10.4081/btvb.2022.9
This is a retrospective, record-linkage study aimed at comparing the effectiveness and safety of two management models of vitamin K antagonists: a Network model (NAS), in which anticoagulation clinics and general practitioners (GP) share the same management software and database, and an individual General Practitioners model. Main outcomes were thromboembolic events (TE), major bleeding (MB) and all-cause mortality. Crude incidence rate and sub-distribution hazard ratio were calculated. Fine and Grey models were used to calculate SHR in multi-variable analysis. 9,418 patients in the NAS and 5,508 in the Routine General Care (RGC) cohort were included. Patients in the NAS cohort had a lower incidence of TE and mortality in respect to the RGC (sHR 0.76%, 95% CI 0.64-0.90 and 0.82%, 95% CI 0.75-0.89, respectively). More patients in the NAS than in the RGC cohort attained a Time in Therapeutic Range &gt;60% (62.2% vs 35.7%, p&lt;0.001). No statistically significant difference was found in MB incidence. This study shows that the NAS model for vitamin K antagonist oral anticoagulants management significantly improves the TTR and reduces the incidence of TE and mortality, without affecting the MB rate.
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en
Marco Marietta
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Bleeding, Thrombosis and Vascular Biology
Management model
Safety and efficacy of treatment with vitamin K antagonists in patients managed in a network of anticoagulation services or as routine general care
Text.Serial.Journal
https://www.btvb.org/btvb
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Original Articles
2022-04-15
2021-12-08
2022-03-22
2022-05-02
Bleed Thromb Vascul Biol
Marco Marietta
2022/04/15
10.4081/btvb.2022.9
Hematology Unit, Azienda Ospedaliero-Universitaria di Modena, Ospedale Policlinico, Modena
2785-5309
1
Management model
en
Tosetto A, Testa S, Palareti G, et al. The effect of management models on thromboembolic and bleeding rates in anticoagulated patients: an ecological study. Intern Emerg Med 2019;14:1307-15.
Safety and efficacy of treatment with vitamin K antagonists in patients managed in a network of anticoagulation services or as routine general care
https://www.btvb.org/btvb/article/download/9/15
1
                                                                                                          ORiginAl ARTiCle

Safety and efficacy of treatment with vitamin K antagonists in patients managed
in a network of anticoagulation services or as routine general care
Gianfranco De Girolamo,1 Luca Sarti,2 Sonia Cecoli,3 Karin Bonora,1 Chiara Ajolfi,4 Francesco Bellelli,5
Valeria Coluccio,6 Gualtiero Palareti,7 Marco Marietta6
1
 Department of Public Health, Epidemiology and Risk Communication Unit, Azienda Unità Sanitaria Locale di Modena, Italy;
2
 Internal and Emergency Medicine Unit, Azienda Ospedaliero-Universitaria di Modena, Ospedale Civile Baggiovara, Italy; 3Servizio
Interaziendale Ingegneria Clinica, Azienda Unità Sanitaria Locale di Modena, Italy; 4Local Pharmaceutical Department, Azienda
Unità Sanitaria Locale di Modena, Italy; 5Dipartimento Aziendale di Cure Primarie - U.O. Cure Primarie Distretto di Modena,
Azienda Unità Sanitaria Locale di Modena, Italy; 6Hematology Unit, Azienda Ospedaliero-Universitaria di Modena, Ospedale
Policlinico, Modena, Italy; 7Arianna Anticoagulazione Foundation, Bologna, Italy



ABSTRACT
    This is a retrospective, record-linkage study aimed at comparing the effectiveness and safety of two management models of vitamin K
antagonists: a Network model (NAS), in which anticoagulation clinics and general practitioners (GP) share the same management software
                                                                          and database, and an individual General Practitioners model. Main




                                                                                              ly
                                                                          outcomes were thromboembolic events (TE), major bleeding
                                                                          (MB) and all-cause mortality. Crude incidence rate and sub-distri-




                                                                                       on
  Correspondence: Marco Marietta, Dipartimento di Oncologia ed            bution hazard ratio were calculated. Fine and Grey models were
  Ematologia, Azienda Ospedaliero-Universitaria - Ospedale Poli-          used to calculate SHR in multi-variable analysis. 9,418 patients in
  clinico, via del Pozzo 71, 41124 Modena, Italy.
                                                                          the NAS and 5,508 in the Routine General Care (RGC) cohort



