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Inicio Cirugía Española (English Edition) Unplanned Readmission After Lung Resection Surgery: A Systematic Review
Journal Information
Vol. 97. Issue 3.
Pages 128-144 (March 2019)
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372
Vol. 97. Issue 3.
Pages 128-144 (March 2019)
Review article
DOI: 10.1016/j.cireng.2019.02.011
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Unplanned Readmission After Lung Resection Surgery: A Systematic Review
Reingreso no planificado tras cirugía de resección pulmonar: revisión sistemática
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Javier García-Tiradoa,b,
Corresponding author
fco854@separ.es

Corresponding author.
, Diego Júdez-Legaristic, Hugo Salvador Landa-Oviedod, José María Miguelena-Bobadillab,e
a Servicio de Cirugía Torácica, Hospital Universitario Miguel Servet, Zaragoza, Spain
b Departamento de Cirugía, Ginecología y Obstetricia, Facultad de Medicina, Universidad de Zaragoza, Zaragoza, Spain
c Servicio de Anestesiología, Hospital Ernest Lluch Martín, Calatayud, Zaragoza, Spain
d Cirugía Torácica, Barcelona, Spain
e Servicio de Cirugía General y Digestiva, Hospital Universitario Miguel Servet, Zaragoza, Spain
Article information
Abstract
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Figures (2)
Tables (6)
Table 1. Reasons for exclusion of eligible articles after evaluation of the complete text.
Table 2. Main Characteristics Regarding the Design of the Studies.
Table 3. Studies about readmission after lung resection surgery, with a synopsis of the main results presented.
Table 4. Variables analyzed in the different studies analyzed, showing those that were significant for the different authors in the multivariate analysis (or univariate if that was the resulted given) with OR values and corresponding p value for each significant variable.
Table 5. Risk factors for readmission.
Table 6. Mortality rate for different time periods.
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Abstract

Urgent readmissions have a major impact on outcomes in patient health and healthcare costs. The associated risk factors have generally been infrequently studied. The main objective of the present work is to identify pre- and perioperative determinants of readmission; the secondary aim was to determine readmission rate, identification of readmission diagnoses, and impact of readmissions on survival rates in related analytical studies.

The review was performed through a systematic search in the main bibliographic databases. In the end, 19 papers met the selection criteria.

The main risk factors were: sociodemographic patient variables; comorbidities; type of resection; postoperative complications; long stay.

Despite the great variability in the published studies, all highlight the importance of reducing readmission rates because of the significant impact on patients and the healthcare system.

Keywords:
Hospital readmissions
Lung resection
Risk factors
Systematic review
Resumen

Los reingresos urgentes suponen un impacto importante sobre los resultados en la salud de los pacientes y los costes sanitarios. Los factores de riesgo asociados a reingreso tras cirugía de resección pulmonar han sido poco estudiados. El principal objetivo del presente trabajo es la identificación de factores pre- y perioperatorios determinantes de reingreso; secundariamente, determinación de tasa de reingresos, identificación de diagnósticos de reingreso, e impacto de los reingresos sobre las tasas de supervivencia en los estudios que lo analizaban.

La revisión se realizó mediante búsqueda sistemática en las principales bases de datos bibliográficas. Finalmente, 19 trabajos cumplieron los criterios de selección.

Los principales factores de riesgo fueron: variables sociodemográficas de los pacientes; comorbilidades; tipo de resección; complicaciones postoperatorias; estancia prolongada.

A pesar de la gran variabilidad en los estudios publicados, todos destacan la importancia de reducir los índices de reingreso por su significativo impacto sobre pacientes y sistema sanitario.

Palabras clave:
Reingreso hospitalario
Resección pulmonar
Factores de riesgo
Revisión sistemática
Full Text
Introduction

The Quality Plan of our National Healthcare System contemplates the rate of readmission after surgical procedures as a relevant marker of care quality.1 The adjusted rates of potentially avoidable readmissions are sufficiently solid to justify their inclusion to monitor hospital quality2,3; a high rate of readmissions could indicate inadequate care, with poor care results and a loss of efficiency.4 Thus, avoidable readmissions are estimated as an indirect indicator of quality and are assumedly an opportunity for significant savings in potential costs for the healthcare system,5 while also recognizing their impact on patient health outcomes, both in terms of quality of life as well as survival.6

Several studies have been published about readmissions after various surgical procedures in general, trauma and cardiovascular surgery; meanwhile, other studies have grouped together different major surgeries from different specialties, including pulmonary lobectomy.6,7 However, the specific risk factors associated with readmission, the rate of readmissions and their correlating diagnoses after lung resection surgery have generally not been extensively studied. Recently, several papers have been published analyzing readmissions after lung resection surgery. The main objective of this study is to identify pre- and perioperative determinants for readmission. Secondary objectives were to analyze readmission rates, identify the diagnoses associated with readmission, and calculate the impact of readmissions on survival rates in the studies that analyzed this variable.

Methods

The review was carried out following the guidelines of the Preferred Reporting Items For Systematic Reviews and Meta-Analyses (PRISMA)8 in order to answer the following questions: what is the readmission rate in lung resection surgery?; what are the diagnoses of the patients who are readmitted after a pulmonary resection?; and, is it possible to identify perioperative risk factors predicting readmission? The review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO),9 under record number CRD42017059341.

Search Strategy

The search was carried out until March 2017 in five bibliographic databases (PubMed, US National Library of Medicine-National Institute of Health; Embase, Elsevier; The Cochrane Library and Cochrane Library Plus, Cochrane Collaboration; Spanish Bibliographic Index in the Health Sciences (IBECS); Virtual Health Library (BVS), Carlos III Health Institute), and an additional search was conducted in Tripdatabase and Google Scholar.

The search terms in Spanish were “readmisión” and “cirugía”, as well as “readmission” and “lung surgery” in English. The searches excluded “transplants” and were limited to studies in humans, with no time restriction.

