria.

References
[1]
J. Sorensen, J. Kondrup, J. Prokopowicz, M. Schiesser, L. Krähenbühl, R. Meier, et al.
EuroOOPS study group. EuroOOPS: an international, multicentre study to implement nutritional risk screening and evaluate clinical outcome.
Clin Nutr, 27 (2008), pp. 340-349
[2]
J. Álvarez-Hernandez, M. Planas Vila, M. Leon-Sanz, A. García de Lorenzo, S. Celaya-Pérez, P. García-Lorda, et al.
PREDyCES researchers. Prevalence and costs of malnutrition in hospitalized patients; the PREDyCESR Study.
Nutr Hosp, 27 (2012), pp. 1049-1059
[3]
O. Ljüngqvist, F. de Man.
Under nutrition - a major health problem in Europe.
Nutr Hosp, 24 (2009), pp. 368-370
[4]
A. Weimann, M. Braga, F. Carli, T. Higashiguchi, M. Hübner, S. Klek, et al.
ESPEN guideline: Clinical Nutrition in Surgery.
Clin Nutr, 36 (2017), pp. 623-650
[5]
W.H. Hu, L.C. Cajas-Monson, S. Eisenstein, L. Parry, B. Cosman, S. Ramamoorthy.
Preoperative malnutrition assessments as predictors of postoperative mortality and morbidity in colorectal cancer: an analysis of ACS-NSQIP.
[6]
M.F. Van Stijn, I. Korkic-Halilovic, M.S. Bakker, T. van der Ploeg, P.A. van Leeuwen, A.P. Houdijk, et al.
Preoperative nutrition status and postoperative outcome in elderly general surgery patients: a systematic review.
J Parenter Enteral Nutr, 37 (2013),
[7]
J. Marco, R. Barba, A. Zapatero, P. Matía, S. Plaza, J.E. Losa, et al.
Prevalence of the notification of malnutrition in the departments of internal medicine and its prognostic implications.
Clin Nutr, 30 (2011), pp. 450-454
[8]
M.A. Van Bokhorst-de van der Schueren, P.R. Guaitoli, E.P. Jansma, H.C. de Vet, et al.
Nutrition screening tools: does one size fit all? A systematic review of screening tools for the hospital setting.
Clin Nutr, 33 (2014), pp. 39-58
[9]
J.P. Suarez Llanos, N. Benitez Brito, J.G. Oliva Garcia, F. Pereyra-García Castro, M.A. López Frías, A. García Hernández, et al.
Introducing a mixed nutritional screening tool (CIPA) in a tertiary hospital.
Nutr Hosp, 29 (2014), pp. 1149-1153
[10]
J.P. Suarez-Llanos, A. Mora-Mendoza, N. Benitez-Brito, L. Pérez-Méndez, F. Pereyra-García-Castro, J.G. Oliva-García, et al.
Validity of the new nutrition screening tool Control of Food Intake, Protein, and Anthropometry (CIPA) in non-surgical inpatients.
Arch Med Sci, 14 (2018), pp. 1020-1024
[11]
A. Mora-Mendoza, J.P. Suarez-Llanos, I. Delgado-Brito, F. Pereyra-García Castro, R. López Travieso, N. Pérez Delgado, et al.
Optimisation of nutritional screening tool CIPA: are two parameters of protein really necessary?.
Nutr. Hosp., 35 (2018), pp. 914-919
[12]
J.P. Suarez-Llanos, N. Benitez-Brito, L. Vallejo-Torres, I. Delgado-Brito, A. Rosat-Rodrigo, C. Hernández-Carballo, et al.
Clinical and cost-effectiveness analysis of early detection of patients at nutrition risk during their hospital stay through the new screening method CIPA: a study protocol.
BMC Health Serv. Res., 17 (2017), pp. 292
[13]
D. Eglseer, R.J.G. Halfens, C. Lohrmann.
Is the presence of a validated malnutrition screening tool associated with better nutritional care in hospitalized patients?.
Nutrition, 37 (2017), pp. 104-111
[14]
F. Neelemat, J. Meijers, H. Kruizenga, H. van Ballegooijen, M. van Bokhorst-de van der Schueren.
Comparison of five malnutrition screening tools in one hospital inpatient sample.