                                                                                  e
  Tel. +39.059.4224640 - Fax +39.059.4224429.
  E-mail: marco.marietta@unimore.it                                       were included. Patients in the NAS cohort had a lower incidence

  Key words: Vitamin k antagonists, Oral anticoagulants, Anticoag-
                                                                             us
                                                                          of TE and mortality in respect to the RGC (sHR 0.76%, 95% CI
                                                                          0.64-0.90 and 0.82%, 95% CI 0.75-0.89, respectively). More pa-
  ulation clinics, Management model.                                      tients in the NAS than in the RGC cohort attained a Time in Ther-
                                                                             al
                                                                          apeutic Range >60% (62.2% vs 35.7%, p<0.001). No statistically
  Contributions: The authors contributed to the study conception and
                                                                          significant difference was found in MB incidence. This study
                                                          ci

  design. Material preparation, data collection and analysis were per-
  formed by GDG, LS, KB. The first draft of the manuscript was            shows that the NAS model for vitamin K antagonist oral antico-
                                                        er


  written by GDG, LS and GP and all authors commented on previ-           agulants management significantly improves the TTR and reduces
  ous versions of the manuscript. All authors read and approved the       the incidence of TE and mortality, without affecting the MB rate.
                                                       m




    final manuscript.
                                            om




    Conflict of interest: The authors declare no potential conflict of in-
    terest.                                                                   INTRODUCTION
    Funding: None.                                                                Vitamin K antagonist oral anticoagulants (VKA) for
                                     -c




    Availability of data and material: data from the database included        over 50 years have been the only drugs available for
                                                                              chronic anticoagulation, exhibiting a good efficacy and
                            on




    in the study are available for consultation, according to the Italian
    law on the personal data protection.                                      an acceptable safety.1
                                                                                  Starting from 2009, oral anticoagulant directly inhibit-
                        N




    Code availability: PARMA® software for the VKA management;
    STATA 15 software for statistical analyses.                               ing thrombin (dabigatran) or activated factor X (apixaban,
                                                                              edoxaban and rivaroxaban) (DOAC) have been authorized
    Ethics approval: approval was obtained by Modena Ethics Com-
    mittee on 11.8.2017, protocol n. 3050.
                                                                              for the prevention of stroke and systemic embolism in pa-
                                                                              tients with non-valvular atrial fibrillation (NVAF) and for
    Consent to participate informed consent from all individual partic-       the treatment of venous thromboembolism (VTE).2-6 VKA
    ipants to the study was waived by the local Ethics Committee, ac-         have been progressively replaced by DOACs in a large pro-
    cording to the Italian law about the personal data protection on
    retrospective studies.                                                    portion of patients, whilst remaining the only suitable an-
                                                                              ticoagulants in some clinical situations, such as mechanical
    Received for publication: 7 December 2021.                                heart valve prostheses or severe renal impairment.7,8 Cur-
    Accepted for publication: 21 March 2022.
                                                                              rently, it is estimated that about 50,000 patients in the
    This work is licensed under a Creative Commons Attribution Non-           Emilia-Romagna, a region of Italy, still receive VKAs.
    Commercial 4.0 License (CC BY-NC 4.0).                                        A major concern on the VKA’s use is the need for a
    ©
     Copyright: the Author(s), 2022
                                                                              careful dose titration to maintain the anticoagulant effect
    Licensee PAGEPress, Italy                                                 within the narrow therapeutic range, as it has been shown
    Bleeding, Thrombosis and Vascular Biology 2022; 1:9                       that the quality of anticoagulation control strongly im-
    doi:10.4081/btvb.2022.9
                                                                              pacts on patients’ outcome.9,10

                                                 Bleeding, Thrombosis and Vascular Biology 2022; 1:9
30                                                  G. De Girolamo et al.




    These needs can be addressed by different manage-             tor (either GPs or private specialist) receives INR results
ment models, usually defined as anticoagulation clinic            (performed in either public or private laboratories) from the
(AC) or general practitioner-based model (GP).                    patient and manage anticoagulation conduction in full au-
    Nonrandomized, retrospective studies have reported            tonomy, outside of the previously described network.
better outcomes in patients whose anticoagulant therapy
is managed by an AC compared with a GP model.11,12 The            Study design
AC model is widely adopted in the Emilia-Romagna re-                  This was a multicentre, retrospective, observational
gion, ensuring a good quality of VKA treatment, as                study by record-linkage of administrative healthcare
showed by a mean Time in Therapeutic Range (TTR) of               datasets.
74% reported in a recent prospective study.13                         This study design provides only the observation of the
    Since 2010 in the Modena province the AC and GP               clinical practice in a defined setting, not allowing a priori
models have been integrated in a network model (Network           definition of the sample size.
Anticoagulation Services, NAS) in which both specialists              Rather, the optimal balance of demographic and clin-
of hospital-based AC and GPs share the same management            ical characteristics between the two cohorts were obtained
software and patients’ database. The NAS model encom-             by applying the covariate balancing propensity score
passes almost 60% of VKA treated patients in the Modena           (CBPS) methodology and the Fine and Grey competitive
province, a province of the Emilia-Romagna region, the re-