Inclusion and Exclusion Criteria

The scope of the study was readmission after lung resection surgery in human adults. Therefore, the inclusion criteria were studies conducted on unplanned readmissions in adult humans (18 and older) who had undergone pulmonary resection surgery (any technique). We excluded the studies about readmission in thoracic surgery focused on other types of surgical interventions other than lung resections, as well as studies in which readmission was not the main objective of the study but was used as an indicator of quality to evaluate certain programs or was used in the comparison of results between different hospital teams.

All article types were included, excluding editorials, letters to the editor or redundant papers.

Measurement of Results

The main result of interest was the identification of pre- and perioperative factors that led to readmission.

The secondary outcomes were the rate of unplanned readmissions after lung resection surgery and the readmission diagnoses. Another result assessed was the influence of readmissions on survival rates, although not all the studies analyzed this variable.

Study Selection; Data Extraction

Study titles and/or abstracts were retrieved by applying the search strategy in the different bibliographic databases consulted; these were then examined independently by two authors of the review (GT and LO). The full texts of these potentially eligible studies were obtained and evaluated independently by two members of the review team (GT and LO). Any disagreement was resolved through discussion with a third reviewer (MB). A standardized form was used to extract the data from the included studies, and two reviewers extracted data independently (GT and JL); any discrepancies were resolved by discussion with a third author (MB).

Quality Assessment (Risk of Bias)

The methodological quality of the studies was assessed independently by two researchers (JL and MB) using the Cochrane Collaboration10 bias risk assessment tool. Using this tool, we evaluated: selection bias (patient inclusion criteria, including losses and exclusions from the analysis, reporting the reasons for these losses and exclusions); detection bias (establishing the criteria for identifying the main event: readmission); attrition (identifying the sources for obtaining the data, with possible bias due to quantity, nature or incomplete data management); information bias (possible selectively reported results); and other biases (any important observation of possible unforeseen biases). Possible disagreements were resolved with the participation of a third review author (GT).

Data Analysis

Given the heterogeneity in the data analysis, a narrative synthesis was undertaken of the results from the studies analyzed (data from heterogeneous studies grouped into a meta-analysis can produce erroneous results).11

ResultsBibliographic Search

After filtering and eliminating duplicates of the 904 papers initially identified, 579 articles were obtained (Fig. 1). In the end, the full texts of 37 articles were reviewed, 18 of which were excluded for different reasons (Table 1). Thus, 19 studies met the selection criteria and were included in the review.5–7,12–27

Fig. 1.

Bibliometric search and article selection; PRISMA flow diagram.

(0.21MB).
Table 1.

Reasons for exclusion of eligible articles after evaluation of the complete text.

Articles excluded after complete evaluation (n=18): 
No results from thoracic surgery (n=6) 
Readmission as a quality indicator: 
Evaluation of clinical practice guidelines (n=7) 
Evaluation of hospital volume (n=1) 
Effect of the place of readmission on the results (n=1) 
Letter to the Editor (n=1) 
Editorial (n=1) 
Communication at a medical conference with data included in a later article (n=1) 
Characteristics of the Included Studies

All the studies analyzed presented a retrospective cohort design, with the exception of one case–control study19 and one prospective cohort study with a one-year follow-up.27 One retrospective cohort study had been published as a communication at a national congress.22Table 2 shows the main characteristics of the study designs.

Table 2.

Main Characteristics Regarding the Design of the Studies.

1st Author/year/country  Study type  Database  Period of readmission  Lung resection type  Indication  Other characteristics  Patients lost  Readmission hospital 
12 Handy (2001) USA  COHr  Hospital  90 d  All  All    Not specified  Any 
13 Varela (2004) Spain  COHr  Hospital  30 d  Major (N-L)  All    Not specified  Any 
14 Farjah (2009) USA  COHr  SEER-Mc  30 d  All  NSCLC  Age66 yrs  Specified  Any 
5 Freeman (2013) USA  COHr  PIDb  90 d  NSCLC    Specified  Any 
7 Lucas (2013) USA  COHr  ACS-NSQIP  30 d (post-op)  Pulmonary and non-pulmonary  All  GDS, VS, TS
Excl. Hospital stay>10 d 
Specified  Any 
15 McDevitt (2013) Ireland  COHr  NCR, HIPE  28 d  All  NSCLC    Not specified  Any 
16 Hu (2014) USA  COHr  SEER-Mc  30 d  All  NSCLC  Age66 yrs  Not specified  Any 
6 Gonzalez (2015) USA  COHr  MedPAR  30 d  All  All  GDS, CS, TS
Age66 yrs 
Not specified  Any 
17 Puri (2015) USA  COHr  NCDB-ACS  30 d  All  NSCLC  Stage I-III  Not specified  Hospital II 
18 Rajaram (2015) USA  COHr  ACS-NSQIP  30 d (post-op)  Major (Pn-L)  All    Specified  Any 
19 Ogawa (2015) Japan  CC  Hospital  90 d  Major (Pn-L)  NSCLC    Not specified  Any 
20 Assi (2015) USA  COHr  Hospital  30 d  All    Not specified  Any 
21 Langan (2015) USA  COHr  Multicentric  30 and 90 d  Major (?)  NSCLC  GDS, TS
Age65 yrs 
Not specified  Hospital II 
22 Ward (2015) USA  COHr  ACS-NSQIP  30 d (post-op)  All  All  Communication at national congress (ACS 2015)  Not specified  Not specified 
23 Stitzenberg (2015) USA  COHr  SEER-Mc  30 and 90 d  All  NSCLC  GDS, TS
Age66 yrs 
Not specified  Any 
24 Stiles (2016) USA  COHr  SIDB-HCUP  30 and 90 d  All    Not specified  Any 
25 Medbery (2016) USA  COHr  NCDB-ACS  30 d  NSCLC  StageT2N0M0  Not specified  Not specified 
26 Rosen (2016) USA  COHr  NCDB-ACS  30 d  NSCLC  Excl. Hospital stay>36 d  Specified  Hospital II 
27 Dickinson (2017) USA  COHp  Hospital  30 d  All  All    Specified  Any 