J Clin Nurs, 20 (2011), pp. 2144-2152
[15]
T. Cederholm, G.L. Jensen, M.I.T.D. Correia, M.C. Gonzalez, R. Fukushima, T. Higashiguchi, et al.
(GLIM Core Leadership Committee; GLIM Working Group). GLIM criteria for the diagnosis of malnutrition - a consensus report from the global clinical nutrition community.
[16]
W. Alazawi, N. Pirmadid, R. Lahiri, S. Bhattacharya.
Inflammatory and immune responses to surgery and their clinical impact.
Ann Surg, 64 (2016), pp. 73-80
[17]
M. Hübner, S. Mantziari, N. Demartines, F. Pralong, P. Coti-Bertrand, M. Markus Schäfer.
Postoperative albumin drop is a marker for surgical stress and a predictor for clinical outcome: a pilot study.
Gastroenterol Res Pract, (2016), pp. e8743187
[18]
I. Labgaa, G.R. Joliat, A. Kefleyesus, S. Mantziari, M. Schäfer, N. Demartines, et al.
Is postoperative decrease of serum albumin an early predictor of complications after major abdominal surgery? A prospective cohort study in a European centre.
[19]
M. Wierdak, M. Pisarska, B. Kuśnierz-Cabala, J. Witowski, J. Dworak, P. Major, et al.
Changes in plasma albumin levels in early detection of infectious complications after laparoscopic colorectal cancer surgery with ERAS protocol.
Surg Endosc, 32 (2018), pp. 3225
[20]
S. Sandrucci, G. Beets, M. Braga, K. Dejong, N. Demartines.
Perioperative nutrition and enhanced recovery after surgery in gastrointestinal cancer patients. A position paper by the ESSO task force in collaboration with the ERAS society (ERAS coalition).
Eur J Surg Oncol., 44 (2018), pp. 509-514
[21]
A.A. Ghaferi, J.D. Birkmeyer, J.B. Dimick.
Variation in hospital mortality associated with inpatient surgery.
N. Engl. J. Med., 361 (2009), pp. 1368-1375
[22]
R.M. Pearse, R.P. Moreno, P. Bauer, P. Pelosi, P. Metnitz, C. Spies, et al.
European Surgical Outcomes Study (EuSOS) group for the Trials groups of the European Society of Intensive Care Medicine and the European Society of Anesthesiology. Mortality after surgery in Europe: a 7 day cohort study.
Lancet., 380 (2012), pp. 1059-1065
[23]
G. Malagón-Londoño, R. Galán-Morera, G. Pontón-Laverde.
Indicadores de gestión y funcionamiento hospitalario. In: Administración hospitalaria.
Editorial Panamericana, (2008), pp. 472-491
[24]
Servicio Canario de la Salud.
Documento de consenso: abordaje de la desnutrición hospitalaria relacionada con la enfermedad..
[25]
J.P. Suarez-Llanos, L. Vallejo-Torres, M.A. García-Bello, C. Hernández-Carballo, E.M. Calderón-Ledezma, A. Rosat-Rodrigo, et al.
Cost-effectiveness of the hospital nutrition screening tool CIPA.
[26]
J.P. Suárez-Llanos, A. Rosat-Rodrigo, J. García-Niebla, L. Vallejo-Torres, I. Delgado-Brito, M.A. García-Bello, et al.
Comparison ofclinical outcomes in surgical patients subjected to CIPA nutri-tion screening and treatment versus standard care.
Nutrients, 11 (2019), pp. 889

Please cite this article as: Mora Mendoza A, Suárez Llanos JP, Sánchez Morales A, Lorenzo González C, Zambrano Huerta Y, Llorente Gómez de Segura I. Validación del cribado nutricional CIPA mediante variables clínicas pronósticas en pacientes quirúrgicos hospitalizados. Endocrinol Diabetes Nutr. 2020;67:304–309.

Copyright © 2020. SEEN and SED
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