                                                                                           ly
                                                                  risk models with Inverse Probability of Treatment Weight-
maining being managed by GPs using either manual dosing           ing (IPTW), as reported in the Statistical analysis para-




                                                                                   on
or individual software for VKAs management (Routine               graph of the Methods.
General Care, RGC) outside of this network.                           Accordingly, the effect size measures were assessed
    The aim of this study is to compare the effectiveness         by means of standardized difference, before and after


                                                                              e
and safety of the NAS and RGC models for the manage-              CBPS-weighting.
                                                                       us
ment of VKA therapy in the Modena province.                           The 95% CI provide a standard esteem of the statistic
                                                                  reliability of the study’s findings, being clearly dependent
                                                                al
                                                                  on the number of included subjects.
MATERIALS AND METHODS                                                 The study obtained ethics approval by the local Insti-
                                                    ci


Setting                                                           tutional Review Board (protocol number 3050 of
                                                  er


                                                                  11.8.2017).
    The Modena province is located in Northern Italy and
has an incident population of about 700,000 inhabitants.14
                                                 m




                                                                  Data sources
    The health care service in this area is provided by the
                                         om




Azienda Unità Sanitaria Locale (AUSL)-Modena, a struc-                 Data about VKA patients were collected by record-
ture of the Regional Health Care System. The AUSL di-             linkage of the following Emilia-Romagna Regional
rectly manages 6 general hospitals and several primary            Healthcare System databases:
                                   -c




care services, and coordinates about 470 GPs. A Univer-           i. Drug prescription database (Assistenza Farmaceutica
sity Hospital situated in two locations completes the                  Territoriale, AFT).
                            on




healthcare network of the Province.                               ii. Regional inpatient register (Schede di Dimissione Os-
    VKA-anticoagulated patients are managed in the                     pedaliera, SDO).
                        N




Modena province by two different models.                          iii. Modena Local Health Unit registry.
    The NAS model integrates eight AC, located in the             iv. Laboratory Information System (LIS).
hospitals in the area, and about two hundred GPs, ade-            v. PARMA® dataset.
quately formed on anticoagulant treatments. Both AC and           vi. Diabetes register of Modena province.
GP share the same management software (PARMA®,                    vii. Mortality register of the Modena province.
Werfen, Italy) in a tightly connected network for the man-
agement of VKA therapy.                                              For a detailed description of databases, please refer to
    Anticoagulated patients included in the NAS model             Supplementary Methods S1.
have blood sampled for INR determination in one of the               All record-linkage operations among databases were
40 blood sampling facilities, spread over the whole               performed in accordance with the Italian law, by
province of Modena; blood samples are then concentrated           anonymized identification codes.
in the Modena Central laboratory, where INR tests are
                                                                  Study population and follow-up
performed, and the results are electronically sent to the
treating physicians by the PARMA® software.                          From the start of the observation period (1st January
    On the other model (RGC), which includes about 40%            2011) to its end (31st December 2014), all citizens of the
of VKA-anticoagulated patients, each patient’s trusted doc-       AUSL-Modena were eligible to participate.

                                     Bleeding, Thrombosis and Vascular Biology 2022; 1:9
           Vitamin K antagonists in patients managed in a network of anticoagulation services or as routine general care         31