The corresponding bibliographic reference appears with each author.

yrs: years; ACS-NSQIP: American College of Surgeons-National Surgical Quality Improvement Program; NSCLC: non-small cell lung cancer; CC: case–control; GDS: general and digestive surgery; COHp: cohort, prospective; COHr: cohort, retrospective; TS: thoracic surgery; VS: vascular surgery; CS: cardiac surgery; d: days; Excl.: excluded; HIPE: Hospital In-Patient Enquiry; L: lobectomy; MedPAR: Medicare Provider Analysis and Review; Pn: pneumonectomy; NCDB-ACS: National Cancer Data Base- American College of Surgeons and American Cancer Society; NCR: National Cancer Registry; PIDb: Premier Inpatient Database; SEER-Mc: Surveillance, Epidemiology and End Results-Medicare; SIDB-HCUP: State Inpatient Database-Healthcare Cost and Utilization Project; ?: not defined; II: admission rate

In many studies, recruitment was from large databases, some from a hospital setting12,13,19,20,27 and one was a multicenter study.21 Significant variability was observed in the type of lung resection included in the studies, as well as in the indications for lung resection, being restricted to patients with bronchogenic carcinoma in many cases, or to all types of indications in many others. The criterion of readmission was established in the majority of the studies as that occurring during the 30 days following patient discharge after the initial admission, while in other studies a 90-day period was established5,12,19 and in some cases the 30-day period was established after surgery7,18,22; in yet another study, the limit was 28 days,15 and two authors carried out the study with 30- and 90-day periods after hospital discharge.21,23,24

The study design profiles reveal the main biases that could be derived from patient selection: several studies restricted patient age (including patients over 6521 or 666,14,16,23); others excluded patients who had prolonged hospital stays for a certain period after admission7,26; some articles were very large population studies that included different types of surgery, including abdominal,6,7,21,23 vascular7 or cardiac,6 although they provided detailed readmission information in thoracic surgery, fulfilling the criteria for inclusion in the review.

Another potential source of bias was the possible incomplete collection of data and their selective reporting: only six of the studies made specific mention of the loss of patients5,7,14,18,26,27; and, regarding the readmitting hospital, two studies did not specify whether the possibility of readmission at a different hospital had been considered,22,25 and three papers collected only the readmissions at the hospital where the initial admission had occurred.17,21,26

Readmission Rates

The rate of readmissions within 30 days ranged between 4.3%17,25 and 15%,14 including the studies that established a criterion of 28 days after discharge15 and 30 days after surgery.7,18,22 The articles that analyzed readmission within 90 days obtained a rate that ranged between 7%5 and 23%23; excluding the study at the lower end of the range,5 all the other 90-day studies placed the readmission rate above 18%. The only study done in Spain that met the inclusion criteria of this study (Varela et al.,13 2004) reported a readmission rate of 6.9%.

Risk Factors Associated With Readmission

Table 3 provides a synopsis of the main results found by the different authors; Table 4 demonstrates the complete list of variables analyzed in the different studies, providing details about those that were significant for the different authors with their statistical result, and Table 5 schematically reflects the risk factors leading to readmission.

Table 3.

Studies about readmission after lung resection surgery, with a synopsis of the main results presented.

1st author/year/country  n  Readmission  Exitus readmission  Risk factors  Main causes of readmission  Survival  Observations 
12 Handy (2001) USA  374  18.9% (90 d)  11.6%  Pneumonectomy  Respiratory complications, infections  Exitus 5 a.:
-Readmission: 11.6%
-No readmission 4% 
 
13 Varela (2004) Spain  727  6.9%  6%  Postoperative complications, Pneumonectomy  Respiratory complications  N/A   
14 Farjah (2009) USA  21 067  15%  N/A  Age>80 yrs, unmarried, male, Pneumonectomy, Comorbidities, Advanced stage  N/A  Exitus 2.5 a.:
-Readmission: 33%
-No Readmission: 19% 
 
5 Freeman (2013) USA  4296  7% (90 d)  N/A  Hospital stay<5d or >16 d
Age >78 a. 
Respiratory, atrial fibrillation  N/A   
7 Lucas (2013) USA  TS: 3375
(GDS, VS, TS: 230 864) 
TS: 11.1%
(global: 7.8%) 
N/A  ASA, alb. <3.5mg/dL, DM, complications, urgent, discharged to rehab, prolonged hospital stay  N/A  N/A  Predictive model:
St/2+ASA
TS: ROC=0.507 
15 McDevitt (2013) Ireland  1284  10% (28 d)  3.36%  Residence, Comorbidities>2, Tumor stage III-IV  Respiratory complications, cardio/cerebrovascular, infections  N/A   
16 Hu (2014) USA  11 432  12.8%  N/A  Patient comorbidity (CHF and COPD), resection type, neoadjuvant chemoradiotherapy, socioeconomic factors (age; residence in place with moderate population)  Respiratory (respiratory failure, pneumonia, pneumothorax), cardiac complications  Exitus 90 d:
-Readmission: 14.4%
-No Readmission: 2.5% 
28.3% readmissions at other hospitals
 
6 Gonzalez (2015) USA  TS: 90 188 (TS, CAB, colectomy:
1 033 255) 
TS:10.8%  2.66%  Complications: influence time until readmission. Other factors not analyzed  Postoperative complications, cardiac complications  Exitus 90 d:
-Readmission: 10.8%
-No Readmission: 3.7%
 
Mortality declines as time until readmission increases 
17 Puri (2015) USA  129 893  4.3%  3.9%  Age, Male, pre-op radiotherapy, Comorbidity (Charlson-Deyo), Pneumonectomy  N/A  Exitus 30 d:
-Readmission: 3.9%
-No Readmission: 2.8%
Exitus 90 d:
-Readmission: 7%
-No Readmission: 3.3% 
 
