Design, population, and sample

This is an analytical, observational, longitudinal, and retrospective study carried out in the Basic Health Zone of Torrijos. This health area is made up of 9 localities with a total population of 24,132 inhabitants.

The study population consisted of patients with chronic pathologies in this Basic Health Zone under periodic follow-up by nurses in Primary Care (PC). The people with chronic pathologies most frequently seen in these consultations are people with high blood pressure, type 2 diabetes mellitus, obesity, hyperlipidemia, chronic heart failure (CHF), chronic renal failure (CKD) and chronic obstructive pulmonary disease (COPD).

The inclusion criteria were:

The exclusion criteria were:

A request was made to the Primary Care Management Department of Toledo for a list of patients with the pathologies described above and for permission to access the medical histories of these patients, in accordance with the current regulations of SESCAM (Castilla-La Mancha Health Service) (Circular 1/2009).

A search was carried out in the Data Exploitation Module of the Computerized Clinical History System of Primary Care of the SESCAM (Turriano), obtaining a total of 3720 patients.

To calculate the sample size, the "Sample Size Calculator" software was used: https://www.surveysystem.com/sscalc.htm; assigning an error of 5% and a confidence level of 95%, obtaining a sample of 348 patients.

The type of sampling used was simple randomized. Randomization was performed by a person outside the study, in this case, belonging to the Teaching Unit of the Primary Care Management Department of Toledo. In the randomization, 20% more patients were included to make up for the exclusions due to lack of registration in the medical histories ²⁰, making a total of 420.

Variables of the study

The study variables were:

Data collection procedure.

For each variable (except socio-demographics), the last measurements before confinement ⁶, on March 14^th 2020, were selected and compared with the first one after home confinement ²¹, on May 1^st 2020, since from this date onwards, non-professional physical activity in the open air was allowed during the health crisis caused by COVID-19.

A data collection sheet was used with the study variables specified above, which was completed by reviewing medical records. The data were obtained from the Computerized Primary Health Care History or from the Clinical Viewer, which allows us to consult the Hospital's history.

Statistical analysis

Firstly, a descriptive analysis of the different variables collected was carried out. Quantitative variables were expressed as means and standard deviation (SD) and qualitative variables as absolute and relative frequencies.

The Kolmogorov-Smirnov test was used to check the normality of the data.

To determine whether there are differences between the different clinical and metabolic parameters, the parametric Student's t-test, or the non-parametric Wilcoxon test for two related samples was used. And the non-parametric Friedman test for three related samples.

In all analyses, a value of p<0.05 (95% confidence interval) has been established to be considered statistically significant.

SPSS version 25.0 (SPSS Science, Chicago, Illinois, USA) was used for data analysis.

>Ethical considerations

This research obtained a positive evaluation from the Clinical Research Ethics Committee of the Area of Health from Toledo, Spain on May 26^th 2021, (Reg. Nº 725).

The participants' data have been processed in accordance with Organic Law 3/2018, of December the 5^th, on the Protection of Personal Data and the Guarantee of Digital Rights.

Characteristics of the participants

Of the 420 medical records reviewed, 349 participants met the inclusion criteria and made up the final study sample.

52.7% (184) are men with a mean age of 64.84 years (SD=14.732), while that of women is 69.67 years (SD=14.167).

Participants have a mean number of diseases of 2.77 (SD=1.320). The included patients have a mean of 6.17 (SD=4.104) active medicines on the medication sheet of their primary care medical record.

Of these chronic patients, 12.9% (45) have had COVID-19 infection.

The characteristics of the sample are described in Table 1.

Table 1: Socio-demographic/clinical characteristics of the sample. 

Relationship between clinical and metabolic parameters before and after confinement

All chronic patients

In general, all clinical parameters increased after home confinement, finding statistically significant differences only in diastolic blood pressure (DBP) (p=0.018). The only variable that decreased after confinement was weight (p=0.016), (Table 2).

Table 2: Clinical parameters before and after confinement. 

^*Paired Student's t-test or the non-parametric Wilcoxon test for two related samples.

SD=Standard deviation.

SBP=Systolic blood pressure. DBP=Diastolic blood pressure.

Frequency and type of nursing consultations

There is a considerable decrease in the total number of nursing consultations during and after confinement, which is statistically significant (p=0.000).

Figure 1 shows the distribution of nursing consultations before, during and after confinement. During confinement there is a reduction in face-to-face and home visits and an increase in telephone visits.

Figure 1: Distribution of types of nursing consultations. 

Main findings

During the SARS-CoV-2 outbreak, health systems began to postpone and reduce some aspects of routine chronic disease management, outpatient visits and non-urgent surgeries to avoid unnecessary hospital visits, reduce the burden on hospitals and reduce the risk of infection ^2,3,6,7. It is known that even the patient considered clinically sTable, considered to be low risk, requires close clinical follow-up, because there is evidence of silent disease progression and a significant incidence of events even in the presence of apparent stability ^8)(16)(22.