    Inclusion criteria were:                                             The follow-up data included all information regarding
i. age 30-99 years having had one prescription of either             the management of VKA treatment, and events or com-
    warfarin (Coumadin®) or acenocoumarol (Sintrom®),                plications occurring during treatment.
    the two VKAs commercially available in Italy, fol-                   The quality of anticoagulation laboratory control was
    lowed by at least another prescription or by two INR             assessed using the percentage of time within (Time in
    determinations within 90 days, irrespective of the clin-         Therapeutic Range, TTR), above or below the therapeutic
    ical indication;                                                 range calculated according to Rosendaal et al.15 Only INR
ii. do not having had any prescription of a DOAC during              values performed no more than 60 days apart were con-
    the observation period.                                          sidered for this computation.
                                                                         Because of exclusion of patients having had a mechan-
    Patients reported in any of the available datasets hav-          ical prosthetic heart valve substitution, the INR range was
ing had a surgery for mechanical prosthetic heart valve              assumed to be between 2 and 3 for all enrolled patients.
substitution (excluding bio-prosthesis) where excluded
from the study.                                                      Outcomes
    The beginning of the observation period for each pa-
tient was the date of the first VKA prescription.                        Primary outcomes were as follows.
    Patients were classified into two cohorts, according to              Efficacy: the hospital admission rate for:




                                                                                       ly
the current management of VKA treatment:                             i. any thromboembolic event, including ischemic stroke,
                                                                         cerebral transitory ischemic attacks (TIA), peripheral




                                                                               on
i. NAS cohort: included patients who were monitored
    exclusively through the PARMA® software                              arterial thromboembolism, pulmonary embolism
ii. RGC cohort: included patients who had received pre-                  and/or deep venous thrombosis
                                                                     ii. ischemic stroke or TIA


                                                                          e
    scription for VKAs but did not have any control in the
    PARMA® database.                                               us    Safety: the hospital admission rate for:
     Patients were referred to NAS or RGC cohort accord-             i. major bleeding (MB), defined as bleeding in critical
                                                            al
ing to their preference and to the GP’s willingness to ad-               sites such as intracranial, spinal, gastrointestinal or in-
here to the local network for VKA management.                            traocular bleeding, or any bleeding resulting in hospi-
                                              ci


     Patients included in both cohorts, because of a mixed               tal admission.
                                            er



management approach, were excluded from analysis.                    ii. intracerebral hemorrhage (ICH)
     Patients having had at least one VKA prescription from
                                           m




2010 to the beginning of observation were defined as “ex-                Mortality: the mortality rate for:
                                                                     i. all-cause mortality
                                  om




perienced”, whereas those starting VKA therapy at the be-
ginning of individual observation were defined as “naïve”.           ii. cerebrovascular diseases
     Patients’ follow-up was stopped at the occurrence of
                             -c




any of the following events, whichever came first:                      Secondary outcome was the percentage of patients
i. primary outcome achievement;                                      achieving a TTR value equal or above 60%.
                     on




ii. exclusion from the list of all subjects assisted by the             All outcomes were assessed by record-linkage of the
     AUSL-Modena (usually because of transfer to another             described dataset, according to the ICD-9/ICD-10 codes
                 N




     area),                                                          reported in the Supplementary Methods S2 and S3.
iii. A time lapse of more than 90 days from:
     a. the last available INR test                                  Statistical analysis
     b. the last VKA prescription                                        Characteristics of patients at inclusion and drugs co-
     c. the last control recorded in the PARMA® database             therapy were analyzed by descriptive statistics: percent-
     d. the end of study observation period (31st Decem-             ages for categorical variables, mean and standard
         ber 2014)                                                   deviation for continuous variable. Comparisons between
     The individual patient’s follow-up time was calculated          the NAS and RGC cohorts were performed by chi-square-
after exclusion of the days spent during a hospital stay.            test and t-test, respectively (Table 1).
                                                                         Crude incidence of primary outcomes was calculated
Collected baseline data
                                                                     as number of events per 1,000 person-years. Time-to-
   Demographic and clinical characteristics of patients              event analysis was performed to calculate crude incidence
and routine laboratory data were collected by the available          rate ratio (IRR) and sub-distribution hazard ratio (SHR).
databases (see Supplementary Methods S1).                                Due to the retrospective design of the study, the study
   A detailed description of comorbidities and concomitant           populations might display some relevant unbalances in
drug therapies is provided in the Supplementary Table S1.            baseline characteristics. To account for these unbalances,

                                      Bleeding, Thrombosis and Vascular Biology 2022; 1:9
32                                                      G. De Girolamo et al.