18 Rajaram (2015) USA  1847  9.3%  N/A  Complications  Respiratory complications  N/A  No differences VATS-TT 
19 Ogawa (2015) Japan  979  22.1% (90 d)  3.2%  Male, “lung age” and “age difference”, tobacco habit rate, intraoperative bleeding, complications, histologic type, prolonged hospitalization (total and postoperative)  Respiratory complications  5-yr survival:
-
No Readmission: 78%
-Readmission: 44% 
Proposed predictive model (complications and Readmission 90 d): Age difference=Biological “lung age” 
20 Assi (2015) USA  213  13%  N/A  Readmission in ICU, Charlson-Deyo>0, COPD  N/A  N/A  Approach (TT-VATS) and complications: No risk factor 
21 Langan (2015) USA  TS: 1032
(GDS, TS: 2797) 
TS:
10.5% (30 d)
18% (90 d) 
N/A  Comorbidities>2, complications>2, hospital of initial admission  Infections, gastrointestinal and pulmonary complications  N/A  Risk factors, similar at 30 and 90 d 
22 Ward (2015) USA  8930  7.4%  N/A  ASA: 3, Pneumonectomy, complications  Air leak (VATS), infections (TT)  N/A  Approach (TT-VATS): No risk factor 
23 Stitzenberg (2015) USA  TS: 20 362
(GDS, TS: 29,719) 
13% (30 d)
23% (90 d) 
N/A  Age, male, stage, comorbidity, no home discharge, hospital stay, complications (90 d, not 30 d), hospital volume and residence-hospital distance (30 d, not 90 d)  Respiratory complications (dyspnea, pneumonia, thoracic pain) Cardiac (arrhythmia, CHF)  Exitus 90 d:
-Readmission: 14.6%
-No Readmission: 9%
Exitus 1 yr:
-Readmission: 30%
-No Readmission: 15% 
Risk factors and causes for readmission similar for 30 and 90 d 
24 Stiles (2016) USA  22 647  11.5% (30 d)
19.8% (90 d) 
4.7%  Male, insurance, comorbidities, hospital stay  Respiratory, cardiovascular, postoperative complications  N/A  Approach (TT-VATS) Charlson-Deyo and complications: No risk factor 
25 Medbery (2016) USA  19 711  4.3%  N/A  Male, Comorbidities, socioeconomic level, insurance, residence, VATS (univariate: non-teaching hospital, hospital stay)  N/A  N/A  Special attention to influence of socioeconomic factors on readmission 
26 Rosen (2016) USA  59 734  4.5%  N/A  Male, age (bivariate), Charlson-Deyo, Comorbidities, grade, advanced stage  N/A  N/A  Special attention to influence of hospital stay reduction program: No more readmissions (VATS nor TT) 
27 Dickinson (2017) USA  505  8.3%  0%  FEV1, operative time, postoperative pain scale 12–24h6, perioperative furosemide, transfusion, air leak>5 d, discharge to rehab  Respiratory complications  N/A  Prospective study with 1 yr of follow-up 

The corresponding bibliographic reference appears together with the author.

yrs: years; alb. albumin; ASA: American Society of Anesthesiologists; CAB: coronary artery bypass; c: C-statistic; GDS: general and digestive surgery; TS: thoracic surgery; VS: vascular surgery; d: days; DM: diabetes mellitus; Ex.Readmission: Exitus during readmission; n: sample size; FEV1: forced expiratory volume in one second; CHF: congestive heart failure; N/A: not analyzed; preop.: preoperative; ROC: Receiver Operating Characteristic curve; TT: thoracotomy; ICU: intensive care unit; VATS: video-assisted thoracoscopic surgery; vol.: volume.

Table 4.

Variables analyzed in the different studies analyzed, showing those that were significant for the different authors in the multivariate analysis (or univariate if that was the resulted given) with OR values and corresponding p value for each significant variable.

1st author/yr/country  Variables analyzed  Risk factors  OR (range) – 95% CI – Univariate results  P value  Observations 
12 Handy (2001) USA  Demographics
Comorbidity
Type of surgery
Associated procedures
Histopathology
Tumor stage (if cancer)
Postoperative complications
Operative mortality
Hospital stay 
Pneumonectomy  36% vs 17%  P=.005  Univariate analysis:
Pneumonectomy: 36% readmission
vs
Other resections: 17% readmission 
13 Varela (2004) Spain  Age
Body mass index
Type of surgery
ppoFEV1%
Postoperative complications
Hospital stay 
Postoperative complications
Pneumonectomy 

2.42 (1.36–4.66)

3.83 (1.98–7.45) 
P<.001
P=.008 
Multivariate 
14 Farjah (2009) USA  Age
Sex
Race
Low income
Low level of education
Not married
Residence
Previous cancer
Comorbidity (Charlson-Klabunde)
Histopathology
Stage
Neoadjuvant
Type of resection 
Age>80 yrs
Not married
Male
Residence: Midwest
Residence: South
Pneumonectomy
Comorbidity (Charlson-Klabunde): 1
Comorbidity (Charlson-Klabunde): 2
Comorbidity (Charlson-Klabunde): 3
Advanced stage: IIIB
Advanced stage: IV 
1.29 (1.11–1.51)
1.19 (1.08–1.32)
1.30 (1.18–1.43)
1.19 (1.04–1.36)
1.51 (1.29–1.78)
1.42 (1.17–1.74)
1.31 (1.17–1.46)
1.80 (1.56–2.07)