The aim of this study was to assess the overall impact of confinement and modifications in the health care system on the health of chronically ill people in a Basic Health Zone during the COVID-19 pandemic. This study found a significant reduction in weight in the total sample, over 65 years, women and patients with hypertension and patients with hyperlipemia. There was also an increase in DBP in the total sample, over 65 years, women, and patients with hypertension, although this increase did not lead to clinically relevant changes, from a mean of 78.24 mmHg to 79.89 mmHg. There was a significant increase in LDL in patients aged 65 years, which has clinical relevance since for these patients with average cardiovascular risk in the SCORE Tables, the therapeutic objective would be an LDL<100 mg/dl, so this variation could imply the need to prescribe pharmacological treatment ²³.

In the study population, we observed an increase in admissions after confinement and how these admissions are mainly related to decompensation and/or complication of their underlying chronic pathology.

In relation to the change in the nursing consultations, the reduction in the total number of visits of these patients with confinement may be related to the loss in the records of each clinical/metabolic parameter that occurs in these patients, since the follow-up of these patients is mainly performed in the nursing consultations.

In terms of the type of visits, there was an increase in telephone consultations during and after confinement, and a decrease in face-to-face consultations. It should also be noted that consultations at home increase after confinement, which may indicate that there are chronic patients who require this type of care, as they are unable to get to the Health Centre.

Comparison with other studies

Regarding the weight reduction that appears in our sample, there are several reviewed articles that also identify modifications in weight ^24)(25)(26. In the study by Bello Torres ²⁴, an increase in BMI is described. Martínez-Ferrán ²⁷ indicates that a reduction in physical activity leads to an increase in fat mass and a reduction in lean mass in overweight people.

The increase we describe in patients' DBP can be explained within the negative effects of confinement. Thus, Flaherty ⁸ states that confinement has negative socio-economic and psychological consequences, which are risk factors for atherosclerotic vascular disease. Mattioli ¹⁹ also links increased sympathetic nervous activity due to confinement with a negative effect on the heart and vessels. However, in Di Tano's study ¹⁶, in a sample of CHF patients, 78.4% remained unchanged in BP.

In relation to the increase in LDL in those over 65 years of age and also, in people with hyperlipidemia, Martínez-Ferrán ²⁷ indicates in his review that physical inactivity leads to an increase in total cholesterol, LDL and triglycerides. Changes in dietary habits have also been described that may have an impact on the metabolic control of chronic diseases ^2)(4)(27. The combination of a balanced diet and regular physical exercise should serve to maintain a sTable metabolic balance ²⁷.

In diabetic patients the increase in control parameters is possibly related to the change of habits during confinement. Increased consumption of sugary foods during confinement seems to have affected glycemic control in type 2 diabetics ⁴. Martinez-Ferran ²⁷ suggests that reduced physical activity may worsen glycemic control in healthy adults, overweight people, and the elderly. Ghosal et al. have developed a predictive model to explore the impact of confinement in diabetic patients and have demonstrated the presence of a direct relationship between the duration of confinement and non-compliance with treatment, leading to an increase in glycaemia ²⁸. On the other hand, other studies show that the level of glycemic control improved or was maintained during confinement in patients with type 1 diabetes ^12)(25)(29. In a study involving patients with DM2, the incidence of hypo- or hyperglycemia did not vary significantly ²⁵. These results have been related to the fact that taking time off work reduced their stress levels, gave them more time and allowed for greater adherence to healthy lifestyle habits ^12,25.

People with chronic renal failure and chronic heart failure are recognized as one of the most vulnerable groups of chronic patients ^8,16, so they are more at risk of severe COVID-19 ^8,16, and the interruption of regular follow-up visits may affect them more than other chronic groups ^2)(8)(16. Although in studies of patients with chronic heart failure, postponement of scheduled visits did not cause significant clinical relapses^16,30).

With regard to changes in nursing consultations, the adaptation to the situation caused by the pandemic has led to an increase in telephone consultations ^8)(9)(10 and a decrease in face-to-face consultations ^2)(8)(9)(10. Some articles indicate that these changes in healthcare can have a negative impact on patients' health, delaying the diagnosis of serious pathologies or worsening chronic pathologies ^{13)(14)(17)(25)(27}. In our context, there is a significant loss in the records of clinical/metabolic parameters in chronic patients. On the other hand, the increase in hospital admissions related to chronic pathology after confinement, without being able to establish a clear causal relationship, may be related to the decrease in the number of face-to-face consultations during and after confinement. In this sense, more research on long-term complications is needed.

Strengths and limitations of the study

The main strength of our study is the fact that it provides more information on the impact of confinement on the follow-up of chronic patients, and it has been conducted in the context of Primary Care, which is where the usual follow-up of these patients takes place. Thus, we will be able to reorient and update health care systems to be able to cover and provide adequate follow-up to these patients, modifying the frequency and type of follow-up visits and/or reinforcing healthy behaviours and habits.

Another strength is that it includes all chronic patients, with the pathologies that most frequently require follow-up. Probability sampling was used to select participants, which guarantees the representativeness of the population and makes selection bias less likely.

The limitations of the study are the usual limitations of a retrospective design. The project is based on a review of medical records, and therefore depends on adequate recording by the professionals attending the patient.

The records of the different parameters will be made at different times of the pandemic with different restrictions, so the conditions at the time of measurement will not be the same for all patients.