Fine and Grey competitive risk models,16-18 with Inverse               were excluded as being carriers of mechanical heart valve
Probability of Treatment Weighting (IPWT) were per-                    prostheses and 2,027 were excluded because recorded in
formed.19 Patients’ weights were obtained by applying                  both NAS and RGC cohorts. Of the remaining 14,926 pa-
the covariate balancing propensity score (CBPS)                        tients, 5,597 (37.5%) were naïve to anticoagulation treat-
methodology, to obtain an optimal balance of demo-                     ment at entry.
graphic and clinical characteristics between the two co-                   9,418 patients (63.1% of the total) were included in
horts. Balance of the baseline characteristics, between                the NAS cohort and 5,508 (36.9%) the RGC one. The de-
cohorts, and the effect size measures were assessed by                 mographic and clinical characteristics of the two cohorts
means of standardized difference, before and after                     are summarized in the Table 1.
CBPS-weighting.20                                                          Analysis of standardized differences showed a fair
    The 95% CIs provide a standard esteem of the statistic             balance between the two cohorts, excluding age at entry
reliability of the study’s findings, being clearly dependent           and naïve status for the whole sample, and renal failure
on the number of included subjects.                                    among naïve patients only. These differences had only a
    Separate models were used to obtain estimates of SHR               small potential impact on the effect estimates. After
for each outcome, for all patients, experienced patients               weighing with IPTW, the two cohorts were well balanced,
and naïve patients.                                                    showing zero standardized differences for all variables at
    Models included co-therapy variables: anti-platelets,              baseline (Supplementary Table S2).21




                                                                                                ly
heparin derivatives, statins, non-steroidal anti-inflamma-                 Five hundred eleven thromboembolic events (TE)




                                                                                        on
tory drugs, proton pump inhibitors.                                    were reported during follow-up, with a cumulative inci-
    Statistical analyses were performed with STATA 15                  dence of 14.75 per 1000 patient/years (‰p/ys).
software.                                                                  The crude incidence rate of TE was 12.50 ‰p/ys in



                                                                                   e
                                                                       the NAS and 18.69 ‰ in the RGC cohort. Both non-ad-
                                                                            us
                                                                       justed IRR and adjusted SHR were significantly lower in
                                                                       the NAS than in the RGC cohort (IRR 0.67, 95%CI: 0.56-
RESULTS
                                                                       0.80, p=0.000; sHR 0.76%, 95%CI: 0.64-0.90, p=0.002).
                                                                       al
   The flow-chart of patients’ inclusion is shown in                   IRR and SHR were significantly lower in the NAS than
Figure 1.                                                              in the RGC also when naïve and experienced patients
                                                        ci


   Among the initially selected 17,527 patients, 574                   were separately analyzed (Table 2).
                                                      er
                                                     m
                                           om
                                      -c
                              on
                         N




                                                                                VKA: vitamin K antagonists; INR: international
                                                                                normalized ratio; NAS: network of anticoagulation
                                                                                services; RGC: routine general care.
Figure 1. Flow-chart of patients analyzed and included in the study.


                                       Bleeding, Thrombosis and Vascular Biology 2022; 1:9
               Vitamin K antagonists in patients managed in a network of anticoagulation services or as routine general care                      33



Table 1. Demographic and clinical characteristics of included patients.
                                                         nAS cohort                                  RgC cohort                         P value
                                                          (n = 9,418)                                 (n = 5,508)
                                                         (py = 22,074)                               (py = 12,575)
                                                   n                       %                  n                        %
Men                                              5,023                    53.3               2,887                    52.4              0.278
Age at entry (mean, SD)                          74.9                    10.07               75.9                    10.09              0.000
Age classes (at entry)                                                                                                                  0.000
 <50                                              346                      3,7                181                      3.3
 50-64                                           1,067                    11.3                557                     10.1
 65-80                                           4,819                    51.2               2,620                    47.6
 >80                                             3,186                    33,8               2,150                    39.0
Co-payment exemption for (at entry)
 Low-income                                      2,655                    28.2               1,449                    26.3              0.013
 Disability                                       621                      6.6                322                      5.8              0.013
Naïve to anticoagulation (at entry)              3,728                    39.6               1,869                    33.9              0.070
Comorbidity (history of, at entry)                                                                                                      0.000
 Diabetes                                        2,044                    21.7                1,27                    23.1              0.055




                                                                                                    ly
 Hypertension                                    6,842                    72.6               4,014                    72.9              0.763




                                                                                            on
 Kidney diseases                                  462                      4.9                348                      6.3              0.000
 Liver diseases                                   131                      1.4                 87                      1.6              0.354
 Cancer                                          1,119                    11.9                535                      9.7              0.000
 Myocardial infarction                            436                      4.6                239                      4.3              0.410