2.10 (1.76–2.150)
1.43 (1.20–1.70)
2.01(1.70–2.37) 
P=.001
P=.001
P<.001
P=.001
P<.001
P=.001
P<.001
P<.001

P<.001
P<.001
P<.001 
Multivariate 
5 Freeman (2013) USA  Demographic
Comorbidity (Charlson)
ECOG scale
Postoperative complications
Operative mortality
Hospital stay 
Hospital stay<5 days
Hospital stay>16 day
Age>78 yrs 
1.61 (N/A)
1.37 (N/A)
1.49 (N/A) 
P=.001
P=.001
P<.001 
Multivariate 
7 Lucas (2013) USA  Demographic
Indications
Preoperative risk factors
Details of surgery
30-day results 
ASA 2
ASA 3
ASA 4
Albumin<3.5mg/dL
Diabetes mellitus
Complications
Urgent surgery
Prolonged hospital stay
Discharge to rehab 
2.02 (1.82–2.24)
3.92 (3.55–4.33)
6.66 (5.99–7.42)
2.07 (1.99–2.16)
1.61 (1.55–1.68)
2.67 (2.55–2.79)
1.47 (1.42–1.53)
3.50 (3.38–3.62)
2.82 (2.68–2.96) 
N/A  Attributable population risk:
ASA: 66.1%
12.6%
8.8%
9.7%
10.3%
47.9%
7.8% 
15 McDevitt (2013) Ireland  Demographic
Married/single
Socioeconomic situation
Comorbidities
Tobacco habit
Stage
Resection type
Hospital characteristics
Destination at discharge 
Residence in poor area
Comorbidities>2
Tumor stage III-IV 
1.56 (1.11–2.20)
2.38 (1.43–3.96)
1.62 (1.13–2.34) 
P=.0095
P=.011
P=.039 
Multivariate 
16 Hu (2014)
USA 
Demographic
Socioeconomic factors
Comorbidities
Stage
Type of resection
Mortality 
Cardiac insufficiency
COPD
VATS lobectomy
Neoadjuvant chemoradiotherapy
Age>85 yrs
Residence in area with moderate population density 
1.56 (1.32–1.83)
1.47 (1.29–1.67)
0.74 (0.58–0.95)
1.52 (1.19–1.93)
1.47 (1.11–1.94)
1.24 (1.03–1.50) 
P<.001
P<.001
P=.018
P<.001
P=.025
P=.032 
Multivariate 
6 Gonzalez (2015)
USA 
Demographics
Dates of admission, discharge and death
Diagnosis
Procedure
Complications
Time until readmission
Mortality 
Impact on time until readmission:
Age>80 yrs
Female sex
Comorbidities>3
Major complications 
13% vs 17%/16%
50% vs 41%/46%
35% vs 39%/42%
15% vs 21%/22% 


P=.526
P=.002
P=.084
P=.449 
Univariate:
No readmission group
vs
Readmission group: <5d/21–30 d after discharge (p value referred to the difference between intervals of the readmission group) 
17 Puri (2015) USA  Demographics
Socioeconomic factors
Comorbidities (Charlson-Deyo)
Tumor variables
Type of resection
Mortality
Survival
Teaching/non-teaching hospital 
Age: 70–74 yrs
Age: 75–79 yrs
Age80 yrs
Male
Preoperative radiotherapy
Charlson-Deyo Index: 1
Charlson-Deyo Index: ≥2
Pneumonectomy 
1.168 (1.066–1.280)
1.256 (1.142–1.381)
1.205 (1.080–1.345)
1.159 (1.094–1.228)
1.213 (1.064–1.383)
1.354 (1.272–1.441)
1.592 (1.466–1.728)
1.685 (1.476–1.923) 
P=.001
P<.001
P=.001
P<.001
P=.004
P<.001
P<.001
P<.001 
Multivariate 
18 Rajaram (2015) USA  Demographics
ASA
Body mass index
Comorbidities
Tobacco habit
Type of surgery
Recent chemoradiotherapy
Disseminated tumor
Postoperative complications 
Complications  4.89 (3.05–6.04)  P<.001  Multivariate 
19 Ogawa (2015) Japan  Demographics
“Lung age”
“Age difference”
Comorbidities
Tobacco habit
Surgery type
Tumor variables
Stage
Complications
Hospital stay
Mortality
Survival 
Male
“Lung age”
“Age difference”
Tobacco habit
Bleeding
Complications
Squamous histology type
Total hospitalization
Postoperative hospitalization 
63% vs 85%
73.3 yrs vs 87 yrs
7.0 yrs vs 12.3 yrs
32 yrs vs 47 yrs
130mL vs 240mL
36% vs 82%
18% vs 33%
18 d vs 21 d
14 d vs 17 d
 
P=.018
P=.009
P=.012
P=.002
P<.001
P<.001
P<.013
P=.003
P=.001 
Univariate:
No readmission group
vs
Readmission group
__________
Multiple logistic regression:
“Lung age”
P=.040
“Age difference”
P=.040
Bleeding
P=.030
Complications
P<.001 
20 Assi (2015) USA  Demographics
Body mass index
Comorbidities (Charlson)
Chronic lung disease
Respiratory function tests
Tumor type
Stage
Neoadjuvant
Epidural, paravertebral catheter
Approach
Type of resection
Complications
Hospital stay in ICU
Admission in ICU
Total hospital stay
Destination at discharge
Mortality
Time until readmission
Mortality readmission
 
ICU readmission
Charlson-Deyo>0
COPD 
10.4 (1.1–103.5)
1.5 (1.04–2.03)
4.91 (1.96–13.46) 
P=.04
P=.03
P=.0006 


Multivariate 
21 Langan (2015) USA  Demographic
Insurance type
Comorbidities
Type of surgery
Complications
Admitting hospital 
Comorbidities>2

Complications>2

Hospital “E” 

30 d: 1.7 (1.19–2.49)
90 d: 1.8 (1.34–2.54)
30 d: 1. 6 (1.16–2.29)
90 d: 1.6 (1.19–2.15)
30 d: 0.6 (0.43–0.88)
90 d: 0.6 (0.41–0.76) 
N/A  Multivariate

Hospital “E”, a participating hospital 
22 Ward (2015) USA  Demographic
ASA
Type of surgery
Cancer vs no cancer
Complications
Mortality 
ASA: 3
Pneumonectomy
Superficial wound infection
Deep wound infection
Infection of organ/cavity
Pneumonia
Thromboembolism
Sepsis
Reoperation 
1.75 (1.383–2.227)
1.52 (1.004–2.308)
3.59 (2.083–6.217)
14.9 (2.854–77.874)
11.11 (5.44–22.72)
3.1 (2.337–4.114)
4.59 (2.941–7.176)
3.62 (2.256–5.812)
4.25 (3.161–5.736) 
P<.0001
P=.048
P<.0001
P=.0014
P<.0001
P<.0001
P<.0001
P<.0001
P<.0001 
Multivariate 
23 Stitzenberg (2015) USA  Demographics
Married/single
Residence
Distance to hospital
Hospital volume
Type of insurance
Stage
Comorbidities (Charlson)
Complications
Hospital stay
Mortality
Destination at discharge
Readmission, 30 and 90 d 
Age