                                                                                      e
 Heart failure                                   3,813                    40.5               2,407                    43.7              0.000
 Mitral stenosis
 Pulmonary embolism
                                                   49
                                                  366
                                                                           0.5
                                                                           3.9
                                                                               us              15
                                                                                              195
                                                                                                                       0.3
                                                                                                                       3.5
                                                                                                                                        0.025
                                                                                                                                        0.284
 Ischemic stroke/TIA                              789                      8.4                481                      8.7              0.453
 Aortic plaque /arterial thromboembolism           98                      1.0                 74                      1.3              0.094
                                                                    al
 Peripheral artery disease                        140                      1.5                102                      1.9              0.088
 Venous thromboembolism                           237                      2.5                168                      3.1              0.053
                                                    ci

 Bleedings                                        469                      5.0                300                      5.4              0.213
                                                  er


Drugs co-therapy (during follow-up)
 Anti-platelets                                  1,845                    19.6               1,012                    18.4              0.068
                                                 m




 NSAIDs                                           896                     9.5                 695                     12.6              0.000
 Heparin derivatives                             3,708                    39.4               1,672                    30.4              0.000
 Statins                                         3,779                    40.1               1,931                    35.1              0.000
                                          om




 PPIs                                            4,807                    51.0               2,797                    50.8              0.759
py: person-years; CVD: cerebrovascular diseases; NAS: network of anticoagulation services; NSAID: non-steroidal anti-inflammatory drugs; PPIs:
proton pump inhibitors; RGC: routine general care.
                                  -c
                          on




Table 2. Clinical events recorded during follow-up in the two cohorts. Thromboembolic events.
                Cohorts       events n.          Rate                            non adjusted iRR                             Adjusted SHR
                      N




                                              (x1000 p/y)                   95% Ci            p-value                   95% Ci             p-value

                                                            Thromboembolic events (all)
All patients    ALL              511             14.75
                RGC              235             18.69                           1                                           1
                NAS              276             12.50                   0.67 (0.56-0.80)      0.000                 0.76 (0.64-0.90)        0.002
Experienced RGC                  176             17.97                           1                                           1
            NAS                  211             13.02                   0.72 (0.59-0.89)      0.002                 0.81 (0.67-1.00)        0.046
Naïve           RGC               59             21.21                           1                                           1
                NAS               65             11.07                   0.52 (0.36-0.76)      0.000                 0.61 (0.43-0.88)        0.008
                                                               ischemic stroke or TiA
All patients    ALL              390             11.26
                RGC              171             13.60                           1                                           1
                NAS              219              9.92                   0.73 (0.59-0.90)      0.002                 0.84 (0.69-1.03)        0.096
Experienced RGC                  133             13.58                           1                                           1
            NAS                  175             10.80                   0.80 (0.63-1.00)      0.048                 0.91 (0.72-1.14)        0.393
Naïve           RGC               38             13.66                           1                                           1
                NAS               44             7.50                    0.55 (0.35-0.87)      0.008                 0.66 (0.43-1.02)        0.062
IRR: incidence rate ratio; SHR: sub-distribution hazard ratio; RGC: routine general care; NAS: network of anticoagulation services.


                                           Bleeding, Thrombosis and Vascular Biology 2022; 1:9
34                                                           G. De Girolamo et al.




    Adjusted SHRs for ischemic stroke or TIA were found                       IRR 0.98, 95%CI 0.84-1.16, P=0.85). A marginally non-
lower in the NAS cohort as compared to the RGC one, al-                       significant trend toward an increased risk in the NAS co-
though the difference did not achieve statistical signifi-                    hort (sHR 1.14, 95%CI 0.97-1.34, P=0.121) for this
cance (0.84, 95%CI:0.69-1.03, p=0.096). The same trend                        endpoint was found (Table 3).
was observed in naïve and experienced patients, with a                            Crude incidence rate for all-cause mortality and mor-
SHR non-significantly lower in the NAS cohort (0.66;                          tality for cerebrovascular disease were 52.39 and 4.22
95%CI: 0.43-1.02, p=0.062 and 0.91; 95%CI: 0.72-1.14,                         ‰p/ys in the NAS cohort and 72.50‰p/ys and 7.00
p=0.393, respectively).                                                       72.50‰p/ys in the RGC one, respectively. Non-adjusted
    Crude incidence rates and IRRs for major and intracra-                    IRR and adjusted SHR of all-cause mortality and mortal-
nial hemorrhages did not differ significantly between                         ity for cerebrovascular disease were significantly lower
NAS and RGC cohorts (18.17 vs 18.45 ‰p/ys, unadjusted                         in the NAS than in the RGC cohort (Table 4).


Table 3. Clinical events recorded during follow-up in the two cohorts. Bleeding events.
               Cohorts       events n.           Rate                         non adjusted iRR                      Adjusted SHR
                                              (x1000 p/y)                 95% Ci              p-value                95% Ci           p-value




                                                                                                          ly
Major bleedings




                                                                                                  on
All patients   ALL              633              18.27
               RGC              232              18.45                        1                                          1
               NAS              401              18.17                0.98 (0.84-1.16)         0.848             1.14 (0.97-1.34)      0.121




                                                                                            e
Experienced RGC                 174              17.77                        1                                          1

Naïve
            NAS
               RGC
                                285
                                 58
                                                 17.59
                                                 20.85                        1
                                                                                    us
                                                                      0.99 (0.82-1.20)         0.913             1.14 (0.94-1.38)
                                                                                                                         1
                                                                                                                                       0.171

               NAS              116              19.76                0.95 (0.69-1.32)         0.733             1.10 (0.80-1.52)      0.542
                                                                            al
intracranial haemorrhages
                                                               ci

All patients   ALL              262              7.56
               RGC              95               7.55                         1                                          1
                                                             er


               NAS              167              7.57                 1.00 (0.77-1.30)         0.996             1.17 (0.91-1.51)      0.220
Experienced RGC                  72              7.35                         1                                          1
                                                            m




            NAS                 118              7.28                 0.99 (0.73-1.35)         0.944             1.14 (0.85-1.53)      0.377
Naïve          RGC               23              8.27                         1                                          1
                                                om




               NAS               49              8.35                 1.01 (0.60-1.74)         0.982             1.26 (0.75-2.10)      0.379
IRR: incidence rate ratio; SHR: sub-distribution hazard ratio; RGC: routine general care; NAS: network of anticoagulation services.
                                          -c




Table 4. Clinical events recorded during follow-up in the two cohorts. Mortality.
                                 on




               Cohorts       events n.           Rate                        non adjusted iRR                      Adjusted SHR
                            N




                                              (x1000 p/y)                 95% Ci              p-value                95% Ci           p-value

All-cause mortality
All patients   ALL              2171             60.69
               RGC              978              75.20                        1                                          1
               NAS              1193             52.39                0.70 (0.64-0.76)         0.000             0.82 (0.75-0.89)      0.000
Experienced RGC                 755              74.61                        1                                          1
            NAS                 929              55.46                0.74 (0.67-0.82)         0.000             0.84 (0.76-0.93)      0.001
Naïve          RGC              223              77.28                        1                                          1
               NAS              264              43.87                0.57 (0.47-0.68)         0.000             0.72 (0.60-0.86)      0.000
Deaths due to cerebrovascular events (ischemic/haemorrhagic)
All patients   ALL              187              5.23
               RGC              91               7.00                         1                                          1
               NAS              96               4.22                 0.60 (0.45-0.81)         0.001             0.73 (0.54-0.98)      0.035
Experienced RGC                  65              6.42                         1                                          1
            NAS                  77              4.60                 0.72 (0.51-1.01)         0.049             0.85 (0.61-1.19)      0.342
Naïve          RGC               26              9.01                         1                                          1
               NAS               19              3.16                 0.35 (0.18-0.66)         0.001             0.45 (0.24-0.83)      0.010
IRR: incidence rate ratio; SHR: sub-distribution hazard ratio; RGC: routine general care; NAS: network of anticoagulation services.


                                           Bleeding, Thrombosis and Vascular Biology 2022; 1:9
               Vitamin K antagonists in patients managed in a network of anticoagulation services or as routine general care                     35



    More patients in the NAS cohort achieved the second-                     thromboembolic events (sHR 0.76%, 95%CI: 0.64-0.90,
ary outcome of a TTR value equal or above 60% as com-                        p=0.002) as well as the mortality for any cause and for
pared to the RGC: 74.4% vs 52.1%, p<0.001. A similar                         cerebrovascular events (sHR 0.82, 95% CI 0.75-0.89,
significant difference was found when naïve and experi-                      p=0.000 and 0.73, 95% CI 0.54-0.98, p=0.035). More-
enced subgroups were analyzed (Table 5).                                     over, it allows more patients to attain an INR >60%
    Of note, data about TTR distribution below or above                      (74.4% vs 52.1%, p<0.001), with no significant increase
the range showed that in the RGC cohort more time was                        of major bleeding.
spent with INR below the assigned range in respect to the                        We found a greater proportion of days spent with INR
NAS one, in the whole population as well as in naïve and                     below the assigned range in the RGC cohort in respect to
experienced subgroups. By the other side, percentage of                      the NAS one.
days over therapeutic range was very similar in the three                        It can be assumed that this trend to a lower-intensity
populations (Table 6).                                                       anticoagulation could account for both the statistically sig-
                                                                             nificant increase in TE events in the RGC cohort and the
                                                                             non-significant increase in MB rate in the NAS one. The
DISCUSSION                                                                   different clinical impact of these two issues matches the
                                                                             finding of a lower SHR of mortality in the NAS cohort.
    In this retrospective study, we found that the NAS                           Although VKAs are used since as much as fifty years,