Sex
Stage

Comorbidity

Discharge not to home

Hospital stay
Complications (90 d, not 30 d)
Hospital volume

Distance home to hospital (30 d, not 90 d) 
75–79 yrs: 1.23 (1.09–1.38)
≥ 80 yrs: 1.24 (1.08–1.41)
Fem.: 0.64 (0.59–0.70)
N+: 1.12 (1.02–1.23)
M+: 1.44 (1.20–1.74)
Ch.I.1: 1.13 (1.03–1.25)
Ch.I.2: 1.46 (1.32–1.63)
Hosp: 1.61 (1.42–1.81)
Resid: 3.25 (2.54–4.16)
1.03 (1.03–1.04)
90 d: 1.08 (1.03–1.12)

Q2: 1.25 (1.11–1.41)
Q3: 1.15 (1.02–1.29)
Q4: 1.26 (1.12–1.43)
Q2: 1.14 (1.01–1.28)
Q4: 1.27 (1.12–1.45)
 
P<.001
P<.01
P<.001
P<.05
P<.001
P<.05
P<.001
P<.001
P<.001
P<.001
P<.001

P<.001
P<.05
P<.001
P<.05
P<.001 
Multivariate 
24 Stiles (2016)
USA 
Demographic
Hospital stay
Comorbidities (Charlson-Deyo)
Type of surgery
Complications
Type of insurance 
Male
Medicaid
Comorbidities:
Weight loss
Electrolyte disorder
Iron-deficiency anemia
Blood-loss anemia
Peripheral vasculopathy
Complicated diabetes
Complicated HTN
Non-complicated HTN
Hospital stay:
6–8d
≥9 d 
1.19 (1.11–1.28)

1.29 (1.09–1.52)

1.34 (1.05–1.69)
1.22 (1.01–1.46)
1.32 (1.16–1.49)
1.89 (1.16–3.09)
1.21 (1.06–1.38)
1.14 (1.03–1.25)
1.47 (1.09–1.99)
1.12 (1.03–1.22)

1.42 (1.25–1.61)
1.88 (1.62–1.27) 
P<.0001

P<.004

P=.02
P=.04
P<.01
P=.01
P<.01
P=.01
P<.01
P<.01

P<.01
P<.01 
Multivariate 
25 Medbery (2016) USA  Demographics
Socioeconomic (income, education, place of residence)
Comorbidities (Charlson-Deyo)
Type of surgery
Hospital stay
Type of hospital
Type of insurance 
Male
Charlson-Deyo1
Socioeconomic level
< $30 000
$30 000–34 999
$35 000–45 999
Private insurance
Residence:
Urban (vs metropolitan)
Rural (vs metropolitan)
VATS 
1.23 (1.07–1.43)
1.23 (1.06–1.42)

1.51 (1.18–19.92)
1.38 (1.12–1.71)
1.23 (1.03–1.48)
0.79 (0.67–0.93)

0.71 (0.57–0.88)
0.47 (0.26–0.84)
1.42 (1.20–1.65) 
P=.004
P=.006

P<.001
P=.003
P=.025
P=.004

P=.002
P=.011
P<.001 
Multivariate 
26 Rosen (2016) USA  Demographic
Comorbidities (Charlson-Deyo)
Type of insurance
Socioeconomic (income, education)
Hospital stay (discharge practices)
Type of surgery
Tumor variables (histology, grade, stage)
Hospital variables (type, volume, location) 
Male
Charlson-Deyo:
1
≥2

Grade 4 malignancy
Advanced stage
III
IV 


1.16 (1.07–1.26)

1.19 (1.09–1.30)
1.38 (1.23–1.55)

1.4 (1.01–1.92)

1.21 (1.07–1.37)
1.38 (1.06–1.79) 

P<.001

P<.001
P<.001

P=.041

P=.0027
P=.016
 
Multivariate 
27 Dickinson (2017) USA  Demographics
Place of residence
Comorbidities
Type of surgery
Operative time
Readmission ICU
Post-op pain scale
Perfusion:
Furosemide post-op
Transfusion
Mortality
Complications
Destination at discharge
Day of week of discharge
Hospital stay
Discharge with pleural drain or urinary cath. 
ppoFEV1% (median)
Operative time (minutes, median)
Post-op pain scale 12–24h6
Perioperative furosemide
Transfusion
Air leak>5 d
Discharge to home 
82(33–147) vs 75(39–107)
130.8(84.2) vs 161.3(84.3)

OR: 2.696 (1.372.5.299)

23% vs 48%
4% vs 16.7%
5.8% vs 14.3%
OR: 0.323 (0.113–0.937) 
P=.042
P=.031

P=.004

P=.0008
P=.003
P=.027
P=.0375 
Intermixed univariate with multivariate results

Univariate:
No readmission group
vs
Readmission group

Multivariate: OR 

The corresponding bibliographic reference appears together with the author.

yrs: years; ASA: American Society of Anesthesiologists; d: days; COPD: chronic obstructive pulmonary disease; Fem.: female; HTN: hypertension; CI: confidence interval; Ch.I.: Charlson index; M+: distant metastasis; N/A: not analyzed, not available; N+: node involvement; OR: odds ratio; post-op: postoperative; ppoFEV1%: predicted post-op forced expiratory volume in one second %; Q: quartile; Hosp.: hospital; V.: variables; VATS: video-assisted thoracic surgery; vs: versus; ICU: intensive care unit; $: US dollars.

Table 5.

Risk factors for readmission.

Sociodemographic factors  Socioeconomic variables  Hospital characteristics  Comorbidities  Preoperative variables  Perioperative surgery  Tumor variables  Postoperative complications  Hospital stay 
Age5,14,16,17,19,23,26  Discharge to rehab7,23,27  Admitting hospital21  Comorbidities in general14,17,20,23–26  FEV127  Pneumonectomy12–14,17,22  Advanced stage14,15,23,26  Complications in general7,13,18,19,21–23 (a23: A 90 d, NO a 30 d)  Prolonged7,17,19,23,25 
Male sex14,17,19,23–26  Place of residence15,16,23,25  Hospital volume23  Diabetes mellitus7  Lung age19  Type of resection16  Histologic type19  Complications>221  <5d, >16d5 
Unmarried14  Insurance24,25  Non-teaching hospital25  Congestive heart failure16  RxT neoadj17  TT=VATS180,20,22,24,26  Grade26  Readmission in ICU20   
      COPD16,20  CTX-RxT neoadj16  VATS25    Blood transfusion27   
      Comorbidities>215,21  Albumin<3.5mg/dL7  Operative bleeding19    Air leak>5 d27   
      ASA7; ASA=322    Operative time27    Pain6 (VAS) 12–24h after surgery27   
      Tobacco habit19    Perioperative furosemide27    No correlation with readmission20,24   
          Urgent7    Impact on readmission, not on time until readmission6   

The corresponding bibliographic reference appears in superscript.

ASA: American Society of Anesthesiologists; VATS: video-assisted thoracoscopic surgery; d: days; VAS: visual-analog scale; COPD: chronic obstructive pulmonary disease; CTx: chemotherapy; RxT: radiotherapy; TT: thoracotomy; ICU: Intensive Care Unit; FEV1: forced expiratory volume in one second.

a

In this article, the complications are found to be risk factors for readmission in the 90-day post-op period but a 30-day period was not considered.

Regarding sociodemographic variables as determining factors for readmission, several studies showed an association with sex, which was male in all cases14,17,19,23–26; advanced age was also associated with readmission in several of the articles5,14,16,17,19,23,26; one study also found a relationship between being single/unmarried and the risk of readmission.14

According to results presented by different authors, a patient's socioeconomic situation was also associated with the probability of readmission (estimated as discharge to a care facility,7,23,27 place of residence,15,16,23,25 or even insurance24,25).

The hospital of the initial admission,21 hospital volume,23 and non-teaching hospitals25 were also associated with readmission in certain studies.

As for the clinical characteristics of the patients, the presence of comorbidities was associated with readmission (in a broad sense for some authors,14,17,20,23–26 and more specifically for others – diabetes mellitus,7 congestive heart failure,16 chronic obstructive pulmonary disease [COPD],16,20 more than two comorbidities15,21). The ASA classification was associated with the risk of readmission in two studies,7,22 tobacco habit only in one,19 and two of the studies found a correlation with respiratory function tests (forced expiratory volume in one second [FEV1])27; and a parameter described by the authors themselves, the “lung age”, based on the results of said respiratory tests19). Radiotherapy17 and neoadjuvant chemoradiotherapy16 were found to be risk factors in isolated studies.

Regarding the surgical variables, pneumonectomy was identified as a determining factor for readmission in several of the studies,12–14,17,22 while another found differences between the different types of resection.16 As for the approach, several studies did not find differences in risk of readmission between thoracotomy and video-assisted thoracoscopic surgery (VATS)18,20,22,24,26; however, one study suggested that VATS was a risk factor for readmission,25 while another found a protective effect.16 The study by Lucas et al.7 was the only paper that identified the urgent nature of the surgery as a risk factor for readmission.

Perioperative events were considered significant risk factors by two authors: Ogawa et al. (intraoperative bleeding)19 and Dickinson et al. (operative time, perioperative use of furosemide and transfusion).27

Several authors described postoperative complications as being very significant determinants for readmission,7,13,18,19,21–23 although with a few clarifications in certain cases: Langan et al. found them to be a risk factor when there were more than two complications,21 and Stitzenberg et al. found them to be a significant factor for readmission within 90 days, but not within 30 days.23 Furthermore, Assi et al. only found readmission in the ICU to be a determining factor,20 and Dickinson et al. associated readmission particularly with blood transfusion, air leak longer than 5 days, and pain intensity in the 12–24h postoperative period that was 6 or greater on the visual–analog scale.27 However, Gonzalez et al. only analyzed the possible correlation of complications over the time to readmission, with no observed relationship between the two events6; likewise, Assi et al.20 and Stiles et al.24 also found no correlation between complications and readmission after a specific evaluation.

Pathological characteristics and tumor stage have also been associated with the risk of readmission by some authors, including both the histological type19 or the degree of malignancy,26 as well as advanced tumor stage.14,15,23,26

A prolonged postoperative hospital stay was identified as a risk factor by several authors7,17,19,23,25 and differentially (when it was less than 5 days or greater than 16 days) by Freeman et al.5

In the studies evaluating readmission within 30 and 90 days, two determined that the risk factors were similar for readmission in both time periods,21,23 and the article by Stitzenberg et al.23 also found similar causes for readmission in both periods.

Main Causes of Readmission

The most frequent causes of readmission were respiratory in origin (respiratory failure, dyspnea, pneumonia, pneumothorax, chest pain)5,12,13,15,16,18,19,21,23,24,27 followed by cardiovascular complications (arrhythmias, heart failure).5,6,15,16,23,24 Only a few studies identified infectious causes as significant.12,15,21,22 Postoperative complications were a cause of readmission in two studies,6,24 and one study identified gastrointestinal causes.21

Impact on Survival

The impact of readmission on survival was analyzed by several authors, determining 5-year survival rates (78% in the non-readmission group [NRG] vs 44% in the readmission group [RG])19 or the mortality rate at different time periods, as shown in Table 6.

Table 6.

Mortality rate for different time periods.