                                                                                                 ly
model, integrating AC laboratory and GP by the use of a                      the best healthcare model to fulfil the specific healthcare




                                                                                          on
shared management software, allows a better quality of                       needs of those patients remains to be defined. Earlier stud-
VKA treatment on both clinical and laboratory outcomes,                      ies have suggested that an AC management model may
as compared to a routine general care model, outside of                      improve the outcome of anticoagulated patients compared



                                                                                   e
this network.                                                                to those managed by general practitioners. However, this
    Indeed, we found that the NAS model adopted in the
                                                                            us
                                                                             “centrally based” model has some limits, first of all the
Modena province significantly reduces the incidence of                       struggle for some patients to gain access to INR monitor.
                                                                      al
                                                    ci

Table 5. Percentages of patients with time in therapeutic range (TTR, 2.0-3.0 INR) ≥ 60%.
                                                  er



                Cohort        Patients         Mean of follow-up days           Patients with TTR(b) ≥60%           Patients with TTR(c) ≥60%
                                                percentage covered by                      n (%)                               n (%)
                                                 m




                                                      useful inR(a)
                                         om




All patients    RGC             5,508            67.3                             2,870 (52.1)                        1,967 (35.7)
                NAS            9,418             88.5                 ***         7,006 (74.4)         ***            5,862 (62.2)         ***
                Total          14,926            80.7                             9,876 (66.2)                        7,829 (52.5)
                                 -c




Experienced RGC                3,639             70.4                             2,032 (55.8)                        1,475 (40.5)
            NAS                5,69              91.8                 ***         4,431 (77.9)         ***            3,904 (68.6)         ***
                         on




            Total              9,329             83.5                             6,463 (69.3)                        5,379 (57.7)
Naïve           RGC            1,869             61.3                              838 (44.8)                          492 (26.3)
                        N




                NAS            3,728             83.3                 ***         2,575 (69.1)         ***            1,958 (52.5)         ***
                Total          5,597             75.9                             3,413 (61.0)                        2,450 (43.8)
  INRs performed at no more than 60 days apart (useful for TTR calculus); (b)calculated on patient’s valid follow-up days (covered by useful INR);
(a)

  calculated on patient’s total follow-up days. *p<0.05, **p<0.01, ***p<0.001.
(c)




Table 6. Percentages of days spent with TTR below or above the range.
                Cohort                    TTR% mean                           TbTR% mean                         ToTR% mean
All patients    RGC                            53.1                                20.6                               13.2
                NAS                            68.3                                18.4                               13.0
                Total                          62.7                                19.2                               13.1
Experienced RGC                                55.2                                18.4                               13.4
            NAS                                70.2                                15.5                               14.0
            Total                              64.4                                16.7                               13.8
Naïve           RGC                            48.9                                24.8                               12.8
                NAS                            65.5                                22.8                               11.4
                Total                          60.0                                23.5                               11.9
TTR%: percentage of days in therapeutic range; TbTR%: percentage of days below therapeutic range; ToTR%: percentage of days over therapeutic range.


                                           Bleeding, Thrombosis and Vascular Biology 2022; 1:9
36                                                  G. De Girolamo et al.




Moreover, a management model of VKA treatment                        Moreover, as the PARMA® software used in the NAS
mainly, or totally, delegated to hospital specialists could       model has recently been updated to allow its use also in
undermine a proper and timely sharing of information be-          DOAC treatment, it is advisable that further studies will
tween hospital specialists and a comprehensive approach           be carried out to explore the hypothesis that such a com-
to the patient’s care.                                            prehensive management model may also improve out-
    It has been shown that a comprehensive management             comes in DOAC users.
model providing centralized dose prescription and follow-
up may improve the outcome of VKA-treated patients.22
    This integrated approach is granted also in our NAS           REFERENCES
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