Period  % Exitus GR  % Exitus NRG 
30 days17  3.9  2.8 
90 days6,16,17,23  7–14.6  2.5–9 
1 year23  30  15 
2.5 yrs14  33  19 
5 yrs12  11.6 

Next to the time period, the corresponding bibliographic reference appears in superscript.

NRG: no readmission group; GR: readmission group.

In addition to the impact of readmission, the study by Farjah et al.14 found that prolonged hospital stay and hospitalization in care centers also have a significant effect on mortality.

Hu et al.16 did not find higher 90-day mortality among patients who were readmitted two or more times during the first 60 days (16.2%) than those who were only readmitted once (13.8%, P=.295); also. the greater risk is determined by readmission during the first 30 days (OR: 5.79, P <.001). Similarly, the mortality rate showed no differences between patients who were readmitted at the hospital where they were operated on (13.6%) versus those who were readmitted at other medical centers (16.4%, P=.16). According to the results of this study, readmission for postoperative problems did not lead to higher mortality when these were due to other unrelated diagnoses (OR: 1.22, P=.21).

In a study focusing on the impact of the time elapsed until readmission, Gonzalez et al. found that the risk of mortality within 90 days increased if the readmission occurred during the first 5 days after discharge (OR: 8.12; 95% CI: 7.26–9.09), compared to when the readmission occurred after 21 days (OR: 5.97, 95% CI: 5.16–6.90). This effect was also detected on 30- and 60-day mortality rates.

The study by Puri et al.17 also showed that readmission was an independent risk factor for both 30-day mortality (OR: 1.20; 95% CI: 1.01–1.42) as well as 90-day mortality (HR: 1.37, 95% CI: 1.28–1.47).

However, the retrospective study by Dickinson et al.27 including patients who had undergone surgery over the course of a year did not find a significant difference in mortality between the readmission group and the group that did not present readmission during the 30 days after discharge (HR: 1.13; 95% CI: 0.43–2.93; P=.8).

Discussion

To give an idea of the specific impact of readmissions on the national healthcare system, in addition to their impact on patients themselves, it is estimated that 19% of all patients are readmitted in the first 30 days after discharge, with an annual economic impact for the US Medicare system of 17 billion dollars.28

In Spain, according to data from the Ministry of Health, Social Services and Equality, based on data from the Minimum Basic Data Set, in the last year analyzed (2013) the hospital readmission rate was 7.48% for all Major Diagnostic Categories, a figure that has been gradually increasing in successive years.29

Readmissions are more frequent in medical care processes (often related with emergency admissions) than in surgical treatment (usually scheduled and with previously prepared patients). As a result, approximately 75% of all readmissions are due to medical processes.28,30,31 However, the factors associated with readmissions and the diagnoses leading to readmission after lung surgery have not been extensively studied.

In the literature, most of the studies published on postoperative readmission focus on the readmission rates of specific processes and in specific populations, with widely varying methodologies and study population characteristics.32 Almost all of the studies evaluated in this review have been population-based retrospective cohort studies, based on large national databases in many cases. This type of studies presents an important risk of selection bias: for instance, population studies based on the Medicare database, which registers patients over 65, can only have data from older patients6,14,16,23; studies that use the National Surgical Quality Improvement Program (NSQIP) database analyze readmission after the surgical intervention,33 not only after hospital discharge7,18,22 (possible attrition bias); studies based on the National Cancer Data Base (NCDB) have a good probability of detection bias by collecting only the readmissions occurring at the hospital where the initial admission took place.17,25,26 This limitation was also presented by the multicenter study published by Langan et al.21 (in general, it is estimated that approximately one-third of readmissions occur at a different hospital than where the initial admission took place, as observed in several of the studies analyzed,5,12,13,16,27 mainly due to geographical reasons or insurance, depending on the healthcare system). Other inclusion criteria in the different studies that were presented heterogeneously were the type of surgery that the patients underwent and the indication for surgery (bronchogenic carcinoma, or other pathologies).

The readmission rates found by the different studies analyzed showed a variability that is probably explained by the disparate methodological aspects that we have just discussed, ranging from the characteristics of the population studied, databases used or participating hospitals, to the type of surgery conducted and its indications.32

Regarding the risk factors for readmission (Tables 4 and 5), the different studies on readmission after lung resection confirmed the following main factors: patient sociodemographic and socioeconomic variables; comorbidities; resection type, especially pneumonectomy, with no differences found in terms of the approach (thoracotomy vs video-assisted thoracoscopic surgery); postoperative complications; and prolonged hospital stay. In general terms, these findings correlate with published studies about readmission after different surgical procedures in different specialties.34,30

The main causes of readmission found were medical complications, especially respiratory, followed by cardiac complications. This aspect also agrees with articles published about readmissions in different types of surgical procedures, which usually conclude that the majority of postoperative admissions are due to medical complications in up to 70% of cases.35

The impact on survival is another significant dimension of postoperative readmission, as confirmed by all the studies in the series that analyzed this variable, which concurs with published data for both medical and surgical procedures in general.30

In short, the majority of studies published on readmission after lung resection surgery are widely heterogeneous in the methodology used and in the characteristics of the population studied. Nevertheless, all of them emphasize the importance of reducing postoperative readmission rates due to their impact on the healthcare system, patient survival and quality of life.

Authors’ Contributions

Study design: García-Tirado, Júdez-Legaristi, Landa-Oviedo, Miguelena-Bobadilla.

Data collection: García-Tirado, Júdez-Legaristi, Landa-Oviedo.

Analysis and interpretation of the results: García-Tirado, Júdez-Legaristi.

Article composition: García-Tirado, Miguelena-Bobadilla.

Critical review and approval of the final version: García-Tirado, Júdez-Legaristi, Landa-Oviedo, Miguelena-Bobadilla.

Conflict of Interests

The authors have no conflicts of interests to declare.

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Please cite this article as: García-Tirado J, Júdez-Legaristi D, Landa-Oviedo HS, Miguelena-Bobadilla JM. Reingreso no planificado tras cirugía de resección pulmonar: revisión sistemática. Cir Esp. 2019;97:128–144.

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